Account Fluctuations Research Articles

ASSESSMENT OF THE CONNECTION BETWEEN THE BANK'S CAPITALIZATION LEVEL AND THE COUNTRY'S MACROECONOMIC STABILITY

A well-capitalized banking system is crucial for maintaining macroeconomic stability, preventing financial crises, and bolstering the economy's resilience to shocks. Governments often strive to ensure adequate bank capitalization to foster stable economic growth. This article aims to assess the relationship between bank capitalization and macroeconomic stability in 34 European countries from 2010 to 2021, based on World Bank statistics.The study utilizes the principal components method to identify relevant indicators of bank capitalization and macroeconomic stability, canonical analysis and regression analyses to detail the interconnections between these blocks. The canonical analysis confirms a link between bank capitalization and macroeconomic stability indicators with a coefficient of determination of 0.617 signifying that 61.8% of the variance in macroeconomic stability is explained by fluctuations in bank capitalization.The article presents one fixed-effect and two random-effect regression models detailing the directions and strength of influence of independent variables (NPL, ROA, ROE - indicators of the bank capitalization level) on dependent variables (INFLATION, UNEMPL, GINI - indicators of macroeconomic stability). The Wald criteria and a p-value less than 0.05 indicated that the models with random effects (UNEMPL, GINI) were statistically significant.The results reveal that a 1% increase in non-performing loans correlates with a 0.25% rise in the unemployment rate, and a 1% increase in return on assets leads to a 0.08% increase in the unemployment rate. Additionally, a 1% increase in non-performing loans raises the Gini index by 0.05%, while a 1% increase in return on equity decreases the Gini index by 0.03%. Notably, the impact of return on assets on the unemployment rate and the Gini coefficient is not statistically significant (p-value greater than 0.05).These results can inform the forecasting of national indicators, the development of tools to ensure sufficient bank capitalization, and the formulation of effective macroeconomic policies, taking into account fluctuations in banks' capitalization levels as key financial intermediaries.

Clustered jamming and antenna beam-width fluctuations for UAV-assisted cellular networks

Jamming devices have the capability to deliberately disrupt legitimate communications. Clustered jamming pertains to the deployment of jammers that are concentrated within specific clusters to amplify the interference. This paper models the impact of clustered jamming interference on unmanned aerial vehicles (UAV)-assisted cellular networks, taking into account fluctuations of the 3-dimensional (3D) beam-width of low altitude platform (LAP) antennas. The distribution of UAVs and macro base station (MBS) is modeled by independent 3D and 2D homogeneous Poisson point processes, respectively, while jammers are modeled using an independent Matern cluster process. Antenna 3D beam-width fluctuations are modeled according to Normal distribution. The modeling centers on the probability of association as well as coverage and spectral efficiency for line-of-sight LAP, non-line-of-sight LAP, and MBS links. This modeling investigation is conducted under multiple jamming clusters and the antenna 3D beam-width fluctuations of UAV. Analytical expressions are derived to characterize association, coverage, and SE performance in the context of clustered jamming and UAV beam-width variation. The obtained results indicate that UAV-assisted cellular networks experience a notable decline in the proximity of clustered jammers. Furthermore, this performance degradation is significantly exacerbated when the antenna 3D beam-width exhibits fluctuations. Consequently, to enhance the performance of UAV-assisted cellular networks, it is imperative for system designers to consider the implementation of robust anti-jamming techniques.

Концепція оцінки ергономічної стійкості транспортного потоку великих міст з урахуванням динамічності зміни впливових факторів

