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A mathematical model describing the dynamics of HIV-1 infection in a single lymph node during the initial period of infection development is presented. Within the framework of the model, the infection of an individual is set by a nonnegative finite function describing the rate of entry of the initial viral particles into the lymph node. The equations of the model are derived with consideration of two factors: 1) the interaction of viral particles with naive CD4+ T lymphocytes in various phases of the cell cycle; 2) contact interaction between multiplying naive CD4+ T lymphocytes and infected CD4+ T lymphocytes producing viral particles. The specific feature of intercellular contact interactions is the formation of complexes consisting of pairs of these cells. The duration of the complexes’ existence is determined by the distribution functions over finite time intervals. The model is presented as a high-dimensional system of nonlinear delay differential equations, including two equations with distributed delay, and is supplemented with non-negative initial data. In the absence of HIV-1 infection, the model is reduced to four delay differential equations describing the number of naive CD4+ T-lymphocytes in different phases of the cell cycle. The global solvability of the model (the existence and uniqueness of the solution on the semi-axis) is determined, and the non-negativity of the solution components is established. To carry out computational experiments with the model, an algorithm for numerically solving the used system of differential equations are developed based on the semi-implicit Euler scheme for the case of uniform distribution of durations of the complexes existence. The results of computational experiments aimed at approximation the numerical solution of the model to describing the kinetics of HIV-1 infection spread in its acute phase, including the eclipse phase, are presented. The variable used as the observable is the variable describing the number of viral particles per milliliter of blood on days 10–12 after the onset of acute infection. The dynamics of the observable variable is numerically studied depending on the variation of the model parameters reflecting the patterns of complex formation and the formation of cells producing viral particles. The possibility of attenuation of HIV-1 infection in the lymph node at certain values of some of the model parameters is shown.

Dam safety assessment increasingly relies on continuous monitoring of hydrometeorological variables; however, identifying early-stage instability remains challenging due to complex spatio-temporal interactions and highly imbalanced failure observations. This study proposes a deep learning framework based on a Convolutional Bidirectional Gated Recurrent Unit (CNN–BiGRU) architecture to learn spatio-temporal precursors of dam instability from multivariate hydrometeorological time series. The convolutional component extracts localized temporal patterns associated with short-term fluctuations, while the bidirectional recurrent structure captures long-range dependencies and evolving dynamics preceding critical states.

The proposed model is evaluated on a real-world dam monitoring dataset comprising multiple water-level, meteorological, and derived dynamic indicators. To address class imbalance, a cost-sensitive training strategy using class weighting is adopted without synthetic oversampling. Experimental results demonstrate strong predictive performance, achieving an accuracy of 0.961, precision of 0.901, recall of 0.757, and an F1-score of 0.823. The model further attains a ROC-AUC of 0.907 and a PR-AUC of 0.819, indicating robust discrimination capability under imbalanced conditions.

Feature importance analysis reveals that short- and medium-term water level variability, including rolling standard deviation, volatility, and multi-scale gradients, play a dominant role in characterizing pre-instability behavior, providing physically interpretable insights into dam response dynamics. The findings suggest that the CNN–BiGRU framework effectively captures meaningful spatio-temporal precursors and offers a reliable data-driven tool for supporting dam safety monitoring and decision-making under real operational conditions.

A model, describing the influence of external factors on temporal evolution of phytoplankton distribution in a horizontally-homogenous water layer, is presented. This model is based upon the reactiondiffusion equation and takes into account the main factors of influence: mineral nutrients, insolation and temperature. The mineral nutrients and insolation act oppositely on spatial phytoplankton distribution. The results of numerical modeling are presented and the prospect of applying this model to reconstruction of phytoplankton distribution from sea-surface satellite data is discussed. The model was used to estimate the chlorophyll content of the Peter the Great Bay (Sea of Japan).

In the paper the model for a one-dimensional non-equilibrium riverbed process is proposed. The model takes into account the suspended and bed-load sediment transport. The bed-load transport is determined by using the original formula. This formula was derived from the thin bottom layer motion equation. The formula doesn’t contain new phenomenological parameters and takes into account the influence of bed slope, granulometric and physical mechanical parameters on the bed-load transport. A number of the model test problems are solved for the verification of the proposed mathematical model. The comparison of the calculation results with the established experimental data and the results of other authors is made. It was shown, that the obtained results have a good agreement with the experimental data in spite of the relative simplicity of the proposed mathematical model.

