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【Objective】 Reducing water and fertilizer application is critical to developing sustainable agriculture worldwide. This paper investigates the optimal water-saving drip irrigation and nitrogen-reducing fertilization for cultivation of young apple in arid and semi-arid regions in northwestern China. 【Method】 The two-year experiment consisted of three irrigation treatments by keeping soil water content at 75%~90% (W1), 60%~75% (W2) and 45%~60% (W3) of the field capacity. For each treatment, there were four fertilizations by applying N-P2O5-K2O to each plant at 18-12-6 g (F1), 15-12-6 g (F2), 12-12-6 g (F3), and 9-12-6 g (F4). For each treatment, we measured the growth, photosynthetic traits, and water use efficiency of the trees. 【Result】 F2+W2 combination gave the highest plant growth, basal stem growth, and leaf area, demonstrating that a moderate water deficit and fertilization reduction was beneficial to the tree growth. Leaf SPAD started to increase from the budding and flowering stage, with the impact of fertilization on it ranked in the order of F1 > F2 > F3 > F4, and the influence of irrigation ranked in the order of W1 > W2 > W3 at the fruit-set and ripening stages. The F1+W1 combination gave the highest leaf SPAD. Photosynthesis and transpiration increased with the increase in fertilization and irrigation amount. Maximum water use efficiency was achieved in F1+W2 and F2+W2, with its value being 5.16 and 4.81 μmol/mmol, respectively, which were 8.6% and 5.3% more than those in F1+W1. Irrigation amount affected tree growth more than fertilization, and strong correlations were found between growth, leaf area, SPAD, and photosynthetic traits of the trees. 【Conclusion】 The comparative results show that F2+W2 is optimal for young apple tree under drip irrigation. It indicates that a moderate reduction in irrigation and fertilization did not result in a noticeable effect on tree growth and can be used as an improved agronomic practice for apple production in arid and semi-arid regions in Northern China and areas with similar climates.

In this study, nonsingular modeling and cross-domain trajectory tracking control problems for a special class of coaxial hybrid aerial–underwater vehicles (HAUVs) are investigated. Coaxial HAUVs need to effectively overcome the influence of hydrodynamic factors when moving underwater, so the attitude angle required by coaxial HAUVs is much larger than that in the air. The attitude representation based on quaternion modeling is adopted to avoid the inherent singularity of Euler angle modeling. A cascade sliding mode control and proportion differentiation (SMC-PD) controller is proposed, which is used to position trajectory and attitude quaternion tracking control, respectively. An adaptive sliding mode controller based on disturbance observer (DO) enhancement is adopted in the outer loop to carry trajectory tracking control. At the same time, the expected attitude angle is calculated by the outer loop (position) and is converted into the expected quaternion. With reference to the idea of enhanced robustness in active disturbance rejection control (ADRC), a feedforward proportion derivation (PD) controller based on DO enhancement is used to track the desired quaternion. A variable parameter adaptive algorithm based on the learning rate is introduced in the cascaded SMC-PD controller. The error convergence speed of the system is further improved by adaptively changing the controller parameters. The stability of the proposed control scheme is proved by using the Lyapunov theory. The numerical simulation results show that the controller has good robustness and effectiveness. [ABSTRACT FROM AUTHOR]

In contrast to other swimming modes, the motions of fins in the labriform mode can be categorized into the drag-based mode and the lift-based mode, which differ in terms of the thrust generation mechanisms. This variance in thrust generation mechanisms gives the labriform mode unique advantages in underwater propulsion. The term labriform indicates that propulsion occurs due to oscillatory movements of pectoral fins. Herein, to identify the key features of labriform locomotion, numerical simulations of a self-propelled biomimetic robotic fish with a Reynolds number (Re) of up to 3 000 000 in the labriform mode are performed. This study includes a detailed analysis of swimming performance and hydrodynamic mechanisms and their connection to three-dimensional vortex dynamics. Compared with the drag-based mode, the fish is observed to cruise faster and swim more smoothly in the lift-based mode. This study also finds that the pectoral fin can produce continuous thrust during one cycle in lift-based mode but can only generate thrust during the power stroke in the drag-based mode. By connecting vortex dynamics and surface pressure, the results show that the leading-edge vortices generated by pectoral fins are associated with most of the thrust production in both motion modes. The analysis of the vortex structure shows that the pectoral fins shed one vortex ring in one cycle of the drag-based mode and two vortex rings in one cycle of the lift-based mode. Our results provide new insights regarding the self-propelled swimming mechanism of biomimetic robotic fish with different labriform propulsion modes. [ABSTRACT FROM AUTHOR]

The occurrence of maize diseases is frequent but challenging to manage. Traditional identification methods have low accuracy and complex model structures with numerous parameters, making them difficult to implement on mobile devices. To address these challenges, this paper proposes a corn leaf disease recognition model SNMPF based on convolutional neural network ShuffleNetV2. In the down-sampling module of the ShuffleNet model, the max pooling layer replaces the deep convolutional layer to perform down-sampling. This improvement helps to extract key features from images, reduce the overfitting of the model, and improve the model's generalization ability. In addition, to enhance the model's ability to express features in complex backgrounds, the Sim AM attention mechanism was introduced. This mechanism enables the model to adaptively adjust focus and pay more attention to local discriminative features. The results on a maize disease image dataset demonstrate that the SNMPF model achieves a recognition accuracy of 98.40%, representing a 4.1 percentage point improvement over the original model, while its size is only 1.56 MB. Compared with existing convolutional neural network models such as EfficientNet, MobileViT, EfficientNetV2, RegNet, and DenseNet, this model offers higher accuracy and a more compact size. As a result, it can automatically detect and classify maize leaf diseases under natural field conditions, boasting high-precision recognition capabilities. Its accurate identification results provide scientific guidance for preventing corn leaf disease and promote the development of precision agriculture. [ABSTRACT FROM AUTHOR]

In maritime engineering, ensuring vessel stability remains a paramount concern. This study investigates the hydrodynamic response of Magnus anti-rolling devices, modeled as swinging or slewing rotating cylinders, under a ship's rolling motion. Through numerical simulations using the overset mesh technique and large eddy simulation, we analyze various parameters, including rolling angles, rotating speeds, and swinging amplitudes. Our findings highlight the importance of considering the ship's degree of freedom as substantial ship rolling significantly affects hydrodynamic coefficients on the rotating cylinder. We observe interesting dynamics during slewing motion, with the cylinder forming a spiral tip vortex. Optimizing the cylinder's rotating speed enhances the lift-to-drag ratio, particularly for small rolling angles. Furthermore, the effective lift generated during swinging motion is lower than during slewing motion, emphasizing the need to optimize the swinging amplitude, which is recommended to be no less than 170°. These insights advance our understanding of Magnus anti-rolling devices and offer practical guidance for improving vessel stability in complex maritime environments. [ABSTRACT FROM AUTHOR]