The methodological approach of forecasting the congestion of the streets of large cities, taking into account the fluctuations in the density of traffic flows and the speed of movement of cars in the flow, received further development. The methodical approach takes into account fluctuations in the dynamics of the traffic flow in the form of changes in the acceleration of the movement of cars in the flow and fluctuations in changes in the infrastructure of the road environment, which is associated with the number of traffic lights, pedestrian crossings and the number of lanes for the movement of vehicles. Through modeling, it was found that increasing the acceleration values of cars in the stream significantly increases the range of robustness. At low values of acceleration of cars, the reserve of resistance to the formation of traffic jams decreases, which negatively affects the traffic flow, there is a probability of the formation of traffic jams. The presence of fluctuations in the density of the traffic flow and the speed of movement of cars in the flow, due to changes in the acceleration of cars, allows making adjustments to the value of the robustness criterion. Adjustments can be made for different clusters of the road network, for different times of the day, and take into account the period of fluctuations. The dependences of the change in the robustness range of the traffic flow upon changing the infrastructure of the road network are given. It has been established that increasing the number of lanes and simultaneously reducing the number of traffic lights and pedestrian crossings on the controlled cluster significantly increases the stability of the movement of vehicles in the flow. Conversely, reducing the number of lanes, increasing the number of traffic lights and pedestrian crossings on the controlled cluster significantly reduces the stability of the movement of vehicles in the flow. Adjustment of density and movement speed can be performed taking into account the amplitude of oscillations. The concept of modeling and forecasting the stability of traffic flows of large cities to the formation of traffic jams is formulated. The main components of the concept, according to which such an assessment is performed step by step, taking into account the dynamics of changes in influencing factors, are substantiated. The proposed concept differs from the known ones in that it takes into account fluctuations in traffic flow parameters - the density and speed of movement of vehicles over time. Such changes are characteristic of the city's road network during "peak hours".

Analysis of research on smart rail circuits

The purpose of the article is to study intelligent continuous-type rail circuits with current receivers, respectively, to identify the possibility of determining the unit located on the rail lines with a standard shunt prescribed in the operating rules, as well as monitoring for breakage of a continuoustype rail circuit. To study smart railway circuits, it is necessary to take into account the circuit diagram of this track circuit and its operation with various factors influencing it. One of the points of the study is to determine the maximum and minimum resistance at the beginning and at the end of this rail line and also taking into account the worst influencing parameters on an intelligent rail circuit of unlimited length, carry out calculations and determine on the graphs the probability of failure-free operation in all modes. The study took into account fluctuations in temperature decline, both during the seasons, winter, summer, etc., and sharp continental changes within an hour in operating mode. When conducting the study, we also took into account the insulating resistance that affects the power supply of the composition determination sensor, which leads to a dependence on the length of the smart sensor. The parameters of changes in the sensor supply voltage, its variability from the supplier and the resistance of the rails and their fluctuations were taken. For this purpose, the requirements for the length of the intelligent rail circuit, shunt resistance and insulation resistance used on the road were applied, as well as determining the influence of all unfavorable conditions.

АДАПТИВНОЕ УПРАВЛЕНИЕ С ПРОГНОЗИРОВАНИЕМ ВНЕШНЕЙ НАГРУЗКИ В АВТОНОМНЫХ ЭЛЕКТРИФИЦИРОВАННЫХ ПЛАТФОРМАХ

One of the effective ways to intensify technological processes in the agricultural sector and at the facilities of the agro-industrial complex is the automation of cargo transportation both inside production and storage facilities and between the facilities of livestock and crop production complexes. Complex automation is possible on the basis of adaptive methods of vehicle management, taking into account fluctuations in the parameters of technological processes due to weather, organizational and other factors. (Research purpose) The research purpose is evaluating the prospects of using adaptive systems with external load forecasting for automatic control of autonomous electrified platforms in non-deterministic conditions. (Materials and methods) The structure of adaptive flow control of an electrified platform is proposed. It is shown that the greatest effect in undetermined conditions is created by systems that combine the functions of self-organization and self-tuning. The complementary implementation of these functions allows you to get the maximum effect in adaptive automatic control with significant changes in external conditions. (Results and discussion) Based on the proposed complex dependence of the moment of the resistance forces on time and the angle of rotation of the drive, a new variant of the approach to modeling the external load acting on the drive is recommended. Zero, first and second order models are considered, for which power and kinematic vectors are given. (Conclusions) Taking into account the dynamically changing external load on the drive of rotational motion, it is proposed to use power and kinetic vectors characterizing the movement of the drive link. The use of zero, first and second order models makes it possible to organize effective adaptive control of an electrified platform at all phases of its movement. This makes it possible to use the proposed approach in transport and technological systems at agribusiness facilities.