The article presents the results of computer simulations aimed to assess the influence of tree spatial locations (planting schemes) on the productivity and the dynamics of soil fertility in forest plantations. The growth of aspen (Populus tremula L.) in plantations with short rotation (30 years) was simulated in the EFIMOD system of models with the soil and climatic data matching forested lands in the Mari El Republic. The outcome reveals that higher biomass rates, increase in soil organic matter stocks, and the minimal loss of soil nitrogen can be obtained when the distance between trees in the row equals 1–4 m and 4–6 м in aisles.

Technical diagnosis’ current trends are connected to application of FEM computer simulation, which allows, to some extent, replace real experiments, reduce costs for investigation and minimize risks. Computer simulation, just at the stage of research and development, allows carrying out of diagnostics of equipment to detect permissible fluctuations of parameters of equipment’s work. Peculiarity of diagnosis of rolling equipment is that functioning of rolling equipment is directly tied with manufacturing of product with required quality, including accuracy. At that design of techniques of technical diagnosis and diagnostical modelling is very important. Computer simulation of cold rolling of strip was carried out. At that upper working roll was doing vibrations in horizontal direction according with published data of experiments on continuous 1700 rolling mill. Vibration of working roll in a stand appeared due to gap between roll’s craft and guide in a stand and led to periodical fluctuations of strip’s thickness. After computer simulation with the help of DEFORM software strip with longitudinal and transversal thickness variation was gotten. Visualization of strip’s geometrical parameters, according with simulation data, corresponded to type of inhomogeneity of surface of strip rolled in real. Further analysis of thickness variation was done in order to identify, on the basis of simulation, sources of periodical components of strip’s thickness, whose reasons are malfunctions of equipment. Advantage of computer simulation while searching the sources of forming of thickness variation is that different hypothesis concerning thickness formations may be tested without conducting real experiments and costs of different types may be reduced. Moreover, while simulation, initial strip’s thickness will not have fluctuations as opposed to industrial or laboratorial experiments. On the basis of spectral analysis of random process, it was established that frequency of changing of strip’s thickness after rolling in one stand coincides with frequency of working roll’s vibration. Results of computer simulation correlate with results of the researches for 1700 mill. Therefore, opportunity to apply computer simulation to find reasons of formation of thickness variation of strip on the industrial rolling mill is shown.

Transport of respiratory gases by respiratory and circulatory systems is one of the most important processes associated with living conditions of the human body. Significant and/or long-term deviations of oxygen and carbon dioxide concentrations from the normal values in blood can be a reason of significant pathological changes with irreversible consequences: lack of oxygen (hypoxia and ischemic events), the change in the acidbase balance of blood (acidosis or alkalosis), and others. In the context of a changing external environment and internal conditions of the body the action of its regulatory systems aimed at maintaining homeostasis. One of the major mechanisms for maintaining concentrations (partial pressures) of oxygen and carbon dioxide in the blood at a normal level is the regulation of minute ventilation, respiratory rate and depth of respiration, which is caused by the activity of the central and peripheral regulators.

In this paper we propose a mathematical model of the regulation of pulmonary ventilation parameter. The model is used to calculate the minute ventilation adaptation during hypoxia and hypercapnia. The model is developed using a single-component model of the lungs, and biochemical equilibrium conditions of oxygen and carbon dioxide in the blood and the alveolar lung volume. A comparison with laboratory data is performed during hypoxia and hypercapnia. Analysis of the results shows that the model reproduces the dynamics of minute ventilation during hypercapnia with sufficient accuracy. Another result is that more accurate model of regulation of minute ventilation during hypoxia should be developed. The factors preventing from satisfactory accuracy are analysed in the final section.

Respiratory function is one of the main limiting factors of the organism during intense physical activities. Thus, it is important characteristic of high performance sport and extreme physical activity conditions. Therefore, the results of this study have significant application value in the field of mathematical modeling in sport. The considered conditions of hypoxia and hypercapnia are partly reproduce training at high altitude and at hypoxia conditions. The purpose of these conditions is to increase the level of hemoglobin in the blood of highly qualified athletes. These conditions are the only admitted by sport committees.

