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The Big Headed Treefrog, Polypedates megacephalus Hallowell, 1861, is widespread throughout subtropical and tropical regions from northeastern India to South Myanmar. In Vietnam, P. megacephalus is currently known in the North. However, the knowledge about the feeding ecology of this White-lipped Treefrog is still lacking. As a result of our field trips in Son La and Lai Chau provinces, northern Vietnam, this study provides novel data about the feeding ecology of P. megacephalus. We used the stomach-flushing method to obtain the stomach contents of 232 individuals at three sites. A total of 19 prey categories with 415 items were found in the stomachs of P. megacephalus. This species has a wide food spectrum and the dominant prey items of P. megacephalus were Araneae, Opiliones, insect larvae, Blattodea, Coleoptera, Hemiptera, Hymenoptera, Isoptera, and Orthoptera. The importance index for these categories ranged from 1.87% to 31.03%. Orthoptera was the prey category with the highest frequency of occurrence and its representatives were found in 81 stomachs. The result of multiple regression analysis indicated that both snout-vent length and mouth width were associated positively with prey sizes consumed by P. megacephalus.

The quality of machining is dependent on the machine’s dynamic behavior throughout the operating process. Because of the loads or vibration during operation, the rigidity of the machine structure can be reduced. Therefore, the study of advances in the dynamic characteristics has great significance for the development of machine tools, especially for high-speed machines. This paper presents the design and analysis of a rigid gantry structure with a spindle speed in the range of (6.000 ÷ 24.000)rpm, corresponding to the natural frequency of the machine structure more than (100 ÷ 400)Hz. Use CAE (computer-aided engineering) analysis software to analyze the natural frequency of machine structure. The research results show that the machine structure will have good stiffness, high vibration resistance and avoid resonance to achieve the best machining surface. In addition, it is the basis for selection of cutting mode suitable for the machining process in order to improve the reliability and efficiency of work of the machine structure and the accuracy of the processed products.

In this paper, a sliding mode control (SMC) system based on combining chemical reaction optimization (CRO) algorithm with radial basis functional link net (RBFLN) for an n-link robot manipulator is proposed to achieve the high-precision position tracking. In the proposed scheme, a three-layer RBFLN with powerful approximation ability is employed to approximate the uncertainties, such as parameter variations, friction forces, and external disturbances, and to eliminate chattering phenomenon of the SMC. In order to achieve the expected performance in the initial phase as well as the improved convergence rate, the RBFLN parameters need to be optimized in advance. Therefore, the initial parameters of the RBFLN are optimized offline by CRO algorithm instead of random selection. Furthermore, the RBFLN weights are determined online according to adaptive tuning laws in the sense of a projection algorithm and the Lyapunov stability theorem to guarantee the stability and convergence of the system. The simulation results of three-link de-icing robot manipulator (DIRM) are provided to verify the robustness and effectiveness of the proposed methodology.