Preparation of polyvinyl alcohol/graphene oxide composites and their adsorption properties

The polyvinyl alcohol/graphene oxide (PVA/GO) hydrogel was prepared. It was confirmed that the adsorption performance of polyvinyl alcohol/graphene oxide hydrogel composite material was improved, and it does not cause secondary pollution. According to adsorption experiments, it was found that PVA/ GO adsorbent with a content of 30 % graphene oxide has the best comprehensive performance. The suitable environment of adsorption was under 25°C, 12-18 h for adsorption time and acidic conditions. The suitable adsorbent dosage was 0.3g and the suitable concentration of the dye was 10 mg/LThe authors gratefully acknowledge the financial support of the Shaoxing Public Welfare Project (Grant No. 2017B70042), and the International Science and Technology Cooperation Project of Shaoxing University (Grant No. 2019LGGH1004)Postprint (published version

Properties of Graphene Oxide/Epoxy Resin Composites

The graphene oxide (GO) was obtained by pressurized oxidation method using natural graphite as raw materials. Then the GO/epoxy resin composites were prepared by casting. The mechanical and damping properties of composites were studied. As a result, the impact intensity of GO/epoxy resin composites was prominently improved with the content of the graphene oxide increasing. The glass transition temperature decreased and the damping capacity is improved

Aggregate-Breaking Mechanism Response to Polyacrylamide Application of Purple Soils in Southwestern China Using Le Bissonnais Method

Polyacrylamide (PAM) is a water-soluble polymer with strong cohesiveness and a strong water absorption capacity, and it has been widely used to modify soil structural stability. However, little information is available on the impact of PAM application on the aggregate-breaking process of purple soils in hilly areas of southwestern China. Therefore, the current study aimed to examine the influence of PAM application on the aggregate stability of purple soil in terms of different breakdown mechanisms at different hillslope locations. Three disruptive tests employing the Le Bissonnais method (FW, fast-wetting sieving; SW, slow-wetting sieving; and WS, wet-stirring sieving) were used to determine the mean weight diameter (MWD), geometric mean diameter (GMD), and mass fractal dimension (D) of the soil aggregates, and soil erodibility factor (K) was calculated as an index of soil anti-erodibility. Overall, the major aggregate-breaking mechanism for purple soils was the following: SW (differential swelling) > WS (mechanical breakdown) > FW (slaking). The content of water-stable aggregates (>0.25 mm) obviously rose after PAM application, with the most significant influences shown under FW. A significant difference in MWD was observed between PAM application and without polyacrylamide application (CK) under WS (p p < 0.05) under FW and SW. In comparison with CK, D value in PAM under FW and SW was significantly reduced, mainly at the slope locations of 0 and 20 m. A descending order of FW, WS, and SW was found on the basis of K value at different slope locations. These findings contribute to improved understanding of proper application of soil amendments to control soil and water loss in purple soils

The Relationship between Urbanization and the Water Environment in the Chengdu-Chongqing Urban Agglomeration

Ensuring the harmonization between urbanization and water environment systems is imperative for fostering sustainable regional development in the future. With urban agglomerations and metropolitan areas increasingly dominating urbanization trends in China, it is crucial to explore the interdependent relationship between urbanization and the water environment. Such exploration holds significant implications for water resource management and the formulation of urbanization policies. This study utilizes a comprehensive index system encompassing urbanization and the water environment. It examines the coupled and coordinated spatial and temporal dynamics of these systems within the Chengdu-Chongqing Urban Agglomeration from 2011 to 2019. This analysis employs the Coupled Coordination Degree model alongside the spatial autocorrelation model. The results show that there is still much room for improving the urbanization development level and the water environment quality. During the study period, a nonlinear and nearly U-shaped evolutionary trajectory was observed between the two systems. The results suggest that there is a progression from basic to more advanced coordination between urbanization and water environment at the city cluster scale. Urbanization appears to generally lag behind the water environment in terms of coordination. At the municipal scale, there is a gradient in which some cities show better coordination compared to others. Spatially, the coupling and coordination of this region exhibited dual-core development characteristics centered around Chengdu and Chongqing. The region is in the transition stage towards a core-type networked and decentralized development mode, which has not yet formed an integrated pattern. This offers a theoretical and technical framework for harmonizing water environments and urbanization in similar regions globally

Transmission Line Segmentation Solutions for UAV Aerial Photography Based on Improved UNet

The accurate and efficient detection of power lines and towers in aerial drone images with complex backgrounds is crucial for the safety of power grid operations and low-altitude drone flights. In this paper, we propose a new method that enhances the deep learning segmentation model UNet algorithm called TLSUNet. We enhance the UNet algorithm by using a lightweight backbone structure to extract the features and then reconstructing them with contextual information features. In this network model, to reduce its parameters and computational complexity, we adopt DFC-GhostNet (Dubbed Full Connected) as the backbone feature extraction network, which is composed of the DFC-GhostBottleneck structure and uses asymmetric convolution to capture long-distance targets in transmission lines, thus enhancing the model’s extraction capability. Additionally, we design a hybrid feature extraction module based on convolution and a transformer to refine deep semantic features and improve the model’s ability to locate towers and transmission lines in complex environments. Finally, we adopt the up-sampling operator CARAFE (Content-Aware Re-Assembly of FEature) to improve segmentation accuracy by enhancing target restoration using contextual neighborhood pixel information correlation under feature decoding. Our experiments on public aerial photography datasets demonstrate that the improved model requires only 8.3% of the original model’s computational effort and has only 21.4% of the original model’s parameters, while achieving a reduction in inference speed delay by 0.012 s. The segmentation metrics also showed significant improvements, with the mIOU improving from 79.75% to 86.46% and the mDice improving from 87.83% to 92.40%. These results confirm the effectiveness of our proposed method

