Advances in Systems Science and Applications

Comparative Analysis of the Efficiency of Molybdenum Trioxide Extraction from a Spent Hydraulic Catalyst

Elena Yurievna Nevskaya — 2023-04-16

This work is a continuation of the search for optimal conditions for the selective extraction of molybdenum from spent molybdenum-containing hydrotreating catalysts. The optimal conditions for extracting molybdenum from molybdenum (VI) oxide MoO3 are determined. The kinetic regularities of the interaction of solutions of nitric acid (HNO₃) and sodium carbonate (Na₂CO₃) with a molybdenum-containing catalyst were described.

On Codimension 3 Singular Points of First-order Implicit Differential Equations

Yana Sergeevna Agakhanova — 2023-04-16

We investigate local phase portraits of first-order implicit differential equations in a neighborhood of their singular points of codimension~3. Namely, we consider singular points where the lifted field of the equation on a surface is non-singular, but the projection of the surface to the phase plane has a singularity of one of three types: lips, beaks, swallowtail. We also consider generic bifurcations in one-parameter families of such equations.

The Disease Centered Multimorbidity Model at the Example of Type 2 Diabetes Mellitus

Dmitry Meshkov — 2023-04-16

Multimorbidity is a condition when few diseases (multimorbidity pattern) are diagnosed in same patient. According to the disease centered model the pattern is formed around one “marker” disease at the expense of other diseases which have non-random relationships with the “marker” disease and between each other. The totality and probabilistic connections between pairs of diseases determine the specifics of the pattern and indicate the possibilities for managing individual and population health as a result of interactions of all components of the the pattern. Algorithms have been developed assessing the degree of non-random connections between pairs of diseases in the pattern and establishing a hierarchical relationship between both “marker” and other diseases as well as between pairs of non-marker diseases. The calculation of non-random statistical relationships between pairs of diseases included in the T2DM (Type 2 Diabetes Mellitus) multimorbidity pattern proved the consistency of the data obtained with the current clinical description of T2DM pathogenesis and complications.

Piecewise Constant Functions in Dynamic Optimization Problems

Olga Evgenievna Orel — 2023-04-16

We consider a direct method of dynamic optimization to approximate the global extremum. This method is based on splitting the state space into classes (cells) and constructing piecewise constant functions on the partition. Such an approach leads to a generalization of the Euler polygonal method and makes it possible to use shortest path algorithms on graphs. In the suggested algorithm, for each class we construct a path from an initial point to this class. Note that the program remembers only the terminal point of the path, functional value along the path and number of the preceding class. If one found another path with the same boundary conditions but less functional value (for the minimization problem), this path would become the current approximation. We prove that if the partition is sufficiently small, then, by using our method, we obtain the optimal polygon. The suggested approach can also be applied to problems of dynamic optimization with incomplete information (differential games, control of systems with unknown dynamics). In addition, some results of numerical solutions of optimal control problems and differential games are given.

Assessing the Fires Impact on Vegetation Cover Using Remote Sensing Data: Indonesia Case Study

Elizaveta Andreevna Grigorets — 2023-04-16

Wildfires in Indonesia have become abnormally frequent due to the human-driven degradation of forest and agricultural lands, as well as climate change. The authors analyze recent studies that provide evidence for an increase in the fire hazard to various ecosystems in Indonesia (forests, peatlands, agricultural lands) considering changes in climatic and meteorological parameters of the environment. This work establishes a relationship between burnt areas, measured by Moderate Resolution Imaging Spectroradiometer (MODIS), and the following parameters, retrieved from the Reanalysis v5 (ERA5) ECMWF dataset: monthly precipitation amount, temperature at a height of 2 m above sea level, soil temperature in the upper layer (0 to 7 cm depth), water content in the upper soil layer (0 to 7 cm depth), specific air humidity, zonal wind speed, meridional wind speed, and a standard deviation of precipitation. The authors reveal a correlation and a direct dependence of wildfires on the potential factors influencing the area: air temperature and soil temperature. It is assumed to be associated with the rainfall type, winds (speed, direction, and oscillations), improper land use, and the El Niño–Southern Oscillation.

