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The article focuses on the limitations of current reinforcement learning-based sequential recommendation models, which fail to utilize supervision signals and auxiliary information, leading to slow convergence and limited exploration of user preferences. It mentions to overcome these challenges, the authors propose MELOD, a multiplex information-guided RL model, incorporating Teach and Explore components to accurately capture user preferences.

Selective oxidation of hydrocarbons using molecular oxygen as sole oxidant under mild conditions remains a challenging task. In this context, metal‐organic frameworks (MOFs) have been widely used in various oxidation reactions due to their porosity, high surface area and designability. However, the slow diffusion of substrates/products in micropores of three‐dimensional (3D) bulk MOFs hinders the efficient catalytic performance of such materials. Herein an ultrathin two‐dimensional (2D) porphyrin‐based Zr‐MOF nanosheet (Zr‐TCPP) is synthesized through modulator‐control strategy. Subsequently, various metal ions are anchored into the porphyrin ring by post synthesis modification to afford a series of 2D Zr‐TCPP(M) (M=Mn, Fe, Co, Ni, Cu and Zn). Various structural characterization techniques indicate Zr‐TCPP(M) is nanoflower structure with ultrathin nanoplate petals which provides fully exposed accessible active sites. Among them, Zr‐TCPP(Fe) shows excellent catalytic performance in styrene epoxidation reactions and benzylic C−H oxidation reactions using O2 as sole oxidant under ambient temperature and pressure. The remarkable activity arises from high density of exposed porphyrin‐Fe active sites, low diffusion barriers for substrates and products, as well as a similar homogeneous reaction space. Furthermore, Zr‐TCPP(Fe) nanosheet is easily recycled by centrifugation and reused at least five times without significant loss of catalytic activity. [ABSTRACT FROM AUTHOR]

Rapid global changes since the last deglaciation can be well documented in marginal sea sediments, while isolating individual paleoenvironmental signals is still challenging. Here, we identified magnetic minerals and unmixed their variations in sediments from the northwestern South China Sea to decipher environmental variations since the last deglaciation. The variation in the hematite to goethite ratio indicates a relatively drier mid‐Holocene and a wetter early and late Holocene in the Red River catchment. The position shift and intensity variation of Western Pacific Subtropical High may account for the Holocene precipitation changes. A higher chemical weathering intensity accompanied by a relatively more fine‐grained magnetite input during the last deglaciation suggests decoupling of the Asian Summer Monsoon and chemical weathering in the catchment, which might have been caused by the shelf exposure during the deglaciation. In addition, the relative abundance of biogenic magnetite increased with the sea level and possible deep‐water temperature rise. Therefore, magnetic minerals such as hematite, goethite, detrital and biogenic magnetite are markedly potential fingerprints for continent‐ocean environmental changes. Plain Language Summary: The global climate, which has changed rapidly since the last deglaciation, has been recorded by marginal sea sediments. However, the mixing of environmental factors renders it difficult to isolate individual information. Here, we unmixed the magnetic mineralogical signals of sediments from the northwestern South China Sea since the last deglaciation. We found that a higher hematite to goethite ratio (Hm/Gt) in our core represents higher precipitation in Red River catchment. The Hm/Gt variation indicates a relatively drier mid‐Holocene and a wetter early and late‐Holocene in the Red River catchment, which is consistent with the precipitation records in Southern China but opposite to that of Northern China. The chemical weathering of the Red River catchment was decoupled from the Asian Summer Monsoon, exhibiting a higher weathering extent (more fine‐grained magnetite was generated) during the last deglaciation due to secondary weathering on the continental shelf. Moreover, the relative abundance of magnetofossils in our core was consistent with changes of the sea level and deep‐water environments. Therefore, the isolation of magnetic mineral information from marginal sea sediments can help to reconstruct the continent‐ocean environmental changes. Key Points: A drier mid‐Holocene and wetter late‐Holocene occurred in Red River catchment controlled by the shift of Western Pacific Subtropical HighA decoupling between chemical weathering in Red River catchment and summer monsoon was caused by shelf exposure during the deglaciationThe relative content of magnetofossils in northwestern South China Sea is controlled by the sea level and deep‐water environment changes [ABSTRACT FROM AUTHOR]

The Harris Hawks Optimization algorithm (HHO) is a sophisticated metaheuristic technique that draws inspiration from the hunting process of Harris hawks, which has gained attention in recent years. However, despite its promising features, the algorithm exhibits certain limitations, including the tendency to converge to local optima and a relatively slow convergence speed. In this paper, we propose the multi-strategy improved HHO algorithm (MSI-HHO) as an enhancement to the standard HHO algorithm, which adopts three strategies to improve its performance, namely, inverted S-shaped escape energy, a stochastic learning mechanism based on Gaussian mutation, and refracted opposition-based learning. At the same time, we conduct a comprehensive comparison between our proposed MSI-HHO algorithm with the standard HHO algorithm and five other well-known metaheuristic optimization algorithms. Extensive simulation experiments are conducted on both the 23 classical benchmark functions and the IEEE CEC 2020 benchmark functions. Then, the results of the non-parametric tests indicate that the MSI-HHO algorithm outperforms six other comparative algorithms at a significance level of 0.05 or greater. Additionally, the visualization analysis demonstrates the superior convergence speed and accuracy of the MSI-HHO algorithm, providing evidence of its robust performance. [ABSTRACT FROM AUTHOR]