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Modeling is a process that allows to present and analyze the economic realities together with their quantitative description, extending to the key development factors, their mutual relationships and assessment of their relevance. The essence of the assessment process is the quantification which means expressing the relevance of specific factors in numeric terms. This approach results in creating a model that enables the proper stimulation of development and is used to conceive effective solutions which form a unified framework for development planning and budgeting. The aim of the study is to construct the development model and to assess development priorities for the Local Administrative Unit (LAU). There is no standard model used to assess the process of development of local administrative units. The fuzzy analytic hierarchy process (FAHP) (Chang, 1996) based on expert opinions was used to solve this problem. The essence of this process is to build a hierarchy structure for the problem considered. The hierarchy consists of the main goal, the sub-goals and the tasks. At each hierarchy level, the importance of strategic factors is pairwise compared by experts. Experts' opinions are the basis for the assessment of each strategic factor. The research was based on data from a survey among the councilors of the urban and rural municipality of Stęszew in the Wielkopolska Voivodeship in Poland in 2017. The proposed approach to the construction of the model and the assessment of strategic factors for administrative units is a universal tool for local and regional development planning. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

The main aim of this study is to assess the strategic factors (objectives, tasks and development scenarios) and to select the best scenario for local administrative units. Two approaches are used to solve this problem: classical and fuzzy analytic hierarchy process based on experts' opinions. The research was based on data from surveys with the councillors of the urban and rural municipality of Międzychód and the rural municipality of Chrzypsko Wielkie. The importance of strategic factors for both municipalities was assessed, and the best development scenario was selected. As shown by the research, the most important scenario for the municipality of Chrzypsko Wielkie involves the development through support for entrepreneurship and agri-food processing, while that for the municipality of Międzychód involves the development by supporting housing, services and tourism. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

• The positional TOPSIS, combined with different optimal tail selection methods of the variable distribution, is proposed to assess the sustainable development of territorial units. • The cluster compactness measure is proposed to evaluate the classification results of the positional TOPSIS with the optimal tail selection of variable distribution. • The automated Eye-Ball method and the Guillou and Hall's method enable correct identification of extreme values of variables describing the economic, social, and environmental development of municipalities. • The positional TOPSIS with selected optimal tail selection methods enable correct classification of the municipalities and assessment of their sustainable development in terms of levels and statuses. In the face of accelerating climate change, economic instability and limited resources, it is essential to find indicators that better measure the sustainable development of territorial units. Despite ambiguous definitions of sustainable development, numerous studies describe quantitative indicators of sustainable development. Main methodological problems include data availability and their use, spatial and time scales, selection of indicators, and their aggregation. Usually, analysts and decision-makers apply well known conventional methods that have numerous limitations. These methods in many cases cause excessive simplification of the real phenomena and relations between their determinants. Moreover, variables describing the development of territorial units (especially the environmental pillar) are often characterized by strong asymmetry or extreme observations. Even a single outlier for a given territorial unit may significantly affect the analysis and the resulting conclusions. The objective of this paper is to present the application potential of a Multi-Criteria Decision Making (MCDM) approach with an optimal tail selection to assess the sustainable development of territorial units. The proposed approach is based on the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) and different methods of optimal tail selection of variable distribution. The Oja's spatial median and the optimal tail selection methods are used to reduce the impact of strong asymmetry and extreme values of variables. Moreover, the measure of cluster compactness is proposed for the evaluation of the proposed method. The proposed approach was used to assess the sustainable development of municipalities in Poland in 2018. We found that the automated Eye-Ball method and the Guillou and Hall's method enabled correct identification of extreme values of variables describing the economic, social, and environmental development of municipalities. This made it possible to distinguish the types of sustainable development level and its pillars and enabled to provide the statuses of the sustainable development level of the examined municipalities with respect to other municipalities in Poland. [Display omitted] [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Studies on the economic development of government units are among the key challenges for authorities at different levels and an issue often investigated by economists. In spite of a considerable interest in the issue, there is no standard procedure for the assessment of economic development level of units at different levels of government (national, regional, sub-regional). This assessment needs a complex system of methods and techniques applicable to the various types of data. So, adequate methods must be used at each level. This paper proposes a complex procedure for a synthetic indicator. The units are assessed at different government levels. Each level (national, regional, and sub-regional) may be described with a particular type of variables. Set of data may include variables with a normal or near-normal distribution, a strong asymmetry or extreme values. The objective of this paper is to present the potential behind the application of a complex Multi-Criteria Decision Making (MCDM) procedure based on the tail selection method used in the Extreme Value Theory (EVT), i.e., Mean Excess Function (MEF) together with one of the most popular MCDM methods, namely the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS), to assess the economic development level of units at different government levels. MEF is helpful to identify extreme values of variables and limit their impact on the ranking of local administrative units (LAUs). TOPSIS is suitable in ranking units described with multidimensional data set. The study explored the use of two types of TOPSIS (classical and positional) depending on the type of variables. These approaches were used in the assessment of economic development level of LAUs at national, regional and sub-regional levels in Poland in 2017. [ABSTRACT FROM AUTHOR]