This paper presents an adaptive gain-scheduled backstepping control U+0028 AGSBC U+0029 scheme for the balance control of an underactuated mechanical power line inspection U+0028 PLI U+0029 robotic system with two degrees of freedom and a single control input. First, a nonlinear dynamic model of the balance adjustment process of the PLI robot is constructed, and then the model is linearized at a nominal equilibrium point to overcome the computational infeasibility of the conventional backstepping technique. Second, to solve generalized stabilization control issue for underactuated systems with multiple equilibrium points, an equilibrium manifold linearized model is developed using a scheduling variable, and then a gain-scheduled backstepping control U+0028 GSBC U+0029 scheme for expanding the operational area of the controlled system is constructed. Finally, an adaptive mechanism is proposed to counteract the impact of external disturbances. The robust stability of the closed-loop system is ensured by Lyapunov theorem. Simulation results demonstrate the effectiveness and high performance of the proposed scheme compared with other control schemes.

In the current paper, the dynamic mechanical properties of sustainable lightweight aggregate concrete (SLAC) were numerically studied with a newly developed mesoscopic model. In the model, a fissure-based filling method was utilized for placing spherical aggregates, in which the aggregate geometric data were collected from specimen cross-profiles. The interfacial transition zone (ITZ) was also created in the meso-scale finite element model. The model was then utilized to simulate the Split Hopkinson Pressure Bar (SHPB) test of SLAC. The results indicated that the waveforms, dynamic compression strength, and strain rate effects obtained from the simulation closely matched the experimental ones, which demonstrated the effectiveness of the established mesoscopic model. The parametric analysis showed that the aggregate content and ITZ thickness had an important effect on the dynamic mechanical behavior of SLAC. It is believed that the current study can provide a valuable reference for the numerical study of the failure mechanism of sustainable lightweight aggregate concrete.

With the rapid development of technology and market environment, e-commerce research is deepening and expanding. This paper takes the new technology marked by big data and artificial intelligence as the main axis, and utilizes the LSTM-ARIMA hybrid model to make real-time prediction of e-commerce merchants' incoming shipments and combines the Kmeans algorithm with Spearman indicators and so on, to improve the depth and breadth of the research. The research results of this paper show that (1) LSTM-ARIMA model is an important tool in the current and future e-commerce field to utilize big data and artificial intelligence technology, and it is an important way to improve the market competitiveness of e-commerce merchants. (2) In the research process, we focus on the optimization of the model and the configuration of the parameters, combining the AIC principle, Adam optimizer, etc., which improves the prediction accuracy of the model and avoids excessive prediction errors. (3) Due to the objectivity of the research, the model itself on the prediction data may lead to the existence of errors, the research conclusions and prediction accuracy are also the later research in this field need to be improved.

To address the impact-induced damage to concrete pile foundations of transmission structures caused by nearby blasting vibrations, this study investigates the dynamic splitting tensile behavior of an environmentally friendly lightweight rubberized concrete—Rubber-Toughened Ceramsite Concrete (RTCC)—under impact loading. Quasi-static tests show that the static splitting tensile strength increases first and then decreases with increasing rubber content, reaching a maximum value of 2.01 MPa at a 20% replacement ratio. Drop-weight impact tests indicate that RTCC20 exhibits the highest peak impact force (42.48 kN) and maximum absorbed energy (43.23 J) within the medium strain-rate range. Split Hopkinson Pressure Bar (SHPB) tests further demonstrate that RTCC20 shows the highest strain-rate sensitivity. Overall, RTCC with 20% rubber content provides the best comprehensive performance, achieving a favorable balance between strength and toughness across the entire strain-rate range. These findings offer experimental support for applying RTCC to blast-vibration-resistant transmission structure foundations.