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In recent years, global geo-economic transformations have been considerably affected by the development of the People's Republic of China, its reviving leadership and ambitions, and its increasing efforts to reformat and integrate the Eurasian space. The One Belt — One Road Initiative is a manifesto and a tool to advance China's long-term geostrategic interests that spread to the bordering states and regions and to the prospects of their socioeconomic development. The initiative encompasses transportation and logistics, production and investment, finances, research and technology, humanitarian affairs, and foreign policy. In this article, we will highlight the key geoeconomic and geopolitical aspects of the One Belt — One Road initiative implementation, based on the Chinese and Russian studies. Another goal is to weigh up the risks and benefits associated with the extension of the project to Russian territories. Special attention is paid to Russia's western borderlands — 17 regions that account for 8.6 % of the country's territory, 17.4 % of the total GRP, and 20.8 % of the national population. We analyse the factors in effect — including geopolitical ones, as well as current trends in the development of Russia's western borderlands. It is shown that the inclusion into the Chinese Eurasian integration initiatives creates additional incentives for a positive re-evaluation of the Russian space as a whole and holds special relevance for Russia's western borderlands. We analyse the possibility of including Russia's Baltic regions — the infrastructural and economic island of the Kaliningrad exclave among them — into the One Belt — One Road Initiative.

As the threats from unmanned aerial vehicles (UAVs) increases gradually, to recognize and classify unknown UAVs have became more and more important in both civil and military security fields. Classification of signal modulation types is one of the basic techniques for specific UAV recognition. In this paper, to represent the hidden features involved in the transmitted signals from UAVs, we propose a two-dimensional squeezing transform (TDST) to characterize the UAV communication signals in a compressed time-frequency plane. The new time-frequency representation, TDST, retains the instantaneous characteristics of the UAV signal, and is with excellent data reduction and noise suppression capabilities. The TDST plane of different modulation types are then considered as input features, and we propose a convolutional neural network (CNN) based on deep-learning to recognize the UAV signals. We design an interception system and consider 10 types of UAV signals with random initial phase, bandwidth and frequency offset. Experimental results demonstrate the effectiveness and superiority of the proposed algorithm.

13 pages, 6 figures, 2 tables.-- This is an Open Access article distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivatives License ; The rapid, global spread of COVID-19, and the measures intended to limit or slow its propagation, are having major impacts on diverse sectors of society. Notably, these impacts are occurring in the context of other anthropogenic-driven threats including global climate change. Both anthropogenic stressors and the COVID-19 pandemic represent significant economic challenges to aquaculture systems across the globe, threatening the supply chain of one of the most important sources of animal protein, with potential disproportionate impacts on vulnerable communities. A web survey was conducted in 47 countries in the midst of the COVID-19 pandemic to assess how aquaculture activities have been affected by the pandemic, and to explore how these impacts compare to those from climate change. A positive correlation between the effects of the two categories of drivers was detected, but analysis suggests that the pandemic and the anthropogenic stressors affect different parts of the supply chain. The immediate measurable reported losses varied with aquaculture typology (land vs. marine, and intensive vs. extensive). A comparably lower impact on farmers reporting the use of integrated multitrophic aquaculture (IMTA) methods suggests that IMTA might enhance resilience to multiple stressors by providing different market options under the COVID-19 pandemic. Results emphasize the importance of assessing detrimental effects of COVID-19 under a multiple stressor lens, focusing on areas that have already locally experienced economic loss due to anthropogenic stressors in the last decade. Holistic policies that simultaneously address other ongoing anthropogenic stressors, rather than focusing solely on the acute impacts of COVID-19, are needed to maximize the long-term resilience of the aquaculture sector. ; The Open Access publication of the MS was funded by M. Cristina Mangano FOE N. 418 at Stazione Zoologica Anton Dohrn (personal OA publication fund). People at Laboratory of Ecology have been found by the PRIN-MAHRES project (Ministry of Italian Research; MUR) 2017MHHWBN_003 Linea C and by the HARMONY Project Italy-Malta 2016 (grant C1-3.1-31) funded by the Sicilian Region and Maltese Government. A. Nogueira thanks FCT/MCTES for the financial support to CESAM (UIDP/50017/2020+UIDB/50017/2020), through national funds. J.M.F. Babarro thanks project PID2019-106008RB-C21 for support through Spanish Government funds ; Peer reviewed