Forecast Scenarios Research Articles

Scenario inference model of urban metro system cascading failure under extreme rainfall conditions

Metro systems have become high-vulnerability entities due to the increasing frequency and severity of urban flooding. Flood events may cause cascading failure to metro systems; therefore, exploring the cascading failure risk of the metro system is a prerequisite for urban flooding prevention and risk management. This study presented a Rank-Order Centroid (ROC) based CIA-ISM (Cross-Impact Analysis, and Interpretive Structural Modeling) method to accurately assess the reliability of emergency management in metro systems under extreme rainfall conditions. We applied this approach to a metro flooding case in Zhengzhou on July 20, 2021. The reliability results show that efficient rescue and timely shutdown notification are the most critical causal events in the cascading failure scenarios. The events of system vulnerability that have the most significant impact on casualties, property losses, and social panic are, respectively, timely notification of the shutdown, humanitarian aid, and public opinion guidance. In forecast scenarios with emergency management measures in effect, the probability of casualties, property losses, and social panic decrease by 96.3%, 58.58%, and 64.28%, respectively. Moreover, a comparison with Bayesian Network (BN) model verified the effectiveness of the ROC-based CIA-ISM approach. Based on the study, we suggest the metro companies release a timely notification of the shutdown. This study can provide scientific data for decision-makers to reasonably develop emergency strategies, significantly reducing flood losses and promoting cities’ sustainable development.

Planning and Energy–Economy–Environment–Security Evaluation Methods for Municipal Energy Systems in China under Targets of Peak Carbon Emissions and Carbon Neutrality

In order to mitigate the negative effects of global climate change, the Chinese government has committed to achieving peak carbon emissions by 2030 and carbon neutrality by 2060. Since municipal cities are the bottom administrative level for drawing up development plans, it is necessary and important to conduct decarbonization pathway research on municipal energy systems (MESs). However, there is little research on decarbonization at the municipal level, and the impact of development paths in each forecast scenario is mostly based on expert evaluation and qualitative assessment. Therefore, this study established a complete decarbonization framework for MESs, including general research procedures, models, and a sustainable evaluation method. The models of energy consumption and carbon emission were adapted and improved for MESs. In order to quantitatively evaluate the energy system development for each scenario, we proposed an energy–economy–environment–security (3E–S) evaluation method, in which principal component analysis (PCA) was adopted for multi-criterion decision making. According to the analysis results of the case city in Guangdong, this evaluation method was proved to be an effective way to identify the factors that may influence coordinated development. By adjusting the relevant parameters and factors in the model, the optimal decarbonization pathway can be found to promote sustainable and coordinated development, thus helping government decision makers to quantitatively evaluate planning paths.

Modeling approaches and tools of the mutual influence of the migration activity of the population and economic development of the territories

Introduction of sanctions restrictions, curtailment of international relations that caused significant reduction of volume of foreign trade turnover and the intensity of interaction between the world countries in technological and financial area, is continuing to have a significant impact on the economic development of the Russian Federation. One of the topical tasks within the general issues of improving strategic planning mechanisms is extending the opportunities for application of the existing methods and tools for identifying the degree of interrelationship between the economic development of the territorial entities and dynamics of the migration process including the perspective of the further creation of forecast scenarios for changes in the migration attractiveness of the entities of the Russian Federation. An effective tool for solving this problem is development and implementation of various economic and mathematical models that provide the opportunity for identifying the key factors affecting the migration activity of the population, carrying out scenario forecasting to evaluate the effect of various measures of government regulation on the dynamics of social and economic development of the territories in the medium- and long-term perspectives. The study in hand involves comparative assessment of well-known approaches and tools used for imitative modelling of economic and demographic development of territorial systems with different level. The authors have conducted the analysis that made it possible to reveal the opportunities and the limits of their practical implementation within the task of evaluating the mutual influence of the migration activity of the population and economic development of the territories. Taking into account the results of assessment, the authors formulate basic principles and requirements for establishing an appropriate set of modelling tools. They justify the approach to studying the mutual influence of the migration activity of the population and economic development of the region based on the complex application of imitation modelling methods, indistinct logic, parameter analysis as well as geographical information technologies. Complex application of these methods will provide for the development of mechanisms of regulating interregional migration and allow establishing the measures for ensuring sustainable development of the economics of the regions of the Russian Federation in the long-term perspective.

