The aim of this work is to explore and analyze an unconventional style of programming based on a pro- pagator-oriented model of computation. The paradigm of propagation is characterized by networks of local, independent, stateless machines interconnected with stateful storage cells. This model allows for a highly modular design and multidirectional computation, enabling the creation of complex systems that can respond to changes and update their state accordingly. This work provides an overview of the propagator- oriented programming model, its motivations, and its advantages over other well-known alternative styles, using unsophisticated examples written in the Java programming language. We illustrate how propagator networks can be used to build flexible and efficient systems and present a basic framework for building such networks. The foun- dational components of the propagation model are imple- mented in Java as groundwork for the general-purpose framework. We demonstrate the power of propagator-oriented prog- ramming through an example of a Pythagorean Theorem implementation. The example shows how the model can be used to build complex systems of an arbitrary number of constraints and cells. We highlight the importance of information propagation over limited linear computation and the benefits of the multidirectional computation enabled by propagator networks.

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The theoretic fundamentals of the geography of extremal situations as a new approach for environmental science and socio-economic investigations are disclosed. The new direction of research named the geography of extreme situations is substantiated. The formation of the extreme operating mode in socio-ecological-economic systems (landscapes) that have a destructive, unbalanced nature and lead to imbalances in their development is explored. The term «geography of extreme situations» is introduced to determine the particular area of geographical knowledge, which studies natural and socio-economic phenomena that have the character of fast imbalance. The methodical approaches to investigation of the extremeness level of the territory via the example of Ukraine and the European Union are shown. In geography this approach was applied only to determine the specific features of the influence of natural conditions on human activity. The indicators of environmental disasters that include the amount of pollutant emissions into the atmosphere, the discharge of contaminated sewage into the natural surface water, the degradation of soil resources, the reduction of the forest fund, the species diversity of flora and fauna are disclosed. The different indices of extremeness such as medical and demographic, socioeconomic, engineering, physical-geographical and others are proposed.

Abstract. The study identifies the main indicators and prerequisites for digital transformation of the tourism industry and the current problematic issues experienced at the level of regional management; the forecast and key features of a new evolutionary stage in the branch. i.e., the development of smart digital tourism, is provided; an extended model of tourism destination «7A» is described, taking into account the digital transformation factor; the role of the digital service portfolio in how the reputation of a tourism destination is formed and perceived is outlined; the systematization criteria and classification of digital tools and services used in regional administration and operational management of tourist activity are listed; KPI for tourist sites around the world are attributed; the structural analysis of domestic tourist sites is described; a critical assessment for the digitalization of the national tourism destinations across Ukraine is provided; the current digital channels for promoting the national tourist product are offered. Keywords: digitalization of tourism industry, smart digital tourism, evolution of tourism, management and administration of tourism regions, tourism destination model, digital services in tourism, destination management organization (DMO), tourism destination reputation, reputation management. JEL Classification L83 Formulas: 0; fig.: 2; tabl.: 5; bibl. 22.