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The increasing population and income inequality in the last decades have made it necessary to focus on the concept of sustainability. In the changing world order, with economic crises, instabilities, pandemics, and social media, sustainability awareness differs significantly from past years. In addition, developing new technologies and concepts (big data, blockchain, IoT, robotic, etc.) plays a crucial role in meeting social awareness in terms of sustainability. Food sustainability is also one of the most important pillars in this concept. The integration of new technologies in agriculture and food chains will enable the current world population to use resources more efficiently and sustainably. Blockchain, one of the technologies that emerged with the arrival of Industry 4.0, is a technology that can be used effectively in many sectors.Particularly in supply chain networks, it is seen as a technology that supports the sustainability concept due to its features such as decentralization, reliability, transparency, consensus standards, and traceability. However, since blockchain is an immature and new technology, there are some challenges with integrating it into existing conventional systems. This study aims to present a conceptual framework for the integration of blockchain technology to establish a sustainable tea supply chain, define possible actions, and prioritize the possible risks that may arise in this integration process; this will be done through the Spherical Fuzzy Analytic Hierarchy Process (SF-AHP) approach. In this context, initially, the current tea supply chain will be considered and the activities carried out will be defined in terms of technological, environmental, and strategic sustainability. Then, the design that includes the integration of all activities with blockchain technology is presented. The proposed design covers the entire tea supply chain from end to end and is considered with regard to all sustainability dimensions. In the proposed framework, barriers that may be encountered and risks that may arise at each stage of the tea supply chain process are identified; managerial implications are then presented to eliminate these risks. To enhance the use of the recommendations made, risks and barriers are prioritized with SF-AHP management. Thus, the problems that need to be solved primarily in the

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Wireless communication networks have been witnessing unprecedented demand due to the increasing number of connected devices and emerging bandwidth-hungry applications. Although there are many competent technologies for capacity enhancement purposes, such as millimeter wave communications and network densification, there is still room and need for further capacity enhancement in wireless communication networks, especially for the cases of unusual people gatherings, such as sport competitions, musical concerts, etc. Unmanned aerial vehicles (UAVs) have been identified as one of the promising options to enhance capacity due to their easy implementation, pop-up fashion operation, and cost-effective nature. The main idea is to deploy base stations on UAVs and operate them as flying base stations, thereby bringing additional capacity where it is needed. However, UAVs mostly have limited energy storage, hence, their energy consumption must be optimized to increase flight time. In this survey, we investigate different energy optimization techniques with a top-level classification in terms of the optimization algorithm employed—conventional and machine learning (ML). Such classification helps understand the state-of-the-art and the current trend in terms of methodology. In this regard, various optimization techniques are identified from the related literature, and they are presented under the above-mentioned classes of employed optimization methods. In addition, for the purpose of completeness, we include a brief tutorial on the optimization methods and power supply and charging mechanisms of UAVs. Moreover, novel concepts, such as reflective intelligent surfaces and landing spot optimization, are also covered to capture the latest trends in the literature.