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The effect of copper ions on the primary processes of photosynthesis in freshwater microalgae Scenedesmus quadricauda was studied using a set of biophysical and mathematical methods. Chlorophyll a fluorescence transients were recorded both in cell suspensions and at the level of single cells after incubation at copper concentrations of 0.1–10 $\mu$M under light and dark conditions. It was found that copper has a dose-dependent effect on the photosynthetic apparatus of microalgae. At low copper concentration (0.1 $\mu$M), a stimulating effect on a number of studied parameters was observed, whereas significant disruption of Photosystem II activity was detected at 10 $\mu$M. The method of analyzing fluorescence of single cells proved to be more sensitive compared to traditional suspension measurements, allowing the detection of heterogeneous cellular responses to the toxicant. Analysis of chlorophyll a fast fluorescence kinetics showed that the JIP-test parameters $\delta_{Ro}$ and $\varphi_{Ro}$ were the most sensitive to copper exposure and were significantly different from the control when exposed not only to high but also to medium (1 $\mu$M) copper concentrations. The decrease in photochemical activity of cells during light incubation was less pronounced compared to dark conditions. The application of data normalization to optical density at $\lambda = 455$ nm significantly increased the sensitivity of the method and accuracy of result interpretation. The use of L₁-regularization (LASSO) by the least angles method (LARS) for the spectral multi-exponential approximation of the fluorescence transients allowed us to reveal their temporal characteristics. Mathematical analysis of the obtained data suggested that copper exposure leads to increased non-photochemical quenching of fluorescence, which serves as a protective mechanism for dissipating excess excitation energy. The revealed heterogeneity of cellular responses to copper action may have important ecological significance, ensuring the survival of part of the population under stress conditions. The obtained data confirm the promise of using fluorescent analysis methods for early diagnosis of heavy metal stress effects on photosynthesizing organisms.

This paper presents new research results that have been conducted at the Institute of Economics of the Russian Academy of Sciences since 2011 under the leadership of Academician of the Russian Academy of Sciences V. I.Mayevsky. These works are aimed at developing the theory of switching mode of reproduction and corresponding mathematical models, the peculiarity of which is that they explicitly model the interaction of the financial and real sectors of the economy, and the country’s economy itself is not disaggregated according to the sectoral principle (engineering, agriculture, services, etc.), but by production subsystems that differ from each other by the age of the fixed capital. One of the mathematical difficulties of working with such models, called models of switching mode of reproduction (SMR), is the difficulty of modeling competitive relationships between subsystems of different “ages”. Therefore, until now, the interaction of a finite number of production subsystems has been considered in the SMR models, the models themselves were of a discrete-continuous nature, calculations were done exclusively on computers, and obtaining analytical dependencies was difficult. This paper shows that for the special case of balanced economic growth and a continuum of production subsystems, it is possible to obtain analytical expressions that allow a better understanding of the impact of monetary policy on economic dynamics. In addition to purely scientific interest, this is of great practical importance, since it allows us to assess the possible reaction of the real sector of the economy to changes in the monetary sphere without conducting complex simulation calculations.

Based on modified rescaled range scale computation algorithm, the technique of Hurst exponent and its characteristic time estimation is proposed. The approach of increase the accuracy and simplification automatic Hurst exponent calculation is developed. The Hurst exponent and characteristic time is calculated for power time sets of speech signals with various motor pathologies (aphasias and dysarthrias). Results is statistically analyzed, the correlation between Hurst exponent and characteristic time is estimated.

The aim of the work was to study and develop methods of forecasting the dynamics of the human respiratory reactions, based on mathematical modeling. To achieve this goal have been set and solved the following tasks: developed and justified the overall structure and formalized description of the model Respiro-reflex system; built and implemented the algorithm in software models of gas exchange of the body; computational experiments and checking the adequacy of the model-based Lite-ture data and our own experimental studies.

In this embodiment, a new comprehensive model entered partial model modified version of physicochemical properties and blood acid-base balance. In developing the model as the basis of a formalized description was based on the concept of separation of physiologically-fi system of regulation on active and passive subsystems regulation. Development of the model was carried out in stages. Integrated model of gas exchange consisted of the following special models: basic biophysical models of gas exchange system; model physicochemical properties and blood acid-base balance; passive mechanisms of gas exchange model developed on the basis of mass balance equations Grodinza F.; chemical regulation model developed on the basis of a multifactor model D. Gray.

