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Investigation of logical deterministic cellular automata models of population dynamics allows to reveal detailed individual-based mechanisms. The search for such mechanisms is important in connection with ecological problems caused by overexploitation of natural resources, environmental pollution and climate change. Classical models of population dynamics have the phenomenological nature, as they are “black boxes”. Phenomenological models fundamentally complicate research of detailed mechanisms of ecosystem functioning. We have investigated the role of fecundity and duration of resources regeneration in mechanisms of population growth using four models of ecosystem with one species. These models are logical deterministic cellular automata and are based on physical axiomatics of excitable medium with regeneration. We have modeled catastrophic death of population arising from increasing of resources regeneration duration. It has been shown that greater fecundity accelerates population extinction. The investigated mechanisms are important for understanding mechanisms of sustainability of ecosystems and biodiversity conservation. Prospects of the presented modeling approach as a method of transparent multilevel modeling of complex systems are discussed.

This paper is dedicated to discussing methods of statistical modeling the outcomes of sport events and, particularly, matches with continuous time. We propose a simulation-based approach to predicting the outcome of a match, somehow medium between pure statistical methods and agent simulation of individual players. An example of retrospective prediction is given.

Theoretical and experimental investigations of water vapor interaction with porous materials are carried out both at the macro level and at the micro level. At the macro level, the influence of the arrangement structure of individual pores on the processes of water vapor interaction with porous material as a continuous medium is studied. At the micro level, it is very interesting to investigate the dependence of the characteristics of the water vapor interaction with porous media on the geometry and dimensions of the individual pore.

In this paper, a study was carried out by means of mathematical modelling of the processes of water vapor interaction with suffering pore of the cylindrical type. The calculations were performed using a model of a hybrid type combining a molecular-dynamic and a macro-diffusion approach for describing water vapor interaction with an individual pore. The processes of evolution to the state of thermodynamic equilibrium of macroscopic characteristics of the system such as temperature, density, and pressure, depending on external conditions with respect to pore, were explored. The dependence of the evolution parameters on the distribution of the diffusion coefficient in the pore, obtained as a result of molecular dynamics modelling, is examined. The relevance of these studies is due to the fact that all methods and programs used for the modelling of the moisture and heat conductivity are based on the use of transport equations in a porous material as a continuous medium with known values of the transport coefficients, which are usually obtained experimentally.

This article solves the problem of developing a technology for collecting initial data for building models for assessing the functional state of a person. This condition is assessed by the pupil response of a person to a change in illumination based on the pupillometry method. This method involves the collection and analysis of initial data (pupillograms), presented in the form of time series characterizing the dynamics of changes in the human pupils to a light impulse effect. The drawbacks of the traditional approach to the collection of initial data using the methods of computer vision and smoothing of time series are analyzed. Attention is focused on the importance of the quality of the initial data for the construction of adequate mathematical models. The need for manual marking of the iris and pupil circles is updated to improve the accuracy and quality of the initial data. The stages of the proposed technology for collecting initial data are described. An example of the obtained pupillogram is given, which has a smooth shape and does not contain outliers, noise, anomalies and missing values. Based on the presented technology, a software and hardware complex has been developed, which is a collection of special software with two main modules, and hardware implemented on the basis of a Raspberry Pi 4 Model B microcomputer, with peripheral equipment that implements the specified functionality. To evaluate the effectiveness of the developed technology, models of a single-layer perspetron and a collective of neural networks are used, for the construction of which the initial data on the functional state of intoxication of a person were used. The studies have shown that the use of manual marking of the initial data (in comparison with automatic methods of computer vision) leads to a decrease in the number of errors of the 1st and 2nd years of the kind and, accordingly, to an increase in the accuracy of assessing the functional state of a person. Thus, the presented technology for collecting initial data can be effectively used to build adequate models for assessing the functional state of a person by pupillary response to changes in illumination. The use of such models is relevant in solving individual problems of ensuring transport security, in particular, monitoring the functional state of drivers.

