Composite modification technology is widely used in the materials field. To enhance the property of polyurethane modified asphalt and realize its application in road engineering, the bone glue/polyurethane composite modified asphalt (CMA) was prepared using bone glue, polyurethane, and neat asphalt in this research. The bone glue content ranges 5–10%, that of the polyurethane is 1–5%. The relationship between the modifier’s content and the conventional properties and rheological properties of CMA was revealed by response surface methodology (RSM). The CMA performance was further verified under the optimal content of the bone glue and polyurethane. The differences of properties of styrene–butadienestyrene (SBS) modified asphalt mixture, neat asphalt mixture, and bone glue/polyurethane CMA mixture were compared and analyzed by using the pavement performance test. The results showed that the CMA’s conventional properties and rheological properties are improved. The optimal bone glue content and polyurethane content determined by RSM are 6.848% and 2.759%, respectively. The low-temperature crack resistance and water stability of the CMA mixture are enhanced, better than neat asphalt mixture and SBS modified asphalt mixture. The CMA mixture’s dynamic stability is 85% of SBS modified asphalt mixture, but it is 2.4 times of neat asphalt mixture. The result indicated that the bone glue/polyurethane CMA mixture still has certain advantages of high-temperature stability. In this research, the composite modification of bone glue and polyurethane can significantly enhance the characteristic of asphalt and asphalt mixture and provide a new method for applying and promoting polyurethane modified asphalt in road engineering.
In spite of the high electrical conductivity of carbon nanotube (CNT), its tendency to aggregate and expensive cost in fabricating aerogel, foams, and porous materials remains a problem. Therefore, we described a simple and feasible way to design light-weight, high electrically conductive, and cost-efficient polylactic acid (PLA)/CNT foams. The branched PLA (BPLA) resin with excellent melt elasticity and foamability was induced by nucleophilic ring-opening reaction of epoxy-based acrylic/styrene copolymer and PLA. After that, BPLA/CNT composites and foams were prepared by melt-mixing and supercritical carbon dioxide foaming technology, respectively. The thermal, electrical, and foaming properties were studied. The resultant BPLA/CNT foam possessed a low density of 0.174 g/cm3 and high crystallinity of 3.03%. An improvement of the oriented structure of CNT induced by cell growth in BPLA matrix increased the conductivity of the foam up to 3.51 × 104 Ω/m. The proposed foaming materials provided a way for designing and preparing high performance CNT products.
Implicit emotional tendency recognition is a challenging task, for the patterns of implicit emotional sentences have no obvious sentiment words or privative words. Currently, deep learning approaches have shown a huge potential for this problem. This paper proposes a hierarchical disconnected recurrent neural network to overcome the problem of the lack of emotional information in implicit sentiment sentence recognition. The proposed network first encodes both words and characters in implicit sentiment sentence by using the disconnected recurrent neural network and then fuses the context information of this sentence through the hierarchical structure. The capsule network is adopted to construct different fine-grained context information for extracting high-level feature information and provide additional semantic information for emotion recognition by using the context information. This approach improves the accuracy in implicit emotion recognition. Experimental results prove that the proposed model outperform various current mainstream models. The F 1 of ours reaches 81.5%, which is 2%-3% higher than those of the current mainstream models.
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