Social media and politics: the case of Ukraine

Abstract Nowadays, politics is undergoing several changes, especially because of the growing use of social media from politicians, who are using these virtual platforms as tools to gain more and more consent. Social media are also leading to extreme democratization of politics, making it possible for non-politicians not only to enter the sphere of politics but even to win major competitions, such as presidential elections. To bring an actual and highly illustrative example, in this article the authors go through a deep analysis of the former actor and recently elected prime minister of Ukraine Volodimir Zelenskij and his strategical use of social media compared to the one carried out by his opponents, leading him to win the presidential elections with an enormous consent

Ukraine a country in crisis between Europe, Russia, and a complex electoral process

Abstract To this day, Ukraine is still experiencing difficult times both economically and politically. The economic and political crisis at the end of 2014, which led to the dismissal of President Yanukovich, meant that the territory of Crimea and, therefore, the port of Sevastopol as well, remained under Russian control. The new elections of 2019 carried a breath of fresh air and hope also for new relationships with Russia. The paper wants to photograph this situation and analyse the recent 2019 presidential elections

Memes and education: opportunities, approaches and perspectives

Abstract This article presents the results of an international research of using Internet-memes in education process. The writing team set out to explore the reasons and ways of using Internet memes in education in different language spaces – English, Italian, Russian and Chinese. To achieve this goal, a number of tasks were formulated, including: 1. to study the linguistic factor of the use of memes in the educational process, 2. to classify the ways of using memes depending on the purpose, 3. to analyze the content of memes in the liberal, ideological, as well as in the field of exact sciences. The first part of the research made by Alexander Malakhov (PFUR) reveals the basic concepts associated with Internet memes. The second one written by Olga Matys (PFUR) is about using memes in a sphere of Russian liberal education in journalism. The third part of the research made by Ludovico De Serio (University of Genoa) presents an analysis using memes during studying math. The last but not the least part of this article made by Xie Dongqiang (PFUR) and reveals the aspects of an ideological studying using memes. This research was carried out using such scientific methods as analysis, comparison, description. In the course of the study, the authors used the work of such researchers as Susan Blackmore, G. Bini, M. Montagnani, Anna Zagoruyko, Maria Efremova, etc. Also there was used the content of sources such as VK publics "Memology: from antiquity to the present day" and "30 seconds before my expultion", GeoGebra, www.padlet.com, etc

Effect of Friction Stir Process Parameters on the Mechanical and Thermal Behavior of 5754-H111 Aluminum Plates

A study of the Friction Stir Welding (FSW) process was carried out in order to evaluate the influence of process parameters on the mechanical properties of aluminum plates (AA5754-H111). The process was monitored during each test by means of infrared cameras in order to correlate temperature information with eventual changes of the mechanical properties of joints. In particular, two process parameters were considered for tests: the welding tool rotation speed and the welding tool traverse speed. The quality of joints was evaluated by means of destructive and non-destructive tests. In this regard, the presence of defects and the ultimate tensile strength (UTS) were investigated for each combination of the process parameters. A statistical analysis was carried out to assess the correlation between the thermal behavior of joints and the process parameters, also proving the capability of Infrared Thermography for on-line monitoring of the quality of joints

Prediction of the Vickers Microhardness and Ultimate Tensile Strength of AA5754 H111 Friction Stir Welding Butt Joints Using Artificial Neural Network

A simulation model was developed for the monitoring, controlling and optimization of the Friction Stir Welding (FSW) process. This approach, using the FSW technique, allows identifying the correlation between the process parameters (input variable) and the mechanical properties (output responses) of the welded AA5754 H111 aluminum plates. The optimization of technological parameters is a basic requirement for increasing the seam quality, since it promotes a stable and defect-free process. Both the tool rotation and the travel speed, the position of the samples extracted from the weld bead and the thermal data, detected with thermographic techniques for on-line control of the joints, were varied to build the experimental plans. The quality of joints was evaluated through destructive and non-destructive tests (visual tests, macro graphic analysis, tensile tests, indentation Vickers hardness tests and t thermographic controls). The simulation model was based on the adoption of the Artificial Neural Networks (ANNs) characterized by back-propagation learning algorithm with different types of architecture, which were able to predict with good reliability the FSW process parameters for the welding of the AA5754 H111 aluminum plates in Butt-Joint configuration

Giunti di testa in lega di alluminio 5754-H111 realizzati con il processo di Friction Stir Welding: Applicazione delle reti neurali artificiali per la previsione delle caratteristiche meccaniche dei giunti