Evaluation and prediction of land use change impacts on ecosystem service values in Nanjing City from 1995 to 2030.

Land use changes have a considerable impact on ecosystem services (ESs). In recent years, land use changes caused by urban expansion in Nanjing City have been obvious and are expected to further change in the future. Therefore, it is urgent to quantitatively assess ecosystem service value (ESV) changes caused by previous land use changes and future potential changes in Nanjing. In this study, land use data products based on remote sensing images, Dyna-CLUE model, and the ESV equivalent coefficient method were applied to assess the impact of land use changes on ESVs in Nanjing City over the past 23 years (1995-2018), and to forecast the changes of ESV in 2030. The results indicated that the total ESVs of Nanjing City displayed a trend of first increasing and then declining in 1995-2018. From the land use classification, the water area had the largest ESV in Nanjing, followed by arable land. Additionally, the regulating service value was the highest among the four primary ESs in Nanjing from 1995 to 2030, with the highest value of 13.73 billion yuan in 2015. Among the three forecast scenarios, the ecological protection scenario had the highest total ESV and was followed by the urban expansion and business as usual scenarios. These findings may assist for the scientific decision-making of sustainable land use and ecosystem management in Nanjing City.

Growth Recovery and COVID-19 Pandemic Model: Comparative Analysis for Selected Emerging Economies

The outburst of the COVID-19 pandemic and its rapid spread throughout the world in 2020 shed a new light on mathematic models describing the nature of epidemics. However, as the pandemic shocked economies to a much greater extent than earlier epidemics, the recovery potential of economies was emphasized and its inclusion in epidemic models is becoming more important. The present paper deals with the issues of modeling the recovery of economic systems that have undergone severe medical shocks, such as COVID-19. The proposed mathematical model considers the close relationship between the dynamics of pandemics and economic development. This distinguishes it from purely “medical” models, which are used exclusively to study the dynamics of the spread of the COVID-19 pandemic. Unlike standard SIR models, the present approach involves the introduction of the “vaccine” equation to the SIR model and introduces correction components that include the possibility of re-infection and other nuances such as the number of people at risk of infection (not sick with COVID but not vaccinated); sick with COVID; recovered; fully vaccinated (two doses) citizens; the rate of COVID infection; the rate of recovery of infected individuals; the vaccination coefficients, respectively, for those who have not been ill and recovered from COVID; the coefficient of revaccination; the COVID re-infection rate; and the population fluctuation coefficient, which takes into account the effect of population change as a result of births and deaths and due to the departure and return of citizens. The present model contains governance so that it not only generates scenario projections but also models specific governance measures as well to include the pandemic and restore economic growth. The model also adds management issues, so that it not only generates scenario forecasts but simultaneously models specific management measures as well, aiming to suppress the pandemic and restoring economic growth. The model was implemented on specific data on the dynamics of the spread of the COVID-19 pandemic in selected developing economies.

WindGMMN: Scenario Forecasting for Wind Power Using Generative Moment Matching Networks

With the increasing penetration of wind power generation, the fluctuating and intermittent behavior of wind power poses huge challenges to the operation and planning of distribution networks. A popular way to mitigate these challenges is to provide a group of possible wind power forecasting scenarios instead of depending on deterministic point forecasting values, so that system operators can consider the uncertainties. This letter proposes a novel WindGMMN method for wind power scenario forecasting, in which necessary modifications are made on the generative moment matching network (GMMN), and an optimization strategy is designed to find a series of wind power scenarios with similar shapes, probability distributions, and temporal correlations as potential scenarios. Simulations and analyses were performed on a public dataset with 2190 wind power generation curves and their corresponding meteorological features. The results show that the proposed WindGMMN outperforms popular baselines (e.g., variational auto-encoders and generative adversarial networks) for scenario forecasting of wind power, without any restrictions on the time horizon (e.g., times ranging from 10 min to 24 h).