Mathematicity of physics is surprising, but it enables us to understand the laws of nature through the analysis of mathematical structures describing it. This concerns, however, only physics. The degree of the mathematization of biology is low, and attempts to mathematize it are limited to the application of mathematical methods used for the description of physical systems. When doing so, we are likely to commit an error of attributing to biological systems features that they do not have. Some argue that biology does need new mathematical methods conforming to its needs, and not known from physics. However, because of a specific complexity of biological systems, we should speak of their algorithmicity, rather than of their mathematicity. As an example of algorithmic approach one can indicate so called individual-based models used in ecology to describe population dynamics or fractal models applied to describe geometrical complexity of such biological structures as trees.

The dynamics of public attention to COVID-19 epidemic is studied. The level of public attention is described by the daily number of search requests in Google made by users from a given country. In the empirical part of the work, data on the number of requests and the number of infected cases for a number of countries are considered. It is shown that in all cases the maximum of public attention occurs earlier than the maximum daily number of newly infected individuals. Thus, for a certain period of time, the growth of the epidemics occurs in parallel with the decline in public attention to it. It is also shown that the decline in the number of requests is described by an exponential function of time. In order to describe the revealed empirical pattern, a mathematical model is proposed, which is a modification of the model of the decline in attention after a one-time political event. The model develops the approach that considers decision-making by an individual as a member of the society in which the information process takes place. This approach assumes that an individual’s decision about whether or not to make a request on a given day about COVID is based on two factors. One of them is an attitude that reflects the individual’s long-term interest in a given topic and accumulates the individual’s previous experience, cultural preferences, social and economic status. The second is the dynamic factor of public attention to the epidemic, which changes during the process under consideration under the influence of informational stimuli. With regard to the subject under consideration, information stimuli are related to epidemic dynamics. The behavioral hypothesis is that if on some day the sum of the attitude and the dynamic factor exceeds a certain threshold value, then on that day the individual in question makes a search request on the topic of COVID. The general logic is that the higher the rate of infection growth, the higher the information stimulus, the slower decreases public attention to the pandemic. Thus, the constructed model made it possible to correlate the rate of exponential decrease in the number of requests with the rate of growth in the number of cases. The regularity found with the help of the model was tested on empirical data. It was found that the Student’s statistic is 4.56, which allows us to reject the hypothesis of the absence of a correlation with a significance level of 0.01.

The collective behavior of crowd leaving a room is modeled. The model is based on molecular dynamics approach with a mixture of socio-psychological and physical forces. The new algorithm for complicatedly branched space is proposed. It suggests that each individual develops its own plan of escape, which is stochastically transformed during the evolution. The algorithm includes also the separation of original space into rooms with possible exits selected by individuals according to their probability distribution. The model is calibrated on the base of empirical data provided by fire case in the nightclub “Lame Horse” (Perm, 2009). The algorithm is realized as an end-user Java software. It is assumed that this tool could help to test the buildings for their safety for humans.

This article considers the task of multiclass classification of coniferous trees with varying degrees of damage by insect pests on images obtained using unmanned aerial vehicles (UAVs). We propose the use of convolutional neural networks (CNNs) for the classification of fir trees Abies sibirica and Siberian pine trees Pinus sibirica in unmanned aerial vehicles (UAV) imagery. In our approach, we develop three CNN models based on the classical U-Net architecture, designed for pixel-wise classification of images (semantic segmentation). The first model, Mo-U-Net, incorporates several changes to the classical U-Net model. The second and third models, MSC-U-Net and MSC-Res-U-Net, respectively, form ensembles of three Mo-U-Net models, each varying in depth and input image sizes. Additionally, the MSC-Res-U-Net model includes the integration of residual blocks. To validate our approach, we have created two datasets of UAV images depicting trees affected by pests, specifically Abies sibirica and Pinus sibirica, and trained the proposed three CNN models utilizing mIoULoss and Focal Loss as loss functions. Subsequent evaluation focused on the effectiveness of each trained model in classifying damaged trees. The results obtained indicate that when mIoULoss served as the loss function, the proposed models fell short of practical applicability in the forestry industry, failing to achieve classification accuracy above the threshold value of 0.5 for individual classes of both tree species according to the IoU metric. However, under Focal Loss, the MSC-Res-U-Net and Mo-U-Net models, in contrast to the third proposed model MSC-U-Net, exhibited high classification accuracy (surpassing the threshold value of 0.5) for all classes of Abies sibirica and Pinus sibirica trees. Thus, these results underscore the practical significance of the MSC-Res-U-Net and Mo-U-Net models for forestry professionals, enabling accurate classification and early detection of pest outbreaks in coniferous trees.