The article deals with the process of creating an effective algorithm for determining the amount of emitted quanta from an X-ray tube in computer tomography (CT) studies. An analysis of domestic and foreign literature showed that most of the work in the field of radiometry and radiography takes the tabulated values of X-ray absorption coefficients into account, while individual dose factors are not taken into account at all since many studies are lacking the Dose Report. Instead, an average value is used to simplify the calculation of statistics. In this regard, it was decided to develop a method to detect the amount of ionizing quanta by analyzing the noise of CT data. As the basis of the algorithm, we used Poisson and Gauss distribution mathematical model of owns’ design of logarithmic value. The resulting mathematical model was tested on the CT data of a calibration phantom consisting of three plastic cylinders filled with water, the X-ray absorption coefficient of which is known from the table values. The data were obtained from several CT devices from different manufacturers (Siemens, Toshiba, GE, Phillips). The developed algorithm made it possible to calculate the number of emitted X-ray quanta per unit time. These data, taking into account the noise level and the radiuses of the cylinders, were converted to X-ray absorption values, after which a comparison was made with tabulated values. As a result of this operation, the algorithm used with CT data of various configurations, experimental data were obtained, consistent with the theoretical part and the mathematical model. The results showed good accuracy of the algorithm and mathematical apparatus, which shows reliability of the obtained data. This mathematical model is already used in the noise reduction program of the CT of own design, where it participates as a method of creating a dynamic threshold of noise reduction. At the moment, the algorithm is being processed to work with real data from computer tomography of patients.

In this paper, we proposed a two-dimensional chemo-mechanical model of the growth of invasive carcinoma in epithelial tissue. Each cell is modeled by an elastic polygon, changing its shape and size under the influence of pressure forces acting from the tissue. The average size and shape of the cells have been calibrated on the basis of experimental data. The model allows to describe the dynamic deformations in epithelial tissue as a collective evolution of cells interacting through the exchange of mechanical and chemical signals. The general direction of tumor growth is controlled by a pre-established linear gradient of nutrient concentration. Growth and deformation of the tissue occurs due to the mechanisms of cell division and intercalation. We assume that carcinoma has a heterogeneous structure made up of cells of different phenotypes that perform various functions in the tumor. The main parameter that determines the phenotype of a cell is the degree of its adhesion to the adjacent cells. Three main phenotypes of cancer cells are distinguished: the epithelial (E) phenotype is represented by internal tumor cells, the mesenchymal (M) phenotype is represented by single cells and the intermediate phenotype is represented by the frontal tumor cells. We assume also that the phenotype of each cell under certain conditions can change dynamically due to epithelial-mesenchymal (EM) and inverse (ME) transitions. As for normal cells, we define the main E-phenotype, which is represented by ordinary cells with strong adhesion to each other. In addition, the normal cells that are adjacent to the tumor undergo a forced EM-transition and form an M-phenotype of healthy cells. Numerical simulations have shown that, depending on the values of the control parameters as well as a combination of possible phenotypes of healthy and cancer cells, the evolution of the tumor can result in a variety of cancer structures reflecting the self-organization of tumor cells of different phenotypes. We compare the structures obtained numerically with the morphological structures revealed in clinical studies of breast carcinoma: trabecular, solid, tubular, alveolar and discrete tumor structures with ameboid migration. The possible scenario of morphogenesis for each structure is discussed. We describe also the metastatic process during which a single cancer cell of ameboid phenotype moves due to intercalation in healthy epithelial tissue, then divides and undergoes a ME transition with the appearance of a secondary tumor.

The most important principle of military science and border security is the principle of concentrating the main efforts on the main directions and tasks. At the tactical level, there are many mathematical models for computing the optimal resource allocation by directions and objects, whereas at the state level there are no corresponding models. Using the statistical data on the results of the protection of the US border, an exponential type border production function parameter is calculated that reflects the organizational and technological capabilities of the border guard. The production function determines the dependence of the probability of detaining offenders from the density of border guards per kilometer of the border. Financial indicators in the production function are not taken into account, as the border maintenance budget and border equipment correlate with the number of border agents. The objective function of the border guards is defined — the total prevented damage from detained violators taking into account their expected danger for the state and society, which is to be maximized. Using Slater's condition, the solution of the problem was found — optimal density of border guard was calculated for the regions of the state. Having a model of resource allocation, the example of the three border regions of the United States has also solved the reverse problem — threats in the regions have been assessed based on the known allocation of resources. The expected danger from an individual offender on the US-Canada border is 2–5 times higher than from an offender on the US-Mexican border. The results of the calculations are consistent with the views of US security experts: illegal migrants are mostly detained on the US-Mexican border, while potential terrorists prefer to use other channels of penetration into the US (including the US-Canadian border), where the risks of being detained are minimal. Also, the results of the calculations are consistent with the established practice of border protection: in 2013 the number of border guards outside the checkpoints on the US-Mexican border increased by 2 times compared with 2001, while on the American-Canadian border — 4 times. The practice of border protection and the views of specialists give grounds for approval of the verification of the model.