Evidential policy in the management decision making mechanism at the macro level

The article presents a comparative analysis of alternative approaches to the formation of state economic policy in the modern world — purely ideological, political-conjunctural and scientific-evidential ones disclosing the unconditional advantages of the latter. Evidential economic policy that comprehensively assess available options for achieving high-priority macroeconomic goals is seen as a way to counter real-world threats to management decision-making at the macro level, based only on the ideological leanings of political parties and their theorists (classics and Keynesians), as well as the fact that opportunistic politicians persistently serve not the public interests, but their own selfi sh ones. Contributing to the formation of the methodological foundations of evidential economic policy, the author emphasizes the need to not limit oneself to careful collection of real facts, to formation of a "register of best practices" in world economic history and to the use of modern econometric methods in order to avoid reproaches in empiricism. Absolute emphasis in this case should be made on identifying cause-eff ect relations in the economic system in their strong correlation. Thus, success in the implementation of the evidential economic policy of the country is mostly associated with the state of macroeconomic theory, its ability to provide comprehensive analysis and scenario forecasting of the economic situation.

Asymptotic-Preserving Neural Networks for multiscale hyperbolic models of epidemic spread

When investigating epidemic dynamics through differential models, the parameters needed to understand the phenomenon and to simulate forecast scenarios require a delicate calibration phase, often made even more challenging by the scarcity and uncertainty of the observed data reported by official sources. In this context, Physics-Informed Neural Networks (PINNs), by embedding the knowledge of the differential model that governs the physical phenomenon in the learning process, can effectively address the inverse and forward problem of data-driven learning and solving the corresponding epidemic problem. In many circumstances, however, the spatial propagation of an infectious disease is characterized by movements of individuals at different scales governed by multiscale partial differential equations. This reflects the heterogeneity of a region or territory in relation to the dynamics within cities and in neighboring zones. In presence of multiple scales, a direct application of PINNs generally leads to poor results due to the multiscale nature of the differential model in the loss function of the neural network. To allow the neural network to operate uniformly with respect to the small scales, it is desirable that the neural network satisfies an Asymptotic-Preservation (AP) property in the learning process. To this end, we consider a new class of AP neural networks for multiscale hyperbolic transport models of epidemic spread that, thanks to an appropriate AP formulation of the loss function, is capable of working uniformly at the different scales of the system. A series of numerical tests for different epidemic scenarios confirms the validity of the proposed approach, highlighting the importance of the AP property in the neural network when dealing with multiscale problems especially in presence of sparse and partially observed systems.

The development of natural gas in Asia—the results of the forecast scenarios of the POLES model

Abstract Many studies have shown the important role of natural gas in worldwide energy transition to gradually reduce the impacts on climate change. Asia is considered the centre of future gas demand growth. With a view to demonstrating the role of natural gas in the energy transition in Asia, this article will analyse the results from the scenarios forecasting the development of natural gas based on the Prospective Outlook on Long-term Energy Systems energy forecasting model.

An Improved Climatological Forecast Method for Projecting End-of-Season Water Requirement Satisfaction Index

Abstract A simple—yet powerful—indicator for monitoring agricultural drought is the water requirement satisfaction index (WRSI). In data-sparse, food-insecure areas, the WRSI is used to guide billions of dollars of aid every year. The WRSI uses precipitation (PPT) and reference evapotranspiration (RefET) data to estimate water availability relative to water demand experienced over the course of a growing season. If the season is in progress, to-date conditions can be combined with climatological averages to provide insight into potential end-of-season (EOS) crop performance. However, if the average is misrepresented, these forecasts can hinder early warning and delay precious humanitarian aid. While many agencies use arithmetic average climatologies as proxies for “average conditions,” little published research evaluates their effectiveness in crop-water balance models. Here, we use WRSI hindcasts of three African regions’ growing seasons, from 1981 to 2019, to assess the adequacy of the arithmetic mean climatological forecast—the Extended WRSI. We find that the Extended WRSI is positively biased, overestimating the actual EOS WRSI by 2%–23% in East, West, and southern Africa. The presented alternative combines to-date conditions with data from previous seasons to produce a series of historically realistic conclusions to the current season. The mean of these scenarios is the WRSI Outlook. In comparison with the Extended WRSI, which creates a single forecast scenario using average inputs that are not covarying, the WRSI Outlook employs an ensemble of scenarios, which more adequately capture the historical distribution of distribution of rainfall events along with the covariability between climate variables. More specifically, the impact of dry spells in individual years is included in the WRSI Outlook in a way that is smoothed over in the Extended WRSI. We find that the WRSI Outlook has a near-zero bias score and generally has a lower RMSE. In total, this paper highlights the inadequacies of the arithmetic mean climatological forecast and presents a less biased and more accurate scenario-based approach. To this end, the WRSI Outlook can improve our ability to identify agricultural drought and the concomitant need for humanitarian aid.

