The wide use of disinfectants has prompted resistance from the microbiome which will in turn reduce the bactericidal effect of disinfectants. Hence, glutaraldehyde (GA) and didecyldimethylammonium bromide (DDAB) were used to develop a combination disinfectant with high stability and antimicrobial effects, which was named GA-DDAB combination disinfectant (GD). The bactericidal mechanism against Escherichia coli was studied in our earlier work. In this study, we focused on GD's bactericidal efficacy in both the laboratory and environment, the genetic toxicity to mouse lymphoma L5178Y TK+/− cells, acute peroral toxicity in mice, and its metal corrosion properties with a view to providing theoretical support for developing a high-efficiency, low toxicity, and weakly corrosive disinfectant for general use.

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The excessive use of cultivated land for non-grain production activities is considered a threat to grain security. This study presents an analysis framework on unraveling the causal mechanisms for non-grain production of cultivated land. We apply the analysis framework in Liyang, which is located in the Yangtze River Delta and is also an important “national grain base” county of China. We first determine four non-grain production categories as immediately recoverable (IMR), simple-engineering recoverable (SER), engineering recoverable (ENR), and irrecoverable (IR) based on the effect of non-grain activities on the degree of soil damage of the cultivated land, especially the difficulty of restoring the capacity for grain production. Then, we analyze the spatial pattern features for non-grain production of four given categories at the village scale. Furthermore, we reveal the mechanisms of the four categories using multiple linear regression modeling with geophysical, demographic, economic, and policy variables. The results show that the total non-grain area of cultivated land in Liyang is 28,158.38 hectares, and the non-grain rate is 48.09%, ranging from 10.59% to 96.75% among villages. The IMR, SER, ER, and IR rates are 11.81%, 17.76%, 15.07%, and 3.45%, respectively. There is also a significant neighborhood effect among the four categories, indicating that non-grain production activities have a stimulating effect on the surrounding operators of cultivated land. Farming conditions such as the proportion of irrigated farmland and economic variables such as the tourism scale have stronger effects on non-grain production than demographic variables. Policy variables, especially the cultivated land transfer policy, neither inhibit nor promote non-grain production. Based on these findings, we make policy suggestions for reducing non-grain production activities and protecting cultivated land. This analysis framework contributes to a new perspective for unraveling the causal mechanisms and making categorical governance decisions of non-grain production on cultivated land at the village level.

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