Power quality investigation of a grid tied hybrid energy system using a D-STATCOM control and grasshopper optimization technique

This research delves into the control strategy and modeling of a utility-grid tied hybrid system that conjoins a Solar Photovoltaic (SPV) and wind energy system. To maximize real power output under varying environmental conditions, both SPV-wind energy systems are controlled by Perturb & Observe (P&O) type Maximum Power Point Tracking (MPPT) algorithm. A sine varying modulating signal is generated through Proportional Integral (PI) based voltage and current controllers. Additionally, the target of reactive power compensation is achieved by connecting Distributed Static Synchronous Compensator (D-STATCOM) at coupling point. Its application helps in maintaining a stable utility-grid connection, and efficient power distribution. Simulation studies reveal that harmonics are reduced at various coupling points and are less than 5 %, as per IEEE-519 standard. It ensures that the proposed system operates at its peak efficiency, taking into account fluctuations in SPV radiations and wind speed. In addition, the steady-state response of the developed system is obtained with PI controller and analyzed. Results obtained are compared by implementing Grasshopper Optimization (GO) technique for validation and accuracy. It is found that rise time, settling time and maximum overshoot are 0.246 s, 0.38 s and 6 %, respectively with GO technique. Therefore, it is envisaged that the operation of D-STATCOM with GO technique is successfully integrated and is capable to address the key PQ issues, like voltage and current profile amongst others. Overall, the results demonstrate that the proposed system is highly efficient, making it an ideal choice for rural communities seeking to adopt renewable energy solutions.

Учет переменного характера расчетных нормативов плана формирования поездов с использованием технологий вычислительного интеллекта

Purpose: The train formation plan is the most important logistics tool for cargo transportation management. But the use of discrete values of design standards in its development — the quantity of car-hours for the accumulation of trains and savings from passing of cars through technical station without processing — do not always guarantee the optimal solution due to the objectively existing unevenness of operational work. It is precisely this factor that generates uncertainty, which is not inherently stochastic, and necessitates adjustments to the train formation plan throughout its lifecycle. In addition to fluctuations in car traffic, it causes a change in the values of the calculated standards. To manage such uncertainty, there are special methods, one of which is fuzzy logic. The article describes a way to account for changes in all calculation standards of the train formation plan. Methods: The methods of one of the technologies of computational artificial intelligence are used — fuzzy logic, fuzzy sets and fuzzy mathematics. Results: The dependence has been established on how changes in the calculated parameters of the train formation plan are affected by fluctuations in car flows on specific destinations. The formulas obtained on the basis of known analytical expressions allow us to determine the values of the standards of the formation plan without using auxiliary tables and graphs. Practical significance: The use of the obtained dependencies in the development of the formation plan will improve the accuracy of its calculation by taking into account fluctuations not only of car traffic, but also the values of the calculated standards depending on them.

Generalized effective string rope model for the initial stages of ultrarelativistic heavy ion collisions

We present a Generalized Effective String Rope Model (GESRM) for the description of the initial state of relativistic heavy ion collisions. We start from the Effective String Rope Model (ESRM) and take into account fluctuations in the initial state following the Glauber Monte Carlo approach. Results from symmetric Au+Au collisions at different impact parameters and asymmetric A+Au head on collisions are presented at RHIC energies. The produced initial state is used as an initial condition for further hydrodynamical calculations.

Instanton gas approach to the Hubbard model

In this paper, we consider a path integral formulation of the Hubbard model based on a Hubbard-Stratonovich transformation that couples the auxiliary field to the local electronic density. This decoupling is known to have a saddle-point structure that shows a remarkable regularity: The field configuration at each saddle point can be understood in terms of a set of elementary field configurations localized in space and imaginary time which we coin instantons. The interaction between instantons is short ranged. Here, we formulate a classical partition function for the instanton gas that has predictive power. For a given set of physical parameters, we can predict the distribution of instantons and show that the instanton number is sharply defined in the thermodynamic limit, thereby defining a unique dominant saddle point. Decoupling in the charge channel conserves SU(2) spin symmetry for each field configurations. Hence, the instanton approach provides an SU(2) spin-symmetric approximation to the Hubbard model. It fails, however, to capture the magnetic transition inherent to the Hubbard model on the honeycomb lattice despite being able to describe local moment formation. In fact, the instanton itself corresponds to local moment formation and concomitant short-ranged antiferromagnetic correlations. This aspect is also seen in the single particle spectral function that shows clear signs of the upper and lower Hubbard bands. Our instanton approach bears remarkable similarities to local dynamical approaches, such as dynamical mean-field theory, in the sense that it has the unique property of allowing for local moment formation without breaking the SU(2) spin symmetry. In contrast to local approaches, it captures short-ranged magnetic fluctuations. Furthermore, it also offers possibilities for systematic improvements by taking into account fluctuations around the dominant saddle point. Finally, we show that the saddle point structure depends upon the choice of lattice geometry. For the square lattice at half filling, the saddle-point structure reflects the itinerant to localized nature of the magnetism as a function of the coupling strength. The implications of our results for Lefschetz thimble approaches to alleviate the sign problem are also discussed.

