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The aerosol produced during welding affects the working environment and the health of workers. The formation mechanism of welding aerosols and the factors affecting the amount of welding dust were summarized, and the research status and conclusions of each influencing factor were summarized, and the methods and development trend of the formation mechanism of welding aerosols and the factors affecting the amount of welding dust were prospected. Late need to build a unified model based on dynamic conditions to study the formation mechanism of aerosol and many factors influence the amount of hair dust change rule, and combined with high, speed camera and image processing technology, the research methods from the simple experimental observation to regularity. [ABSTRACT FROM AUTHOR]

Geosynthetic clay liner (GCL) is a new type of material commonly used for lake bottom seepage prevention, but if the roots of lake aquatic plants penetrate into GCL, it will affects its seepage prevention effect. In order to explore the influence of GCL􀆳s hydraulic conductivity under the penetration of plant roots, model tests were carried out on plants such as Thalia dealbata, reed, and cattail, global digital systems (GDS) geoenvironmental permeameter was used to test the hydraulic conductivity of GCL after the penetration of aquatic plant roots. The results show as follows. Under the same confining pressure, with the increases of the penetration rate of plant roots, the GCL hydraulic conductivity under the penetration of Thalia dealbata, reed and cattail roots gradually increase, and the maximum increases to 10 -7 m/ s. When the root penetration rate is greater than 1%, the GCL hydraulic conductivity of withered roots is about 1. 26 ~3. 13 times that of the normal roots morphology. The withered roots have a more significant impact on GCL permeability than the normal root morphology. The roots of cattails and reeds have similar effects on the hydraulic conductivity of GCL, while the roots of Thalia dealbata have little effect on the hydraulic conductivity of GCL. [ABSTRACT FROM AUTHOR]

: In order to monitor illegal land use in real time, video surveillance technology was used to monitor the vulnerable areas of illegal land use. Excavator was one of the most important construction machinery in the engineering construction, an automatic real-time detection of excavator could provide important information for non-contact field monitoring of illegal land. But it was difficult to accurately detect the excavator due to the complex background, uneven illumination and partial occlusion in natural scene, This paper proposed a real-time excavator detection algorithm in natural scene based on the SSD-like (Single Shot Detector). Specifically, the lightweight network DDB (Depthwise Dense Block) was used as the basic network to extract shallow feature and fuse with high-level features in the excavator objection model to enhance the feature representation capability. Meanwhile, the BDM (Bottleneck Down-sampling Module) which was designed based on the lightweight network MobileNetV2 was used as the multi-scale feature extraction network to reduce the parameter quantity and computation. The data sets included 18 537 images of excavators with different shooting angles and natural scenes, 15 009 images were used as training set and 3 528 images were chosen as test set randomly. To enhance the diversity of training data, data set expansion methods such as rotation and image were adopted. Based on the Caffe deep learning framework, the proposed model in this paper was trained with end-to-end approximate joint methods and the model weight was fine-tuned by using SGD (Stochastic Gradient Descent) algorithm. The DDB module of the network was initialized with the weights pre-trained on the PASCAL VOC dataset, and the training time and resources were further reduced by transferring learning. Then the model pre-trained on the large data sets was transplanted to excavator object detection by transfer learning. The proposed method was transplanted and performed on the mainstream Jetson TX1 embedded hardware platform, and experiments on the actual data set of detecting excavator object at different angles of view and natural scenes. Experiment results showed that the parameter quantity and computational complexity of proposed model with BDM was reduced by 68.4% compared to SSD, the mAP (Mean Average Precision) of proposed method reached 90.6% on the testing set, which was 0.4% and 0.4% higher than that of SSD based on VGG16 basic net and MobileNetV2SSD based on MobileNetV2 basic net, respectively. The model size of propose method was 4.2 MB, which was about 1/25 and 1/4 of SSD and mobilenetv2ssd, respectively, and the time-consuming of each frame was 145.2 ms, which was 122.7% and 28.2% faster than SSD and MobileNetV2SSD, respectively. The proposed method not only had better generalization and robustness, but also can be better deployed on the embedded hardware platform which demonstrated the feasibility of real-time monitoring of the excavator at site of illegal land use. [ABSTRACT FROM AUTHOR]

