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The 2280 km long Jinsha River has been blocked at least four times in the past 30 years. A landslide damming hazard chain can endanger communities and infrastructures hundreds of kilometers downstream from the damming site in alpine gorges. Past damming events have resulted in severe consequences, demanding a thorough assessment of damming threats along the entire Jinsha River. This study digitizes the Jinsha River and visualizes its topographic, tectonic, hydrologic, and climate characteristics in detail. A two-stage full-probability method is proposed for assessing the damming threats along this river, making it possible to identify potential damming hotspots and high-priority zones for hazard mitigation. It is found that the upper reach of the Jinsha River poses the greatest damming threat, and the threat level gradually decreases downstream. Approximately 33.4%, 36.7%, 20.5%, and 9.4% of the entire length of the Jinsha River are classified as low, moderate, high, and very high threat levels, respectively. Compared with existing hydropower projects, future projects in the upper reach are more likely to be exposed to landslide damming. We highlight the value of basin-scale spatial threat analysis and envisage that our findings will promote more targeted local-scale risk assessments for potential damming hotspots. These outcomes provide the basis for managing the risks of river damming and hydropower infrastructure along the Jinsha River.

Sapphire is extensively utilized in the optical, aerospace, and civil electronic industries due to its favorable optical, physical, and chemical characteristics. To enhance the efficiency and quality of sapphire lapping, an orthogonal experiment was conducted on a single-side sapphire substrate using a ceramic lapping plate. The study examined the impact of lapping plate material, lapping pressure, lapping speed, and abrasive particle size on the surface roughness, profile, and removal rate. By analyzing the signal-to-noise ratio and variance of machining parameters, the influence rule and influence of the weight of machining parameters on machining results were obtained. The results of the experiment demonstrate that the material removal rate of sapphire was positively affected by an increase in lapping pressure, speed, and abrasive particle size. Moreover, the removal rate of the SiC lapping plate was the highest among the experimental materials. The roughness of the sapphire surface decreased with increasing lapping pressure, speed, and abrasive particle size, while the SiC plate had the lowest surface roughness. The profile tolerance of sapphire diminished as the lapping pressure, lapping speed, and the abrasive particle size increased. Additionally, the ZrO2 lapping plate exhibited the most minor profile tolerance. The size of the abrasive particle significantly impacted the material removal rate, with a specific gravity exceeding 70%. Similarly, the lapping pressure had a significant effect on both the surface roughness and the profile tolerance. The ideal machining parameter combination comprised an abrasive particle size of 10 µm, a lapping pressure of 22 785.0 Pa, a lapping speed of 60 rpm, and a lapping plate of SiC. Under optimal machining conditions, sapphire exhibited a material removal rate of 0.65 µm/h, a surface roughness of 0.0920 µm, and a profile tolerance of 2.0915 µm after 20 min of lapping. This demonstrated that the lapping process enables highly efficient and high-quality machining of sapphire substrates.

The data-driven phenomenological models based on deformation measurements have been widely utilized to predict the slope failure time (SFT). The observational and model uncertainties could lead the predicted SFT calculated from the phenomenological models to deviate from the actual SFT. Currently, very limited study has been conducted on how to evaluate the effect of such uncertainties on SFT prediction. In this paper, a comprehensive slope failure database was compiled. A Bayesian machine learning (BML)-based method was developed to learn the model and observational uncertainties involved in SFT prediction, through which the probabilistic distribution of the SFT can be obtained. This method was illustrated in detail with an example. Verification studies show that the BML-based method is superior to the traditional inverse velocity method (INVM) and the maximum likelihood method for predicting SFT. The proposed method in this study provides an effective tool for SFT prediction.