Characterization of State-Preparation Uncertainty in Quantum Key Distribution

To achieve secure quantum key distribution, all imperfections in the source unit must be incorporated in a security proof and measured in the lab. Here we perform a proof-of-principle demonstration of the experimental techniques for characterising the source phase and intensity fluctuation in commercial quantum key distribution systems. When we apply the measured phase fluctuation intervals to the security proof that takes into account fluctuations in the state preparation, it predicts a key distribution distance of over 100 km of fiber. The measured intensity fluctuation intervals are however so large that the proof predicts zero key, indicating a source improvement may be needed. Our characterisation methods pave the way for a future certification standard.

The model of austenite structure state taking into account fluctuations of magnetic nature

The results of magnetic state simulation of carbon steel austenite are presented in this work. Quantitative parameters of the areas of short-range magnetic order, which are presented in paramagnetic austenite matrix and are observed as potential places of α-phase nucleation, are examined. This austenite heterogeneity in steels and clean iron is confirmed by the experimental data; however, detailed quantitative study meets technical complication of such experiments. It is suggested to use the Ising model for realization of the calculation experiment. The obtained spin configurations were analyzed for determination of geometric parameters of magnetic inhomogeneities and period of their sustainable existence. Calculations were conducted within the temperature range of austenite phase existence in steel, as well as without and with taking into account presence of external magnetic field, which strengthens existing austenite heterogeneity and has the effect on conduction of phase transformations in steel. The results of simulation confirm presence of the areas of short-range magnetic order in austenite, their size is close to the existing theoretical assessments and experimental data. It is shown that temperature rise leads to decrease of dimensions, number and life period of clusters, but these parameters are still important at the temperature of martensite transformation in steel. Overlapping of external magnetic field creates the conditions for existence of large-size ferromagnetic clusters also at more high temperatures, as well as increases time of their sustainable existence. The external magnetic field provides the conditions for more intensive and multiplicative nucleation of ferromagnetic phase, similar to short-range magnetic order fluctuations in location of atoms during liquid metal cooling. 

An empirical review of ICES reference points

Abstract The International Council for the Exploration of the Sea (ICES) has provided scientific stock advice based on reference points to manage fisheries in the North Atlantic Ocean and adjacent seas for decades. ICES advice integrates the precautionary approach with the objective of achieving maximum sustainable yield. Here, we examine ICES reference point evolution over the last 25 yr and provide a comprehensive empirical review of current ICES reference points for data-rich stocks (Category 1; 79 stocks). The consistency of reference point estimation with the ICES guidelines is evaluated. We demonstrate: (1) how the framework has evolved over time in an intergovernmental setting, (2) that multiple precautionary components and sources of stochasticity are included, (3) that the relationship and historical context of stock size and recruitment are crucial for non-proxy reference points, (4) that reference points are reviewed frequently, taking into account fluctuations and multiple sources of variability, (5) that there are occasional inconsistencies with the guidelines, and (6) that more comprehensive and clearer documentation is needed. Simplifying the stock-recruit typology and developing quantitative criteria would assist with this critically important classification. We recommend a well-documented, transparent, and reproducible framework, and periodic syntheses comparing applications across all stocks.

Cell-cell interactions and fluctuations in the direction of motility promote directed migration of osteoblasts in direct current electrotaxis.

