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Research on the lithospheric elastic thickness (Te) of lunar mascon basins can provide a deeper understanding of heterogeneous thermal activity. In this study, we focused on four basins (Moscoviense, Freundlich‐Sharonov, Hertzsprung, and Apollo) located on the far side of the Moon. These basins exhibit a significant variation in admittance and correlation spectra, making it challenging to develop precise fitted models. Based on the global lunar crustal thickness model and mare basalt thickness, we developed a mantle and mare basalt load model to estimate the Te. This small Te (10.1 km) suggests a double impact process or extreme thermal activity caused by volcanism during the formation of the Moscoviense. For the typical highland basins, that is, Freundlich‐Sharonov and Hertzsprung, the Te (∼20 km) corresponds to a minimum heat flux of 34 mW m−2. Considering the additional energy introduced by the impact, this heat flux can be considered as the upper limit for the heat flux of the highland itself during the formation of a mascon basin. For the Apollo basin within the South Pole‐Aitken (SPA) terrane, the Te is 30.7 km. The crust beneath the SPA region is thinned, allowing a greater contribution of stiffer mantle material to the lithosphere, perhaps explaining the higher effective Te. Furthermore, the disparity between the highland and SPA terranes can give rise to their distinct basin formation processes. Impact basins formed within the SPA terrane may have experienced a faster cooling process compared to those formed on the highland terrane following the impact event, leading to a higher Te. Plain Language Summary: The study of impact basins on the far side of the moon not only provides valuable insights into the strength of the early growth stage of the lithosphere but also gives a glimpse into the different thermal evolution histories of the lunar highland and the South Pole‐Aitken (SPA). In this study, we construct a lithospheric load model by incorporating the contributions of both mantle plug and mare basalts. The proposed model is applied to the four typical mascon (mass concentration) basins. The smaller elastic thickness of the Moscoviense basin may be attributed to a double shock process or intense thermal activity. The Nectarian Hertzsprung basin is younger than the Pre‐Nectarian Freundlich‐Sharonov basin on the highland. However, the two basins exhibit similar elastic thickness, indicating that the latter have either a slow cooling rate or rapid completion of the super‐isostatic adjustment process. The difference in elastic thickness between the Apollo and the highland basins such as the Freundlich‐Sharonov and Hertzsprung basins could be attributed to variations in geological composition, density, and porosity between the SPA and the highland terrane. Key Points: The smaller Te of the Moscoviense basin suggests that it might have undergone either a double impact process or intense volcanic activityThe elastic thickness of the typical highland mascon basins is about 20 km, corresponding to a minimum heat flux of 34 mW m−2The mascon basins formed in the SPA terrane and the typical highland terrane may experience distinct post‐impact cooling processes [ABSTRACT FROM AUTHOR]

The bond behavior of CFRP-concrete interface is the analysis foundation for concrete structures with external strengthening CFRP. In the paper, the influences of the thickness of CFRP plate and adhesive layer on interfacial adhesive properties are investigated through the finite element program. The influence rules of the thickness on the interfacial ultimate bearing capacity and the effective bond length are performed. The results show that the thickness of adhesive layer and CFRP plate has a significant effect on the interfacial performance of CFRP-concrete.

In the research, the effects of sea water for mixing, curing on the gain in strength of different grades of concrete was investigated. A total of 192 concrete cubes were tested for their compressive strength. The study shows that sea water affects the rate of gain in strength of concrete when used for mixing or curing. The strength of concrete made by using sea water was observed to be decreased by about 15% as compared to the similar concrete specimens made and cured with fresh water at 90 days. The concrete with higher strength showed poorer resistance against strength deterioration as compared to the lower strength concrete which used sea water for curing. And the concrete made with sea water decreased the stability of concrete properties.

To predict traffic flow under adverse weather, a hybrid deep learning model concerning adverse weather (DLW-Net) is formulated. The DLW-Net model consists of the target and global analysis parts. For the target analysis part, the spatio-temporal characteristics of traffic flow data are analyzed using the convolutional neural network (CNN), the long short-term memory (LSTM) and gated recurrent unit (GRU) neural networks. For the global analysis part, the variation rules of traffic flow and weather data are extracted using the LSTM model. Additionally, the characteristics of traffic flow under normal and adverse weather are also discussed. The developed model is verified using three cases. The results show that traffic volume and speed would reduce under heavy rain compared to normal weather, however, drizzle has little impact on traffic flow patterns; the rules of traffic speed data are disturbed by strong wind; and the DLW-Net model performs best under all the conditions. [ABSTRACT FROM AUTHOR]