For a software implementation of the model, calculations were made in MatLab programming environment. To solve the equations of the method of Runge–Kutta–Fehlberga. It is assumed that the model will be presented in the form of a computer research program, which allows implements vat various hypotheses about the mechanism of the observed processes. Calculate the expected value of the basic indicators of gas exchange under giperkap Britain and hypoxia. The results of calculations as the nature of, and quantity is good enough co-agree with the data obtained in the studies on the testers. The audit on Adek-vatnost confirmed that the error calculation is within error of copper-to-biological experiments. The model can be used in the theoretical prediction of the dynamics of the respiratory reactions of the human body in a changed atmosphere.

A dynamic game theoretic model of struggle against corruption in resource allocation is considered. It is supposed that the system of resource allocation includes one principal, one or several supervisors, and several agents. The relations between them are hierarchical: the principal influences to the supervisors, and they in turn exert influence on the agents. It is assumed that the supervisor can be corrupted. The agents propose bribes to the supervisor who in exchange allocates additional resources to them. It is also supposed that the principal is not corrupted and does not have her own purposes. The model is investigated from the point of view of the supervisor and the agents. From the point of view of agents a non-cooperative game arises with a set of Nash equilibria as a solution. The set is found analytically on the base of Pontryagin maximum principle for the specific class of model functions. From the point of view of the supervisor a hierarchical Germeyer game of the type Г_2t is built, and the respective algorithm of its solution is proposed. The punishment strategy is found analytically, and the reward strategy is built numerically on the base of a discrete analogue of the initial continuous- time model. It is supposed that all agents can change their strategies in the same time instants only a finite number of times. Thus, the supervisor can maximize his objective function of many variables instead of maximization of the objective functional. A method of qualitatively representative scenarios is used for the solution. The idea of this method consists in that it is possible to choose a very small number of scenarios among all potential ones that represent all qualitatively different trajectories of the system dynamics. These scenarios differ in principle while all other scenarios yield no essentially new results. Then a complete enumeration of the qualitatively representative scenarios becomes possible. After that, the supervisor reports to the agents the rewardpunishment control mechanism.

In this paper, we discuss the procedure for finding nominal trajectories of the planar five-link bipedal robot with point contact. To this end we use a virtual constraints method that transforms robot’s dynamics to a lowdimensional zero manifold; we also use a nonlinear optimization algorithms to find virtual constraints parameters that minimize robot’s cost of transportation. We analyzed the effect of the degree of Bezier polynomials that approximate the virtual constraints and continuity of the torques on the cost of transportation. Based on numerical results we found that it is sufficient to consider polynomials with degrees between five and six, as further increase in the degree of polynomial results in increased computation time while it does not guarantee reduction of the cost of transportation. Moreover, it was shown that introduction of torque continuity constraints does not lead to significant increase of the objective function and makes the gait more implementable on a real robot.

We propose a two step procedure for finding minimum of the considered optimization problem with objective function in the form of cost of transportation and with high number of constraints. During the first step we solve a feasibility problem: remove cost function (set it to zero) and search for feasible solution in the parameter space. During the second step we introduce the objective function and use the solution found in the first step as initial guess. For the first step we put forward an algorithm for finding initial guess that considerably reduced optimization time of the first step (down to 3–4 seconds) compared to random initialization. Comparison of the objective function of the solutions found during the first and second steps showed that on average during the second step objective function was reduced twofold, even though overall computation time increased significantly.

Automatic recognition of personal identity by biometric features is based on unique peculiarities or characteristics of people. Biometric identification process consist in making of reference templates and comparison with new input data. Iris pattern recognition algorithms presents high accuracy and low identification errors percent on practice. Iris pattern advantages over other biometric features are determined by its high degree of freedom (nearly 249), excessive density of unique features and constancy. High recognition reliability level is very important because it provides search in big databases. Unlike one-to-one check mode that is applicable only to small calculation count it allows to work in one-to-many identification mode. Every biometric identification system appears to be probabilistic and qualitative characteristics description utilizes such parameters as: recognition accuracy, false acceptance rate and false rejection rate. These characteristics allows to compare identity recognition methods and asses the system performance under any circumstances. This article explains the mathematical model of iris pattern biometric identification and its characteristics. Besides, there are analyzed results of comparison of model and real recognition process. To make such analysis there was carried out the review of existing iris pattern recognition methods based on different unique features vector. The Python-based software package is described below. It builds-up probabilistic distributions and generates large test data sets. Such data sets can be also used to educate the identification decision making neural network. Furthermore, synergy algorithm of several iris pattern identification methods was suggested to increase qualitative characteristics of system in comparison with the use of each method separately.