Multi-Scale Correlation between Soil Loss and Natural Rainfall on Sloping Farmland Using the Hilbert–Huang Transform in Southwestern China

The Hilbert–Huang transform (HHT) has been used as a powerful tool for analyzing nonlinear and nonstationary time series. Soil loss is controlled by complicated physical processes and thus fluctuates with nonlinearity and nonstationarity over time. In order to further clarify the relationship between rainfall, surface runoff, and sediment yield, this study adopted the HHT to analyze these characteristics through multiple time scales and investigated their relationship through time-dependent intrinsic correlation (TDIC) in the time series. A six-year study (2015–2020) was conducted on sloping farmlands to explore the relationships between soil loss and rainfall in southwest China. Time series of soil loss and rainfall were identified as the relevant characteristics at different time scales based on the method of HHT. Local correlation between the soil loss and runoff was carried out by the method of TDIC. The original time series of the rainfall, runoff, and soil loss were decomposed into eight intrinsic mode functions (IMFs) and a residue by ensemble empirical mode decomposition (EEMD). The residue indicated that the rainfall and runoff increased and then decreased during the maize-growing season from 2015 to 2020, whereas the soil loss gradually decreased. IMF1 and IMF2 accounted for nearly 80% of the temporal variations in rainfall, runoff, and soil loss, indicating that the variables varied the most at short time scales. The TDIC analysis showed that strong and positive correlations between the soil loss, rainfall, and runoff prevailed over the entire time domain at the scales of IMF1 and IMF2, indicating the rapid response of the soil loss to rainfall and runoff at short time scales. Time-varying correlations were observed at the IMF3–IMF5 scales. At the IMF7 scale, an evident switchover in the nature of the correlation was identified during the years 2018 and 2019; this could be related to a sudden rainstorm under low vegetation coverage conditions. The EEMD-based TDIC tool is an effective means to clarify the relationship between soil loss, rainfall, and runoff. Our results provide a better understanding of the relationship between soil loss and rainfall varied with time at multiple time scales. Short-term heavy rainfall and rapid surface runoff are the important factors causing serious soil and water loss on a short time scale in a mountainous region with yellow soil, which is of great significance for the construction of a regional soil erosion prediction model

Discovery of Anti-Inflammatory Triterpenoid Glucosides from the <i>Heritiera littoralis</i> Dryand

Two new triterpenoid glucosides, Heritiera A (1) and Heritiera B (2), and six known triterpenoid analogs (3–8) were isolated from Heritiera littoralis Dryand. Their structures were identified by comprehensive spectroscopic analyses and comparisons with the literature. The anti-inflammatory activity of the isolates from H. littoralis was evaluated using a lipopolysaccharide (LPS) stimulated RAW 264.7 cells model. The result showed that four triterpenoids exhibited potent anti-inflammatory activity. Among these compounds, compound 2 substantially inhibits the release of nitric oxide (NO) with an IC50 value of 10.33 μM. The triterpenoids from H. littoralis could be used as potential candidates for the development of new anti-inflammatory agents

Laboratory-Scaled Investigation into Combined Impacts of Temporal Rainfall Patterns and Intensive Tillage on Soil and Water Loss

Many studies have focused on the impacts of rainfall duration and intensity, while overlooking the role of rainfall patterns on intensive tillage erosion in hilly agricultural landscapes. The objective of this study was to determine the combined effects of rainfall patterns and tillage erosion on surface runoff and soil loss on sloping farmland in the purple soil area of China. Five simulated rainfall patterns (constant, rising, falling, rising–falling, and falling–rising) with the same total precipitation were designed, and the intensive tillage treatment (IT) and no-tillage treatment (NT) were subjected to simulated rainfall using rectangular steel tanks (2 m × 5 m) with a slope of 15°. To analyse the differences in the hydrological characteristics induced by tillage erosion, we calculated the flow velocity (V), Reynolds number (Re), Froude number (Fr), and Darcy–Weisbach resistance coefficient (f). The results indicate that significant differences in surface runoff and sediment yield were found among different rainfall patterns and rainfall stages (p f varied from 0.30 to 9.05 for the IT and 0.48 to 11.57 for the NT and exhibited an approximately inverse trend to V and Fr over the course of the rainfall events. Compared with the NT, the mean sediment yield rates from the IT increased the dynamic range of 8.34–16.21% among the different rainfall patterns. The net contributions of the IT ranged from 2.77% to 46.39% in terms of surface runoff and 10.14–78.95% in terms of sediment yield on sloping farmland. The surface runoff and sediment yield were positively correlated with rainfall intensity, V, and Fr, but negatively correlated with f irrespective of tillage operation (p < 0.05). The results showed that the tillage erosion effects on soil and water loss were closely related to rainfall patterns in hilly agricultural landscapes. Our study not only sheds light on the mechanism of tillage erosion and rainfall erosion but also provides useful insights for developing tillage water erosion prediction models to evaluate soil and water loss on cultivated hillslopes