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The dynamics of various gaseous substances is of great importance in the vital activity of phytoplankton. The dynamics of oxygen and carbon dioxide are the most indicative for aquatic plant communities. These dynamics are important for the global ratio of oxygen and carbon dioxide in the Earth’s atmosphere. The goal of the work is to use the mathematical modeling to study the role of oxygen and carbon dioxide in the life of aquatic plant organisms, in particular, the phytoplankton. The series of mathematical models of the dynamics of oxygen and carbon dioxide in the phytoplankton body are proposed. The series of models are built according to the increasing degree of complexity and the number of modeled processes. At first, the simplest model of only gas dynamics is considered, then there is a transition to models with the interaction and mutual influence of gases on the formation and dynamics of energy-intensive substances and on growth processes in the plant organism. Photosynthesis and respiration are considered as the basis of the models. The models study the properties of solutions: equilibrium solutions and their stability, dynamic properties of solutions. Various types of equilibrium stability, possible complex non-linear dynamics have been identified. These properties allow better orientation when choosing a model to describe processes with a known set of data and formulated modeling goals. An example of comparing an experiment with its model description is given. The next goal of modeling — to link gas dynamics for oxygen and carbon dioxide with metabolic processes in plant organisms. In the future, model designs will be applied to the analysis of ecosystem behavior when the habitat changes, including the content of gaseous substances.

A model of the behavior of the active neuron, which was the development of the model described in Shamis A.L. [Shamis, 2006], is designed. Proposed topology is locally connected matrix of the active neural network and the structure integration of information from different sources. An example of the script behavior robot controlled by this neural network is described. The results of experiments with the software implementation of a neural network are presented.

Investigation of the influence of external fields on living systems is one of the most interesting and rapidly developing areas of modern biophysics. However, the mechanisms of such an impact are still not entirely clear. One approach to the study of this issue is associated with modeling the interaction of external fields with internal mobility of biological objects. In this paper, this approach is used to study the effect of external fields on the motion of local conformational distortions — kinks, in the DNA molecule. Realizing and taking into account that on the whole this task is closely connected with the problem of the mechanisms of regulation of vital processes of cells and cellular systems, we set the problem — to investigate the physical mechanisms regulating the motion of kinks and also to answer the question whether permanent and periodic fields can play the role of regulators of this movement. The paper considers the most general case, when constant and periodic fields are switching on and off asynchronously. Three variants of asynchronous switching on/off are studied in detail. In the first variant, the time intervals (or diapasons) of the actions of the constant and periodic fields do not overlap, in the second — overlap, and in the third — the intervals are putting in each other. The calculations were performed for the sequence of plasmid pTTQ18. The kink motion was modeled by the McLaughlin–Scott equation, and the coefficients of the equation were calculated in a quasi-homogeneous approximation. Numerical experiments showed that constant and periodic fields exert a significant influence on the character of the kink motion and regulate it. So the switching on of a constant field leads to a rapid increase of the kink velocity and to the establishment of a stationary velocity of motion, and the switching on of a periodic field leads to the steady oscillations of the kink with the frequency of the external periodic field. It is shown that the behavior of the kink depends on the mutual arrangement of the diapasons of the action of the external fields. As it turned out, events occurring in one of the two diapasons can affect the events in the other diapason, even when the diapasons are sufficiently far apart. It is shown that the overlapping of the diapasons of action of the constant and periodic fields leads to a significant increase in the path traversed by the kink to a complete stop. Maximal growth of the path is observed when one diapason is putting in each other. In conclusion, the question of how the obtained model results could be related to the most important task of biology — the problem of the mechanisms of regulation of the processes of vital activity of cells and cellular systems is discussed.

The article deals with the modeling of the number of employed population by branches of the economy at the national and regional levels. The lack of targeted distribution of workers in a market economy requires the study of systemic processes in the labor market that lead to different dynamics of the number of employed in the sectors of the economy. In this case, personal strategies for choosing labor activity by economic agents become important. The presence of different strategies leads to the emergence of strata in the labor market with a dynamically changing number of employees, unevenly distributed among the sectors of the economy. As a result, non-linear fluctuations in the number of employed population can be observed, the toolkit of agentbased modeling is relevant for the study of the fluctuations. In the article, we examined in-phase and anti-phase fluctuations in the number of employees by economic activity on the example of the Jewish Autonomous Region in Russia. The fluctuations found in the time series of statistical data for 2008–2016. We show that such fluctuations appear by age groups of workers. In view of this, we put forward a hypothesis that the agent in the labor market chooses a place of work by a strategy, related with his age group. It directly affects the distribution of the number of employed for different cohorts and the total number of employed in the sectors of the economy. The agent determines the strategy taking into account the socio-economic characteristics of the branches of the economy (different levels of wages, working conditions, prestige of the profession). We construct a basic agentoriented model of a three-branch economy to test the hypothesis. The model takes into account various strategies of economic agents, including the choice of the highest wages, the highest prestige of the profession and the best working conditions by the agent. As a result of numerical experiments, we show that the availability of various industry selection strategies and the age preferences of employers within the industry lead to periodic and complex dynamics of the number of different-aged employees. Age preferences may be a consequence, for example, the requirements of employer for the existence of work experience and education. Also, significant changes in the age structure of the employed population may result from migration.