: Irrigation water in Yellow River is decreasing due to global warming, the uneven distribution of rainfall, serious surface evaporation and underground leaks. Water-use efficiency has posed a great challenge in the arid and semi-arid areas, particularly on western China, such as Tongxin County, Ningxia. To meet challenge, it is necessary to explore an efficient water-saving method using the depth of underground infiltration irrigation and pan evaporation coefficient. In this study, an experiment was performed on two factors and 12 treatments in three depths of underground infiltration irrigation: D15 (15 cm), D30 (30 cm), D45 (45 cm), and four irrigation volume: W0.6 (Kcp = 0.6), W0.8 (Kcp = 0.8), W1.0 (Kcp = 1.0), W1.2 (Kcp = 1.2), where the crop-pan coefficient (Kcp) was used to evaluate irrigation volume, and the 7-year Tongxin round jujube was selected as the subject. The field experiments were conducted from January 2017 to December 2018 in the Water-saving and Efficient Agricultural Science and Technology Park (36°50′N, 105°60′E) in the dry area of Wangtuan Town, Tongxin County, Ningxia, China. The spatial and temporal changes were investigated by soil moisture, annual growth of root system, agronomic traits, yield and water-use efficiency. Then, a spatial analysis was used to search the areas, where jujube yield and water-use efficiency were better matched, and to obtain the optimal underground level, where the irrigation range was determined by the depth of infiltration irrigation and crop-pan coefficient. The test results showed that the water contents in the soil from 0-100 cm in the vertical direction, and from 0-80 cm in the horizontal was higher than others with the increase of irrigation volume, whereas, the peak of soil water content moved downward with the increase in the depth of underground infiltration irrigation. The buried depth of 15 cm or 30 cm can increase the moisture content in the soil depth of 0-40 cm, while the buried depth of 45 cm can increase that in the soil depth of 40-60 cm. The irrigation volume and the depth of subsurface infiltration irrigation have a great impact on the root system distribution of 20-80 cm soil layer. There were significant differences in the root system increments under various subsurface infiltration irrigation depths. Specifically, the D30W0.6 and D30W0.8 treatments increased the root dry density from 20-60 cm soil layer, and the D45W1.0 and D45W1.2 treatments increased that from the 60-80 cm soil layer, compared with other treatments. Two-year experiments showed that the D30W1.0 treatment was optimum to increase the hanging length of jujube, the number of flowers per hang, the number of fruits per hang, fruit set rate and yield. The highest water-use efficiency of D30W0.8 was 4.68kg/m3 in 2017 and 5.32 kg/m3 in 2018, increased by 17.88% (2017), 16.41 % (2018), but the yield decreased by 9.32% (2017) and 5.94% (2018), compared with D30W1.0 treatment, indicating D30W0.8 treatment was significantly different from other treatments (P<0.05). Therefore, the yield and water use efficiency (WUE) can be used to optimize the irrigation strategies for jujube trees by using multivariate regression and spatial analysis. In this case, the optimal irrigation amount and the depth of subsurface infiltration irrigation can be selected as follows: 370-410 mm and 28-33 cm, respectively. The finding can provide a sound basis and technical support for high efficient management of jujube trees during subsurface irrigation in arid areas of Ningxia, China. [ABSTRACT FROM AUTHOR]

Ningxia Helan County was taken as the research area in this paper to study the distribution characteristics and ecological risk of heavy metals in farmland soil in northwest China. 140 topsoil samples were collected aiming to analyze and measure the concentration of Cr, Ni, Cu, Zn, As, Cd and Pb belonging to heavy metal elements. The distributions, soil environment status and ecological risk of the seven heavy metals were studied by Nemerow pollution index and Håkanson potential ecological risk index methods. The results showed that concentrations of Cr, Ni, Cu, Zn, As and Pb were all lower than the second-level of Environmental Quality Standard for Soils of China except that concentrations of Cd of 1.42% samples were appeared to exceed the standard. Compared with the background values, seven heavy metals of all samples showed different degree accumulation, in which Cd, Ni elements beyond the background value ratio reached 100% and 85%. Spatial distribution of the concentrations of the seven heavy metals had obvious accordance. The content of each element was evenly distributed. The high content of each element was concentrated in the central and eastern part of Helan County, which was related to human activities. The calculation results of single-factor pollution index showed that among the 140 soil samples, 0.71% of Cd were moderate contamination, 7.14% of Ni and 5% of As were slight clean, Cr, Cu, Zn, Pb of all samples were all clean. According to the individual potential ecological risk index（Ei r）of heavy metals, the average potential ecological risk index of Cd element was 97.68, which indicated that Cd had reached the serious risk level, becoming the main element of potential ecological risk. All in all, the quality of farmland soil in Helan County of Ningxia is good, but it is noteworthy that the concentration of Cd, Ni has a serious accumulation. [ABSTRACT FROM AUTHOR]