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The biomass growth yield is the ratio of the newly synthesized substance of growing cells to the amount of the consumed substrate, the source of matter and energy for cell growth. The yield is a characteristic of the efficiency of substrate conversion to cell biomass. The conversion is carried out by the cell metabolism, which is a complete aggregate of biochemical reactions occurring in the cells.

This work newly considers the problem of maximal cell growth yield prediction basing on balances of the whole living cell metabolism and its fragments called as partial metabolisms (PM). The following PM’s are used for the present consideration. During growth on any substrate we consider i) the standard constructive metabolism (SCM) which consists of identical pathways during growth of various organisms on any substrate. SCM starts from several standard compounds (nodal metabolites): glucose, acetyl-CoA 2-oxoglutarate, erythrose-4-phosphate, oxaloacetate, ribose-5- phosphate, 3-phosphoglycerate, phosphoenolpyruvate, and pyruvate, and ii) the full forward metabolism (FM) — the remaining part of the whole metabolism. The first one consumes high-energy bonds (HEB) formed by the second one. In this work we examine a generalized variant of the FM, when the possible presence of extracellular products, as well as the possibilities of both aerobic and anaerobic growth are taken into account. Instead of separate balances of each nodal metabolite formation as it was made in our previous work, this work deals at once with the whole aggregate of these metabolites. This makes the problem solution more compact and requiring a smaller number of biochemical quantities and substantially less computational time. An equation expressing the maximal biomass yield via specific amounts of HEB formed and consumed by the partial metabolisms has been derived. It includes the specific HEB consumption by SCM which is a universal biochemical parameter applicable to the wide range of organisms and growth substrates. To correctly determine this parameter, the full constructive metabolism and its forward part are considered for the growth of cells on glucose as the mostly studied substrate. We used here the found earlier properties of the elemental composition of lipid and lipid-free fractions of cell biomass. Numerical study of the effect of various interrelations between flows via different nodal metabolites has been made. It showed that the requirements of the SCM in high-energy bonds and NAD(P)H are practically constants. The found HEB-to-formed-biomass coefficient is an efficient tool for finding estimates of maximal biomass yield from substrates for which the primary metabolism is known. Calculation of ATP-to-substrate ratio necessary for the yield estimation has been made using the special computer program package, GenMetPath.

Metal hydrides are an interesting class of chemical compounds that can reversibly bind a large amount of hydrogen and are, therefore, of interest for energy applications. Understanding the factors affecting the kinetics of hydride formation and decomposition is especially important. Features of the material, experimental setup and conditions affect the mathematical description of the processes, which can undergo significant changes during the processing of experimental data. The article proposes a general approach to numerical modeling of the formation and decomposition of metal hydrides and solving inverse problems of estimating material parameters from measurement data. The models are divided into two classes: diffusive ones, that take into account the gradient of hydrogen concentration in the metal lattice, and models with fast diffusion. The former are more complex and take the form of non-classical boundary value problems of parabolic type. A rather general approach to the grid solution of such problems is described. The second ones are solved relatively simply, but can change greatly when model assumptions change. Our experience in processing experimental data shows that a flexible software tool is needed; a tool that allows, on the one hand, building models from standard blocks, freely changing them if necessary, and, on the other hand, avoiding the implementation of routine algorithms. It also should be adapted for high-performance systems of different paradigms. These conditions are satisfied by the HIMICOS library presented in the paper, which has been tested on a large number of experimental data. It allows simulating the kinetics of formation and decomposition of metal hydrides, as well as related tasks, at three levels of abstraction. At the low level, the user defines the interface procedures, such as calculating the time layer based on the previous layer or the entire history, calculating the observed value and the independent variable from the task variables, comparing the curve with the reference. Special algorithms can be used for solving quite general parabolic-type boundary value problems with free boundaries and with various quasilinear (i.e., linear with respect to the derivative only) boundary conditions, as well as calculating the distance between the curves in different metric spaces and with different normalization. This is the middle level of abstraction. At the high level, it is enough to choose a ready tested model for a particular material and modify it in relation to the experimental conditions.

