Lviv Polytechnic National University (Ukrainian: Націона́льний університе́т «Льві́вська політе́хніка») is the largest scientific university in Lviv. Since its foundation in 1816, it has been one of the most important centres of science and technological development in Central Europe. In the interbellum period, the Polytechnic was one of the most important technical colleges in Poland, together with the Warsaw Polytechnic. In 2020, Lviv Polytechnic was ranked globally among the top 1000 universities according to Times Higher Education. As of 2019, there were approximately 35,000 students in the university.
The relevance of the study is due to the growing number of diseases of the cerebrovascular system, in particular stroke, which is one of the leading causes of disability and mortality in the world. To improve stroke risk prediction models in terms of efficiency and interpretability, we propose to integrate modern machine learning algorithms and data dimensionality reduction methods, in particular XGBoost and optimized principal component analysis (PCA), which provide data structuring and increase processing speed, especially for large datasets. For the first time, explainable artificial intelligence (XAI) is integrated into the PCA process, which increases transparency and interpretation, providing a better understanding of risk factors for medical professionals. The proposed approach was tested on two datasets, with accuracy of 95% and 98%. Cross-validation yielded an average value of 0.99, and high values of Matthew's correlation coefficient (MCC) metrics of 0.96 and Cohen's Kappa (CK) of 0.96 confirmed the generalizability and reliability of the model. The processing speed is increased threefold due to OpenMP parallelization, which makes it possible to apply it in practice. Thus, the proposed method is innovative and can potentially improve forecasting systems in the healthcare industry.
A two-stage synthesis of the Cu2O nanoparticles–clinoptilolite composite was carried out, which involved ultrasonic cavitation-intensified ion exchange of cations in the clinoptilolite framework for Cu2+ ions from an aqueous solution of copper sulfate and reduction of Cu2+ ions to Cu2O nanoparticles with hydrazine. In addition to the clinoptilolite peaks, the diffractogram of the synthesized material contained other peaks, which were mutually consistent with the cuprite (Cu2O) model with a cubic structure, and the average size of the Cu2O crystallite, calculated from the reflection assigned to the (111) plane, was approximately 13 nm. Pseudospherical Cu2O nanoparticles were uniformly distributed over the surface of the clinoptilolite framework, and the average size of Cu2O nanoparticles was approximately 61 nm. The Cu2O nanoparticles–clinoptilolite composite was tested as a catalyst for the potassium periodate decomposition during the Acid Red 14 dye degradation in an ultrasonic cavitation field. A dye degradation degree of 96.9
The mechanisms of hydrogen-induced failure and the processes of hydrogen transport in metals are considered. A mathematical model of hydrogen diffusion which accounts for the interaction between local elastoplastic deformations and hydrogen diffusion is proposed. The distribution of hydrogen in the vicinity of crack-like defects on the inner surface of steel pipelines under internal pressure using the finite element method is analyzed. Analytical dependences to assess the local hydrogen concentration near defects of various geometric shapes are derived. It is established that with increasing internal pressure, the concentration of both diffusible and trapped hydrogen significantly increases, contributing to hydrogen embrittlement of the material. The obtained results can be used to predict the service life of pipelines in hydrogen power applications.
This paper extends the frequency symbolic method (FS method) for analyzing linear periodically time-varying (LPTV) circuits to highly complex circuits. It has been demonstrated that this extension is achieved by applying the d-tree method to the FS method developed by the authors. At the same time, the d-tree method, based on the nodal voltage method and extended to LPTV circuits, has demonstrated high efficiency, making it possible to analyze circuits of high complexity. The paper considers the problem of transforming a system of linear integro-differential equations describing a circuit into a system of linear differential equations, which requires the application of L.A. Zadeh’s equation in the FS method. Two methods for eliminating integral expressions from a system of differential equations are proposed, one of which (the variable substitution method) is implemented in the UDF MAOPCs program. The reverse transformation to the original variables in the form of nodal voltages is proposed to be performed by differentiating transfer functions or multiplying them by the corresponding values of complex variables associated with individual harmonic components present in the transfer function. The results of analyzing a highly complex LPTV circuit, containing 33 nodes and 32 parametric elements, have been presented.
Methodology for analyzing the stress-strain state of the composite plate elements of structures weakened by the double-periodic system of the openings is developed. The determination of stresses and effective elastic constants is carried out using the singular integral equations. The kernels of the equations presented in a simple form are constructed using Lekhnitski’s method and Weierstrass quasi-periodic functions. The stress state of the plates with elliptical and rectangular openings with rounded corners in the main rectangular and parallelogram shaped periods is analyzed. The effective elastic constants for the plates with the main periods and openings of various shapes made of orthotropic materials or materials with general anisotropy are calculated.
