Challenges and opportunities of teaching English with reduced contact hours

The paper looks at some problems and opportunities of teaching English language with reduced contact hours at the university. The classroom and remote learning are compared and contrasted. The author examines the ways how the English syllabus can be streamlined in order to make the course more effective and motivating. Some practical activities, which can help teachers and students to make the most of the classroom time, are presented in the article. Special attention is given to some challenges that language instructors may face when they teach English with reduced contact hours, and solutions to these problems are provided

ELECTRICITY USAGE AND ASSET PRICING OVER THE BUSINESS CYCLE

The well-known difficulty in finding the predictors capable of explaining the Italian stock returns is at the basis of this thesis. The morphology of the Italian Stock Exchange is characterised by the presence of numerous small capitalisation stocks. This fact prevents the widely spread asset pricing models and predictors, both financial and real business cycle, to operate as expected. So, this thesis fills the abovementioned gaps. The first part of the thesis (Pirogova and Roma, (2020)) investigates the performance of size- and value-based strategies in the Italian Stock Market in the period 2000 - 2018. Previous research (Beltratti and Di Tria (2002)) argued the impossibility to define properly value-sorted portfolios due to the inaccuracy of book-to-market ratios available for Italian listed stocks. Using more accurate data, I implement portfolios sorting based on value and growth stocks, in order to assess the relevance of the value factor in the Italian Stock Market. I find that the CAPM, the capital asset pricing model, fails to explain the cross section of returns on the different strategies while the Fama and French (1993) three-factor model provides a better fit. The results show that all three factors are significant in explaining Italian stock returns during the sample period. Unlike previous studies, which either found no value effect at all (Barontini (1997); Aleati et al., (2000)) or no clear-cut results when testing the book-to-market variable (Bruni et al. (2006); Rossi (2012)), I find that the value factor is statistically significant, and the associated risk premium is of a considerable size. Pursuing the aim of finding new real business cycle predictors of the Italian stock returns, the second part of the study concentrates on the industrial electricity usage variable following the work of Zhi Da et al. (2017). The reason for using industrial electricity usage for this matter lies in the difficulty in storing energy. Therefore, the logic suggests that the changes in energy consumption can be used to track industrial production in real time. Real business cycle variables, like production, co-move with stock market returns. Zhi Da et al. (2017) show that industrial energy usage performs optimally in the prediction of US stock returns. However, despite the previous encouraging results, a deeper understanding of the industrial technologies used in the production process suggests that the matter is not so simple. The reason for this can be found in the concept of energy efficiency of the equipment that plants use. A comparable measure of energy efficiency is the intensity of energy consumption which is the ratio of the total final energy consumption (in GJ) and the value added of production at constant price. Another possible efficiency measure is the specific energy consumption per unit of the product. Moreover, the energy efficiency is closely linked to the analysis of the carbon footprint (emissions of greenhouse gases (GHG)) that each firm leaves during its production process, with special attention paid to the emissions of CO2. So, the task of this part of work is to check whether the industrial electricity usage variable is capable of predicting future Italian stock returns, either alone or after the correction using one or more energy efficiency measures. The theoretical basis of this study could be found in the production-based model by Burnside, Eichenbaum, Rebelo (1995). The fixed-coefficient energy-production relationship proposed by the authors was modified to vary throughout the sample period based on available energy intensity measures. The study concentrates on three energy-intensive Italian industrial sectors, Construction & Materials, Chemicals and Basic Resources. The relative time-series of the prices were downloaded from the website www.investing.com, the time-series of the electricity consumption of the subsectors of Concrete, Chemicals, Steel and Non-ferrous metals were kindly provided by Terna s.p.a., all energy-efficiency measures were downloaded from Odyssee Mure website. The main statistical method is the ordinary least squares (OLS). The third part of this study applies the same procedure of the second part of the thesis to the Swedish data. The only difference is that the data relative to the industrial electricity consumption come from the Statistics Sweden and there is no subdivision in Steel and Non-ferrous Metals of the Basic Resources electricity consumption time-series. The rest of the data come from the same sources as for Italy. This chapter’s goal is to enrich the Italian dataset and to confirm the obtained results. I find that the electricity consumption influences the stock returns through the impact on the productivity which then influences the financial values such as the book-to-market ratio and the price-earnings ratio. The relative tests showed that these ratios are explained by the electricity consumption together with the energy efficiency variables. The results of the tests on industrial electricity consumption growth rates referred to Italian and Swedish energy-intensive industrial sectors and their role in asset pricing are encouraging. The industrial electricity consumption variable corrected by the energy efficiency measures does influence the industrial stock returns and does so with significative predictor power. The sign of the regression coefficients of the energy efficiency measures remains the same for each Italian industrial sector no matter whether the month-over-month or the year-over-year data is used. This means that the correcting impact of these intensities is present, and it is stable and strong. The same result is true for most of the Swedish data

