Phonostilistic Pecularities of German Rhyming Discourse

The vocal side of language has aroused the interest of scientists and researchers since antiquity. This direc¬tion in linguistic research is still relevant today, as evidenced by numerous treatises and experiments. In the present contribution, the authors tried to generalize and to analyze the most important means of pho¬nostilistics and their realization in different types of rhyming discourse, such as nursery rhymes, children’s poems, puzzles, lyrical poems etc. It has been proved very clearly that alliteration, assonance, phonetic imitation, phonetic symbolism as well as linguistic design are characterized by the aesthetic function as well. They create a special atmosphere in a finished work and thus achieve a certain emotional influence not only on the listener but also on the reader. This realizes the existence of the finest thread between the author and the auditorium, for which his rhyming work is forseen

Компаративний аналіз методів моделювання та прогнозування нестабільних часових рядів короткої вибірки

The article summarizes the international experience in univariate time series modeling approaches and methodology. It aims to make empirical assessment of their relevance and forecasting power for short sample volatile data with numerous aberrant observations and structural breaks with the help of the time series R packages. The findings revealed the pitfalls of outliers’ neglection including stationarity and model misspecification, biased parameter estimates, deterioration of residuals’ properties and prediction accuracy of the models. Empirical research demonstrated the outperformance of the outlier detection methods versus robust approaches that use smaller weights for aberrant observations. We tested a method of improving the forecasting power of the ARMA models by proper identification of hidden patterns and incorporation of additional information about extraordinary events into the model. We also considered frequency domain and nonparametric methods including exponential smoothing, seasonal and trend-cycle decomposition, structural and neural networks models to make comparative forecasting diagnostics. The findings showed slightly worse accuracy of the exponential smoothing and structural state-space models for short prediction horizons and their outperformance for longer forecasting periods. Neural networks showed outstanding in-sample approximation but poor out-of-sample quality. We recommend further studying of the Bayesian regime switching models that have proven to be a comprehensive way to explore hidden patterns in data, as well as dynamic factor multivariate models that can improve explanatory and forecasting power of the time series models in various applications.Проведено емпіричне оцінювання адекватності та прогнозної точності класичних лінійних моделей авторегресії та ковзного середнього, моделей експоненційного згладжування, структурних, нелінійних та непараметричних моделей для одновимірних часових рядів невеликої вибірки з чисельними відхиленнями. Запропоновано метод покращення якості ARMA моделі за рахунок включення фіктивних та пояснювальних змінних, які відтворюють інформацію щодо рідких і аномальних спостережень ряду, та відповідної корекції порядку інтегруванн

Development of the method of peanuts detoxification and improvement of its digestion

Heat treatment, namely hydrothermal treatment, followed by roasting was chosen in order to reduce the content of toxicants and antinutritional substances. Rational duration of hydrothermal processing is the temperature of 100º C at which the content of oxalic acid and its salts is reduced by 67.2...76.0%, and copper salts – by 28.8...38.0%, duration of 30...40 min being chosen. The duration for peanut kernels roasting (t = 120º C) was determined by the change of its color. It was determined that rational colour-parametric characteristics of peanut kernels (dominant wavelength 581.3 - 582.5 nm, color purity 35.9 - 36.0%, brightness 37.1 - 38.1%) are achieved during roasting for 30 - 35 min. The digestibility of peanut protein increased by 20 mg of tyrosine per 1 g of protein indicating the improvement of enzymatic hydrolysis of protein