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ABSTRACTThe carburising tests were carried out at 1100 ℃ for 50 h, 100 h, 150 h and 200 h for a new type of tungsten-aluminium alloyed ethylene cracking furnace tube. The composition, microstructure transformation and performance of furnace tubes were analysed. The results showed that the average carbon content within 1 mm of the inner wall increased with the prolongation of carburising time. The thickness of carburised layer increased from 0.3 mm to 1.5 mm. The carbides in as cast structure were mainly massive (Cr, Fe, W)23C6on the outside and fishbone (Cr, Fe, W)7C3on the inside. During carburising process, the external (Cr, Fe, W)23C6carbides coarsened and transformed into (Cr, Fe)7C3, and then gradually transformed into (Cr, Fe, W)7C3. Carbide coarsening mainly occurred in internal (Cr, Fe, W)7C3during carburising. The carbide precipitation and transformation also led to Vickers hardness value of furnace tube increased.

Burns often cause loss of skin barrier protection, fluid exudation, and local tissue edema, which hinder functional recovery. Effectively improving the quality of deep burn wound healing, shortening the wound healing time, and reducing tissue fluid leakage are urgent problems in the medical field. Human mesenchymal stem cells (MSCs) can effectively stabilize vascular endothelial injury. Fetal dermal MSCs (FDMSCs) are a newly discovered source of MSCs derived from the skin of accidentally aborted fetuses. However, the effect of FDMSCs on vascular permeability remains poorly understood. In this study, conditioned media from FDMSCs (F-CM) extracted from fetal skin tissue was prepared. The effect of F-CM on vascular permeability was evaluated using the internal circulation method FITC-dextran in vivo, and several in vitro assays, including cell viability assay, transwell permeability test, immunofluorescence, and western blotting. Altogether, our results demonstrate that F-CM could inhibit burn-induced microvascular hyperpermeability by increasing the protein expression levels of occludin and VE-cadherin, while restoring the expression of endothelial F-actin, and providing the foundation of a novel therapy for the treatment of burns with F-CM.

The development of full-spectrum photocatalysts active in the near-infrared (NIR) region has gained increasing attention for deleterious pollutant removal. The integration of plasmonic metals with semiconductors is an effective way to widen the light response range of photocatalysts due to the strong light absorption and fast plasmonic energy transfer of the localized surface plasmon resonance (LSPR). In this work, the full-spectrum responsive Bi@SrTiO3was prepared via facile solvothermal chemical reduction. The optimal Bi@SrTiO3achieves exceptional photocatalytic Cr(VI) reduction efficiency and tetracycline degradation, realizing bi-directional promotion effects on redox reaction. According to density functional theory (DFT) simulations, the extraordinary photocatalytic performance is attributed to the tunable built-in electric field (IEF) of the Ohmic contact. The favorable adaptability in real water and high stability of BSTO-25 were proved by experimental results. And the possible photocatalytic mechanism was proposed based on theoretical calculation and experimental results. Furthermore, the non-toxicity of the BSTO-25 was evaluated by E.colicultivation, which further proves the feasibility of treating wastewater with BSTO-25. This work provides a new perspective on constructing full-spectrum-driven photocatalysts for applications dealing with environmental remediation.

Reactive oxygen species are essential in photocatalytic water treatment. In this paper, Gd doped carbon nitride (CN) photocatalysts were prepared by simple thermal polymerization for the photocatalytic degradation of tetracycline under visible light irradiation. The photodegradation rate of 1.0GdCN is as high as 95% in 18 min, and the photocatalytic performance is much higher than that of CN. The improvement of photocatalytic performance is mainly attributed to the fact that Gd ion implantation directly provides active sites for oxygen activation and induces the formation of N vacancies. The results of characterizations show that the introduction of Gd in CN can improve the conversion ability of activated oxygen, carrier separation and energy band structure adjustment. Therefore, 1.0GdCN photocatalyst can be employed for efficient photocatalytic synthesis of tetracycline. Furthermore, three ways of photocatalytic degradation of tetracycline were revealed by high performance liquid chromatography-mass spectrometry. This work provides insights into the doping strategy of CN to improve the production of reactive oxygen species for environmental remediation.

Hierarchical graph neural networks (HGNNs) provide a feasible method for modeling complex spatiotemporal dependencies during mobile traffic forecasting. However, most existing studies have adopted spatial node clustering methods to construct a coarsened graph that overlooks the temporal correlation within the original station graph. Furthermore, existing state-of-the-art methods fail to fully exploit the cross-regional feature impacts on stations, which limits their ability to model nonlocal spatial dependency. To overcome these limitations, we proposed a hierarchical sequence-to-sequence (HSeq2Seq) approach that combines HGNNs with a sequence-to-sequence architecture (Seq2Seq) for mobile traffic forecasting. First, a spatiotemporal node clustering method was designed to construct the hierarchical structure. Second, a convolution encoder was employed to extract the local spatiotemporal features from a hierarchical perspective, and a novel attention-based feature fusion module was built to capture the nonlocal spatiotemporal features by identifying both the intra- and cross-regional feature impacts on the stations. Finally, a recurrent decoder is introduced to reweight the spatiotemporal features and recursively produce the final prediction. Extensive experiments on two real-world datasets demonstrate that our model outperforms state-of-the-art methods, while the ablation study also verifies the effectiveness of the spatiotemporal node clustering and the attention-based feature fusion module. [ABSTRACT FROM AUTHOR]