Presented paper deals with the morphological category of aspect in Cantonese. Given the lack of a morphological category of tense in Cantonese, aspect holds a particular position in this system, as it is the sole morphological means expressing temporal relations. The aim of the paper is to present the functioning of the various aspects of Cantonese, both perfective and imperfective, based on the theoretical framework presented beforehand, which draws on the previous achievements of linguists in this field. The second section presents what specific morphological means are used to express the category of aspect in Cantonese, which is then followed by a brief discussion of the relation between resultative verb compounds and the perfective aspect. The last, and by far the largest section, presents corpus material which exemplifies the use of different aspect markers. The paper is an attempt to respond to the hitherto lack of consensus among Sinologists about the number as well as the types of aspects that occur in Cantonese.

This paper presents a study on the dry turning of polyoxymethylene copolymer POM-C. The effect of five factors (cutting speed, feed rate, depth of cut, nose radius, and main cutting edge angle) on machinability is evaluated using four output parameters: surface roughness, tangential force, cutting power, and material removal rate. To do so, the study relies on three approaches: (i) Pareto statistical analysis, (ii) multiple linear regression modeling, and (iii) optimization using the genetic algorithm. To conduct the investigation, mathematical models are developed using response surface methodology based on the Taguchi L16 orthogonal array. The results indicate that feed rate, nose radius, and cutting edge angle significantly influence surface quality, while depth of cut, feed, and speed have a notable impact on other machinability parameters. The developed mathematical models have determination coefficients greater than or very close to 95%, making them very useful for the industry as they allow predicting response values based on the chosen cutting parameters. Finally, the optimization using the genetic algorithm proves to be promising and effective in determining the optimal cutting parameters to maximize productivity while improving surface quality.

The aim of the study is to formally compare the explanatory power of Copula-GARCH and MGARCH models. The models are estimated for logarithmic daily rates of return of two exchange rates: EUR/PLN, USD/PLN and stock market indices: SP500, BUX. The analysis is performed within the Bayesian framework. The posterior model probabilities point to AR(1)-tSBEKK(1,1) for the exchange rates and VAR(1)-tCopula-GARCH(1,1) for the stock market indices, as the superior specifications. If the marginal sampling distributions are different in terms of tail thickness, the Copula-GARCH models have higher explanatory power than the MGARCH models.