In this article we propose a new approach to the analysis of econometric industry parameters for the industry consolidation level. The research is based on the simple industry automatic control model. The state of the industry is measured by quarterly obtained econometric parameters from each industry’s company provided by the tax control regulator. An approach to analysis of the industry, which does not provide for tracking the economy of each company, but explores the parameters of the set of all companies as a whole, is proposed. Quarterly obtained econometric parameters from each industry’s company are Income, Quantity of employers, Taxes, and Income from Software Licenses. The ABC analysis method was modified by ABCD analysis (D — companies with zero-level impact to industry metrics) and used to make the results obtained for different indicators comparable. Pareto charts were formed for the set of econometric indicators.

To estimate the industry monopolization, the Herfindahl – Hirschman index was calculated for the most sensitive companies metrics. Using the HHI approach, it was proved that COVID-19 does not lead to changes in the monopolization of the Russian IT industry.

As the most visually obvious approach to the industry visualization, scattering diagrams in combination with the Pareto graph colors were proposed. The affect of the accreditation procedure is clearly observed by scattering diagram in combination with red/black dots for accredited and nonaccredited companies respectively.

The last reported result is the proposal to use the Licenses End-to-End Product Identification as the market structure control instrument. It is the basis to avoid the multiple accounting of the licenses reselling within the chain of software distribution.

The results of research could be the basis for future IT industry analysis and simulation on the agent based approach.

Although the era of exponential performance growth in computer chips has ended, processor core numbers have reached 16 or more even in general-purpose desktop CPUs. As DRAM throughput is unable to keep pace with this computing power growth, CPU designers need to find ways of lowering memory traffic per instruction. The straightforward way to do this is to reduce the miss rate of the last-level cache. Assuming “non-inclusive cache, inclusive directory” (NCID) scheme already implemented, three ways of reducing the cache miss rate further were studied.

The first is to achieve more uniform usage of cache banks and sets by employing hash-based interleaving and indexing. In the experiments in SPEC CPU2017 refrate tests, even the simplest XOR-based hash functions demonstrated a performance increase of 3.2%, 9.1%, and 8.2% for CPU configurations with 16, 32, and 64 cores and last-level cache banks, comparable to the results of more complex matrix-, division- and CRC-based functions.

The second optimisation is aimed at reducing replication at different cache levels by means of automatically switching to the exclusive scheme when it appears optimal. A known scheme of this type, FLEXclusion, was modified for use in NCID caches and showed an average performance gain of 3.8%, 5.4 %, and 7.9% for 16-, 32-, and 64-core configurations.

The third optimisation is to increase the effective cache capacity using compression. The compression rate of the inexpensive and fast BDI*-HL (Base-Delta-Immediate Modified, Half-Line) algorithm, designed for NCID, was measured, and the respective increase in cache capacity yielded roughly 1% of the average performance increase.

All three optimisations can be combined and demonstrated a performance gain of 7.7%, 16% and 19% for CPU configurations with 16, 32, and 64 cores and banks, respectively.

When modeling turbulent flows in practical applications, it is often necessary to carry out a series of calculations of bodies of similar topology. For example, bodies that differ in the shape of the fairing. The use of convolutional neural networks allows to reduce the number of calculations in a series, restoring some of them based on calculations already performed. The paper proposes a method that allows to apply a convolutional neural network regardless of the method of constructing a computational mesh. To do this, the flow field is reinterpolated to a uniform mesh along with the body itself. The geometry of the body is set using the signed distance function and masking. The restoration of the flow field based on part of the calculations for similar geometries is carried out using a neural network of the UNet type with a spatial attention mechanism. The resolution of the nearwall region, which is a critical condition for turbulent modeling, is based on the equations obtained in the nearwall domain decomposition method.

A demonstration of the method is given for the case of a flow around a rounded plate by a turbulent air flow with different rounding at fixed parameters of the incoming flow with the Reynolds number $Re = 10^5$ and the Mach number $M = 0.15$. Since flows with such parameters of the incoming flow can be considered incompressible, only the velocity components are studied directly. The flow fields, velocity and friction profiles obtained by the surrogate model and numerically are compared. The analysis is carried out both on the plate and on the rounding. The simulation results confirm the prospects of the proposed approach. In particular, it was shown that even if the model is used at the maximum permissible limits of its applicability, friction can be obtained with an accuracy of up to 90%. The work also analyzes the constructed architecture of the neural network. The obtained surrogate model is compared with alternative models based on a variational autoencoder or the principal component analysis using radial basis functions. Based on this comparison, the advantages of the proposed method are demonstrated.