Corn (Zea mays L.)–soybean (Glycine max (L.) Merr.) intercropping is one of the main traditional intercropping systems used. We hypothesized that sweet corn–soybean intercropping with reduced nitrogen application could improve the crops’ fresh grain yield and nitrogen acquisition. We clarified whether sweet corn intercropped with soybean has the advantages of improved crop yield and carbon and nitrogen accumulation and assessed interspecific competition in the intercropping systems. A four-year (2017–2020) field experiment was conducted with three nitrogen application levels (0, 150, and 300 kg∙ha−1) and three planting patterns (monocropped sweet corn, monocropped soybean, sweet corn–soybean intercropping) at Jiangxi Agricultural University, Nanchang, China. The LER (land equivalent ratio), AG (aggressivity), and CR (competitive ratio) were calculated using the fresh grain yield and nitrogen and carbon accumulation of sweet corn and soybean. The LER values were greater than 1.0 in most of the intercropped patterns, except for the value based on the crops’ fresh grain yield without nitrogen application in 2020. Sweet corn had greater values of CR and AG than soybean in the intercropping system. Compared with common nitrogen application (300 kg∙ha−1), reduced nitrogen application (150 kg∙ha−1) did not significantly reduce the LER or the average CR and AG values. Under reduced nitrogen application, the values of LER, CR, and AG, based on the crops’ fresh grain yield and nitrogen acquisition, were not significantly different between the four years. In conclusion, based on the LER, CR, and AG, sweet corn–soybean intercropping had the advantage of crop yield and nitrogen acquisition, and sweet corn was the superior competitor. Sweet corn–soybean intercropping with nitrogen application (150 kg N ha−1) showed good inter-annual stability of crop productivity and competitiveness of the sweet corn.

In order to explore the effects of biochar and cropping systems on soil copper (Cu) speciation and copper accumulation in sweet corn (Zea mays L. var. Rugosa Bonaf.) and soybean (Glycine max (L.) Merr.), three ratios of biochar (C0, 0%, C1, 2%, C2, 5% by mass ratio, (w/w)) and three cropping systems (monocropped sweet corn, MC; monocropped soybean, MS; sweet corn–soybean intercropping, CS) were studied under three Cu levels (Cu0, 0 mg·kg−1, Cu1, 200 mg·kg−1, and Cu2, 400 mg·kg−1) in a pot experiment. The following results were obtained: (1) Compared with C0, adding biochar (C1, C2) could significantly reduce the Cu concentration in sweet corn, and C2 significantly reduced the Cu concentration in soybean under Cu1 and Cu2; the Cu concentrations in sweet corn and soybeans under Cu1 were lower than 10 mg·kg−1. (2) Compared with MC or MS, C2 significantly reduced the Cu concentration (below the detection limit) in sweet corn and the Cu concentration (1.65 mg·kg−1) in soybean straw in CS under Cu1. The Cu concentration in sweet corn ears and soybean straw in CS under Cu2 also decreased significantly, reaching 1.84 and 10.36 mg·kg−1, respectively. (3) Compared with C0, C2 significantly reduced the soil acid-soluble Cu concentration under Cu1 and Cu2, but significantly increased soil oxidated Cu concentration. (4) Compared with MC, the concentration of soil acid-soluble Cu was significantly decreased in CSC1 under Cu2. Under Cu1, the concentrations of reducible Cu were significantly increased in CSC1 and CSC2, and the oxidizable Cu concentration was increased in CSC2. In conclusion, sweet corn–soybean intercropping combined with biochar 5% (w/w) is beneficial to reducing the concentration of acid-soluble Cu, and increases the concentration of oxidizable Cu in copper-contaminated soil. Under Cu1 (200 mg·kg−1), the Cu concentrations in sweet corn and soybean were lower than 10 mg·kg−1, which meets the national food safety standard of China. Under Cu2 (400 mg·kg−1), the Cu concentration in sweet corn was lower than 10 mg·kg−1, but it was higher than 10 mg·kg−1 in soybean.

This paper proposed a double-sided staggered conical teeth traveling wave rotating ultrasonic motor based on in-plane bending mode, which reduces the difficulty of rotor preload application and improves the output characteristics of in-plane bending mode traveling wave rotating ultrasonic motor. The motor has four sets of drive teeth alternately distributed on both the inner and outer sides of the vibrator, with the drive teeth gap dedicated to accommodate the piezoelectric ceramic piece, and the staggered drive teeth on both sides of the vibrator are used to drive the rotor rotation. The motor operates in two in-plane third-order bending modes with the same frequency and orthogonal to each other, and is excited by four sets of piezoelectric ceramic disks spaced 90 degrees apart from the inner and outer sides. After the prototype was completed, its vibration characteristics and output performance were experimentally tested, and the actual effects of the three excitation schemes were compared. The experimental results show that the motor can provide a maximum output torque of 1.82N-mm and a maximum no-load speed of 96.4 rpm when the excitation voltage is 300 V and the excitation frequency is 20.60 kHz. [ABSTRACT FROM AUTHOR]