Subjects: Nuclear Science and Technology >> Radiation Physics and Technology submitted time 2024-04-26
Abstract: This paper presents a superhydrophobic melamine (ME) sponge (ME-g-PLMA) prepared via high-energy radiation induced in-situ covalent grafting long alkyl chain dodecyl methacrylate (LMA) onto the ME sponge for efficient oil-water separation. The obtained ME-g-PLMA sponge have the excellent pore structure with superhydrophobic (water contact angle is 154°) and super oleophilic properties, can absorb various types of oil up to 66-168 times of its own weight. The obtained ME-g-PLMA sponge can continuously separate oil slick on water by connecting the pump or separate oil under water with a gravity-driven device. The ME-g-PLMA sponge can also maintain its highly hydrophobic properties after long-term immersion in different corrosive solutions and repeated adsorption of oil for many times. The obtained modified ME-g-PLMA sponge has excellent separation properties and has great potential for oil spill cleanup.
Subjects: Computer Science >> Integration Theory of Computer Science submitted time 2022-11-27 Cooperative journals: 《数据智能(英文)》
Abstract: With the popularity of social media, there has been an increasing interest in user profiling and its applications nowadays. This paper presents our system named UIR-SIST for User Profiling Technology Evaluation Campaign in SMP CUP 2017. UIR-SIST aims to complete three tasks, including keywords extraction from blogs, user interests labeling and user growth value prediction. To this end, we first extract keywords from a user’s blog, including the blog itself, blogs on the same topic and other blogs published by the same user. Then a unified neural network model is constructed based on a convolutional neural network (CNN) for user interests tagging. Finally, we adopt a stacking model for predicting user growth value. We eventually receive the sixth place with evaluation scores of 0.563, 0.378 and 0.751 on the three tasks, respectively.