Neural correlates of contrast normalization in the Drosophila visual system

The fruit fly Drosophila melanogaster has long become a paramount model organism for research in life sciences. As a result of the fly’s high temporal resolution and its reliable optomotor response - a reflex that helps it compensate for movements of the environment, - Drosophila lends itself exceptionally well to the study of vision and, in particular, the mechanism of motion detection. In the wild, Drosophila is active throughout the day, with especially high levels of activity at dawn and dusk, the periods of time when the visuals of the environment are changing rapidly. The fruit flies can also be found in a variety of habitats, from the expanse of an open field to the inside of a cluttered kitchen. Altogether, Drosophila encounters a variety of visual statistics it must employ to robustly respond to the outside world and succeed in finding food, escaping predators, and carrying out courtship behavior. In my thesis, I focused on the effects of visual contrast, i.e., differences in brightness in the environment, on the fly’s motion vision. I studied the impact of the surround contrast on the filtering properties of the visual interneurons within the motion detection circuit, including the first direction-selective T4 and T5 cells and their main inputs, and how the fly compensates for the changes in contrast to faithfully match the direction and speed of its movement to the external motion under various contrast conditions. Firstly, in Manuscript 1, we established the existence of contrast normalization in the early visual system of Drosophila and demonstrated its suppressive effect on the response amplitude at higher contrasts. We determined where contrast normalization first arises in the optic lobe and identified the main inputs into the T4 and T5 cells that exhibit contrast normalizing properties. We comprehensively characterized the normalization process: namely, it is fast, not dependent on the direction of motion, its effect comes from outside the receptive field of a cell and increases in strength with the size of the visual surround. Additionally, we demonstrated that the normalization relies on neuronal feedback and showed that adding a contrast normalization stage to the existing models of motion detection improves their robustness, matching their performance to the results obtained in behavioral experiments. In Manuscript 2, we further investigated the effects of contrast normalization on the main inputs to T4 and T5 cells, now focusing on its effect on the filtering properties of the cells. We demonstrated that spatially or temporally dynamic surrounds elicit contrast normalization, while static ones do not. We further showed that, in addition to the suppressive effect on the amplitude, contrast normalization speeds up the kinetics of the response and confirmed that this effect is not due to signal saturation and involves a change in the filtering properties of the cell. In summary, we elucidated the role of contrast normalization in the motion detection circuit in the early visual system of Drosophila, comprehensively described the characteristics of the normalization process, and outlined its effects on the filtering properties of the cells. We also emphasized the potential role of shunting inhibition and narrowed down the search for the main candidates in the contrast normalization mechanism, paving the way for future studies to further delve into the contrast normalization circuit and implementation mechanism

The discourse analysis of marketing communication texts in mass media

The term ‘marketing communications’ is used to denote communications by means of various persuasive messages about products, organizations, candidates and ideas that marketers send to audiences to build up knowledge of the mentioned objects, to evoke positive attitudes towards them, to stimulate the audience to act in a certain way (buy, use, vote, approve) and remain loyal to them. Possibly the most dominant type of marketing communications in our culture is advertising, but there are many other effective forms of marketing persuasion (public relations, sponsorship, point-of-sale communications, sales promotion, event marketing, product placement, etc.). Advertising uses mass media channels (traditional and new media) to contact and interact with the audiences, and thus the language of advertising has become a special form of mass media language

Development of new computational amino acid parameters for protein structure/function analysis within the resonant recognition model

