Although recent work has shown natural lignin products are promising to fabricate various polymer based functional composites, high-value applications were challenged by their structural complexity and inhomogeneity. This work specially assessed the potential of four technical lignins for cellulose based functional films production. These four technical lignins were obtained by emerging pretreatment systems, i.e., lactic acid-betaine deep eutectic solvent (DES), ethanol organosolv, soda/anthraquinone (Soda/AQ) and the sodium salicylate hydrotrope, and their phenolic substructures were comparatively identified by prevalent ³¹P NMR technique. The influence of lignin chemical structure on the antioxidant potential and UV-shielding performance of the prepared cellulose/technical lignin composite films were assessed. Results showed severe organosolv and soda/AQ pretreatment produced technical lignins with higher total phenolic hydroxyl groups (3.37 and 3.23 mmol g-1 respectively), which also exhibited higher antioxidant activities. The composite films could effectively block the ultraviolet lights especially for UVB region (ultraviolet B, 280–315 nm) at only 5 wt.% lignin content. The contribution of lignin phenolic substructures to both antioxidant activity and UV-shielding property from high to low was syringyl > guaiacyl > p-hydroxyphenyl phenolic hydroxyl groups. This work provided some useful information that could facilitate upstream lignin extraction or downstream value-added applications.

Accurate and reliable prediction of runoff generation is necessary for flood control scheduling, water supply planning, and hydropower generation. Support vector machine (SVM), which is at the forefront of current research of regression and classification, was used in this paper to conduct monthly mean streamflow prediction. A novel heuristic optimization named bat algorithm (BA) was introduced to determine the parameters of SVM [penalty parameter (C) and kernel parameter (η)], in which the initial fitness was supposed to be equal to the initial loudness for all bats. In order to evaluate the effectiveness of the proposed approach, monthly mean streamflow from 1952 to 2011 of Yichang station in the middle reaches of the Yangtze River were trained and tested. In the meantime, the given data set was also modeled using artificial neural networks (ANN) and cross validation–based SVM. The comparison results indicate that the proposed model (bat algorithm–based SVM) is more accurate compared with both A...

Based on the annual data from 1980 to 2014, the path analysis model was employed to investigate the influence of gross domestic product (GDP), total population (TP), and net export value (NEV) on total energy consumption (TEC) in China. The results showed that (1) GDP, influenced 59.73% of TEC, played the most important role to affect TEC. Meanwhile, 37.69% of TEC was directly determined by GDP, and 22.04% of TEC was indirectly influenced by GDP through TP and NEV. (2) TP was the secondary factor to affect TEC; 6.02% of TEC was directly determined by TP, and 15.20% of TEC was indirectly affected by TP. Moreover, 21.22% of TEC was associated with TP. (3) NEV had the least total effect and the least direct effect on TEC; 17.24% TEC was influenced by NEV. Among them, 3.58% of TEC was directly determined by NEV, and 13.66% of TEC was indirectly influenced by NEV.