Comparative analysis of types of plants-transformers in various regions of Central Russia

In this study the results of a comparative analysis of transformer species in nine different regions of Central Russia by life forms of I.G. Serebryakov (1962) and geographical origin of species are presented. Among the invasive and potentially invasive species of the compared regions, there are no common species that are transformers in all 9 regions simultaneously. However, there is a group of plants-transformers, which are represented in 8 of 9 area

Invasive fraction flora analysis in the southwest of the central Russian upland

As a result of the studying the flora invasive component of the southwest of the Central Russian Upland (Russia), the taxonomic and typological structure of alien species in the region was define

The influence of the spectral composition on the root development of ornamental plants in vitro

The results of studying the influence of spectral composition of light on rhizogenesis of ornamental plantmicrocuttings showed that the studied variant of the spectra of the led illuminators intensified the process of rhizogenesis of ornamental plan

Improving English for specific purposes skills of postgraduate students in computer-supported learning environment

Peculiarities of language acquisition in the sistem of higher education in Russia are analyzed in this reseach and the results of virtual educational environment created in Belgorod State UniversityyesBelgorod State Universit

Improving English for specific purposes skills of postgraduate students in computer-supported learning environment

yesPeculiarities of language acquisition in the sistem of higher education in Russia are analyzed in this reseach and the results of virtual educational environment created in Belgorod State UniversityBelgorod State Universit

The Triassic and Jurassic sediments in eastern Stara Planina Mts. (Bulgaria) - an example of classification of geosites in sedimentary rocks

W strukturze wschodniej Starej Planiny (wschodnia Bułgaria) występują dwa typy triasowych i jurajskich osadów Tetydy: basenowe i szelfowe. Skały pochodzenia basenowego uważane są za parautochtoniczne. Osady szelfowe są allochtoniczne. Występują one w dolnojurajskiej formacji Sini Vir oraz w środkowojurajskiej formacji Kotel, w formie olistolitów. Osady parautochtoniczne uczestniczą w prawdopodobnej strukturze płaszczowinowej, przefałdowanej w struktury antyklinalne i synklinalne, intensywnie zerodowanej przed górną kredą. Z punktu widzenia dziedzictwa geologicznego, osady triasowe i jurajskie omawianego regionu tworzą dużą zbiorczą jednostkę geotopową, obejmującą 19 geotopów: 10 w osadach parautochtonicznych, 9 w osadach allochtonicznych. Posiadają one różnorodne cechy geologiczne (tektoniczne, stratygraficzne, paleontologiczne itp.)

A collection of titles and publishers of articles used to explore historical reports of an E.coli incident 2016-2018

Data collected from Lexis Nexis database including the result of a search for UK news articles mentioning phrase "errington cheese" for the period between July 2016 and Jan 2018.Social media and other forms of online content have enormous potential as a way to understand people's opinions and attitudes, and as a means to observe emerging phenomena - such as disease outbreaks. How might policy makers use such new forms of data to better assess existing policies and help formulate new ones? This one year demonstrator project is a partnership between computer science academics at the University of Aberdeen and officers from Food Standards Scotland which aims to answer this question. Food Standards Scotland is the public-sector food body for Scotland created by the Food (Scotland) Act 2015. It regularly provides policy guidance to ministers in areas such as food hygiene monitoring and reporting, food-related health risks, and food fraud. The project will develop a software tool (the Food Sentiment Observatory) that will be used to explore the role of data from sources such as Twitter, Facebook, and TripAdvisor in three policy areas selected by Food Standards Scotland: - attitudes to the differing food hygiene information systems used in Scotland and the other UK nations; - study of an historical E.coli outbreak to understand effectiveness of monitoring and decision making protocols; - understanding the potential role of social media data in responding to new and emerging forms of food fraud. The Observatory will integrate a number of existing software tools (developed in our recent research) to allow us to mine large volumes of data to identify important textual signals, extract opinions held by individuals or groups, and crucially, to document these data processing operations - to aid transparency of policy decision-making. Given the amount of noise appearing in user-generated online content (such as fake restaurant reviews) it is our intention to investigate methods to extract meaningful and reliable knowledge, to better support policy making.</p

