A study on the influencing factors and related paths of farmer's participation in food safety governance-based on DEMATEL-ISM-MICMAC model.

Farmers' participation in food safety governance is an important part of food safety social co-governance, and the accurate identification of its influencing factors and their related paths is of guiding significance to the scientific decision-making of food safety governance. The system of influencing factors of farmers' participation in food safety governance was constructed from four dimensions, and the influence network of each dimension was revealed by decision laboratory analysis (DEMATEL). The hierarchical structure and correlation path of influencing factors were determined by interpretive structural model (ISM), and the attributes of influencing factors were further classified by cross influence matrix multiplication (MICMAC). The results show that the influencing factors of farmers' participation in food safety governance can be divided into seven levels, among which the level of education and the status of village cadres are the fundamental characteristic factors. The degree of rural informatization, the intensity of government supervision, the promotion of village committees, the response of the government and the degree of disclosure of government information are the deep core factors, and risk cognition, political trust and family eating habits are special factors. Taking the importance and attribute status of farmers' participation in food safety governance into decision-making considerations is of great significance to improve the efficiency of food safety governance.

Extensive removal of thallium by graphene oxide functionalized with aza-crown ether.

Thallium (Tl) is a highly toxic heavy metal, and its pollution and remediation in aquatic environments has attracted considerable attention. To reduce or remove Tl pollution in the environment, various strategies have been applied. Graphene oxide (GO) has abundant oxygen-containing functional groups, indicating its high application potential for pollution remediation via methods involving binding to metal ions or positively charged organic molecules or electrostatic interaction and coordination. However, the adsorption of Tl to GO occurs via physical adsorption, for which the adsorption efficiency is low. Therefore, herein, we report a new method to effectively remove Tl pollution in water. We combined GO with aza-crown ether, which enhanced the electronegativity and ability to bind metal ions. The functionalized graphene oxide (FGO) demonstrated high efficiency through a wide pH gradient of 5-10, with a dominant Tl(i) adsorption capacity (112.21 mg g-1) based on the Langmuir model (pH 9.0, adsorbent concentration of 0.8 g L-1). The adsorption of Tl(i) during removal fit a pseudo-second-order kinetic model well. The mechanisms of Tl removal involve physical and chemical adsorption. In summary, our study provides a new method for the detection and treatment of Tl-containing wastewater by using FGO.