The Problem of Controllability with Phase Space Change

Irina Maximova — 2023-04-16

In this paper, we consider differential systems of the following structure: at two consecutive time intervals the motion of the object is described by two different systems of differential equations. We study the controllability of the object described by such system from the initial set in one space to the given set in another space through so-called ''transition hypersurface''. The transition of an object from one space to another one is given by a certain reflection. Sufficient conditions of the controllability of such differential systems in the problem with phase space change are obtained. Approaches to the study of both nonlinear and linear systems are considered.

A Novel Method for Predicting Technology Trends Based on Processing Multiple Data Sources

Thanh Viet Nguyen — 2023-04-16

In order to gain competing capability in conditions of quickly scientific changes, it is crucial to track the evolution of existing technologies and to explore promising and emerging technologies. Moreover, numerous previous studies showed that sudden changes in R&D and patents are actually correlated with great variations in the market profit of firms. For this reason, if stock prices of an enterprise keep uptrend, then the technologies developed by considering one will be likely to become promising innovations in future. In this paper, we proposed a method to predict technology trends based on processing multiple data sources by mining Web news, forecasting stock price trends of high-tech companies, and patent clustering analysis. Different from other studies, our proposed method promotes an idea of predicting technology trends by forecasting stock price trend using univariate and multivariate data preparation approaches, with the utilization of Bayesian optimization for exploring best hyperparameters of machine/deep learning models, also a new method for patent analysis. Besides, a program system was created for analyzing word burst detection, predicting the time series of stock prices, and analyzing patent documents. After collecting patents of Samsung Electronics Co Ltd, as a case study, clustering analysis is implemented on extracted noun phrases to explore technology trends developed by the company. These technology trends have recently been confirmed by domain experts in their corresponding published articles. The obtained forecast precision is about 93.8%, which proves that the proposed method gains positive reliability.

Nowcasting GDP of Major Economies During the Crisis: Does Energy Matter?

Ivan Stankevich — 2023-04-16

In this article we compare the accuracy on nowcasts obtained with different models and different sets of indicators used as predictors for a set of 19 major economies. We compare the performance of mixed-frequency Bayesian VAR models, Dynamic Factor models and unrestricted MIDAS models with L1 regularization. We test different groups of commodity prices as possible predictors: energy indicators, agricultural commodities, precious metals and industrial metals prices. We find that among all the indicator groups tested energy commodities prices yield the highest average nowcasting accuracy, even though the accuracy of models utilizing all the indicators available remains slightly higher. Among all the models tested, the highest quality is yielded by Mixed-Frequency Bayesian VAR models. We also emphasize the importance of manual selection of predictors for non-diversified economies, where it can significantly improve the accuracy of nowcasts compared to the models with a wide set of predictors

Numerical Investigation of Fluid-Structure, Thermal Coupling for a Heated Slab

Oudrane Abdellatif — 2023-04-16

This work focuses on a numerical analysis of fluid-structure thermal coupling
in a heating slab. The latter consists of a rectangular cross-section duct located in the
concrete slab of a discredited habitat. We modeled the thermal transfers of fluid flow in the
pipe. In fact, the Navier-Stokes equations that govern this flow have been solved
numerically. These equations were by an implicit method of finite differences. The systems
of algebraic equations thus obtained were solved by the algorithms of Gauss and Thomas.
The equation of conduction in the concrete slab was solved using the same methodology as
that of flow. In this work, we based on an algorithm that interacts non stationary solid
medium with a fluid medium consisting of permanent a state by ensuring equal flows and
temperatures on the common interface between the two mediums at every moment. The
numerical simulation of heat transfers and the thermal behavior of the heating slab were
analyzed for various parameters influencing thermal diffusion. The results obtained show
that the numerical methodology adopted for the control of fluid-structure coupling is
acceptable in comparison with the literature.

