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This paper analyzes consumer demand using a Quadratic Almost Ideal Demand System (QUAIDS), which is an extension of an Almost Ideal Demand System (a complete demand system). Complete demand system models can be used to find the relationships that are impossible to discover using single-equation models. Additionally, the QUAIDS model can be used to model a nonlinear Engel curve. The research was based on household microeconomic data collected by GUS (the Polish Central Statistical Office) in the period 1999-2015. The complete demand model has been extended by demographic variable. The results show that the QUAIDS model does not reduce to the AIDS model and is an adequate tool to analyze consumer demand.

The study was conducted in October 2020 and March 2021 among Wroclaw Medical University students of different years and faculties. The objective of the study was to establish the relationship between some determinants, such as gender and the levels of physical activity, and the quality of sleep of medical students during the pandemic. Ultimately, 696 responses from October and 652 from March were included. To determine the level of physical activity, the International Physical Activity Questionnaire (IPAQ) was used, and for sleep quality, the Pittsburgh Sleep Quality Index (PSQI) was used. The findings pointed to a higher Total MET m/w (metabolic equivalent of task in minutes a week) in men compared to women in both study periods (2020: 1845.8 to 1542.5, p = 0.009; 2021: 2040.7 to 1826.6, p = 0.025). This was mainly due to a higher Vigorous Exercises MET m/w in men (2020: 837.3 to 635.8, p = 0.008; 2021: 773.3 to 490.3, p = 0.0006). Moreover, women had a lower quality of sleep resulting from problems in Habitual Sleep Efficiency, Sleep Disturbances, and Daytime Dysfunctions. An adequate level of physical activity and a good night’s rest are the fundaments of health; therefore, it is necessary to determine the causes of their deficiencies in order that we can counteract them.

Tree sap has been used for centuries not only as a source of nutrients available in early spring but also as medicinal substance in folk medicine. Traditionally, it was used to treat various conditions, mostly anaemia and chronic fatigue. This study has been designed to establish the content of metallic elements (sodium, potassium, calcium, magnesium, zinc and copper) in sap collected from eight different species (silver birch, downy birch, hornbeam, Norway maple, boxelder maple, black walnut, black alder and white willow) and to identify which sap has mineral content which would be most beneficial for human health. We measured concentrations of calcium, magnesium, sodium, potassium and zinc on an atomic absorption spectrometer equipped with single-element, hollow cathode lamps and an air/acetylene burner. The content of copper was determined using an atomic absorption spectrometer with Zeeman correction equipped with an electrothermal atomizer and argon as inert gas. White willow sap was determined to have the highest concentrations of magnesium, zinc, calcium and potassium. Moreover, this sap contained the lowest concentration of sodium among all the tree species. The sap with the lowest detected concentration of the metallic elements originated from black alder and boxelder. In conclusion, tree sap can be a valuable source of metallic elements, namely copper, zinc and magnesium, in human diet. Tree sap tapped from white willow is the most valuable in terms of its mineral content. Moreover, the most popular sap of sliver birch has proven to be a rich source of magnesium and zinc.

Due to various regulations (e.g., the Basel III Accord), banks need to keep a specified amount of capital to reduce the impact of their insolvency. This equity can be calculated using, e.g., the Internal Rating Approach, enabling institutions to develop their own statistical models. In this regard, one of the most important parameters is the loss given default, whose correct estimation may lead to a healthier and riskless allocation of the capital. Unfortunately, since the loss given default distribution is a bimodal application of the modeling methods (e.g., ordinary least squares or regression trees), aiming at predicting the mean value is not enough. Bimodality means that a distribution has two modes and has a large proportion of observations with large distances from the middle of the distribution; therefore, to overcome this fact, more advanced methods are required. To this end, to model the entire loss given default distribution, in this article we present the weighted quantile Regression Forest algorithm, which is an ensemble technique. We evaluate our methodology over a dataset collected by one of the biggest Polish banks. Through our research, we show that weighted quantile Regression Forests outperform “single” state-of-the-art models in terms of their accuracy and the stability.