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Collective behavior can serve as a mechanism of thermoregulation and play a key role in the joint survival of a group of organisms. In higher animals, such phenomena are usually the subject of study of biology since sudden transitions to collective behavior are difficult to differentiate from the psychological and social adaptation of animals. However, in this paper, we indicate several important examples when a flock of higher animals demonstrates phase transitions similar to known phenomena in liquids and gases. This issue can also be studied experimentally within the framework of synthetic systems consisting of self-propelled robots that act according to a certain given algorithm. Generalizing both of these cases, we consider the problem of phase transitions in a dense group of interacting selfpropelled agents. Within the framework of microscopic theory, we propose a mathematical model of the phenomenon, in which agents are represented as bodies interacting with each other in accordance with an effective potential of a special type, expressing the desire of agents to move in the direction of the gradient of the joint thermal field. We show that the number of agents in the group, the group power, is the control parameter of the problem. A discrete model with individual dynamics of agents reproduces most of the phenomena observed both in natural flocks of higher animals engaged in collective thermoregulation and in synthetic complex systems. A first-order phase transition is observed, which symbolizes a change in the aggregate state in a group of agents. One observes the self-assembly of the initial weakly structured mass of agents into dense quasi-crystalline structures. We demonstrate also that, with an increase in the group power, a second-order phase transition in the form of thermal convection can occur. It manifests in a sudden liquefaction of the group and a transition to vortex motion, which ensures more efficient energy consumption in the case of a synthetic system of interacting robots and the collective survival of all individuals in the case of natural animal flocks.With an increase in the group power, secondary bifurcations occur, the vortex structure in agent medium becomes more complicated.

Coconut plantation plays a vital role in the economy and source of living for millions of farmers around the world, especially in tropical regions. The rugose spiraling whitefly is a highly destructive pest causing severe damage to coconut trees and significantly reducing their productivity. The aim of this paper is to develop and analyze a mathematical model that captures the dynamics of whitefly and to highlight the benefits of using biological control to mitigate the impact of pest damaging coconut palms. To be more realistic, a stage-structured model with maturation delay and lag in the implementation of the control measures has been considered in the model. We identify the equilibrium points of the system and perform a stability analysis to assess the system behavior. The numerical simulation of the proposed system is also reported. The findings reveal that introducing the population of parasitoids can effectively reduce the rugose spiraling whitefly population presenting a promising strategy for mitigating the pest’s impact.

Classical Chanter–Thornley model of mushroom growth has been modified and implemented in AnyLogic simulation environment by means of system dynamics, discrete-event and agent-based approaches. A numerical case study of the model is presented and the problem of optimum age at harvest, providing the maximum integral yield for all fruiting “waves” is solved.

The paper outlines the approaches to mathematical modeling correlation adaptometry techniques widely used in biology and medicine. The analysis is based on models employed in descriptions of structured biological systems. It is assumed that the distribution density of the biological population numbers satisfies the equation of Kolmogorov-Fokker-Planck. Using this technique evaluated the effectiveness of treatment of patients with obesity. All patients depending on the obesity degree and the comorbidity nature were divided into three groups. Shows a decrease in weight of the correlation graph computed from the measured in the patients of the indicators that characterizes the effectiveness of the treatment for all studied groups. This technique was also used to assess the intensity of the training loads in academic rowing three age groups. It was shown that with the highest voltage worked with athletes for youth group. Also, using the technique of correlation adaptometry evaluated the effectiveness of the treatment of hormone replacement therapy in women. All the patients depending on the assigned drug were divided into four groups. In the standard analysis of the dynamics of mean values of indicators, it was shown that in the course of the treatment were observed normalization of the averages for all groups of patients. However, using the technique of correlation adaptometry it was found that during the first six months the weight of the correlation graph was decreasing and during the second six months the weight increased for all study groups. This indicates the excessive length of the annual course of hormone replacement therapy and the practicality of transition to a semiannual rate.

Modern power transportation systems are the complex engineering systems. Such systems include both point facilities (power producers, consumers, transformer substations, etc.) and the distributed elements (f.e. power lines). Such structures are presented in the form of the graphs with different types of nodes under creating the mathematical models. It is necessary to solve the system of partial differential equations of the hyperbolic type to study the dynamic effects in such systems.