Tweets used to study reports of food fraud related to fish products 2018

Data collected from Twitter social media platform (8 June 2018 - 22 June 2018) to study reports of food fraud related to fish products on social media from posts originating in the UK. The dataset contains Tweet IDs and keywords used to search for Tweets using a programatic access via the public Twitter API. Keywords used in this search were generated using a machine learning tool and consisted of combinations of keywords describing terms related to fish and fake.Social media and other forms of online content have enormous potential as a way to understand people's opinions and attitudes, and as a means to observe emerging phenomena - such as disease outbreaks. How might policy makers use such new forms of data to better assess existing policies and help formulate new ones? This one year demonstrator project is a partnership between computer science academics at the University of Aberdeen and officers from Food Standards Scotland which aims to answer this question. Food Standards Scotland is the public-sector food body for Scotland created by the Food (Scotland) Act 2015. It regularly provides policy guidance to ministers in areas such as food hygiene monitoring and reporting, food-related health risks, and food fraud. The project will develop a software tool (the Food Sentiment Observatory) that will be used to explore the role of data from sources such as Twitter, Facebook, and TripAdvisor in three policy areas selected by Food Standards Scotland: - attitudes to the differing food hygiene information systems used in Scotland and the other UK nations; - study of an historical E.coli outbreak to understand effectiveness of monitoring and decision making protocols; - understanding the potential role of social media data in responding to new and emerging forms of food fraud. The Observatory will integrate a number of existing software tools (developed in our recent research) to allow us to mine large volumes of data to identify important textual signals, extract opinions held by individuals or groups, and crucially, to document these data processing operations - to aid transparency of policy decision-making. Given the amount of noise appearing in user-generated online content (such as fake restaurant reviews) it is our intention to investigate methods to extract meaningful and reliable knowledge, to better support policy making.</p

Tweets used to explore the potential role of social media data in responding to new and emerging forms of food fraud 2018

Data collected from Twitter social media platform (6 May 2018 - 16 May 2018) to explore the potential role of social media data in responding to new and emerging forms of food fraud reported on social media from posts originating in the UK. The dataset contains Tweet IDs and keywords used to search for Tweets using a programatic access via the public Twitter API. Keywords used in this search were generated using a machine learning tool and consisted of a combinations of keywords describing terms related to food and outrage.Social media and other forms of online content have enormous potential as a way to understand people's opinions and attitudes, and as a means to observe emerging phenomena - such as disease outbreaks. How might policy makers use such new forms of data to better assess existing policies and help formulate new ones? This one year demonstrator project is a partnership between computer science academics at the University of Aberdeen and officers from Food Standards Scotland which aims to answer this question. Food Standards Scotland is the public-sector food body for Scotland created by the Food (Scotland) Act 2015. It regularly provides policy guidance to ministers in areas such as food hygiene monitoring and reporting, food-related health risks, and food fraud. The project will develop a software tool (the Food Sentiment Observatory) that will be used to explore the role of data from sources such as Twitter, Facebook, and TripAdvisor in three policy areas selected by Food Standards Scotland: - attitudes to the differing food hygiene information systems used in Scotland and the other UK nations; - study of an historical E.coli outbreak to understand effectiveness of monitoring and decision making protocols; - understanding the potential role of social media data in responding to new and emerging forms of food fraud. The Observatory will integrate a number of existing software tools (developed in our recent research) to allow us to mine large volumes of data to identify important textual signals, extract opinions held by individuals or groups, and crucially, to document these data processing operations - to aid transparency of policy decision-making. Given the amount of noise appearing in user-generated online content (such as fake restaurant reviews) it is our intention to investigate methods to extract meaningful and reliable knowledge, to better support policy making.</p