Two-dimensional atomically thick materials, reduced graphene oxide (RGO), and layered molybdenum disulfide (MoS ) have been investigated as potential novel energy storage materials because of their distinct physicochemical properties. These materials suffer, however, from rapid capacity decay and low rate capability. This study describes a facile, binder-free approach to fabricate large-scale, 3D network structured MoS @carbon nanotube (CNT)/RGO composites for application in flexible supercapacitor devices. The as-obtained composites possess a hierarchical porosity, and an interconnected framework. The electrochemical supercapacitive measurements of the MoS @CNT/RGO electrode show a high specific capacitance of 129 mF cm at 0.1 mA cm . The symmetric supercapacitor devices based on the as-obtained composites exhibit a long lifetime (94.7 % capacitance retention after 10 000 cycles), and a high electrochemical performance (29.7 mF cm ). The present experimental findings will lead to scalable, binder-free synthesis of MoS @CNT/RGO hybrid electrodes, with enhanced, flexible, supercapacitive performance, in portable and wearable energy storage devices.

Estimating the origin-destination travel time is a fundamental problem in many location-based services for vehicles, e.g., ride-hailing, vehicle dispatching, and route planning. Recent work has made significant progress to accuracy but they largely rely on GPS traces which are too coarse to model many personalized driving events. In this paper, we propose Customized Travel Time Estimation (CTTE) that fuses GPS traces, smartphone inertial data, and road network within a deep recurrent neural network. It constructs a link traffic database with topology representation, speed statistics, and query distribution. It also uses inertial data to estimate the arbitrary phone's pose in car, and detects fine-grained driving events. The multi-task learning structure predicts both traffic speed at public level and customized travel time at personal level. Extensive experiments on two real-world traffic datasets from Didi Chuxing have demonstrated our effectiveness.

BACKGROUND Selenium has shown effectiveness in protecting plants from herbivores. However, some insects have evolved adaptability to selenium. RESULTS Selenium accumulation in host plants protected them against spider mite feeding. Selenium showed toxic effects on spider mites by reducing growth and interfering with reproduction. After 40 generations on selenium‐rich plants, a Tetranychus cinnabarinus strain (Tc‐Se) developed adaptability to selenium, with an increased rate of population growth and enhanced ability for selenium metabolism. The high expression of two genes (GSTd07 and SPS1) in the selenium metabolism pathway might be involved in selenium metabolism in spider mites. After GSTd07 and SPS1 were silenced, the selenium adaptability decreased. Recombinant GSTd07 protein promoted the reaction between sodium selenite and glutathione (GSH) and increased the production of sodium selenite metabolites. The results indicated that GSTd07 was involved in the first step of selenium metabolism. CONCLUSION Plants can resist spider mite feeding by accumulating selenium. Spider mites subjected to long‐term selenium exposure can adapt to selenium by increasing the expression of key genes involved in selenium metabolism. These results elucidate the mechanism of the interaction between mites and host plants mediated by selenium. This study of the interaction between selenium‐mediated host plants and spider mites may lead to the development of new and less toxic methods for the prevention and control of spider mites. © 2021 Society of Chemical Industry.

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