Grass carp (Ctenopharyngodon idellus) is an important aquaculture species in China that is affected by serious diseases, especially hemorrhagic disease caused by grass carp reovirus (GCRV). Grass carp have previously shown age-dependent susceptibility to GCRV, however, the mechanism by which this occurs remains poorly understood. Therefore, we performed transcriptome and metabolome sequencing on five-month-old (FMO) and three-year-old (TYO) grass carp to identify the potential mechanism. Viral challenge experiments showed that FMO fish were susceptible, whereas TYO fish were resistant to GCRV. RNA-seq showed that the genes involved in immune response, antigen presentation, and phagocytosis were significantly upregulated in TYO fish before the GCRV infection and at the early stage of infection. Metabolome sequencing showed that most metabolites were upregulated in TYO fish and downregulated in FMO fish after virus infection. Intragroup analysis showed that arachidonic acid metabolism was the most significantly upregulated pathway in TYO fish, whereas choline metabolism in cancer and glycerophospholispid metabolism were significantly downregulated in FMO fish after virus infection. Intergroup comparison revealed that metabolites from carbohydrate, amino acid, glycerophospholipid, and nucleotide metabolism were upregulated in TYO fish when compared with FMO fish. Moreover, the significantly differentially expressed metabolites showed antiviral effects both in vivo and in vitro. Based on these results, we concluded that the immune system and host biosynthesis and metabolism, can explain the age-dependent viral susceptibility in grass carp.

The research on the spatiotemporal changes and driving factors of ecosystems in rapidly urbanizing regions has always been a topic of widespread concern. As the fourth pole of China’s economic development, the research on the Chengdu-Chongqing region has reference significance for the urbanization process of developing countries such as India, Brazil, and South Africa.The normalized difference vegetation index (NDVI) has been widely applied in studies of plant and ecosystem changes. Based on MODIS NDVI data from 2001 to 2020 and meteorological data of the same period, this study reveals the evolution of NDVI in the Chengdu-Chongqing region from three aspects: the spatiotemporal variation characteristics of NDVI, the prediction of future trends in vegetation coverage, and the response of vegetation to climate change and human activities. During the period of plant growth, the mean NDVI achieved a value of 0.78, and the vegetation coverage rate is increasing year by year. According to the Hurst index, the future NDVI in Chengdu-Chongqing region will tend to decrease, and its trend is opposite to that of the past period of time. The Chengdu-Chongqing region vegetation positively affected by human activities is greater than those negatively affected, and in terms of vegetation degradation, the impact of human activities is greater than climate change.

Seepage is one of the main causes of dam accidents, characterized by long latency periods and spatiotemporal randomness. In this study, an innovative combined algorithm model (AT‐LSTM‐CUSUM) is proposed to predict such leakage hazards. First, a long short‐term memory (LSTM) network model based on an attention mechanism is established to focus on key influencing factors in predicting the time series data. Following the time series prediction, an improved Cumulative Sum (CUSUM) change‐point monitoring algorithm is introduced. Within a sliding window period, a control function collects cumulative residuals, and a threshold test is performed to determine whether a potential hazard trend exists. Using monitoring data from a pressure measuring pipe in a concrete dam as the experimental subject, five related influencing factors were collected (upstream and downstream water levels, temperature, precipitation, and structural aging). These data were fed into the AT‐LSTM model for iterative parameter tuning, yielding optimal prediction results. These results were compared with those of the LSTM, GRU, ARIMA, and Prophet models, validating the superior performance of the AT‐LSTM model. In addition, by simulating the seepage hazard occurrence process, the change‐point monitoring effectiveness of the improved CUSUM algorithm was tested. A parameter sensitivity analysis of the window period and threshold values revealed that the algorithm performed effectively in detecting seepage hazards. The innovative algorithm proposed in this paper exhibits strong early warning capabilities and holds significant value for dam safety monitoring and maintenance.

In geotechnical engineering, when the natural soil fails to meet the requirements of engineering projects, the soil is often treated by means of compaction and chemical stabilization. China is the world’s largest producer and consumer of cement, making the use of cement highly cost-effective. A large number of studies on cement-stabilized soil have proven that it has good engineering properties. When using cement stabilization to reinforce soil, compaction is often combined to achieve better results. This paper directly proposes that changes in compaction energy will affect the optimum moisture content (OMC) and maximum dry density (MDD) of cement-stabilized soil. From the perspective of changes in cement content and compaction energy, three levels of compaction energy and five levels of cement content are set to systematically analyze the variation trends of liquid limit, plastic limit, and compaction characteristics of stabilized soil under the combined action of cement stabilization and traditional compaction. The results show that with the increase in the cement content, the modified soil exhibits plasticity over a wide range of moisture content due to an increased liquid limit. When the cement content is high, and the compaction energies is low, the soil shows an uncompacted state. This state will decrease significantly with the increase in compaction energy. Both the OMC and the MDD change with the variation of the compaction energies and the cement content.