Forecasting Convection with a “Scale-Aware” Tiedtke Cumulus Parameterization Scheme at Kilometer Scales

Abstract A scale-aware convective parameterization based on the Tiedtke scheme is developed and tested in the Weather Research and Forecasting (WRF) Model and the Model for Prediction Across Scales (MPAS) for a few convective cases at grid sizes in the ranges of 1.5–4.5 km. These tests demonstrate that the scale-aware scheme effectively reduces the outcome of deep convection by decreasing the convective portion of the total surface precipitation. When compared to the model runs that use microphysics without the cumulus parameterization at these grid sizes, the modified Tiedtke scheme is shown to improve some aspects of the precipitation forecasts. When the scheme is applied on a variable mesh in MPAS, it handles the convection across the mesh transition zones smoothly. Significance Statement Representing convection accounting for variations in the size of grid mesh is crucial in numerical models with variable resolutions, and in precipitation events where convection is not well depicted even by a model mesh of a few kilometers. Many convective parameterizations have already considered this grid-size dependency. This paper fills a gap by applying the same concept to a different convective parameterization, and evaluating it in a few precipitation forecast scenarios.

Nowcasting and forecasting COVID-19 waves: the recursive and stochastic nature of transmission.

We propose a parsimonious, yet effective, susceptible–exposed–infected–removed-type model that incorporates the time change in the transmission and death rates. The model is calibrated by Tikhonov-type regularization from official reports from New York City (NYC), Chicago, the State of São Paulo, in Brazil and British Columbia, in Canada. To forecast, we propose different ways to extend the transmission parameter, considering its estimated values. The forecast accuracy is then evaluated using real data from the above referred places. All the techniques accurately provided forecast scenarios for periods 15 days long. One of the models effectively predicted the magnitude of the four waves of infections in NYC, including the one caused by the Omicron variant for periods of 45 days using out-of-sample data.

THE IMPACT OF DIGITALIZATION ON ENSURING ECONOMIC GROWTH

Digitalization of the economy and society of countries creates new opportunities for sustainable socioeconomic development. The level and directions of the impact of digitalization on economic growth require assessment and determination of national differences that is the aim of the given study. The paper reveals the peculiarities of the international experience of tracking the impact of digitalization on economic growth and sustainable economic development. Based on the approbation of the authors’ methodology, the study determines the quantitative measures and assesses the impact of digitalization on sustainable economic growth at the national level. The authors have developed forecast scenarios for the digital sector development to achieve the targets of economic growth contained in the development strategies of Ukraine until 2030.

VIRAL AND ECONOMIC PROBLEMS OF EDUCATION IN THE CONTEXT OF WORLD TRANSFORMATIONS

Abstract. The article presents the data of experts’ assessments of the impact of the coronavirus pandemic on the world economy; the scenario forecast of deepening global crisis in 2021 and 2022. The IMF predicts a slowdown in 2022 in the global economy, which could cause a financial crisis. UN Secretary-General Antonio Guterres shares the same view. According to his statement, the coronavirus pandemic would lead to the worst crisis in the last century. Coronavirus has affected education not only in Ukraine, but also in Western countries, where the traditions of higher education are long and well known, and education is very expensive. The pandemic forced distance learning even at world-renowned universities, sparking a wave of protests among students for several reasons. The first is financial. Full-time education is more expensive than distance learning. Due to the transfer of full-time students to distance learning, they began to require university administrations to review pricing policies. The second reason is the decline in the prestige of education compared to previous years. Thirdly, the pandemic will inevitably lead to an unstable labor market for graduates. During this time, Ukrainian education has faced such problems that occur in the best universities in the world. The global paradigm of higher education is changing rapidly. Short training programs for quick acquisition of new skills come to the fore. Distance learning opens up new perspectives. Anyone can attend lectures from leading universities. The service allows getting a bachelor’s or master’s degree. The positive experience of Polish education is highlighted in this paper. The deterioration of education as a threat not only to the quality of training of highly qualified specialists, but also to the country as a whole is emphasized. The important role of artificial intelligence in education is pointed out. The initiative of the President of Ukraine V. Zelensky on the need to create a presidential university of modern education and a research center - a leader in strategic areas of state development has been announced.