The Resonant Recognition Model (RRM) is a physico-mathematical model developed for analysis of protein and DNA sequences. Biological function of proteins and their 3D structures are determined by the linear sequences of amino acids. Previously, the electron-ion interaction potentials (EIIP) of amino acids have been used to determine the characteristic patterns of different proteins independent of their biological activity. In this study, the effect of various other amino acid parameters on periodicity, obtained using the RRR, were assessed. Here, we are proposing new computational amino acid parameters that could be used successfully for protein analysis instead of EIIP within the RRM

Bioactive peptide design using the Resonant Recognition Model

With a large number of DNA and protein sequences already known, the crucial question is to find out how the biological function of these macromolecules is "written" in the sequence of nucleotides or amino acids. Biological processes in any living organism are based on selective interactions between particular bio-molecules, mostly proteins. The rules governing the coding of a protein's biological function, i.e. its ability to selectively interact with other molecules, are still not elucidated. In addition, with the rapid accumulation of databases of protein primary structures, there is an urgent need for theoretical approaches that are capable of analysing protein structure-function relationships. The Resonant Recognition Model (RRM) [1,2] is one attempt to identify the selectivity of protein interactions within the amino acid sequence. The RRM [1,2] is a physico-mathematical approach that interprets protein sequence linear information using digital signal processing methods. In the RRM the protein primary structure is represented as a numerical series by assigning to each amino acid in the sequence a physical parameter value relevant to the protein's biological activity. The RRM concept is based on the finding that there is a significant correlation between spectra of the numerical presentation of amino acids and their biological activity. Once the characteristic frequency for a particular protein function/interaction is identified, it is possible then to utilize the RRM approach to predict the amino acids in the protein sequence, which predominantly contribute to this frequency and thus, to the observed function, as well as to design de novo peptides having the desired periodicities. As was shown in our previous studies of fibroblast growth factor (FGF) peptidic antagonists [2,3] and human immunodeficiency virus (HIV) envelope agonists [2,4], such de novo designed peptides express desired biological function. This study utilises the RRM computational approach to the analysis of oncogene and proto-oncogene proteins. The results obtained have shown that the RRM is capable of identifying the differences between the oncogenic and proto-oncogenic proteins with the possibility of identifying the "cancer-causing" features within their protein primary structure. In addition, the rational design of bioactive peptide analogues displaying oncogenic or proto-oncogenic-like activity is presented here

Investigation of the applicability of dielectric relaxation properties of amino acid solutions within the resonant recognition model

The resonant recognition model (RRM) is a physicomathematical approach used to analyze the interactions of a protein and its target, using digital signal processing methods. The RRM is based on the finding that there is a significant correlation between the spectra of numerical presentation of protein sequences and their biological activities. Initially, the electron-ion interaction potential was used to represent each amino acid in the protein sequences. In this paper, the dielectric constant (ε') and dielectric loss tangent (tan δ) parameters have been determined for their possible use in the RRM. These parameters are based on the values of capacitance and conductance obtained experimentally for 20 amino acid solutions using dielectric spectroscopy for the case of the real component of dielectric permittivity; the parameter used is the dielectric increment (Δε'), the difference between dielectric constant of the amino acid solution and that of the solvent alone. The results of multiple cross-spectral analyses have shown that parameters analyzed generate in the consensus spectrum one dominant peak corresponding to the common biological activity of proteins studied, allowing the conclusion that these new parameters are suitable for use in the RRM approach

Investigation of the mechanisms of electromagnetic field interaction with proteins

In our earlier work we have proposed that protein activation is electromagnetic in its nature. This prediction is based on the resonant recognition model (RRM) where proteins are analyzed using digital signal processing (DSP) methods applied to the distribution of free electron energies along the protein sequence. This postulate is investigated here by applying the electromagnetic radiation to example of L-lactate dehydrogenase protein and its biological activity is measured before and after the exposures. The concepts presented would lead to the new insights into proteins susceptibility to perturbation by exposure to electromagnetic fields and possibility to program, predict, design and modify proteins and their bioactivit

Adaptation activity of the people

Обоснована концепция психологического механизма адаптации как процесса смены психологических установок, мотивов, целей адаптанта. Обобщены результаты опроса.Grounded the concept of psychological mechanism of adaptation as a process of changing attitudes, motives, objective functions of personality. Summarizes results of survey