Learning Methods for Distributed Diagnosis: a Failure Classification Methodology in Discrete Event Systems

Hanane Serradj — 2023-04-16

In the dependability context, the diagnosis is fundamental for identifying and classifying failures to reduce system malfunctions and accidents that can cause serious damage to property and people. Currently, systems are generally complex and the distribution approach of the diagnostic function makes it possible to better managing the systems to be diagnosed. This article proposes a methodology for the distributed diagnosis of Discrete Event Systems, which are dynamic systems widely spread. The proposed approach, based on a generic model, is formed of two sequential steps. The first one consists in the system modeling giving a mean to understand the real behavior of the studied system, through a distributed recovery of signals. The second step is to standardize and process the obtained data for the classification of failures. To achieve this challenge, two learning classification methods are adopted: the Learning Algorithm for Multivariate Data Analysis (LAMDA) coupled with the K-Nearest Neighbor algorithm (K-NN). To validate the approach, the generic model is applied on a particular discrete event system, a railway transport network following a real case of railway line and the obtained results showed the improvement of the classification by recognition. The proposed framework of distributed diagnosis, based on the two learning methods, seems an efficacy and robust methodology for classify any failures of systems.

Verification of Bounded Rationality Models of Price Dispersion on an Online Marketplace Data

Nikolay Bazenkov — 2023-04-16

We explore how well the models of bounded rationality explain price dispersion observed in Internet price-comparison sites.
This paper considers three hypotheses about the strategic origin of price dispersion in homogeneous product online sales. Two of them are $\varepsilon$-equilibrium and quantal-response equilibrium (QRE) in a pure Bertrand setting, they involve the bounded rationality of sellers. The third hypothesis introduces the fraction of loyal consumers into the model and assumes the sellers are rational. These behavioral models earlier were proposed in the literature as possible explanations of high price dispersion in online markets. They were supported by experimental lab data, but not tested on real prices. We test the hypotheses on real data for 30 models of household appliances collected from the largest Russian online marketplace Market.Yandex.ru, which organizes e-competition in the closest to the Bertrand setting way. We found no support for $\varepsilon$-equilibrium hypothesis and only limited support for loyal consumer hypothesis. QRE showed the best performance on the data. For most of the products it predicts central tendency, i.e. the mean and the median, remarkably well. The shape of the observed price distributions is explained accurately enough in comparison with the two other hypotheses and random behavior.

Evaluation of Microalgae Prebiotic Activity in Long-term Humans Isolation in Confined Habitat

Vyacheslav Ilyin — 2023-04-21

It is known that long-term isolation in sealed compartment the first 10-14 days is called a period of "acute adaptation". It is manifested by an increase of number of opportunistic microflora species together with quantitative decrease of protective microflora species. This is fraught with the development of auto- and cross-infections. In this regard, it is necessary to develop countermeasures against maladjustment processes in these conditions. IBMP conducted research on possibility of using an autotrophic element of biological life support systems, including as an additive in diets. A comparative assessment of the microflora of 6 people, participants of a long-term isolation experiment, was carried out. As countermeasures pills based on spirulina were used. Two pills was taken by all participants times per day. For comparison, archival data from experiments in which subjects did not use any countermeasures were used. The results indicate the stabilization of the microbiocenosis of the intestines and upper respiratory tract when using the spirulina pills. The concentration of Enterococci was maintained at a high level, most of the participants did not have Proteus, Staphylococci or yests. However there were minor fluctuations in the content of protective groups in the intestinal microflora (Bifidobacteria and Lactobacilli), which determines the need to include probiotics as countemesures. Thus, studies have demonstrated the positive results of the use of spirulina as a countermesure. Therefore, it is expedient to consider the issue of equipping the sealed compartments planned for use for the implementation of deep space exploration programs with water-mixture bioreactors.