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Long- distance migrations of insects contribute to ecosystem functioning but also have important economic impacts when the migrants are pests or provide ecosystem services. We combined radar monitoring, aerial sampling, and searchlight trapping, to quantify the annual pattern of nocturnal insect migration above the densely populated agricultural lands of East China. A total of -9.3 trillion nocturnal insect migrants (15,000 t of biomass), predominantly Lepidoptera, Hemiptera, and Diptera, including many crop pests and disease vectors, fly at heights up to 1 km above this 600 km- wide region every year. Larger migrants (>10 mg) exhibited seasonal reversal of movement directions, comprising northward expansion during spring and summer, followed by southward movements during fall. This north-south transfer was not balanced, however, with southward movement in fall 0.66- that of northward movement in spring and summer. Spring and summer migrations were strongest when the wind had a northward component, while in fall, stronger movements occurred on winds that allowed movement with a southward component; heading directions of larger insects were generally close to the track direction. These findings indicate adaptations leading to movement in seasonally favorable directions. We compare our results from China with similar studies in Europe and North America and conclude that ecological patterns and behavioral adaptations are similar across the Northern Hemisphere. The predominance of pests among these nocturnal migrants has severe implications for food security and grower prosperity throughout this heavily populated region, and knowledge of their migrations is potentially valuable for forecasting pest impacts and planning timely management actions. [ABSTRACT FROM AUTHOR]

The original drilling data collected cannot be deeply excavated and utilized by traditional modeling methods. Therefore, an improved K-nearest neighbor(KNN) algorithm is improved. This is a spatial adaptive interpolation fitting algorithm that is developed based on the original KNN algorithm. It incorporates automatic selection of k-values based on different geological layers and utilizes the original geological data for further analysis. The data from a railway investigation project is selected as a data source to put into the improved KNN algorithm model, successfully obtaining the characteristic k-values of each stratum in the site and accomplishing the geological modeling. By comparing the actual borehole and the borehole predicted by original KNN and improved KNN, it is found that the improved KNN algorithm is more accurate in predicting the thin layers, and the overall accuracy is higher. Compared with the original KNN algorithm and other common classification algorithms, the improved algorithm can obtain better stratum prediction results, especially for the thin stratum, and obtain higher precision and accuracy, which can better guide the prediction of underground 3D space. [ABSTRACT FROM AUTHOR]

To suppress the agglomeration of bare CoNi2S4 during the charging and discharging process, herein, Baoqing lignite has been utilized as the raw material, extracted with KOH and melamine solution, and annealed to nitrogen-doped lignite-based porous carbon (NPC), which was subsequently composited with CoNi2S4 by a facile and efficient hydrothermal method. In the CoNi2S4/nitrogen-doped lignite-based porous carbon composites (CoNi2S4/NPC), CoNi2S4 particles are uniformly dispersed on NPC. The as-prepared CoNi2S4/NPC have displayed excellent electrochemical properties with high specific capacitance and good cycle performance. The composites possess a high specific capacitance of 1534.24 F g−1 at a current density of 4 A g−1. The hybrid supercapacitor assembled by the CoNi2S4/NPC cathode and the activated carbon anode has demonstrated a high energy density of 48.58 Wh kg−1 at 400 W kg−1. Moreover, the capacitance retention of the hybrid supercapacitor is 82.42% after 5000 cycles. [ABSTRACT FROM AUTHOR]