This research delves into the urgent requirement for innovative agricultural methodologies amid growing concerns over sustainable development and food security. By employing machine learning strategies, particularly focusing on non-parametric learning algorithms, we explore the assessment of soil suitability for agricultural use under conditions of drought stress. Through the detailed examination of varied datasets, which include parameters like soil toxicity, terrain characteristics, and quality scores, our study offers new insights into the complexities of predicting soil suitability for crops. Our findings underline the effectiveness of various machine learning models, with the decision tree approach standing out for its accuracy, despite the need for comprehensive data gathering. Moreover, the research emphasizes the promise of merging machine learning techniques with conventional practices in soil science, paving the way for novel contributions to agricultural studies and practical implementations.

Regional differentiation in the Russian Federation is considered to be high in terms of gross regional product (GRP) per capita level, growth rate, and other indicators. Inefficient use of region-specific spaces entails redistribution processes in order to maximize positive agglomeration effects throughout the country. These encompass economic restructuring based on production value-added chain extension and expanding inter-regional collaborative linkages. Besides, it is vital to assess the opportunities of individual Russian territories for participation therein. The research goal is to develop a scientifically based methodology to determine promising sectoral composition of the regional economies and that of spatial interactions. Such methodology would consider the feasibility of combining “smart” industrial specializations, regional resource potential, prevailing contradictions in the economic, innovative, and technological development of the country’s internal space. The proposed methodological approach opens the way to exploit the existing regional economic potential to the full, firstly, via establishing sectoral priorities of the region regarding the regulatory factors for the territorial capital to have a major effect on the increased potential GRP level; secondly, through benchmarking performance of the available development reserves within leading regions from homogeneous groups having similar characteristics and factor potentials; thirdly, via developing inter-regional integration prospects in terms of regional potential redistribution to ensure growth in potential gross domestic product. An extensive analytical and applied investigation of the proposed methodological approach was carried out from 2014 to 2020. Diversified estimates were obtained for a wide range of indicators due to evidences from 85 Russian regions and 13 types of economic activity. Such an integrated approach allows revealing actual imbalances and barriers that impede regional development, ensures the efficient use of production factors, and enables to trace ways to implement transformation policies and design effective regulatory mechanisms. The results provide arguments in favor of strengthening inter-regional connectivity and supporting inter-regional cooperation. This insight not only contributes to the academic discourse on complex development of a territory but also holds practical implications for policymakers and regional planners aimed at ensuring comprehensiveness and robustness of the evaluation supporting the decision-making process.

This study aims at analyzing the consumers’ perception towards online purchasing bakery goods on subjective norm (SN), computer self-efficacy (CSE), and technology acceptance model (TAM). Convenience sampling was used and the final sample of respondents was made of 344 participants, with an effective recovery rate of 96%, who bought bakery goods on the LINE social platform in Nantou County. Descriptive statistics, confirmatory factor analysis, and SEM structural equation model were used to test the research hypothesis. The results show that after adding external variables to the technology acceptance model (TAM), the application of purchasing bakery goods online is significant; the consumers’ behavior of purchasing bakery goods online, subjective norm (SN), computer self-efficacy (CSE), and technology acceptance model (TAM) have cause-and-effect relationships. This research concludes that it is easy, helpful, and worthy to use the Internet to buy bakery goods.

This study explores the potential of digital preservation in the documentation of colonial cultural heritage in Egypt. It also explores the stories behind historical wars to revive these sites and attract different segments of visitors. Documentation of these sites should enhance Egyptian colonial cultural heritage sites, which include battlefields, war memorials, commanders’ palaces, assassination and murder spots, cemeteries, and mausoleums. The purpose of this study was fulfilled through field visits supplemented with in-depth interviews with experts on colonial heritage sites in Egypt. The findings showed that technology could play a key role in implementing the storytelling documentation and interpretation of colonial history and its relevant events at the Egyptian sites. However, to date, these sites have not made the best use of technology for digital preservation and documentation due to many challenges. The study recommends that decision-makers should integrate technological innovation, which can revitalize the communities built on the ruins of colonialism and revive the heritage of popular resistance. Technological innovation could be implemented not only in digital preservation and documentation but also in service and marketing of these colonial heritage sites.