Epidemic models are widely used to mimic social activity, such as spreading of rumors or panic. Simultaneously, models of excitable media are traditionally used to simulate the propagation of activity. Spreading of activity in the virtual community was simulated within two models: the SIRS epidemic model and the Wiener – Rosenblut model of the excitable media. We used network versions of these models. The network was assumed to be heterogeneous, namely, each element of the network has an individual set of characteristics, which corresponds to different psychological types of community members. The structure of a virtual network relies on an appropriate scale-free network. Modeling was carried out on scale-free networks with various values of the average degree of vertices. Additionally, a special case was considered, namely, a complete graph corresponding to a close professional group, when each member of the group interacts with each. Participants in a virtual community can be in one of three states: 1) potential readiness to accept certain information; 2) active interest to this information; 3) complete indifference to this information. These states correspond to the conditions that are usually used in epidemic models: 1) susceptible to infection, 2) infected, 3) refractory (immune or death due to disease). A comparison of the two models showed their similarity both at the level of main assumptions and at the level of possible modes. Distribution of activity over the network is similar to the spread of infectious diseases. It is shown that activity in virtual networks may experience fluctuations or decay.

The data of episodic field measurements of carbon dioxide balance components (soil respiration — R_soil, ecosystem respiration — R_eco, net ecosystem exchange — NEE) of hayfields under use and abandoned one are interpreted by modelling. The field measurements were carried within five field campaigns in 2018 and 2019 on the drained part of the Dubna Peatland in Taldom District, Moscow Oblast, Russia. The territory is within humid continental climate zone. Peatland drainage was done out for milled peat extraction. After extraction was stopped, the residual peat deposit (1–1.5 m) was ploughed and grassed (Poa pratensis L.) for hay production. The current ground water level (GWL) varies from 0.3–0.5 m below the surface during wet and up to 1.0 m during dry periods. Daily dynamics of CO2 fluxes was measured using dynamic chamber method in 2018 (August) and 2019 (May, June, August) for abandoned ditch spacing only with sanitary mowing once in 5 years and the ditch spacing with annual mowing. NEE and Reco were measured on the sites with original vegetation, and Rsoil — after vegetation removal. To model a seasonal dynamics of NEE, the dependence of its components (Reco, Rsoil, and Gross ecosystematmosphere exchange of carbon dioxide — GEE) from soil and air temperature, GWL, photosynthetically active radiation, underground and aboveground plant biomass were used. The parametrization of the models has been carried out considering the stability of coefficients estimated by the bootstrap method. R2 (α = 0.05) between simulated and measured Reco was 0.44 (p < 0.0003) on abandoned and 0.59 (p < 0.04) on under use hayfield, and GEE was 0.57 (p < 0.0002) and 0.77 (p < 0.00001), respectively. Numerical experiments were carried out to assess the influence of different haymaking regime on NEE. It was found that NEE for the season (May 15 – September 30) did not differ much between the hayfield without mowing (4.5±1.0 tC·ha–1·season–1) and the abandoned one (6.2±1.4). Single mowing during the season leads to increase of NEE up to 6.5±0.9, and double mowing — up to 7.5±1.4 tC·ha–1·season–1. This means increase of carbon losses and CO2 emission into the atmosphere. Carbon loss on hayfield for both single and double mowing scenario was comparable with abandoned hayfield. The value of removed phytomass for single and double mowing was 0.8±0.1 tC·ha^–1·season^–1 and 1.4±0.1 (45% carbon content in dry phytomass) or 3.0 and 4.4 t·ha^–1·season^–1 of hay (17% moisture content). In comparison with the fallow, the removal of biomass of 0.8±0.1 at single and 1.4±0.1 tC·ha^–1·season^–1 double mowing is accompanied by an increase in carbon loss due to CO2 emissions, i.e., the growth of NEE by 0.3±0.1 and 1.3±0.6 tC·ha–1·season–1, respectively. This corresponds to the growth of NEE for each ton of withdrawn phytomass per hectare of 0.4±0.2 tС·ha–1·season–1 at single mowing, and 0.9±0.7 tС·ha^–1·season^–1 at double mowing. Therefore, single mowing is more justified in terms of carbon loss than double mowing. Extensive mowing does not increase CO2 emissions into the atmosphere and allows, in addition, to “replace” part of the carbon loss by agricultural production.