FORMATION OF A REGIONAL DEVELOPMENT STRATEGY TAKING INTO ACCOUNT THE SPATIAL COMPONENT: ON THE EXAMPLE OF THE REPUBLIC OF BASHKORTOSTAN

The relevance of this study is determined by the need to improve the tools for developing strategies for the development of territorial socio-economic systems, taking into account the realities of the current stage of development. Among these realities are the formation of the economic space of the region and the limited resources for development, which determined the logic, goal and objectives of this study. The purpose of this study is to develop theoretical, methodological and practical recommendations for the formation of a regional development strategy taking into account the spatial component. To achieve this goal, the following tasks were formulated and solved: clarification of the essence and content of the category "economic space" as the basis for accounting for this category in strategic developments; identification of the features of regional development, taking into account the spatial component; development of principles and prerequisites for regional strategy taking into account the spatial component of development; formation of a scheme for accounting for the spatial component in the development of strategies for multi-level territorial entities; development and testing of a modified model of resource provision for territorial development strategies as an updated toolkit for regional strategy. The novelty of the results of this study lies in the development of theoretical, methodological and practical recommendations for using the spatial component in the formation of a regional development strategy, which, unlike existing developments, allow taking into account the properties and characteristics of economic space when developing a block for the distribution of territorial resources and thereby provide conditions for increasing the resulting parameters multilevel territorial entities and the region as a whole.

Soil Classification and Crop Prediction

Agribusiness is the core of numerous nations and soil is the primary significant component of horticulture. There are diverse soil sorts and every sort has various highlights for various yields. In this field, presently a day's various techniques and models are utilized to build the amount of the harvests. So the primary motivation behind this of this task is to make a model that assists ranchers with realizing which harvest should take in a specific kind of soil. In this task, we measure the dirt pictures to produce an advanced soil characterization framework for rustic ranchers for minimal price. Tensorflow climate is utilized from this we can download the necessary bundles. We are utilizing two datasets, that is preparing set comprises of four sorts of soil Alluvial, Red, Dark, Earth and train set. Soil surface is the principle factor to be considered prior to doing development. In this methodology, we can gather 50 examples from the various areas of our country. The examples are shot under light condition utilizing an any camera. Soil pictures are handled through the various stages like Convolution layer is to separate highlights from the info picture, Max pool layer is to decrease the spatial component of the information volume for next layers, Drop out layer is arbitrarily sets input units to 0 with a recurrence of rate at each progression during preparing time, which forestalls over fitting, and different layers.

Perceiving numerosity does not cause automatic shifts of spatial attention

It is debated whether the representation of numbers is endowed with a directional-spatial component so that perceiving small-magnitude numbers triggers leftward shifts of attention and perceiving large-magnitude numbers rightward shifts. Contrary to initial findings, recent investigations have demonstrated that centrally presented small-magnitude and large-magnitude Arabic numbers do not cause leftward and rightward shifts of attention, respectively. Here we verified whether perceiving small or large non-symbolic numerosities (i.e., clouds of dots) drives attention to the left or the right side of space, respectively. In experiment 1, participants were presented with central small (1, 2) vs large-numerosity (8, 9) clouds of dots followed by an imperative target in the left or right side of space. In experiment 2, a central cloud of dots (i.e., five dots) was followed by the simultaneous presentation of two identical dot-clouds, one on the left and one on the right side of space. Lateral clouds were both lower (1, 2) or higher in numerosity (8, 9) than the central cloud. After a variable delay, one of the two lateral clouds turned red and participants had to signal the colour change through a unimanual response. We found that (a) in Experiment 1, the small vs large numerosity of the central cloud of dots did not speed up the detection of left vs right targets, respectively, (b) in Experiment 2, the detection of colour change was not faster in the left side of space when lateral clouds were smaller in numerosity than the central reference and in the right side when clouds were larger in numerosity. These findings show that perceiving non-symbolic numerosity does not cause automatic shifts of spatial attention and suggests no inherent association between the representation of numerosity and that of directional space.

Inverse parabolic problems of determining functions with one spatial-component independence by Carleman estimate

For a parabolic equation in the spatial variable x = ( x 1 , … , x n ) {x=(x_{1},\ldots,x_{n})} and time t, we consider an inverse problem of determining a coefficient which is independent of one spatial component x n {x_{n}} by lateral boundary data. We apply a Carleman estimate to prove a conditional stability estimate for the inverse problem. Also, we prove similar results for the corresponding inverse source problem.

Spatial component of long-term development scenarios for the digital economy

The article discusses the indicators of the development of innovative functioning of enterprises, as well as the main features of the organization of the process of innovative development. Scenarios and directions of innovative development in some countries of the world are defined. Scenarios for predicting changes in the digital economy in the Russian Federation are presented and analyzed.

DEFINITION OF UNIVERSAL CRITERIA FOR EVALUATING THE INTERIORS OF INSTITUTIONS OF ADDITIONAL EDUCATION

The organization of the subject-spatial environment is one of the necessary elements for the successful formation of the educational process, including in institutions of additional education. Currently, researchers pay attention to the importance of the subject-spatial component of the educational environment. To develop a comfortable, creative interior, it is necessary to develop a system for assessing the compliance of this component with modern design requirements. Within the framework of the article, a possible variant of universal criteria for evaluating recreation areas in leisure and educational institutions is proposed, the results of which reveal the existing contradictions and shortcomings, as well as provide a choice of a conceptual solution for subsequent project development.

Temporal variation of spatial autocorrelation of COVID-19 cases identified in Poland during the year from the beginning of the pandemic

The spread of the COVID-19 pandemic has a simultaneous temporal and spatial component. This pattern results from a complex combination of factors, including social ones, that lead to significant differences in the evolution of space-time distributions, both between and within countries. The aim of this study was to assess changes in the regularity of the spatial distribution of the number of diagnosed COVID-19 cases in Poland over more than a year of the pandemic. The analysis utilized daily and weekly data for 380 counties (poviats), using the local – Poisson risk semivariogram – measure of spatial autocorrelation. Despite the heterogeneity and errors in the source data, it was possible to identify clear patterns of temporal changes in the spatial distribution of COVID-19 cases, manifested by differences in the nature and extent of their autocorrelation.