The danger of riverbed processes is considered. Their speed varies from the first few months of the flood to the most dynamic process in nature. It happened in front of people. This may make life on the river bank and the utilization of river resources more difficult. This paper introduces the causes and consequences of the danger performance of riverbed processes, and focuses on the mapping methods of the danger assessment of riverbed processes: determining the danger degree of riverbed processes and different methods of displaying it on the map. An example of displaying danger on the previously drawn map is given, and the distribution of different types and expression degrees of dangerous riverbed processes under various natural conditions in Russia is briefly analyzed.

Electrospinning nanofiber membrane has the advantages of wide raw materials, large specific surface area, and high porosity. It is an ideal separator material for lithium-ion batteries. This paper first introduces two common electrospinning nanofiber diaphragms: polymer, polymer, and inorganic composite, and then focuses on the modification methods of composite modification, blending modification, and inorganic modification, as well as the methods of electrospinning nano modified polyolefin diaphragm. Finally, the development direction of the electrospinning lithium-ion battery separator has prospected.

Introduction: Growth, yield and quality of okra (Abelmoschus esculentus (L.) Moench) are related to fertilizer application, being nitrogen (N) the most outstanding, due to its direct relationship with photosynthesis and vegetative growth of the plant. Objective: The objective was to evaluate the agronomic and productivity characteristics of okra as a function of N dose. Materials and methods: The study was conducted at the experimental area of Campus Gurupi, the Universidad Federal de Tocantins (UFT), Brazil, in two planting periods (autumn/winter and spring/summer). The experimental design used was randomized block design (RBD) with six treatments (50, 100, 150, 150, 200 and 250 kg N ha^-1) and four replications. Urea was used as a source of N. The characteristics evaluated were: productivity, average fruit mass, height and plant chlorophyll index. Results: Productivity and plant height were superior in the fall/winter crop. Mean fruit mass and chlorophyll index were not influenced by planting time. For productivity, a linear response was obtained with increasing dose up to the limit of the N dose used (250 kg ha^-1), with a mean value higher than 14 t of fruit. Mean mass and plant height responded linearly to increasing N dose. Nitrogen affected the chlorophyll index, with maximum values of 45.96 and 47.19, observed in the two evaluation periods. Conclusion: Planting time and N content in the soil interacted with plant height, being favorable in the period without precipitation. N influenced all the characteristics, demonstrating the importance of nitrogen fertilization in the development of okra plants.

Surface-enhanced Raman scattering (SERS) spectrum has the characteristics of fast-detection, high-sensitivity and low-requirements for sample pretreatment. It plays a more and more important role in the detection of organic pollutants. In this study, MIL-101 and Au nanoparticles were prepared by hydrothermal method and aqueous solution reduction method respectively, and MIL-101/Au composite nanoparticles were prepared by electrostatic interaction. The SERS properties of the composite substrate were optimized by adjusting the size of Au nanoparticles and the surface distribution density of MIL-101 nanoparticles. The detection limit of Rhodamine 6G (R6G) for the composite substrate with the optimal ratio was investigated, which was as low as 10^–11 M. It is proved that MIL-101/Au composite nanoparticles have high sensitivity to probe molecules. When they are applied to the detection of persistent organic pollutants, the detection limit for fluoranthene can reach 10^–9 M and for 3,3’,4,4’-tetrachlorobiphenyl (PCB-77) can reach 10^–5 M.

Small and medium-sized enterprises as the main body of Chinese enterprises should be an important driving force for China's economic development. However, the problems of salary management faced by small and medium-sized enterprises are increasingly hindering their own survival and development. Whether it is standing on the position of the enterprise or the workers, the pay problem is that they are more concerned about the problem, while the remuneration is also an indispensable modern means of competition and incentives. Salary management is not only indispensable content of enterprise human resources, but also the establishment of modern enterprise system, and optimization of the allocation of social resources requirements. Enterprise salary management operation flexibility or not, directly affect the production and operation management, which will affect the long-term development of enterprises. This paper analyzes the problems of salary management in small and medium-sized enterprises (SMEs), such as unreasonable pay system, lack of forward-looking management system, and so on, and analyzes and discusses their own countermeasures.

Machine analysis of detection of the face is an active research topic in Human-Computer Interaction today. Most of the existing studies show that discovering the portion and scale of the face region is difficult due to significant illumination variation, noise and appearance variation in unconstrained scenarios. To overcome these problems, we present a method based on Extended Semi-Local Binary Patterns. For each frame, an aggregation of the pixel values over a neighborhood is considered and a local binary pattern is obtained. From these a binary code is obtained for each pixel and then histogram features is computed. Adaboost algorithm is used to learn and classify these discriminative features with the help of exemplar face and non-face signature of the images for detecting the location of face region in the frame. This Extended Semi Local Binary Pattern is sturdy to variations in illumination and noisy images. The developed methods are deployed on the real time YouTube video face databases and found to exhibit significant performance improvement owing to the novel features when compared to the existing techniques.