The aim of this study was to develop an Artificial Neural Networks (RNA) able to model the Friction Stir Welding process (FSW) to provide an accurate prediction of the mechanical properties of AA 5754-H111 butt joints. The input data used for the development of neural models are taken from previous experimental investigations, which are developed according the Design of Experiments (DOE) techniques; all the joints were monitored on-line by means of infrared thermography techniques and they were characterized with destructive and non-destructive testing (visual and macro graphic analysis, tensile and Vickers microhardness tests), in order to highlight their mechanical characteristics. Finally, the significance of the FSW process parameters was evaluated by means of the Analysis of Variance (ANOVA). The use of Artificial Neural Networks to model the FSW process, has the aim of optimizing the technological parameters and to favor the development of a stable welding process, that is able to realize joints without defects and with high mechanical properties. For this purpose, two Artificial Neural Networks have been designed. They worked according the "cascade mode" in order to predict the mechanical behavior of the joints in terms of Ultimate Tensile Strength (UTS) and Vickers micro hardness of the Heat Affected Zone (HAZ). The back-propagation learning logarithm and the analysis of many network architectures has allowed us to formulate reliable predictions. This is shown by the results of the comparison between the model results and experimental data that led to the definition of a final model that can predict the quality of butt joints in aluminum alloy 5754 H111 FSW with good accuracy

Prediction of the Vickers Microhardness and Ultimate Tensile Strength of AA5754 H111 Friction Stir Welding Butt Joints Using Artificial Neural Network

A simulation model was developed for the monitoring, controlling and optimization of the Friction Stir Welding (FSW) process. This approach, using the FSW technique, allows identifying the correlation between the process parameters (input variable) and the mechanical properties (output responses) of the welded AA5754 H111 aluminum plates. The optimization of technological parameters is a basic requirement for increasing the seam quality, since it promotes a stable and defect-free process. Both the tool rotation and the travel speed, the position of the samples extracted from the weld bead and the thermal data, detected with thermographic techniques for on-line control of the joints, were varied to build the experimental plans. The quality of joints was evaluated through destructive and non-destructive tests (visual tests, macro graphic analysis, tensile tests, indentation Vickers hardness tests and t thermographic controls). The simulation model was based on the adoption of the Artificial Neural Networks (ANNs) characterized by back-propagation learning algorithm with different types of architecture, which were able to predict with good reliability the FSW process parameters for the welding of the AA5754 H111 aluminum plates in Butt-Joint configuration

Environmental distribution of Cryptococcus neoformans and C. gattii around the Mediterranean basin

In order to elucidate the distribution of Cryptococcus neoformans and C. gattii in the Mediterranean basin, an extensive environmental survey was carried out during 2012-2015. A total of 302 sites located in 12 countries were sampled, 6436 samples from 3765 trees were collected and 5% of trees were found to be colonized by cryptococcal yeasts. Cryptococcus neoformans was isolated from 177 trees and C. gattii from 13. Cryptococcus neoformans colonized 27% of Ceratonia, 10% of Olea, Platanus and Prunus trees and a lower percentage of other tree genera. The 13 C. gattii isolates were collected from five Eucalyptus, four Ceratonia, two Pinus and two Olea trees. Cryptococcus neoformans was distributed all around the Mediterranean basin, whereas C. gattii was isolated in Greece, Southern Italy and Spain, in agreement with previous findings from both clinical and environmental sources. Among C. neoformans isolates, VNI was the prevalent molecular type but VNII, VNIV and VNIII hybrid strains were also isolated. With the exception of a single VGIV isolate, all C. gattii isolates were VGI. The results confirmed the presence of both Cryptococcus species in the Mediterranean environment, and showed that both carob and olive trees represent an important niche for these yeasts

Environmental distribution of Cryptococcus Neoformans and Cryptococcus Gattii around the Mediterranean basin.

In order to elucidate the distribution of Cryptococcus neoformans and C. gattii in the Mediterranean basin, an extensive environmental survey was carried out during 2012-2015. A total of 302 sites located in 12 countries were sampled, 6436 samples from 3765 trees were collected and 5% of trees were found to be colonized by cryptococcal yeasts. Cryptococcus neoformans was isolated from 177 trees and C. gattii from 13. Cryptococcus neoformans colonized 27% of Ceratonia, 10% of Olea, Platanus and Prunus trees and a lower percentage of other tree genera. The 13 C. gattii isolates were collected from five Eucalyptus, four Ceratonia, two Pinus and two Olea trees. Cryptococcus neoformans was distributed all around the Mediterranean basin, whereas C. gattii was isolated in Greece, Southern Italy and Spain, in agreement with previous findings from both clinical and environmental sources. Among C. neoformans isolates, VNI was the prevalent molecular type but VNII, VNIV and VNIII hybrid strains were also isolated. With the exception of a single VGIV isolate, all C. gattii isolates were VGI. The results confirmed the presence of both Cryptococcus species in the Mediterranean environment, and showed that both carob and olive trees represent an important niche for these yeasts