An approach similar to one already applied in modeling similar problems earlier used in the work. New variant of the splitting method was used proposed by the authors. Unlike most known works, the splitting is not carried out according to physical processes (energy transport without dissipation, separately dissipative processes). We used splitting to the transport equations with the drain and the exchange between Reimann’s invariants. This splitting makes possible to construct the hybrid schemes for Riemann invariants with a high order of approximation and minimal dissipation error. An example of constructing such a hybrid differential scheme is described for a single-phase power line. The difference scheme proposed is based on the analysis of the properties of the schemes in the space of insufficient coefficients.

Examples of the model problem numerical solutions using the proposed splitting and the difference scheme are given. The results of the numerical calculations shows that the difference scheme allows to reproduce the arising regions of large gradients. It is shown that the difference schemes also allow detecting resonances in such the systems.

The article analyzes empirical data on the long-term demographic and economic dynamics of the countries of the world for the period from the beginning of the 19th century to the present. Population and GDP of a number of countries of the world for the period 1500–2016 were selected as indicators characterizing the long-term demographic and economic dynamics of the countries of the world. Countries were chosen in such a way that they included representatives with different levels of development (developed and developing countries), as well as countries from different regions of the world (North America, South America, Europe, Asia, Africa). A specially developed mathematical model was used for modeling and data processing. The presented model is an autonomous system of differential equations that describes the processes of socio-economic modernization, including the process of transition from an agrarian society to an industrial and post-industrial one. The model contains the idea that the process of modernization begins with the emergence of an innovative sector in a traditional society, developing on the basis of new technologies. The population is gradually moving from the traditional sector to the innovation sector. Modernization is completed when most of the population moves to the innovation sector.

Statistical methods of data processing and Big Data methods, including hierarchical clustering were used. Using the developed algorithm based on the random descent method, the parameters of the model were identified and verified on the basis of empirical series, and the model was tested using statistical data reflecting the changes observed in developed and developing countries during the period of modernization taking place over the past centuries. Testing the model has demonstrated its high quality — the deviations of the calculated curves from statistical data are usually small and occur during periods of wars and economic crises. Thus, the analysis of statistical data on the long-term demographic and economic dynamics of the countries of the world made it possible to determine general patterns and formalize them in the form of a mathematical model. The model will be used to forecast demographic and economic dynamics in different countries of the world.

The paper addresses the problem of modeling the formation and propagation of panic states in social groups with relatively stable structures of interpersonal interactions. Panic is interpreted as a nonlinear process of emotional contagion arising from the interaction between individual psychological characteristics and collective effects within a social environment. In contrast to models focused on the spatial dynamics of moving crowds, the proposed approach concentrates on quasi-stationary interaction networks that reflect informational and emotional contacts among individuals.

The developed discrete network dynamical system integrates individual temperament parameters (sanguine, choleric, phlegmatic, melancholic), the structure of social connections, and nonlinear mechanisms of collective behavior. The individual dynamics of panic are described using an S-shaped growth function, which ensures boundedness of the emotional arousal level and captures the stages of its formation and saturation. Social influence is modeled on a graph of interpersonal interactions (an Erdos –Renyi random network) through local contacts between individuals.

Additionally, the model incorporates the effects of collective contagion and avalanche-like amplification driven by the average panic level in the group, as well as a baseline stress factor depending on group size. Numerical simulation is implemented in a discrete iterative form, allowing for the analysis of both individual and group panic trajectories. A quantitative indicator of the panic propagation rate is introduced, defined by the time required for the group to reach a state close to full panic.

A comparative analysis of heterogeneous and homogeneous groups is conducted, demonstrating that group heterogeneity significantly accelerates panic propagation due to inter-temperament interactions: highly excitable individuals act as initiators of emotional contagion, while more stable individuals partially dampen its dynamics. The evaluation of the model quality using the coefficient of determination shows a high degree of consistency within the simulation data.

The practical significance of the work lies in the potential application of the model for analyzing the resilience of social groups to panic states, assessing risks at mass events, and developing intelligent systems for monitoring collective behavior. Future research directions include extending the model to account for directed and dynamic networks, as well as its calibration based on empirical data.

