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Creeping bentgrass (Agrostis stolonifera) is an excellent cool-season turfgrass that is widely used in urban gardening, landscaping, and golf turf. Triennial field experiments from 2017 to 2019 were conducted to investigate effects of the foliar application of chitosan (CTS), γ-aminobutyric acid (GABA), or sodium chloride (NaCl) on mitigating summer bentgrass decline (SBD) and exploring the CTS, GABA, or NaCl regulatory mechanism of tolerance to summer heat stress associated with changes in chlorophyll (Chl) loss and photosynthetic capacity, osmotic adjustment (OA), oxidative damage, and cell membrane stability. The findings demonstrated that persistent ambient high temperatures above 30 °C during the summer months of 2017, 2018, and 2019 significantly reduced the turf quality (TQ), Chl content, photochemical efficiency of PSII (Fv/Fm and PIABS), leaf relative water content, and osmotic potential (OP) but significantly increased electrolyte leakage (EL) and the accumulations of free proline, water-soluble carbohydrate (WSC), hydrogen peroxide (H2O2), and malondialdehyde (MDA). The foliar application of CTS, GABA, or NaCl could significantly alleviate SBD, as reflected by improved TQ and delayed Chl loss during hot summer months. Heat-induced declines in Fv/Fm, PIABS, the net photosynthetic rate (Pn), the transpiration rate (Tr), and water use efficiency (WUE) could be significantly mitigated by the exogenous application of CTS, GABA, or NaCl. In addition, the foliar application of CTS, GABA, or NaCl also significantly improved the accumulations of free proline and WSC but reduced the EL, OP, and H2O2 content and the MDA content in leaves of creeping bentgrass in favor of water and redox homeostasis in summer. Based on the comprehensive evaluation of the subordinate function value analysis (SFVA), the CTS had the best effect on the mitigation of SBD, followed by GABA and NaCl in 2017, 2018, and 2019. The current study indicates that the foliar application of an appropriate dose of GABA, CTS, or NaCl provides a cost-effective strategy for mitigating SBD. [ABSTRACT FROM AUTHOR]

The main hazards in the process of manual handling work are triggered by human factors and ergonomics. This study is intended to implement a valid approach to quantitatively evaluate the risk level during manual handling work. A risk assessment model for manual handling workers was proposed based on subjective and objective correlation. A simulation experiment of manual handling process was developed and an ergonomics evaluation method was carried out. The 33‐point human joint model of BlazePose neural network and the Rapid Upper Limb Analysis (RULA) method were utilized to determine the risk posture and risk index of the manual handling workers. This study brought together hemodynamic parameters and the score of Borg Rating of Perceived Exertion (RPE) scale and Physical Resources Scale (PRS) to obtain the final comprehensive index of work risk. The results showed that the risk indexes from the three stages of the experiment obtained by RULA method were 3, 4, and 7. And the scores of comprehensive indexes obtained by the risk assessment model were 1.841, 1.900, and 1.987, suggesting that the evaluation model based on subjective and objective correlation had the same ability to determine the risk levels of different handling tasks. Therefore, the risk assessment model proposed in this study verified the effectiveness of the comprehensive evaluation index integrating hemodynamic parameters and subjective evaluation scores. [ABSTRACT FROM AUTHOR]

Aiming at the problems of the standard rapidly exploring random tree (RRT) algorithm in a complex environment, such as blind expansion, falling into local search, easy planning failure, low sampling success rate, and long paths, an adaptive goal-oriented strategy combined with an alternative strategy for regional sampling and an improved RRT algorithm of the greedy pruning strategy was proposed. Based on the kinematics of the manipulator, the envelope was used to simplify the manipulator model to improve the efficiency of collision detection. The adaptive goal-oriented strategy solved the problems of blind search, low search success rate, and difficult convergence of the RRT algorithm in complex environments; the regional sampling alternative strategy solved the problems of the RRT algorithm easily falling into local search, low sampling success rate, and long sampling time; the greedy pruning strategy eliminated redundant nodes and shortened the path, improved the path quality, and enhanced the robustness of the algorithm. In the Matlab and robot operating system (ROS), the obstacle avoidance simulation planning was carried out for different scenarios. The results show that the average search success rate of the improved RRT algorithm has increased by 82.4%, the average sampling success rate has increased by 67.5%, and the average path planning success rate has increased by 70%. The average time efficiency is increased by 81.9%, and the average path length is shortened by 63.05%. Finally, the practicability and effectiveness of the algorithm were further verified by the trajectory planning of the physical manipulator.

In order to improve the tracking accuracy and response speed of the articulated robot in the working process under non-strict repetitive conditions, a three-joint articulated robot model is designed, and the kinematics and dynamics analysis are carried out to verify the reasonable structure of the model. In view of the non-repetitive and nonlinear characteristics of the articulated robot system, it is proposed that a high-order internal model iterative learning control algorithm can be applied to the control of the articulated robot system. A reasonable learning gain and a higher internal model order are designed to strictly prove its convergence in theory. The simulation contrast experiment and the trajectory tracking experiment after adding the disturbance are designed. The results show that the high-order internal model iterative learning algorithm converges faster and has good control effect.

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Exceeding the limit of underground hydrogen sulfide not only harms operators, but also damages underground equipment.The concentration of hydrogen sulfide in water in a coal mine roadway in Shanxi is 228.19 mg/m3, and 45.64 mg/m3in the air, rendering it a high hydrogen sulfide coal mine.The method of coal seam drilling and alkali injection is used to control hydrogen sulfide.In order to determine the optimal parameters of alkali injection, this paper uses COMSOL Multiphysics software to carry out single-hole and double-hole alkali injection numerical simulations on the process and effect of coal seam alkali injection to treat hydrogen sulfide.The simulation results of single-hole and double-hole alkali injection show that: the farther away from the drilling center, the lower the alkali injection pressure on the coal seam.The longer the alkali injection time, the larger the diffusion range of the alkali solution.And the diffusion speed of the alkali solution gradually decreases as the diffusion range becomes larger.When the distance of double-hole alkali injection is too close, the cross-flow will cause the diffusion range of the alkali solution to become smaller at the same time.The optimal simulation scheme is as follows: the hole distance is 10 m, the pressure is 8 MPa, and the alkali injection time is 48 h.After alkali injection at the 13103 working face, a 28 d on-site data monitoring was carried out.The maximum hydrogen sulfide concentration in the return air flow was 9.13 mg/m3, which did not exceed the limit during the mining, indicating that the optimal alkali injection parameters can guide the coal seam alkali injection work.