SEMANTIC FEATURES OF THE PHRASEOLOGICAL UNITS WITH THE COMPONENT LIGHT THE WITHIN ARTISTIC DISCOURSE

Purpose: To conduct lexical and semantic analysis on the concept light in the artistic discourse of postmodern fiction. Methodology: In this research, comparative method, search for synonyms, continuous sampling and seminal analysis are used. Main Findings: As a result, it becomes obvious that the boundaries of the artistic concepts are extremely blurred and much wider than the boundaries of the corresponding non-artistic concepts. In conclusion, the concept light is frequently used in English artistic discourses, i.e. significant in the culture, and a special status in the semantic space of the concept light has the meaning of knowledge and information. Applications: The study results can be used by students and universities. Novelty/Originality: In this research, a model of the semantic features of the phraseological units with the component light is presented in a comprehensive and complete manner

Natural Afforestation on Abandoned Agricultural Lands during Post-Soviet Period: A Comparative Landsat Data Analysis of Bordering Regions in Russia and Belarus

Remote monitoring of natural afforestation processes on abandoned agricultural lands is crucial for assessments and predictions of forest cover dynamics, biodiversity, ecosystem functions and services. In this work, we built on the general approach of combining satellite and field data for forest mapping and developed a simple and robust method for afforestation dynamics assessment. This method is based on Landsat imagery and index-based thresholding and specifically targets suitability for limited field data. We demonstrated method’s details and performance by conducting a case study for two bordering districts of Rudnya (Smolensk region, Russia) and Liozno (Vitebsk region, Belarus). This study area was selected because of the striking differences in the development of the agrarian sectors of these countries during the post-Soviet period (1991-present day). We used Landsat data to generate a consistent time series of five-year cloud-free multispectral composite images for the 1985–2020 period via the Google Earth Engine. Three spectral indices, each specifically designed for either forest, water or bare soil identification, were used for forest cover and arable land mapping. Threshold values for indices classification were both determined and verified based on field data and additional samples obtained by visual interpretation of very high-resolution satellite imagery. The developed approach was applied over the full Landsat time series to quantify 35-year afforestation dynamics over the study area. About 32% of initial arable lands and grasslands in the Russian district were afforested by the end of considered period, while the agricultural lands in Belarus’ district decreased only by around 5%. Obtained results are in the good agreement with the previous studies dedicated to the agricultural lands abandonment in the Eastern Europe region. The proposed method could be further developed into a general universally applicable technique for forest cover mapping in different growing conditions at local and regional spatial levels

Natural Afforestation on Abandoned Agricultural Lands during Post-Soviet Period: A Comparative Landsat Data Analysis of Bordering Regions in Russia and Belarus

Remote monitoring of natural afforestation processes on abandoned agricultural lands is crucial for assessments and predictions of forest cover dynamics, biodiversity, ecosystem functions and services. In this work, we built on the general approach of combining satellite and field data for forest mapping and developed a simple and robust method for afforestation dynamics assessment. This method is based on Landsat imagery and index-based thresholding and specifically targets suitability for limited field data. We demonstrated method’s details and performance by conducting a case study for two bordering districts of Rudnya (Smolensk region, Russia) and Liozno (Vitebsk region, Belarus). This study area was selected because of the striking differences in the development of the agrarian sectors of these countries during the post-Soviet period (1991-present day). We used Landsat data to generate a consistent time series of five-year cloud-free multispectral composite images for the 1985–2020 period via the Google Earth Engine. Three spectral indices, each specifically designed for either forest, water or bare soil identification, were used for forest cover and arable land mapping. Threshold values for indices classification were both determined and verified based on field data and additional samples obtained by visual interpretation of very high-resolution satellite imagery. The developed approach was applied over the full Landsat time series to quantify 35-year afforestation dynamics over the study area. About 32% of initial arable lands and grasslands in the Russian district were afforested by the end of considered period, while the agricultural lands in Belarus’ district decreased only by around 5%. Obtained results are in the good agreement with the previous studies dedicated to the agricultural lands abandonment in the Eastern Europe region. The proposed method could be further developed into a general universally applicable technique for forest cover mapping in different growing conditions at local and regional spatial levels

