The author of the text focuses on the economics of everyday life as defined by a contextual and qualitative measuring of various aspects of hospitality through the use of terms such as “more,” “less,” and “just right.” He analyzes the presence of food, alcohol, and coffee during the visit of guests. Each of these three material components of hospitality is regulated according to specific principles: “too much is better than too little” in regard to food, “too little is better than too much” for alcohol, and there has to be “at least” coffee. A detailed analysis of these principles leads to the conclusion that Polish hospitality is today oriented toward moderation. The popular belief in the abundance of Polish hospitality as a national feature is thus called into question.

Coffee is grown in over 50 countries around the world, and its sale is the largest in the world trade after crude oil. In the case of coffee beans, after consumption remains a solid waste in the form of a waste plant extract. At present, coffee waste is not fully managed, which means that it is often deposited in landfills. Taking into account their availability on the market and the content of significant amounts of carbon in them, it was proposed to use them as a reducing agent in the processing of copper slags. The use of Solid Coffee Grounds (SCG) as an alternative reducing agent for coke and coke breeze can be beneficial in two aspects. The first is the reduction of carbon dioxide emissions in the process, and the second is due to the possible release of hydrocarbons from these wastes at high temperatures, which, apart from participating in the reduction process itself, causes also mixing of the bath in the melting unit, which facilitates the process of copper sedimentation in the slag. The experiments carried out on a laboratory scale showed the possibility of reducing the copper content in the slag after the reduction process from 10.3 to 0.41 % by mass. The obtained values of the relative degree of copper splashing for all experiments ranged from 88.4 to 96.0 %. The presented solution is an innovative approach to the use of SCG in the processing of copper slags.

A multiple regression model approach was developed to estimate buffering indices, as well as biogas and methane productions in an upflow anaerobic sludge blanket (UASB) reactor treating coffee wet wastewater. Five input variables measured (pH, alkalinity, outlet VFA concentration, and total and soluble COD removal) were selected to develop the best models to identify their importance on methanation. Optimal regression models were selected based on four statistical performance criteria, viz. Mallow’s Cp statistic (Cp), Akaike information criterion ( AIC), Hannan– Quinn criterion ( HQC), and Schwarz–Bayesian information criterion ( SBIC). The performance of the models selected were assessed through several descriptive statistics such as measure of goodness-of-fit test (coefficient of multiple determination, R2; adjusted coefficient of multiple determination, Adj-R2; standard error of estimation, SEE; and Durbin–Watson statistic, DWS), and statistics on the prediction errors (mean squared error, MSE; mean absolute error, MAE; mean absolute percentage error, MAPE; mean error, ME and mean percentage error, MPE). The estimated model reveals that buffering indices are strongly influenced by three variables (volatile fatty acids (VFA) concentration, soluble COD removal, and alkalinity); while, pH, VFA concentration and total COD removal were the most significant independent variables in biogas and methane production. The developed equation models obtained in this study, could be a powerful tool to predict the functionability and stability for the UASB system.