The article is devoted to the construction and investigation of an averaged mathematical model of an aluminum-cobalt-molybdenum hydrocracking catalyst oxidative regeneration. The oxidative regeneration is an effective means of restoring the activity of the catalyst when its granules are coating with coke scurf.

The mathematical model of this process is a nonlinear system of ordinary differential equations, which includes kinetic equations for reagents’ concentrations and equations for changes in the temperature of the catalyst granule and the reaction mixture as a result of isothermal reactions and heat transfer between the gas and the catalyst layer. Due to the heterogeneity of the oxidative regeneration process, some of the equations differ from the standard kinetic ones and are based on empirical data. The article discusses the scheme of chemical interaction in the regeneration process, which the material balance equations are compiled on the basis of. It reflects the direct interaction of coke and oxygen, taking into account the degree of coverage of the coke granule with carbon-hydrogen and carbon-oxygen complexes, the release of carbon monoxide and carbon dioxide during combustion, as well as the release of oxygen and hydrogen inside the catalyst granule. The change of the radius and, consequently, the surface area of coke pellets is taken into account. The adequacy of the developed averaged model is confirmed by an analysis of the dynamics of the concentrations of substances and temperature.

The article presents a numerical experiment for a mathematical model of oxidative regeneration of an aluminum-cobalt-molybdenum hydrocracking catalyst. The experiment was carried out using the Kutta–Merson method. This method belongs to the methods of the Runge–Kutta family, but is designed to solve stiff systems of ordinary differential equations. The results of a computational experiment are visualized.

The paper presents the dynamics of the concentrations of substances involved in the oxidative regeneration process. A conclusion on the adequacy of the constructed mathematical model is drawn on the basis of the correspondence of the obtained results to physicochemical laws. The heating of the catalyst granule and the release of carbon monoxide with a change in the radius of the granule for various degrees of initial coking are analyzed. There are a description of the results.

In conclusion, the main results and examples of problems which can be solved using the developed mathematical model are noted.

The paper considers the adequacy of the model developed earlier by the author for the analysis of income inequality and based on an empirically confirmed hypothesis that the relative (to the income of the richest group) income values of 20% population groups in total income can be represented as a finite functional sequence, each member of which depends on one parameter — a specially defined indicator of inequality. It is shown that in addition to the existing methods of inequality analysis, the model makes it possible to estimate with the help of analytical expressions the income shares of 20%, 10% and smaller groups of the population for different levels of inequality, as well as to identify how they change with the growth of inequality, to estimate the level of inequality for known ratios between the incomes of different groups of the population, etc.

The paper provides a more detailed confirmation of the proposed model adequacy in comparison with the previously obtained results of statistical analysis of empirical data on the distribution of income between the 20% and 10% population groups. It is based on the analysis of certain ratios between the values of quintiles and deciles according to the proposed model. The verification of these ratios was carried out using a set of data for a large number of countries and the estimates obtained confirm the sufficiently high accuracy of the model.

Data are presented that confirm the possibility of using the model to analyze the dependence of income distribution by population groups on the level of inequality, as well as to estimate the inequality indicator for income ratios between different groups, including variants when the income of the richest 20% is equal to the income of the poor 60 %, income of the middle class 40% or income of the rest 80% of the population, as well as when the income of the richest 10% is equal to the income of the poor 40 %, 50% or 60%, to the income of various middle class groups, etc., as well as for cases, when the distribution of income obeys harmonic proportions and when the quintiles and deciles corresponding to the middle class reach a maximum. It is shown that the income shares of the richest middle class groups are relatively stable and have a maximum at certain levels of inequality.

The results obtained with the help of the model can be used to determine the standards for developing a policy of gradually increasing the level of progressive taxation in order to move to the level of inequality typical of countries with social oriented economy.