Информационные особенности оценивания соответствия состояния экологичности системных объектов

Обґрунтовано необхідність створення нових засад екологічного аналізу в умовах теоретично-практичної реалізації основ сталого розвитку, упровадження синергетичної, ентропійно-інформаційної складових у методичне забезпечення системи комплексного оцінювання екологічності системних об’єктів. Методичне забезпечення комплексного оцінювання якості навколишнього природного середовища подано у вигляді комплексування методик головних компонент і компараторної ідентифікації при багатоплановій вихідній інформації про характеристики системного об’єкта. Практичне застосування поданих пропозицій розглянуто на прикладі дослідження техногенно-навантажених регіональних утворень з використанням моніторингової інформації.In this paper, the necessity for creating new ecological principles in terms of the theoretical analysis and practical implementation of the foundations of sustainable development, implementing a synergetic, entropy-information component in the methodological support of integrated environmental assessment system objects was justified. Supportive comprehensive assessment of environmental quality is provided in the form of integration methods of principal components and comparing identification when using diverse initial information on the characteristics of the system object. A practical application of presented proposals is considered using as an example the study of technologically loaded regional structures using monitoring information.Обоснована необходимость создания новых основ экологического анализа в условиях теоретически-практической реализации основ устойчивого развития, внедрения синергетической, энтропийного-информационной составляющих в методическое обеспечение системы комплексного оценивания экологичности системных объектов. Методическое обеспечение комплексного оценивания качества окружающей природной среды предоставлено в виде комплексирования методик главных компонент и компараторной идентификации при многоплановой исходной информации о характеристиках системного объекта. Практическое применение предоставленных предложений рассмотрено на примере исследования техногенно-нагруженных региональных образований с использованием мониторинговой информации

Seroprevalence of SARS-Cov-2 Antibodies in Adults, Arkhangelsk, Russia.

Population-based data on coronavirus disease in Russia and on the immunogenicity of the Sputnik V vaccine are sparse. In a survey of 1,080 residents of Arkhangelsk 40-75 years of age, 65% were seropositive for IgG. Fifteen percent of participants had been vaccinated; of those, 97% were seropositive

Erot spatiaalisissa ja ajallisissa reaktionormeissa kevään ja syksyn fenologisille tapahtumille

For species to stay temporally tuned to their environment, they use cues such as the accumulation of degree-days. The relationships between the timing of a phenological event in a population and its environmental cue can be described by a population-level reaction norm. Variation in reaction norms along environmental gradients may either intensify the envi- ronmental effects on timing (cogradient variation) or attenu- ate the effects (countergradient variation). To resolve spatial and seasonal variation in species’ response, we use a unique dataset of 91 taxa and 178 phenological events observed across a network of 472 monitoring sites, spread across the nations of the former Soviet Union. We show that compared to local rates of advancement of phenological events with the advancement of temperature-related cues (i.e., variation within site over years), spatial variation in reaction normsPeer reviewe

Chronicles of nature calendar, a long-term and large-scale multitaxon database on phenology

We present an extensive, large-scale, long-term and multitaxon database on phenological and climatic variation, involving 506,186 observation dates acquired in 471 localities in Russian Federation, Ukraine, Uzbekistan, Belarus and Kyrgyzstan. The data cover the period 1890-2018, with 96% of the data being from 1960 onwards. The database is rich in plants, birds and climatic events, but also includes insects, amphibians, reptiles and fungi. The database includes multiple events per species, such as the onset days of leaf unfolding and leaf fall for plants, and the days for first spring and last autumn occurrences for birds. The data were acquired using standardized methods by permanent staff of national parks and nature reserves (87% of the data) and members of a phenological observation network (13% of the data). The database is valuable for exploring how species respond in their phenology to climate change. Large-scale analyses of spatial variation in phenological response can help to better predict the consequences of species and community responses to climate change.Peer reviewe