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https://www.selleckchem.com/products/s63845.html quency, duration, and spatial extent with global climate change, more studies are needed to improve our understanding of lake heat waves and their potential effects on the species, communities, frequency of phytoplankton bloom, and also help providing advanced schemes of water quality management.Technology prediction is an important technique to help new energy vehicle (NEV) firms keep market advantage and sustainable development. Under fierce competition in the new energy industry, there is an urgent necessity for innovative technology prediction method to effectively identify core and frontier technologies for NEV firms. Among the various methods of technology prediction, one of the most frequently used methods is to make technology prediction from patent data. This paper synthesizes the frequent pattern growth (FP-growth) algorithm and input-output analysis to construct a new technology prediction method based on the knowledge flow perspective, takes the data of NEV patent family in 1989-2018 the Derwent patent database as a sample, divides the data according to the 5-year standard, and uses the method to identify the core and frontier technologies in the NEV field during different periods. Furthermore, the multiple co-occurrence method applies to analyze the technology layout and evolution patterns in China's NEV field. The results show that the technology prediction method proposed in this paper can effectively identify core and frontier technologies to achieve NEV technology prediction.The effects of salinity (10 and 50% seawater) and oil in combination on three mangroves, Avicennia marina, Bruguiera gymnorrhiza, and Rhizophora mucronata, were investigated. In all species, plant height, number of leaves, and CO2 exchange were generally higher in 10% than in 50% seawater. Salinity and oil decreased plant height, number of leaves, chlorophyll content, and CO2 exchange, with reductions being greater at the higher s

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