International Scientific Journals
of Scientific Technical Union of Mechanical Engineering "Industry 4.0"

The present study concerns the simulation, in two dimensions, by the finite element method, of the behaviour of the magnetic field created by sources of equivalent neuronal currents by considering a simplified model of a diagnostic device used in MEG (Magnetoencephalography). The simplified geometric model is composed of the head, the magnetic field sensors and the sources of equivalent currents representing the neurons. The geometric model of the head is represented by 3 layers which are brain, bone and skin. The sensors placed above the part of the skin make it possible to calculate the electric voltage induced by the magnetic field resulting from the sources of equivalent currents produced by the neurons. Neurons are represented by equidistant point current sourcesThe Maxwell-multi physics software has been used.

A quantum model of excitation transfer from a donor molecule to an acceptor molecule through a biomolecule represented by a quasi-one-dimensional molecular chain is proposed. The sites of the chain correspond to the structural elements of biomolecules, such as amino acid residues linked into the chain by peptide bonds in proteins or nucleotides in RNA and DNA. Particular attention is paid to the emergence of quantum entanglement between the donor and acceptor molecules as the specific type of quantum correlations, which provides an intramolecular quantum channel for information transmission.

This work presents a numerical Finite Element Modeling of mechanical behavior of a human vein under influence of medical compression sock. The FE Model is developed in form of structural transient analysis by help of program product Ansys. The geometry of the vein and the muscle is assumed as an idealized, and consists of two coaxial cylinders. The stocking pressure is translated to the vein through the muscles contractions, surrounding tissues and the skin. Moreover, such a pressure and its variations, as well the position of the vein in the muscle environment, should also have influence on the functioning of venous valves and on the lymphatic system drainage. Because of preliminary character of this elaboration, these aspects are not discussed here.
The work set-up aims to establish principally how the stocking pressure loads the vein wall depending on different venous elasticity under given constant muscle elasticity.
The mechanical behavior of vein possessing elastic module E=30kPa and 100kPa is considered under stocking pressure Pst=25mmHg and 60.8mmHg and muscle tissue with elastic module Em=12kPa. The displacements in the vein and muscle with corresponded distributions of stress and strain states are identified in the both two elements.
It is concluded, that these two pressures induce similar stress values in the vein walls depending on the two venous elastic modules, correspondingly. Based on that, it is suggested that a 3-Dimensional space of the geometry, pressure and the elastic modules could be existed. In such a space, optimal patient-orientated values of the pressure depending on the geometrical sizes and elasticity should be available.

This study investigates the application of Bayesian statistical methods for comparing ocular perfusion pressure (OPP) between glaucoma and non-glaucoma populations, contrasting it with traditional frequentist approaches. Using OPP measurements from two patient groups, we employ partially informed Bayesian models to test the hypothesis of no difference in means between the groups. We calculate Bayes factor using Savage-Dickey density ratio and offer insights in the hypothesis beyond p-values. The results highlight the advantages of the Bayesian approach, including its flexibility in incorporating prior information and interpreting evidence. We discuss the limitations and potential biases introduced by the choice of priors. This paper contributes to the understanding of Bayesian inference in ophthalmic research and emphasizes its potential for hypothesis testing in clinical studies.

The present work concerns the development of a model which have the capability to represent accurately the skin/sensor contact in an electromagnetic problem study. The later consist of elctro-encyphalography (EEG ) signals encountered in neuroscience health diagnosis. The electromagnetic problem studied is governed by Poisson’s equation and solved using finite element method. The skin/sensor contact is modeled by an analytical solution, which is coupled to finite element resolution. The signals induced by neuronal equivalent charges are presented and investigated. A comparison with existing results is then performed. Neuron loss effect is also investigated.

This elaboration proposes results obtained during initial stages of numerical modeling of the function of aortic heart valve depending on its elastic module and the aortic elastic module.
The actuality of such an elaboration could be based on the advancing progress in the material sciences, as well as on the increasing opportunities given by the development of the medical diagnostic technics for observation of processes in the human organism and the development of computational technics.
The work and the interactions between the aortic valve and the aorta is here structurally modeled according to Finite Element Method by help of Ansys commercial product. Elastic material models are assumed for the materials of aorta and aortic valve. The geometry of the aortic valve and the aorta are designed as averaged ones according to suggested reference data. The boundary conditions are assumed according to reference data about left-ventricle blood pressure and the aortic blood pressure. These material models, geometry and boundary conditions could be reformulated according each separately given case. That will give possibilities of development of the subject of this work following as called patient-orientated model.
The displacements, the stress and strain distributions in both aorta and valve are established depending on both blood pressures aortic and left-ventricle depending on two aortic elastic modules 0.476 and 1MPa under elastic modules of the sinotubular junction 15.34MPa and sinus of Valsalva 20.24MPa. Pumping functions of the heart and the aorta are numerically observed depending on the two aortic elasticmodules. Some variations in the elastic modules of the sinotubular junction and sinuses of Valsalva are commented.
The proposed finite element model and the obtained results could open future possibilities to enlarge this work, for example, through variations in the four elastic modules, variations in the aortic geometry also including additional branches to the aorta or modeling of interactions between pulsating blood flow and arterial-valve structures, also not excluding real experimental formulation or design and synthesis of new biological materials.

