Fuzzy Clustering Methods to Identify the Epidemiological Situation and Its Changes in European Countries during COVID-19.

The main research question concerned the identification of changes in the COVID-19 epidemiological situation using fuzzy clustering methods. This research used cross-sectional time series data obtained from the European Centre for Disease Prevention and Control. The identification of country types in terms of epidemiological risk was carried out using the fuzzy c-means clustering method. We also used the entropy index to measure the degree of fuzziness in the classification and evaluate the uncertainty of epidemiological states. The proposed approach allowed us to identify countries' epidemic states. Moreover, it also made it possible to determine the time of transition from one state to another, as well as to observe fluctuations during changes of state. Three COVID-19 epidemic states were identified in Europe, i.e., stabilisation, destabilisation, and expansion. The methodology is universal and can also be useful for other countries, as well as the research results being important for governments, politicians and other policy-makers working to mitigate the effects of the COVID-19 pandemic.

Assessing the level of the material deprivation of European Union countries.

The purpose of this paper is to assess the level of material deprivation in European Union countries in 2016 from both a local and a global perspective. The Technique for Order Preference by Similarity to an Ideal Solution (TOPSIS) was used in the study. Based on research, five main types of the level of the material deprivation of European Union countries were identified. Research findings suggest that the population of old EU countries is less severely affected by material deprivation than people living in new member states. Also, the level of global material deprivation was assessed. The study was based on 2016 statistical data delivered by Eurostat.

Modification of food preferences by posthypnotic suggestions: An event-related brain potential study.

The preference for high-over low-calorie food and difficulties in inhibiting the desire for high-calorie food are important factors involved in unhealthy food choices. Here, we explored posthypnotic suggestions (PHS), aiming to increase the desire for vegetables and fruits, as a possible new tool to induce a preference for low-calorie food. Following the termination of hypnosis, PHS was activated and deactivated in counterbalanced order, while event-related brain-potentials were recorded. Two tasks were administered, a food-face classification measuring implicit food preferences, where stimuli were categorized as showing food items or faces, and a Go-NoGo task measuring inhibition, where food items were selected as being appropriate for making a salad or not. In the food-face classification task without PHS, the early visual P1 component, a marker of stimulus reward-associations, was larger in response to high-than low-calorie food pictures; PHS eliminated this difference. PHS also yielded faster RTs and larger amplitudes of a late positive component in low-versus high-calorie items. Hence, PHS appeared to neutralize the positive perceptual bias toward high-calorie food items and enhance the effective processing of low-calorie items by increasing motivated attention. In the Go-NoGo task, PHS decreased the NoGo-N2; PHS increased the early Go- and NoGo-P3, possibly by turning low- and high-calorie items more pleasant and unpleasant, respectively, requiring more proactive control to inhibit task-irrelevant food-related emotions. Further, in the Go condition, PHS quickened the rejection of salad-inappropriate high-calorie items and increased the amplitude of late-P3, indicating facilitated classification of high-calorie items and increased response monitoring. Together, PHS effectively increased the preference for low-calorie food and the inhibition of impulses toward high-calorie food; therefore, PHS may be a promising tool for supporting healthy and sustainable food choices.