In this work, the effect of superparamagnetic γ-Fe2O3 nanoparticles/ ultraviolet light (UV) synergistic degradation on the treatment of 1,3,5-triamino-2,4,6-trinitrobenzene (TATB) explosive wastewater was studied. γ-Fe2O3 nanoparticles were prepared by hydrolysis method and its degradation performance of TATB explosive wastewater was systematically studied with UV light assisted. The results showed that γ-Fe2O3 magnetic nanoparticles have low a size distribution ranged from 5 nm to 10 nm and possesses superparamagnetic properties. The optimized degradation condition was investigated and best degradation performance was obtained with the optimized conditions: the initial of pH=3, UV illumination intensity (5 w/cm2), reaction temperature (25 °C), initial TOC concentration (4.025 mg/L) as well as reaction time (60 min). This work can offer a new idea to degrade the explosive wastewater.
In face recognition, deep learning has always been a technology and problem that people need to improve. With the development of time, deep learning has the characteristics of self-learning ability, strong expression ability and better stability, and it is an effective solution to face recognition. However, in the sheltered environment, deep learning still faces many challenges. Different methods are used to expand the new deep learning methods, which can effectively solve the face recognition features in occlusion environment. This paper compares and classifies the related algorithms of deep learning and the traditional algorithms of deep learning. In particular, the network structure and construction principle of some classical algorithms are reviewed. Finally, discusses and summarizes their future development trends and directions. This study has certain reference significance for related scholars.
Abstract. In this paper, we discuss how to combine the idea of sustainable development with urban planning as a public policy, and support the construction of low carbon cities by scientific and reasonable planning according to the concept of low carbon city. The main points of the paper are the guidance and the demands of the construction of low carbon cities to urban planning consisting of spatial planning,transportation planning and industry planning.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.