Artificial intelligence (AI) and machine learning techniques have revolutionized various fields, including 3D modelling of anatomical structures. One such area of research involves the use of AI and machine learning algorithms for approximating spherical harmonics functions in the realm of anatomical structure modelling.
Spherical harmonics functions are mathematical tools that describe functions on the surface of a sphere. In 3D modelling of anatomical structures, these functions are employed to represent complex surface details with accurate precision. However, calculating values of these functions for complex anatomical structures is time-consuming and prone to errors. This is where AI and machine learning come into play.
Using AI and machine learning algorithms, we have developed models that can automatically learn the inherent patterns and complexities of anatomical structures from vast amounts of training data. These models can then approximate the spherical harmonics functions that accurately represent the surface details of these structures. This automation significantly reduces the time and effort required in the 3D
modelling process.

The current publication presents an approach for the elaboration of a disposable microfluidic hollow micro-channel using 2 photon polymerization technology and Photonic Professional GT2 (Nanoscribe, Germany) equipment. The design of a 3D model of a microchannel is realized by the CAD analysis software – SOLIDWORKS. A suitable laminar flow is generated by using computational fluid dynamics (CFD) software. As a result, the critical points of the pressure, velocity, and wall shear stress into the microfluidic channel are obtained. A real prototype of the hollow microfluidic device is created, using a highly innovative technology of 3D nanoprinting by twophoton polymerization. Experimental studies with dilute erythrocyte suspensions are conducted to test the functionality of the developed prototype of nano 3D printed microchannel.

A spongy bone can be considered a multi-porous area with its fissures and pores as the most evident components of a double porous system. The work studies the stress-strain state of a spongy jawbone near the implant under occlusal loading. A mathematical model of the problem is the contact problem of the theory of elasticity between the implant and the jawbone. The problem is solved by using the boundary element methods, which are based on the solutions of Flamant’s (BEMF) and Boussinesq’s (BEMB) problems. The cases of various lengths of implant diameter are considered. Stressed contours (isolines) in the jawbone are drafted and the results obtained by BEMF and BEMB for the different diameter implants are compared.

The present study aims to model and analyze the images of induced in vitro blood clots from healthy donors and patients with type 2 diabetes mellitus (T2DM). By using the BioFlux microfluidic system, blood clots are induced at varying shear rates, and for different fibrinogen concentrations: native and highly modified. The fiber diameter of blood clots is analyzed by the scanning electron microscope (SEM). The obtained images of blood clots are imported as input data into the Image J software environment, after which obtained results for the area, number, and fibrin fiber diameter of blood clots, are further processed in a program developed in IntelliJ IDEA. It is found that patients with T2DM at the native concentration of fibrinogen at all studied shear rates form more blood clots having a larger total area, in comparison with the control group. At the higher modified fibrinogen concentration with increasing shear rate, the group with T2DM forms a smaller number of blood clots with a larger area, compared to healthy donors. From the SEM images, it is found, that denser fibrin networks are formed with increased fibrinogen concentration, which contains numerous thick fibrin fibеrs in healthy and diabetic individuals.

A dose assessment of external neutron irradiation at high-energy accelerating complexes, where neutron energy can be in a wide range of 10-8 to 103 MeV, is important for staff radiation safety. In this case, Bonner multi-sphere spectrometers can be used to register the neutron flow. The work proposes a method for unfolding the neutron spectrum by Bonner spectrometer readings, based on the use of the detector sensitivity functions as the basic functions of decomposition of the spectrum under consideration. To find the decomposition coefficients, the system of integral Fredholm equations of the 1st kind is used. From a mathematical point of view, this problem is the illposed one and is solved numerically using the A.N. Tikhonov regularization method. According to the received energy spectrum of neutrons, an assessment of the dose of irradiation is made at the detection locations. The results of unfolding the neutron spectrum at the JINR Phasotron and the dose to its personnel are presented.

Agent-based modeling proved to be a powerful tool for studying the complex multifactorial processes that take place in human population. In this paper we describe how this approach can be used to study the spread of airborne infections in a big city and the ways to control them. Agent-based modeling includes three main stages: a creating a synthetic population, simulation of disease spread in synthetic population during a fixed time period, and an analysis of the results. We created the population of 10 million agents and united them in a complex network according to their individual characteristics such as age, sex, marital status and occupation. In addition, each agent has a property that characterizes its state of health: susceptible, infected, and recovered. A susceptible agent can become infected if has an infected agent among its contacts and if an event of disease transmission occurs. Disease transmission is simulated as a random event with probability p which calculated for every pair susceptible-infected and depends on their individual characteristics and on the length of the contact. In so doing, the heterogeneity in a number of contacts and in resistance can be modelled. This approach was applied to model a dynamic of COVID-19 in Moscow during the period between October 2020 and December 2021.