Cooperation between Russia and Kazakhstan as a Vector of Eurasian Integration

The study analyzes the areas of cooperation between Russia and Kazakhstan within the framework of Eurasian integration.Aim. To identify the presence of factors contributing to the strengthening of relations between Russia and Kazakhstan at the present stage and obstacles hindering the deepening of integration processes.Tasks. To analyze the current state of cooperation between the two countries within the framework of the Eurasian Union, to identify obstacles to deepening integration processes, to show forecast scenarios of interaction between Russia and Kazakhstan. To analyze how these scenarios will affect the relationship between the two countries, and what consequences will be if each of them is implemented.Methods. The article uses general scientific methods of analysis and synthesis, a systematic approach, as well as an empirical method of expert evaluation.Results. The study showed that there are strong relations between the two countries in the economic sphere within the framework of the EAEU. Russia is the main trading partner of Kazakhstan. Projects related to the Caspian Sea are being developed and look very promising. Joint military exercises and supplies of Russian weapons are of great interest to Kazakhstan. Russia acts as a guarantor of Kazakhstan’s security in the region and its main partner in the Eurasian space. The Collective Security Treaty Organization also plays an important role in the relations between the two countries, which proved its effectiveness in the January 2022 events, contributing to the resolution of the political crisis and preventing extremist actions of armed terrorist groups. At the same time, the role of Kazakhstan as its closest neighbor and ally is also important for Russia, especially in the context of escalating international tensions.Conclusions. Both Russia and Kazakhstan are interested in further cooperation in the economic, military and cultural spheres. At the same time, the further deepening of integration processes is hindered by the absence of large joint investment projects and the multi-vector nature of Kazakhstan’s foreign policy. In the context of the information war of the West against Russia and the increasing international tension, it is extremely important to deepen cooperation between the two countries.

Redesigning a network of primary healthcare centres using system dynamics simulation and optimisation

This paper presents the redesign of a network of health providing facilities, as far as geographical location and allocation of service levels are concerned. A novel methodology which integrates system dynamics (SD) and mathematical programming is used. Simulations of SD models of different patients-facilities system configurations provide forecasting scenarios for demand, which are then supplied as input to a stochastic facility location model formulated as a two-stage process. The first stage determines the strategic decisions concerning the range and type of services that every health centre should provide, while the second stage, which is scenario dependent, assigns patients to health centres. The proposed methodology allows experimentation with different system structures to gain a robust understanding of patient flows and facility service dynamics over the entire planning horizon. The methodology was applied in the (re)location of health services in a network of 32 primary care health centres and 13 hospitals in Southern Greece.

Towards Financing System of Integrated Enterprise Development in the Time of COVID-19 Outbreak

The development of an enterprise under current conditions requires an integrated approach and an appropriate financing system. The purpose of this study is to justify the replication model of financing the integrated enterprise development. The research methodology suggests that each enterprise has its own development “genome”, which makes it possible to apply the replication of its directions based on a justified financing system of such an integration. The proposed replication model is augmented by regression analysis, which made it possible to carry out scenario forecasting of alternative options for the company’s development. The conduction of the study is based on 16 textile enterprises. The formed map of the integrated enterprise development enabled the determination of their points to replicate resources in four directions (environmental and economic, innovative, informational, and organizational). The interaction of companies on the basis of strengths diffusion (exchange of potential) with the application of financial netting is considered an alternative to replication. The research proved that an alternative option can solely be recommended for developed companies and requires the identification and minimization of risks. The strong link between the level of integrated and overall development of companies was acknowledged. Asymmetry of business development in the context of a replication model of its integration enables the achievement of high results while minimizing financial resources. Enterprises implementing the replication model of integration considerably improve their prospects and increase overall development performance. The application of the replication model of financing integration under the crisis and the COVID-19 pandemic fosters efficient use of financial resources and the overall enterprise development.