Certifying a transport airplane for the flights under icing conditions in Russia was carried out within the framework of the requirements of Annex С to the AP-25 Aviation Rules. In force since 2023 to replace AP-25 the new Russian certification document “Airworthiness Standards” (NLG-25) proposes the introduction of Appendix O. A feature of Appendix O is the need to carry out calculations in conditions of high liquid water content and with large water drops (500 microns or more). With such parameters of the dispersed flow, such physical processes as the disruption and splashing of a water film when large drops enter it become decisive. The flow of a dispersed medium under such conditions is essentially polydisperse. This paper describes the modifications of the IceVision technique implemented on the basis of the FlowVision software package for the ice accretion calculations within the framework of Appendix O.

The main difference between the IceVision method and the known approaches is the use of the Volume of fluid (VOF) technology to the shape of ice changes tracking. The external flow around the aircraft is calculated simultaneously with the growth of ice and its heating. Ice is explicitly incorporated in the computational domain; the heat transfer equation is solved in it. Unlike the Lagrangian approaches, the Euler computational grid is not completely rebuilt in the IceVision technique: only the cells containing the contact surface are changed.

The IceVision 2.0 version accounts for stripping the film, as well as bouncing and splashing of falling drops at the surfaces of the aircraft and ice. The diameter of secondary droplets is calculated using known empirical correlations. The speed of the water film flow over the surface is determined taking into account the action of aerodynamic forces, gravity, hydrostatic pressure gradient and surface tension force. The result of taking into account surface tension is the effect of contraction of the film, which leads to the formation of water flows in the form of rivulets and ice deposits in the form of comb-like growths. An energy balance relation is fulfilled on the ice surface that takes into account the energy of falling drops, heat exchange between ice and air, the heat of crystallization, evaporation, sublimation and condensation. The paper presents the results of solving benchmark and model problems, demonstrating the effectiveness of the IceVision technique and the reliability of the obtained results.

Road noise is one of the key issues in maintaining high environmental standards. At speeds between 50 and 120 km/h, tires are the main source of noise generated by a moving vehicle. It is well known that either the interaction between the tire tread and the road surface or some internal dynamic effects are responsible for tire noise and vibration. This paper discusses the application of a new method for modelling the generation and propagation of sound during tire motion, based on the application of the so-called acoustic-vortex decomposition. Currently, the application of the Lighthill equation and the aeroacoustics analogy are the main approaches used to model tire noise. The aeroacoustics analogy, in solving the problem of separating acoustic and vortex (pseudo-sound) modes of vibration, is not a mathematically rigorous formulation for deriving the source (righthand side) of the acoustic wave equation. In the development of the acoustic-vortex decomposition method, a mathematically rigorous transformation of the equations of motion of a compressible medium is performed to obtain an inhomogeneous wave equation with respect to static enthalpy pulsations with a source term that de-pends on the velocity field of the vortex mode. In this case, the near-field pressure fluctuations are the sum of acoustic fluctuations and pseudo-sound. Thus, the acoustic-vortex decomposition method allows to adequately modeling the acoustic field and the dynamic loads that generate tire vibration, providing a complete solution to the problem of modelling tire noise, which is the result of its turbulent flow with the generation of vortex sound, as well as the dynamic loads and noise emission due to tire vibration. The method is first implemented and test-ed in the FlowVision software package. The results obtained with FlowVision are compared with those obtained with the LMS Virtual.Lab Acoustics package and a number of differences in the acoustic field are highlighted.