Under both physiological (development, regeneration) and pathological conditions (cancer metastasis), cells migrate while sensing environmental cues in the form of mechanical, chemical or electrical stimuli. In the case of bone tissue, osteoblast migration is essential in bone regeneration. Although it is known that osteoblasts respond to exogenous electric fields, the underlying mechanism of electrotactic collective movement of human osteoblasts is unclear. Here, we present a computational model that describes the osteoblast cell migration in a direct current electric field as the motion of a collection of active self-propelled particles and takes into account fluctuations in the direction of single-cell migration, finite-range cell-cell interactions, and the interaction of a cell with the external electric field. By comparing this model with in vitro experiments in which human primary osteoblasts are exposed to a direct current electric field of different field strengths, we show that cell-cell interactions and fluctuations in the migration direction promote anode-directed collective migration of osteoblasts.

Optimal Sizing and Techno-Economic Analysis of Grid-Independent Hybrid Energy System for Sustained Rural Electrification in Developing Countries: A Case Study in Bangladesh

The absence of electricity is among the gravest problems preventing a nation’s development. Hybrid renewable energy systems (HRES) play a vital role to reducing this issue. The major goal of this study is to use the non-dominated sorting genetic algorithm (NSGA)-II and hybrid optimization of multiple energy resources (HOMER) Pro Software to reduce the net present cost (NPC), cost of energy (COE), and CO2 emissions of proposed power system. Five cases have been considered to understand the optimal HRES system for Kutubdia Island in Bangladesh and analyzed the technical viability and economic potential of this system. To demonstrate the efficacy of the suggested strategy, the best case outcomes from the two approaches are compared. The study’s optimal solution is also subjected to a sensitivity analysis to take into account fluctuations in the annual wind speed, solar radiation, and fuel costs. According to the data, the optimized PV/Wind/Battery/DG system (USD 711,943) has a lower NPC than the other cases. The NPC obtained by the NSGA-II technique is 2.69% lower than that of the HOMER-based system.

Evolution of a Polydisperse Ensemble of Spherical Particles in a Metastable Medium with Allowance for Heat and Mass Exchange with the Environment

Motivated by a wide range of applications in various fields of physics and materials science, we consider a generalized approach to the evolution of a polydisperse ensemble of spherical particles in metastable media. An integrodifferential system of governing equations, consisting of a kinetic equation for the particle-size distribution function (Fokker–Planck type equation) and a balance equation for the temperature (concentration) of a metastable medium, is formulated. The kinetic equation takes into account fluctuations in the growth/reduction rates of individual particles, the velocity of particles in a spatial direction, the withdrawal of particles of a given size from the metastable medium, and their source/sink term. The heat (mass) balance equation takes into account the growth/reduction of particles in a metastable system as well as heat (mass) exchange with the environment. A generalized system of equations describes various physical and chemical processes of phase transformations, such as the growth and dissolution of crystals, the evaporation of droplets, the boiling of liquids and the combustion of a polydisperse fuel. The ways of analytical solution of the formulated integrodifferential system of equations based on the saddle-point technique and the separation of variables method are considered. The theory can be applied when describing the evolution of an ensemble of particles at the initial and intermediate stages of phase transformation when the distances between the particles are large enough, and interactions between them can be neglected.

The model for calculating the proportions of a baking mixture to produce enriched products taking into account fluctuations in characteristic quality and safety indicators

When developing a new method, the formulation must ensure the stability of the quality and safety of the finished product, provided that the target indicator is reached. A method is proposed for calculating the dosage of an enriching raw ingredient when the boundary conditions for the enriching effect and the quality of the finished product are met. Amaranth extrudate is selected as the enriching ingredient. The enriching effect is predicted in relation to protein while achieving the effect on dietary fiber and calcium content. The authors defined classes of technological and financial limitations, the main of which relate to baking properties of the flour mixture – the amount of gluten as a factor in forming the shape, appearance, crumb structure, ash content, factors like the color of breadcrumb. It was found that it is not possible to expect sensory characteristics identical to the traditional ones for bread with the addition of amaranth extrudate. Within the limits of acceptable changes in organoleptic characteristics, the enriching effect can be achieved with a dosage of flour from amaranth extrudate not exceeding 23 %. The method is implemented by means of modern information technologies and can be used as a tool in the decision support system for the development of new technologies and recipes for enriched bakery products ensuring quality and safety.

