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The effect of exogenous applied nitric oxide on photosynthesis under heat stress was investigated in rice seedlings. High temperature resulted in significant reductions of the net photosynthetic rate (P N) due to non-stomatal components. Application of nitric oxide donors, sodium nitroprusside (SNP) or S-nitrosoglutathione (GSNO), dramatically alleviated the decrease of P N induced by high temperature. Chlorophyll fluorescence measurement revealed that high temperature caused significant increase of the initial fluorescence (F o) and non-photochemical quenching (NPQ) whereas remarkable decrease of the maximal fluorescence (F m), the maximal efficiency of PSII photochemistry (F v/F m), the actual PSII efficiency (ΦPSII), and photochemical quenching (q p). In the presence of SNP or GSNO pretreatment, the increase of F o and decrease of F m, F v/F m, ΦPSII and q p were markedly mitigated, but NPQ was further elevated. Moreover, with SNP or GSNO pretreatment, H2O2 accumulation and electrolyte leakage induced by heat treatment were significantly reduced, whereas zeaxanthin content and carotenoid content relative to chlorophyll were elevated. The potassium salt of 2-(4-carboxyphenyl)-4,4,5,5-tetramethylimidazoline-1-oxyl-3-oxide (cPTIO), a specific NO scavenger, arrested NO donors mediated effects. These results suggest that NO can effectively protect photosynthesis from damage induced by heat stress. The activation effect of NO on photosynthesis may be mediated by acting as ROS scavenging, or/and alleviating oxidative stress via maintaining higher carotenoid content relative to chlorophyll or/and enhancing thermal dissipation of excess energy through keeping higher level of zeaxanthin content under heat stress.
The path following control problem of the underactuated unmanned surface vessel (USV) is studied in this paper. An improved line-of-sight (LOS) guidance algorithm is proposed which can adjust adaptively based on the path following error. The global asymptotically stable path following controller is designed based on the nonlinear backstepping method and the Lyapunov stability theory. Firstly, the USV path following error model is established in the Serret-Frenet (SF) coordinate frame. The path following error in the inertial coordinate frame is transformed into the SF coordinate frame, which is used to define the path following control problem. Secondly, inspired by the traditional LOS guidance algorithm, the longitudinal path following error in the SF coordinate frame is introduced into the improved LOS guidance algorithm. This allows the algorithm to adjust adaptively to the desired path. Thirdly, in order to solve the underactuated problem of the USV path following control system, the tangential velocity of the desired path is designed as a virtual input. The underactuated problem is converted to a virtual fully actuated problem by designing the virtual control law for the tangential velocity. Finally, by combining backstepping design principles and the Lyapunov stability theory, the longitudinal thrust control law and the yaw torque control law are designed for the underactuated USV. Meanwhile, the global asymptotic stability of the path following error is proved. Simulation experiments demonstrate the effectiveness and reliability of the improved LOS guidance algorithm and the path following controller
Radars and sensors are essential devices for an Unmanned Surface Vehicle (USV) to detect obstacles. Their precision has improved significantly in recent years with relatively accurate capability to locate obstacles. However, small detection errors in the estimation and prediction of trajectories of obstacles may cause serious problems in accuracy, thereby damaging the judgment of USV and affecting the effectiveness of collision avoidance. In this study, the effect of radar errors on the prediction accuracy of obstacle position is studied on the basis of the autoregressive prediction model. The cause of radar error is also analyzed. Subsequently, a bidirectional adaptive filtering algorithm based on polynomial fitting and particle swarm optimization is proposed to eliminate the observed errors in vertical and abscissa coordinates. Then, simulations of obstacle tracking and prediction are carried out, and the results show the validity of the algorithm. Finally, the method is used to simulate the collision avoidance of USV, and the results show the validity and reliability of the algorithm
The unmanned surface vehicles (USV) are required to perform a dynamic obstacle avoidance during fulfilling a task. This is essential for USV safety in case of an emergency and such action has been proved to be difficult. However, little research has been done in this area. This study proposes an emergency collision avoidance algorithm for unmanned surface vehicles (USVs) based on a motion ability database. The algorithm is aimed to address the inconsistency of the existing algorithm. It is proposed to avoid collision in emergency situations by sharp turning and treating the collision avoidance process as a part of the turning movement of USV. In addition, the rolling safety and effect of speed reduction during the collision avoidance process are considered. First, a USV motion ability database is established by numerical simulation. The database includes maximum rolling angle, velocity vector, position scalar, and steering time data during the turning process. In emergency collision avoidance planning, the expected steering angle is obtained based on the International Regulations for Preventing Collisions at Sea (COLREGs), and the solution space, with initial velocity and rudder angle taken as independent variables, is determined by combining the steering time and rolling angle data. On the basis of this solution space, the objective function is solved by the particle swarm optimization (PSO) algorithm, and the optimal initial velocity and rudder angle are obtained. The position data corresponding to this solution is the emergency collision avoidance trajectory. Then, the collision avoidance parameters were calculated based on the afore mentioned model of motion. With the use of MATLAB and Unity software, a semi-physical simulation platform was established to perform the avoidance simulation experiment under emergency situation. Results show the validity of the algorithm. Hence results of this research can be useful for performing intelligent collision avoidance operations of USV and other autonomous ships
In this study, wastes and minerals were incorporated into the production of bricks as a kind of waterpurifying substrate. The brick contained 72% clay, 10% bagasse, 10% steel slag, 5% zeolite, and 3% calcite by weight. The brick exhibited highly and hierarchically porous structure. It can remove phosphate and ammonium simultaneously from aqueous solutions with the maximum adsorption amount of 3.8 mg/g for phosphate and 0.7 mg/g for ammonium. Kinetic analysis showed that the brick had a faster removal rate for phosphate than ammonium. The maximum desorbability of phosphate and ammonium were found to be 5.9% and 13.9%, respectively. Considering wastes recycling, easy fabrication, and favorable properties, this type of brick has the potential to be applied to in-situ remediation of aquatic environment.
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