The paper presents a comparative analysis of the enterprises of the Arctic Zone of the Russian Federation (AZ RF) on economic indicators in accordance with the rating of the Polar index. This study includes numerical data of 193 enterprises located in the AZ RF. Machine learning methods are applied, both standard, from open source, and own original methods — the method of Optimally Reliable Partitions (ORP), the method of Statistically Weighted Syndromes (SWS). Held split, indicating the maximum value of the functional quality, this study used the simplest family of different one-dimensional partition with a single boundary point, as well as a collection of different two-dimensional partition with one boundary point on each of the two combining variables. Permutation tests allow not only to evaluate the reliability of the data of the revealed regularities, but also to exclude partitions with excessive complexity from the set of the revealed regularities. Patterns connected the class number and economic indicators are revealed using the SDT method on one-dimensional indicators. The regularities which are revealed within the framework of the simplest one-dimensional model with one boundary point and with significance not worse than p < 0.001 are also presented in the given study. The so-called sliding control method was used for reliable evaluation of such diagnostic ability. As a result of these studies, a set of methods that had sufficient effectiveness was identified. The collective method based on the results of several machine learning methods showed the high importance of economic indicators for the division of enterprises in accordance with the rating of the Polar index. Our study proved and showed that those companies that entered the top Rating of the Polar index are generally recognized by financial indicators among all companies in the Arctic Zone. However it would be useful to supplement the list of indicators with ecological and social criteria.

In this paper, we test the performance of some modern stochastic optimization methods and practices with respect to the digital pre-distortion problem, which is a valuable part of processing signal on base stations providing wireless communication. In the first part of our study, we focus on the search for the best performing method and its proper modifications. In the second part, we propose the new, quasi-online, testing framework that allows us to fit our modeling results with the behavior of real-life DPD prototype, retest some selected of practices considered in the previous section and approve the advantages of the method appearing to be the best under real-life conditions. For the used model, the maximum achieved improvement in depth is 7% in the standard regime and 5% in the online regime (metric itself is of logarithmic scale). We also achieve a halving of the working time preserving 3% and 6% improvement in depth for the standard and online regime, respectively. All comparisons are made to the Adam method, which was highlighted as the best stochastic method for DPD problem in [Pasechnyuk et al., 2021], and to the Adamax method, which is the best in the proposed online regime.

Original representation of statistical digital model of measurement of a macroroughness on a local site (to 15) consisting of determined (bias), correlated (standard periodic making and periodic deviations from flatness) and actually casual making (values of a macroroughness) Is offered.

In many social groups, for example, in technical committees for standardization, at the international, regional and national levels, in European communities, managers of ecovillages, social movements (occupy), international organizations, decision-making is based on the consensus of the group members. Instead of voting, where the majority wins over the minority, consensus allows for a solution that each member of the group supports, or at least considers acceptable. This approach ensures that all group members’ opinions, ideas and needs are taken into account. At the same time, it is noted that reaching consensus takes a long time, since it is necessary to ensure agreement within the group, regardless of its size. It was shown that in some situations the number of iterations (agreements, negotiations) is very significant. Moreover, in the decision-making process, there is always a risk of blocking the decision by the minority in the group, which not only delays the decisionmaking time, but makes it impossible. Typically, such a minority is one or two odious people in the group. At the same time, such a member of the group tries to dominate in the discussion, always remaining in his opinion, ignoring the position of other colleagues. This leads to a delay in the decision-making process, on the one hand, and a deterioration in the quality of consensus, on the other, since only the opinion of the dominant member of the group has to be taken into account. To overcome the crisis in this situation, it was proposed to make a decision on the principle of «consensus minus one» or «consensus minus two», that is, do not take into account the opinion of one or two odious members of the group.

The article, based on modeling consensus using the model of regular Markov chains, examines the question of how much the decision-making time according to the «consensus minus one» rule is reduced, when the position of the dominant member of the group is not taken into account.

The general conclusion that follows from the simulation results is that the rule of thumb for making decisions on the principle of «consensus minus one» has a corresponding mathematical justification. The simulation results showed that the application of the «consensus minus one» rule can reduce the time to reach consensus in the group by 76–95%, which is important for practice.

The average number of agreements hyperbolically depends on the average authoritarianism of the group members (excluding the authoritarian one), which means the possibility of delaying the agreement process at high values of the authoritarianism of the group members.