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Climate change in agriculture has important impacts on human life and health, so it is crucial to explore the process of carbon peaking in China's agricultural resource inputs and to provide data support for greenhouse gas (GHG) emission reduction in agriculture. The LMDI model and Tapio decoupling model were used in this study, and the interrelationship between carbon emissions from agricultural resource inputs and agricultural output was analyzed deeply. Meanwhile, global and local Moran's I indices were introduced to further analyze the degree of spatially significant correlation. The results showed that China's total agricultural carbon emissions from 2003 to 2021 showed an"inverted U-shaped"curve, indicating a first growth and then a downward trend, and reached a peak in 2015. Carbon emissions in east China have always been in the first place, followed by central China. However, the Northwest region, which has the lowest carbon emissions among the seven regions, has risen significantly to become the third largest source of agricultural carbon emissions by 2021. The use of fertilizers was the major factor contributing to agricultural carbon emissions, with an average annual contribution of 58%. while pesticides, agricultural films and diesel use were secondary factors. The global Moran' s I index showed significant spatial correlation in agricultural carbon emissions, but the degree of spatial aggregation gradually weakened over time. The local Moran' s I showed that the high-high aggregation was mainly concentrated in east China and central China. According to the results of the LMDI model, agricultural production efficiency, regional industrial structure, and the size of the agricultural labor force play an inhibitory role in the growth of agricultural carbon emissions, of which agricultural production efficiency is the main inhibitory factor, with an annual average emission reduction of 6.475 7 million tons. Agricultural industrial structure, the level of regional economic development, and the level of urbanization, on the other hand, promote the growth of agricultural carbon emissions, and the level of regional economic development is the main factor that promotes the growth of agricultural carbon emissions, with an annual average of about 8.91 million tons. The Tapio decoupling model showed that all regions achieved strong decoupling after 2016, and that agricultural economic growth was accompanied by a reduction in agricultural carbon emissions, which reached a desirable state, indicating that the effect of emission reduction after 2016 was significant. [ABSTRACT FROM AUTHOR]

The water quality of sources in the Huaihe River Basin significantly affects the lives and health of approximately 16.7% of China's population. Identifying and quantifying pollution sources and risks is essential for effective water resource management. This study utilized Monte Carlo simulations and Geodetector to assess water quality and eutrophication, as well as to evaluate the sources of heavy metals and the associated health risks for both adults and children. The results showed that eutrophication of water sources in Huaihe River was severe, with an overall EI value of 37.92; 67.8% of the water sources were classified as mesotrophic and 32.2% classified as eutrophic. Water quality and eutrophication levels in the southern mountainous regions were better than those in the densely populated northern areas. Adults were found to have a higher carcinogenic risk than children, whereas children faced a higher noncarcinogenic risk than adults. Cr presented the highest carcinogenic risk, affecting more than 99.8% of both adults and children at levels above 1 × 10−6 but not exceeding 1 × 10−4. The noncarcinogenic risk from metals did not surpass a level of 1, except for Pb. As was primarily influenced by agricultural activities and transportation, whereas Cd, Cr, and Pb were mainly affected by industrial activities, particularly in local textile industries such as knitting and clothing manufacturing. The analysis demonstrated that the influence of anthropogenic factors on heavy metal distribution was significantly enhanced by indirect natural factors. For example, the explanatory power of Precipitation and Road Network Density on As was 0.362 and 0.189, respectively, whereas their interaction had an explanatory power as high as 0.673. This study indicates that the geodetector method is effective in elucidating the factors influencing heavy metal distribution in water, thereby providing valuable insights into pollution sources in global drinking water. [ABSTRACT FROM AUTHOR]

Lactate, once recognized as a wasty product from anaerobic glycolysis, is proved to be a pivotal signal molecule. Lactate accumulation occurs in diverse physiological and pathological settings due to the imbalance between lactate production and clearance. Under the condition with drastic changes in local microenvironment, such as tumorigenesis, inflammation, and microbial infection, the glycolysis turns to be active in surrounding cells leading to increased lactate release. Meanwhile, lactate can be utilized by these cells as an energy substrate and acts as a signal molecule to regulate cell functions through receptor‐dependent or independent pathways. In this review, we tended to tease out the contribution of lactate in tumor progression and immunomodulation. And we also discussed the accessory role of lactate, beyond as the energy source only, in the growth of invading pathogens. [ABSTRACT FROM AUTHOR]

In order to find out how big on earth the capacity of the senior tourism market, firstly this paper listed and inducted all the elements involved in the tourism market and then made mathematical analysis on the connections among different elements. Of those elements, purchasing power is considered as a key one. So in order to minimize the effect of uncertainties during the process of building model, linear regression model and ARIMA model were built specifically to analyze and predict the purchasing power. Then based on analysis the senior tourism market capacity model was built. Finally, through the analysis and fitting of authoritative data, the predicative value of the gross senior tourism market capacity and different segment markets in the next five years was worked out. [ABSTRACT FROM AUTHOR]