Soil as a complex multifunctional open system is one of the most difficult object for modeling. In spite of serious achievements in the soil system modeling, existed models do not reflect all aspects and processes of soil organic matter mineralization and humification. The problems and “hot spots” in the modeling of the dynamics of soil organic matter and biophylous elements were identified on a base of creation and wide implementation of ROMUL and EFIMOD models. The following aspects are discussed: further theoretical background; improving the structure of models; preparation and uncertainty of the initial data; inclusion of all soil biota (microorganisms, micro- and meso-fauna) as factors of humification; impact of soil mineralogy on C and N dynamics; hydro-thermal regime and organic matter distribution in whole soil profile; vertical and horizontal migration of soil organic matter. An effective feedback from modellers to experimentalists is necessary to solve the listed problems.

The work focuses on mathematical modeling of light influence mechanisms on macromolecular composition of microalgae batch culture. It is shown that even with a single limiting factor, the growth of microalgae is associated with a significant change in the biochemical composition of the biomass in any part of the batch curve. The well-known qualitative models of microalgae are based on concepts of enzymatic kinetics and do not take into account the possible change of the limiting factor during batch culture growth. Such models do not allow describing the dynamics of the relative content of biochemical components of cells. We proposed an alternative approach which is based on generally accepted two-stage photoautotrophic growth of microalgae. Microalgae biomass can be considered as the sum of two macromolecular components — structural and reserve. At the first stage, during photosynthesis a reserve part of biomass is formed, from which the biosynthesis of cell structures occurs at the second stage. Model also assumes the proportionality of all biomass structural components which greatly simplifies mathematical calculations and experimental data fitting. The proposed mathematical model is represented by a system of two differential equations describing the synthesis of reserve biomass compounds at the expense of light and biosynthesis of structural components from reserve ones. The model takes into account that a part of the reserve compounds is spent on replenishing the pool of macroergs. The rates of synthesis of structural and reserve forms of biomass are given by linear splines. Such approach allows us to mathematically describe the change in the limiting factor with an increase in the biomass of the enrichment culture of microalgae. It is shown that under light limitation conditions the batch curve must be divided into several areas: unlimited growth, low cell concentration and optically dense culture. The analytical solutions of the basic system of equations describing the dynamics of macromolecular biomass content made it possible to determine species-specific coefficients for various light conditions. The model was verified on the experimental data of biomass growth and dynamics of chlorophyll $a$ content of the red marine microalgae Pоrphуridium purpurеum batch culture.

The possibility of numerical 3D simulation of thrombi formation is considered.

The developed up to now detailed mathematical models describing formation of thrombi and clots include a great number of equations. Being implemented in a CFD code, the detailed mathematical models require essential computer resources for simulation of the thrombi growth in a blood flow. A reasonable alternative way is using reduced mathematical models. Two models based on the reduced mathematical model for the thrombin generation are described in the given paper.

The first model describes growth of a thrombus in a great vessel (artery). The artery flows are essentially unsteady. They are characterized by pulse waves. The blood velocity here is high compared to that in the vein tree. The reduced model for the thrombin generation and the thrombus growth in an artery is relatively simple. The processes accompanying the thrombin generation in arteries are well described by the zero-order approximation.

A vein flow is characterized lower velocity value, lower gradients, and lower shear stresses. In order to simulate the thrombin generation in veins, a more complex system of equations has to be solved. The model must allow for all the non-linear terms in the right-hand sides of the equations.

The simulation is carried out in the industrial software FlowVision.

The performed numerical investigations have shown the suitability of the reduced models for simulation of thrombin generation and thrombus growth. The calculations demonstrate formation of the recirculation zone behind a thrombus. The concentration of thrombin and the mass fraction of activated platelets are maximum here. Formation of such a zone causes slow growth of the thrombus downstream. At the upwind part of the thrombus, the concentration of activated platelets is low, and the upstream thrombus growth is negligible.

When the blood flow variation during a hart cycle is taken into account, the thrombus growth proceeds substantially slower compared to the results obtained under the assumption of constant (averaged over a hard cycle) conditions. Thrombin and activated platelets produced during diastole are quickly carried away by the blood flow during systole. Account of non-Newtonian rheology of blood noticeably affects the results.