The paper discusses the numerical modeling of transport and diffusion of air pollutants in the atmospheric boundary layer. There was developed a mathematical model of industrial emissions spread in the atmosphere taking into account the deposition velocity of fine particles. The model is described by multidimensional partial differential equations with appropriate initial and boundary conditions. The basic laws of hydrothermodynamics were used in deriving the model. In order to obtain the numerical solution of the problem, we used one of the splitting methods according to physical processes involved (transport, diffusion and absorption), as well as a second-order implicit finite-difference scheme in time. Analysis of numerical results showed that the developed computational algorithm provides sufficient accuracy of the problem solution compared with field measurement data and it has a certain advantage over other numerical methods. In the course of computational experiments, there was determined the degree of influence of such parameters as wind speed and direction, absorption coefficient and physicomechanical properties of particles on the process of atmospheric air pollutants dispersion.

Myocardial infarction is one of the most severe forms of ischemic heart disease, associated with high mortality and disability worldwide. The accurate and reliable prediction of adverse cardiovascular events is critical for developing effective treatment strategies and improving outcomes in cardiac rehabilitation. Traditional prognostic models, such as the GRACE and TIMI scores, often lack the flexibility to incorporate a wide range of contemporary clinical predictors. Therefore, machine learning methods, particularly deep neural networks, have recently emerged as promising alternatives capable of enhancing predictive accuracy and enabling more personalized care. This study presents a multitask deep learning model designed to simultaneously address two related tasks: multidimensional binary classification of myocardial infarction complications and multiclass classification of mortality causes. The model was trained on a dataset of 1700 patients, encompassing 111 clinical and demographic features. Experimental results demonstrate high predictive accuracy and the model’s capacity to capture complex interactions among risk factors, suggesting its potential as a valuable tool for clinical decision support in cardiology. Comparative analysis confirms that the proposed multitask approach performs comparably to, or better than, conventional machine learning models. Future research will focus on refining the model and validating its generalizability in real-world clinical environments.

The applied problems of hydrodynamics, heat and mass transfer often claim the use of numerical solution techniques in curvilinear coordinates. Such an approach is quite natural and common for flows modelling, particularly in atmosphere dynamics. The paper deals with development of atmospheric dispersion model and numerical algorithm using approximations in curvilinear coordinate systems. The approach allowed significantly simplifying the formulas and reducing the amount of computations during experiments on forecasting the air pollutants concentration nearby existing industrial plants.

The spread of air pollutants in the atmospheric boundary layer is mainly conditioned by complex dynamic processes of the air mass movement and turbulent diffusion. Therefore, in meeting the challenges of monitoring and forecasting the ecological conditions of the atmosphere, first of all, it is necessary to take into account the air flow characteristics and the laws governing their changes. In this regard, one of the essential aspects in studying of the air flow structure is consideration of the dependence of the wind profile on the atmospheric stability and surface roughness. Thus, this work purpose is to study the influence of the vertical wind profile on the process of the spread of harmful emissions in the atmosphere based on the developed mathematical tools and GIS technologies. The results of computational experiments on determination the air flow characteristics at given heights and at various values of the ground-level wind speed and the roughness coefficient are presented in the paper, as well as the results of numerical calculations demonstrating the influence of the horizontal and vertical components of the wind speed on the distribution of suspended aerosol impurities in the considered region.