All issues

Coffee berry disease (CBD), resulting from the Colletotrichum kahawae fungal pathogen, poses a severe risk to coffee crops worldwide. Focused on coffee berries, it triggers substantial economic losses in regions relying heavily on coffee cultivation. The devastating impact extends beyond agricultural losses, affecting livelihoods and trade economies. Experimental insights into coffee berry disease provide crucial information on its pathogenesis, progression, and potential mitigation strategies for control, offering valuable knowledge to safeguard the global coffee industry. In this paper, we investigated the mathematical model of coffee berry disease, with a focus on the dynamics of the coffee plant and Colletotrichum kahawae pathogen populations, categorized as susceptible, exposed, infected, pathogenic, and recovered (SEIPR) individuals. To address the system of nonlinear differential equations and obtain semi-analytical solution for the coffee berry disease model, a novel analytical approach combining the Shehu transformation, Akbari – Ganji, and Pade approximation method (SAGPM) was utilized. A comparison of analytical results with numerical simulations demonstrates that the novel SAGPM is excellent efficiency and accuracy. Furthermore, the sensitivity analysis of the coffee berry disease model examines the effects of all parameters on the basic reproduction number $R_0$. Moreover, in order to examine the behavior of the model individuals, we varied some parameters in CBD. Through this analysis, we obtained valuable insights into the responses of the coffee berry disease model under various conditions and scenarios. This research offers valuable insights into the utilization of SAGPM and sensitivity analysis for analyzing epidemiological models, providing significant utility for researchers in the field.

This paper focuses on the problem of modeling and analyzing dynamic regimes, both regular and chaotic, in systems of coupled populations in the presence of random disturbances. The discrete Ricker model is used as the initial deterministic population model. The paper examines the dynamics of two populations coupled by migration. Migration is proportional to the difference between the densities of two populations with a coupling coefficient responsible for the strength of the migration flow. Isolated population subsystems, modeled by the Ricker map, exhibit various dynamic modes, including equilibrium, periodic, and chaotic ones. In this study, the coupling coefficient is treated as a bifurcation parameter and the parameters of natural population growth rate remain fixed. Under these conditions, one subsystem is in the equilibrium mode, while the other exhibits chaotic behavior. The coupling of two populations through migration creates new dynamic regimes, which were not observed in the isolated model. This article aims to analyze the dynamics of corporate systems with variations in the flow intensity between population subsystems. The article presents a bifurcation analysis of the attractors in a deterministic model of two coupled populations, identifies zones of monostability and bistability, and gives examples of regular and chaotic attractors. The main focus of the work is in comparing the stability of dynamic regimes against random disturbances in the migration intensity. Noise-induced transitions from a periodic attractor to a chaotic attractor are identified and described using direct numerical simulation methods. The Lyapunov exponents are used to analyze stochastic phenomena. It has been shown that in this model, there is a region of change in the bifurcation parameter in which, even with an increase in the intensity of random perturbations, there is no transition from order to chaos. For the analytical study of noise-induced transitions, the stochastic sensitivity function technique and the confidence domain method are used. The paper demonstrates how this mathematical tool can be employed to predict the critical noise intensity that causes a periodic regime to transform into a chaotic one.

Eco-epidemiological models provide insights into factors influencing disease transmission and host population stability. This study developed two eco-epidemiological models to investigate the impacts of prey refuge availability and an Allee effect on dynamics. Model A incorporated these mechanisms, while model B did not. Both models featured predator – prey and disease transmission and were analyzed mathematically and via simulation. Model equilibrium states were examined locally and globally under differing parameter combinations representative of environmental scenarios. Model A and B demonstrated globally stable conditions within certain parameter ranges, signalling refuge and Allee effect terms promote robustness. Moreover, model A showed a higher potential toward extinction of the species as a result of incorporating the Allee effect. Bifurcation analyses revealed qualitative shifts in behavior triggered by modifications like altered predation mortality. Model A manifested a transcritical bifurcation indicating critical population thresholds. Additional bifurcation types were noticed when refuge and Allee stabilizing impacts were absent in model B. Findings showed disease crowding effect and that host persistence is positively associated with refuge habitat, reducing predator – prey encounters. The Allee effect also calibrated stability via heightened sensitivity to small groups. Simulations aligned with mathematical predictions. Model A underwent bifurcations at critical predator death rates impacting prey outcomes. This work provides a valuable framework to minimize transmission given resource availability or demographic alterations, generating testable hypotheses.