Radiopharmaceuticals with iodine radioisotopes are now widely used in imaging and non-imaging methods of nuclear medicine. When evaluating the results of radionuclide studies of the structural and functional state of organs and tissues, parallel modeling of the kinetics of radiopharmaceuticals in the body plays an important role. The complexity of such modeling lies in two opposite aspects. On the one hand, excessive simplification of the anatomical and physiological characteristics of the organism when splitting it to the compartments that may result in the loss or distortion of important clinical diagnosis information, on the other – excessive, taking into account all possible interdependencies of the functioning of the organs and systems that, on the contrary, will lead to excess amount of absolutely useless for clinical interpretation of the data or the mathematical model becomes even more intractable. Our work develops a unified approach to the construction of mathematical models of the kinetics of radiopharmaceuticals with iodine isotopes in the human body during diagnostic and therapeutic procedures of nuclear medicine. Based on this approach, three- and four-compartment pharmacokinetic models were developed and corresponding calculation programs were created in the C⁺⁺ programming language for processing and evaluating the results of radionuclide diagnostics and therapy. Various methods for identifying model parameters based on quantitative data from radionuclide studies of the functional state of vital organs are proposed. The results of pharmacokinetic modeling for radionuclide diagnostics of the liver, kidney, and thyroid using iodine-containing radiopharmaceuticals are presented and analyzed. Using clinical and diagnostic data, individual pharmacokinetic parameters of transport of different radiopharmaceuticals in the body (transport constants, half-life periods, maximum activity in the organ and the time of its achievement) were determined. It is shown that the pharmacokinetic characteristics for each patient are strictly individual and cannot be described by averaged kinetic parameters. Within the framework of three pharmacokinetic models, “Activity–time” relationships were obtained and analyzed for different organs and tissues, including for tissues in which the activity of a radiopharmaceutical is impossible or difficult to measure by clinical methods. Also discussed are the features and the results of simulation and dosimetric planning of radioiodine therapy of the thyroid gland. It is shown that the values of absorbed radiation doses are very sensitive to the kinetic parameters of the compartment model. Therefore, special attention should be paid to obtaining accurate quantitative data from ultrasound and thyroid radiometry and identifying simulation parameters based on them. The work is based on the principles and methods of pharmacokinetics. For the numerical solution of systems of differential equations of the pharmacokinetic models we used Runge–Kutta methods and Rosenbrock method. The Hooke–Jeeves method was used to find the minimum of a function of several variables when identifying modeling parameters.

The paper presents the results of research on the creation of a mathematical model of moral choice based on the development of the approach proposed by V. A. Lefebvre. Unlike V. A. Lefebvre, who considered a very speculative situation of a subject’s moral choice between abstract “good” and “evil” under pressure from the outside world, taking into account the subjective perception of this pressure by the subject, our study considers a more mundane and practically significant situation. The case is considered when the subject, when making decisions, is guided by his individual perception of the outside world (which may be distorted, for example, due to external purposeful informational influence on the subject and manipulation of his consciousness), and “good” and “evil” are not abstract, but are conditioned by a value system adopted in a particular society under consideration and tied to a specific ideology/religion, which may be different for different societies.

As a result of the conducted research, a basic mathematical model has been developed, and special cases of its application have been considered. Some patterns related to moral choice are revealed, and their formal description is given. In particular, the situation of manipulation of consciousness is considered in the language of the model, the law of reducing the “morality” of a society consisting of so-called free subjects (that is, those who strive to act in accordance with their intentions and correspond in their actions to the image of their “I”) is formulated.