Las microhabilidades expresivas orales en los estudiantes de bachillerato de la Unidad Educativa “Luis Fernando Ruiz”

This research describes the use of oral expressive microskills of Luis Fernandez Ruiz High school students at the 2021-2022 school year. This project has a qualitative approach. It addresses a social fact as the application of expressive microskills in the stages of planning, development and evaluation of oral speech. The results of this research demonstrate that in the planning stage those under investigation apply the following expressive microskills: comunicative intention, identifying the kind of speech, script writing, evocation of experienced, but, they do not consider: identification of needs, the stablishment of objective setting, the discursive situation, voice log level identification. In development, they apply the following microskills: discursive sequence, assesment of the discursive sutuation, tone of voice, strategies of initiation, development and closure, hierarchy, coherence and cohesion of ideas, public reaction and spelling. But, they do not apply: adequacy of speech, complexity in sentences, paralinguistic elements, adaptation of the speech to the context, age and level of education of the audience. In the evaluation of oral speech, the microskills they apply are: valuing diversity, correcting mistakes, applying improvements, anticipation, scenario forecasting and they do not take into account: recognition of successes and failures and consolidation of successes. This leads to the conclusion that those students under investigation apply expressive oral microskills that affect directly the quality of oral speech

The impact of Google Trends index and encompassing tests on forecast combinations in tourism

El impacto de Google Trends en la previsión de viajes combinados y su evidencia relacionadaPropósitoDado que el uso de los datos de Google Trends es útil para mejorar la precisión de las predicciones, este estudio examina si el uso del índice de búsqueda web de Google Trends combinado con la agregación de relevancia puede mejorar la precisión del predictor.Diseño/metodología/enfoqueEl modelo predictivo gris genera predicciones bajo un único modelo, mientras que el modelomultivariado utiliza el indicador Google Trends como variable explicativa. Se generaron tresensamblajes generales, incluido el Modelo armónico único (CUGM), los ensamblajes de todos loscomponentes (CAGM) y la prueba de presencia de componentes con predicción (CSET). Laspredicciones individuales encada grupo luego se combinan utilizando métodos de correlación deuso común.RecomendacionesUtilizando el número de turistas en las cuatro ciudades más investigadas de Taiwán, los tresgrupos combinados se clasificaron según su precisión. Las pruebas incluidas muestran que losmodelos multivariados en escala de grises son importantes para la predicción. Además, losresultados de las pruebas muestran que el índice de Google Trends y las pruebas que incluyenmétodos de suma lineal son útiles porque los métodos combinados con CSET funcionan majorque los métodos combinados con CSET. CAGM y VCUG.Implicaciones practicesLa industria de viajes puede usar el índice de búsqueda web de Google Trends para desarrollarestrategias comerciales para atracciones basadas en un conjunto lineal de componentes.Autenticidad/valorCon el objetivo de mejorar la precisión de los pronósticos agregados, este estudio investiga larelación entre el índice de tendencias de Google y las expectativas generales de viaje junto con laevidencia global.Palabras claveDemanda de viajes, Experiencia global, Tendencias de Google, Predicción grisTipo de papelTrabajo de investigación

The algorithms for drawing up annual plans of inspections performed by Rospotrebnadzor’s regional organizations within the framework of risk-based model

The existing model of control and surveillance activities is based on a procedure that involves assigning activities performed by juridical persons or private entrepreneurs and (or) production facilities used by them in these activities into a specific risk category or a specific hazard class (category). The goal of the present work was to develop and improve algorithms for drawing up annual plans of inspections performed by Rospotrebnadzor’s territorial organizations within the framework of the risk-based model. For the first time, we have formulated conceptual and mathematical statement of the problem of planning control and surveillance activities performed by Rospotrebnadzor. This allowed us, among other things, to consider history of violations (integrity of a given subject) over a specific period and availability of objects for inspections. The latter is described with several parameters that include both regional peculiarities (a distance between objects, quality of road networks) and “complexity” of checking a particular object. When analyzing the mathematical statement, we identified certain model parameters that had the greatest influence on a solution to the problem, that is, the most sensitive parameters that should be regulated with special care if we want to make control and surveillance activities more effective. We have created planning algorithms with preset parameter values (scenario forecasting programs) and tested them at the regional level. We have developed three criteria for comparing these algorithms: coverage of a number of subjects that are to be inspected; coverage of a number of objects that are to be inspected; coverage by the total risk. The testing results indicate that the combined algorithm has higher coverage rates since in this case not all objects are inspected when a given subject is being checked. Consequently, this allows reducing overall labor costs required to perform an inspection. The suggested approaches give an opportunity to achieve more effective distribution and use of resources allocated by Rospotrebnadzor for scheduled inspections.