The paper considers the problems of mathematical description of deontological aspects influencing the behavior of decision makers. A methodology is proposed for correlating utilitarian (material) and deontological (value) aspects in their decision-making, taking into account their psychological characteristics. A mathematical model is proposed for the joint consideration of utilitarian and deontological factors in decision-making in various situations. Some patterns related to this consideration are identified, and their formal description is given. The model shows that there is a tendency for a gradual decrease in the level of deontology in evaluating alternatives when making decisions (compared to what the outside world inclines to) towards greater utilitarianism. Over time, this trend begins to influence public opinion and society’s attitude to moral norms, gradually reducing the overall level of morality in society. This process can be stopped only by constantly and purposefully maintaining a high level of deontology by society and the state (ideological work, promotion of traditional values, educational work at school, etc.), otherwise society will inevitably become utilitarian over time, focusing exclusively on material factors when making decisions.

In the future, it is planned to use the developed tools for analyzing specific situations, including for analyzing the patterns of civilizational cycles: the rise and fall of the Roman Empire, the USSR, and modern Western civilization).

In single-photon emission computed tomography (SPECT), patients with bone disorders receive a radiopharmaceutical (RP) that accumulates selectively in pathological lesions. Accurate quantification of RP uptake plays a critical role in disease staging, prognosis, and the development of personalized treatment strategies. Traditionally, the accuracy of quantitative assessment is evaluated through in vitro clinical trials using the standardized physical NEMA IEC phantom, which contains six spheres simulating lesions of various sizes. However, such experiments are limited by high costs and radiation exposure to researchers. This study proposes an alternative in silico approach based on numerical simulation using a digital twin of the NEMA IEC phantom. The computational framework allows for extensive testing under varying conditions without physical constraints. Analogous to clinical protocols, we calculated the recovery coefficient (RC_max), defined as the ratio of the maximum activity in a lesion to its known true value. The simulation settings were tailored to clinical SPECT/CT protocols involving ^99mTc for patients with bone-related diseases. For the first time, we systematically analyzed the impact of lesion-to-background ratios and post-reconstruction filtering on RC_max values. Numerical experiments revealed the presence of edge artifacts in reconstructed lesion images, consistent with those observed in both real NEMA IEC phantom studies and patient scans. These artifacts introduce instability into the iterative reconstruction process and lead to errors in activity quantification. Our results demonstrate that post-filtering helps suppress edge artifacts and stabilizes the solution. However, it also significantly underestimates activity in small lesions. To address this issue, we introduce post-reconstruction correction factors derived from our simulations to improve the accuracy of quantification in lesions smaller than 20 mm in diameter.

We consider a spatiotemporal model of a tritrophic system describing the interaction between prey, predator, and superpredator in an environment with nonuniform resource distribution. The model incorporates superpredator omnivory (Intraguild Predation, IGP), diffusion, and directed migration (taxis), the latter modeled using a logarithmic function of resource availability and prey density. The primary focus is on analyzing the multistability of the system and the role of cosymmetry in the formation of continuous families of steady-state solutions. Using a numerical-analytical approach, we study both spatially homogeneous and inhomogeneous steady-state solutions. It is established that under additional relations between the parameters governing local predator interactions and diffusion coefficients, the system exhibits cosymmetry, leading to the emergence of a family of stable steady-state solutions proportional to the resource function. We demonstrate that the cosymmetry is independent of the resource function in the case of a heterogeneous environment. The stability of stationary distributions is investigated using spectral methods. Violation of the cosymmetry conditions results in the breakdown of the solution family and the emergence of isolated equilibria, as well as prolonged transient dynamics reflecting the system’s “memory” of the vanished states. Depending on initial conditions and parameters, the system exhibits transitions to single-predator regimes (survival of either the predator or superpredator) or predator coexistence. Numerical experiments based on the method of lines, which involves finite difference discretization in space and Runge –Kutta integration in time, confirm the system’s multistability and illustrate the disappearance of solution families when cosymmetry is broken.

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.

Physical-mathematical model of drying of coal particles in the gas stream and the results of calculating the drying of the particles of brown coal in a drying tube are presented. It is shown that for the drying of coal can be used superheated water vapor. Thermodynamic model of drying of a particle in a drying tube are proposed. It allows to conduct a preliminary assessment of parameters of drying process.

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).

Comparative analysis of two models of porous medium (Dacry and Brinkman) on an example of mathematical simulation of transient natural convection in a porous vertical cylindrical cavity with heat-conducting shell of finite thickness in conditions of convective cooling from an environment has been carried out. The boundary-value problem of mathematical physics formulated in dimensionless variables such as stream function, vorticity and temperature has been solved by implicit finite difference method. The presented verification results validate used numerical approach and also confirm that the solution is not dependent on the mesh size. Features of the conjugate heat transfer problems with considered models of porous medium have been determined.