Salinity is a major and complex abiotic stress that inhibits plant growth and reduces crop yield. Given the global increase in soil salinity, there is a need to develop salt-tolerant species. Brassica napus L. is an important oilseed crop with some level of salt tolerance. However, few studies have evaluated its salt tolerance thoroughly or screened for traits that can be reliably evaluated for salt tolerance. Here, we evaluated salt tolerance in 549 B. napus inbred lines with different genetic backgrounds using the membership function value (MFV) of certain traits, including the germination rate, root and shoot length, root and shoot fresh weight, and total fresh weight. According to the evaluation criteria-mean MFV, 50 highly salt-tolerant, 115 salt-tolerant, 71 moderately salt-tolerant, 202 salt-sensitive, and 111 highly salt-sensitive inbred lines were screened at the germination stage. We also developed a mathematical evaluation model and identified that the salt tolerance index of shoot fresh weight is a single trait that reliably represents the salt tolerance of B. napus germplasm at the germination stage. These results are useful for evaluating and breeding salt-tolerant B. napus germplasm.

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In this study, near fully dense (96.5%) pure tungsten bulks were additively manufactured and the cracking behavior was investigated. A crack network with a spacing of * 100 lm was observed in the fabricated bulks. It was observed that the laser scanning strategy, which could tailor the microstructure, affected the crack distribution pattern in fabricated tungsten. The calculated surface temperature difference (7300 K) was much higher than the cracking criterion (800 K) of tungsten, indicating that cracking is almost inevitable in laser additive manufacturing of tungsten. It could be concluded that crack network formed because the cracks emerged in every laser molten track and then interconnected in the layer-by-layer building process.

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At present, many path tracking controllers are unable to actively adjust the longitudinal velocity according to path information, such as the radius of the curve, to further improve tracking accuracy. For this problem, we propose a new path tracking framework based on model predictive control (MPC). This is a multilayer control system that includes three path tracking controllers with fixed velocities and a velocity decision controller. This new control method is named multilayer MPC. This new control method is compared to other control methods through simulation. In this paper, the maximum values of the displacement error and the heading error of multilayer MPC are 92.92% and 77.02%, respectively, smaller than those of nonlinear MPC. The real-time performance of multilayer MPC is very good, and parallel computation can further improve the real-time performance of this control method. In simulation results, the calculation time of multilayer MPC in each control period does not exceed 0.0130 s, which is much smaller than the control period. In addition, when the error of positioning systems is at the centimeter level, the performance of multilayer MPC is still good.

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