Evaluating the Longitudinal Course of Atopic Dermatitis: Implications for Clinical Practice.

Atopic dermatitis (AD) is characterized by a heterogenous longitudinal course with varying severity, flares, and persistence. However, AD course is not routinely assessed in clinical practice or controlled trials. Our objective was to review the longitudinal course of AD in children and adults and discuss implications for routine practice and clinical trials. We conducted a focused review of the published literature, including retrospective, prospective, and interventional studies, clinical trials, and consensus guidelines. Estimates of AD persistence varied widely across studies but suggested that AD can indeed persist through childhood and into adulthood. Predictors of persistence are broad and include both disease-intrinsic and disease-extrinsic (i.e., environmental) factors. In real-world practice, most individuals with AD experience fluctuations in the signs and symptoms over time and do not experience persistent clearance of skin lesions. Clinical trials use mainly static measurements that do not take into account fluctuations in course, which may confound treatment effects. The heterogenous temporal pattern of AD can be incorporated into routine practice to better set expectations and offer a realistic prognosis. AD course should be routinely incorporated into clinical decision making. Future studies are needed to develop a standardized approach to AD assessment and treatment that includes longitudinal course.

Universal model of strong coupling at the nonlinear resonance in open cavity-QED systems

Many molecular, quantum-dot, and optomechanical nanocavity-QED systems demonstrate strong nonlinear interactions between electrons, photons, and phonon (vibrational) modes. We show that such systems can be described by a universal model in the vicinity of the nonlinear resonance involving all three degrees of freedom. We solve the nonperturbative quantum dynamics in the strong-coupling regime of the nonlinear resonance, taking into account quantization, dissipation, and fluctuations of all fields. We find analytic solutions for quantum states in the rotating-wave approximation which demonstrate tripartite quantum entanglement once the strong-coupling regime is reached. We show how the strong coupling at the nonlinear resonance modifies photon emission and vibrational spectra, and how the observed spectra can be used to extract information about relaxation rates and the nonlinear coupling strength in specific systems.

Применение нейронных сетей в системе распознавания промысловых гидробионтов в условиях повышенной флуктуации

The article focuses on using artificial neural networks for the recognition of commercial hydrobionts in conditions of increased fluctuation. Research has not been conducted in the field of recognition of aquaculture objects for reasons of solving the applied problems and achieving the required indicators. There is described the development of software for recognition of aquaculture objects based on the YOLOv5 model, as well as the proper methodology for the semi-automatic formation of effective visual training samples. There has been analyzed the model operation scheme and substantiated the importance of the training sample and its influence on the quality of pattern recognition by a neural network. Effective identification of aquatic organisms requires the methods for dividing it into zones according to various distinctive features and separating the required objects not only from the background, but also taking into account fluctuations above the water surface. There has been developed a method for eliminating fluctuations in order to increase the efficiency of recognition of aquatic organisms by a neural network. There is described the process of testing software for the detection of commercial hydrobionts trained on a sample by the proposed method. 
 It has been inferred that the recognition rate directly depends not only on the quality of the training sample and the volume of images, but also on the technical characteristics of the electronic computer

Transfer matrices and solution of the problem of stochastic dynamics of aerosol clusters by Monte Carlo method

Abstract A Monte Carlo algorithm based on the use of transfer matrices is developed to describe the stochastic dynamics of the rotational--translational motion of aerosol clusters taking into account fluctuations in the molecular fluxes of the gas medium. In the general case, the cluster is immersed into a rarefied gas medium, the temperatures of its surfaces may differ from the temperature of the surrounding gas, for example, due to absorption of visible and infrared radiation. The motion of the cluster is described based on Langevin motion equations. The algorithm allows one to calculate parameters of the probability distribution of a six-dimensional vector consisting of components of the momentum and angular momentum vectors transmitted to the cluster by molecular flows. The numerical method allows one to apply preliminary analytical averaging modulo velocities of molecules for both the average values of the components of momentum and angular momentum and their correlation characteristics, which significantly reduces the calculation time.