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Abstract In this study, to achieve accurate tracking of the desired trajectory during passive control of the lower limb rehabilitation robot, an adaptive sliding mode controller based on disturbance observer and radial basis function neural network (RBFNN) is proposed for the lower limb rehabilitative robot in the presence of uncertain parameters and external bounded disturbances. First, the Euler–Lagrange dynamic model of the lower limb rehabilitative robot is described. Second, a sliding mode controller is designed to stabilize the system with an improved sliding mode reach rate under the assumption that all parameters of the dynamics model are known. To achieve a sliding mode controller without the above assumptions, the proposed adaptive RBFNN and the disturbance observers are employed to compensate for disturbances and the uncertainties in the robot's dynamic mode via feedforward loops. The Lyapunov stability theory is used to prove that the proposed controller has accomplished a significant control effect with excellent performance and the output tracking error can be converted to a very small neighborhood through reasonable design parameters. Finally, the performance of the controller based on the state feedback and state observer are demonstrated by numerical simulations, respectively.

Abstract Efficient photocatalytic reduction of CO2 to high‐calorific‐value CH4, an ideal target product, is a blueprint for C1 industry relevance and carbon neutrality, but it also faces great challenges. Herein, we demonstrate unprecedented hybrid SiC photocatalysts modified by Fe‐based cocatalyst, which are prepared via a facile impregnation‐reduction method, featuring an optimized local electronic structure. It exhibits a superior photocatalytic carbon‐based products yield of 30.0 µmol g−1 h−1 and achieves a record CH4 selectivity of up to 94.3%, which highlights the effectiveness of electron‐rich Fe cocatalyst for boosting photocatalytic performance and selectivity. Specifically, the synergistic effects of directional migration of photogenerated electrons and strong π‐back bonding on low‐valence Fe effectively strengthen the adsorption and activation of reactants and intermediates in the CO2 → CH4 pathway. This study inspires an effective strategy for enhancing the multielectron reduction capacity of semiconductor photocatalysts with low‐cost Fe instead of noble metals as cocatalysts.

Abstract In this study, we investigated the nephroprotective effects of Umbelliferone (UMB) against cisplatin‐induced acute kidney injury (AKI). C57BL/6J mice were treated with cisplatin via a single intraperitoneal injection (25 mg/kg) with or without UMB (40 mg/kg/day) by gavage. Renal function, apoptosis, oxidative stress, inflammation, and mitochondrial function were analyzed to evaluate kidney injury. In vitro, human proximal tubule epithelial cells were treated with cisplatin, with or without UMB, for 24 h. Western blotting and immunohistochemistry were performed to explore the mechanisms underlying the nephroprotective effects of UMB. Cisplatin‐induced renal dysfunction, including increases in blood urea nitrogen, serum creatinine, and renal tubular injury indices (NGAL and KIM‐1), were significantly attenuated by UMB treatment, along with renal phenotypic changes and renal tubular injury, as evidenced by improved renal histology. Moreover, NRF2 was activated by UMB pretreatment, along with the inhibition of oxidative stress and inflammatory response, as evidenced by decreased levels of antioxidant genes and inflammatory cytokines in cisplatin‐induced AKI. Our results demonstrate that UMB can protect against cisplatin‐induced nephrotoxicity, which is mediated by the NRF2 signaling pathway via antioxidant and anti‐inflammatory activities, suggesting the clinical potential of UMB for the treatment of AKI.