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Photocatalytic technology, which is regarded as a green route to transform solar energy into chemical fuels, plays an important role in the fields of energy and environmental protection. An emerging S-scheme heterojunction with the tightly coupled interface, whose photocatalytic efficiency exceeds those of conventional type II and Z-scheme photocatalysts, has received much attention due to its rapid charge carrier separation and strong redox capacity. This review provides a systematic description of S-scheme heterojunction in the photocatalysis, including its development, reaction mechanisms, preparation, and characterization methods. In addition, S-scheme photocatalysts for CO2 reduction are described in detail by categorizing them as 0D/1D, 0D/2D, 0D/3D, 2D/2D, and 2D/3D. Finally, some defects of S-scheme heterojunctions are pointed out, and the future development of S-scheme heterojunctions is proposed. [ABSTRACT FROM AUTHOR]

[Objective] Fan deltas are widely developed in the margins and interior of sedimentary basins, with a large scale, diverse types, and idea source-reservoir-caprock association, and have huge exploration potential for oil and gas resources. However, its fluid type transition and controlling factors, sedimentary process and characteristics of the fan deltas are still unclear. [Methods] Taking the Xiligou fan delta in Qinghai Province as the research object, based on the fine description of outcrop and trench profiles, the characteristics of grain size, structural characteris-tics of sediments in the Xiligou fan delta during different periods were studied by comprehensive use of 14C dating and grain size analysis. [Results and Conclusions] Through the fine description of the field outcrop trough section, 9 types of lithofacies and 7 vertical combination sequences are divided, and 3 types of fluid types including debris flow, sheet flood and traction flow are identified. According to AMS14C dating, the Xiligou Lake delta is divided into three stages, SI, SII, and SIII by calibrating the characteristics of the sedimentary interface, sediment grain size, and structure. The SI stage is a coarse-grained sedimentary stage of clastic flow, and the SII stage is the deposition of sheet-flood reformation. Stage SIII is the period of traction flow reformation and deposition. Based on the analysis of sedimentary particle size-sensitive components, three lobe stages were identified in the delta plane of Xiligou Lake. A comprehensive analysis of the Xiligou delta slopes and the changes in the sporopollenin concentration in Qinghai Lake since 15 ka shows that the fuid type conversion of the Xiligou fan delta is controlled by the changes in the sedimentary slope and climate. The debris flow channel and sheet flooding sediments are the main architectural units. The lower plain of the fan delta was dominated by sheet flooding, and braided channels, braided bar, and flood-diffusion sediments were the main architectural units. The front of the fan delta was dominated by traction flow, and the main architectural units were subaqueous distributary channels, mouth bars, and sheet sands. [ABSTRACT FROM AUTHOR]

Nowadays, deep representations have gained significant attention due to their outstanding performance in a wide range of tasks. However, the interpretability of deep representations in specific applications poses a significant challenge. For instances where the generated quantity matrices exhibit symmetry, this paper introduces a variant of deep matrix factorization (deep MF) called deep L p smooth symmetric non-negative matrix factorization (DSSNMF), which aims to improve the extraction of clustering structures inherent in complex hierarchical and graphical representations in high-dimensional datasets by improving the sparsity of the factor matrices. We successfully applied DSSNMF to synthetic datasets as well as datasets related to post-traumatic stress disorder (PTSD) to extract several hierarchical communities. Specifically, we identified non-disjoint communities within the partial correlation networks of PTSD psychiatric symptoms, resulting in highly meaningful clinical interpretations. Numerical experiments demonstrate the promising applications of DSSNMF in fields like network analysis and medicine. [ABSTRACT FROM AUTHOR]