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During the last 10-15 years the question about food safety has increasingly been a topic of great concern nationally and internationally. Traditionally there has been a conflict of interest between the developed countries with higher food safety standards and the developing countries with lower food safety rules. As long as adequate international rules persist the view of standards as barriers should be replaced by the view of standards as catalysts for increased food quality. This article looks at the food safety issue in China, the largest developing country. The Chinese exports of food products have been confronted with trade restrictions because the products did not comply with the high food standards in the USA, the EU and Japan. These difficulties have contributed to a greater concern in China about the quality of the food products. In the last ten years a series of changes in the rules and in the administration have taken place. It is a complicated task because it touches the whole food chain. The article tries to cast light on these important questions. What have been the consequences of inadequate food safety regulations in China? What have been done until now to improve the food quality standards in China? What further initiatives should be taken to improve the situation in the future?

Ternary gold alloys (TGAs) are highly regarded for their excellent electrical properties. Electrical resistivity is a crucial indicator for evaluating the electrical performance of TGAs. To explore new promising TGAs with lower resistivity, we developed a reverse design approach integrating machine learning techniques and proactive searching progress (PSP) method. Compared with other models, the support vector regression (SVR) was determined to be the most optimal model for resistivity prediction. The training and test sets yielded R2 values of 0.73 and 0.77, respectively. The model interpretation indicated that lower electrical resistivity was associated with the following conditions: a van der Waals Radius (Vrt) of 0, a Vr (another van der Waals Radius) of less than 217, and a mass attenuation coefficient of MoKα (Macm) greater than 77.5 cm2g−1. Applying the PSP method, we successfully identified eight candidates whose resistivity was lower than that of the sample with the lowest resistivity in the dataset by more than 53–60%, e.g., Au1.000Cu4.406Pt1.833 and Au1.000Pt2.232In1.502. Finally, the candidates were validated to possess low resistivity through the pattern recognition method. [ABSTRACT FROM AUTHOR]

As machine learning (ML) continues to advance in the field of materials science, the variation in strategies for the same steps of the ML workflow becomes increasingly significant. These details can have a substantial impact on results, yet they have not received the deserved attention. This review aims to explore the various strategies available for each detail within the general workflow of materials ML. Firstly, the general workflow of materials ML will be introduced to help readers gain an understanding of potential details. Subsequently, different strategies of details within each step of the workflow will be presented through state-of-the-art case studies. The potential outcomes associated with choosing different strategies to details will be explored. Following this, suitable strategies for details will be recommended based on distinct application scenarios. Finally, directions for the future development of materials ML concerning details will be proposed. Through these discussions, we aspire to offer a comprehensive understanding of the nuances in details within materials ML. This will serve as valuable reference and guidance for researchers in both materials science and ML. [ABSTRACT FROM AUTHOR]

Urbanization precipitates substantial economic transformations, with housing markets playing a pivotal role. The expansion of cities escalates housing demand, subsequently increasing housing debt, which is a crucial factor influencing household consumption. This study utilizes data from six rounds of the China Family Panel Studies (CFPS) spanning 2010 to 2020 to investigate the impact of housing debt on household consumption in urban China. Given the dynamics changes in housing debt status, as well as the endogeneity problems caused by reverse causality and selection bias between households' debt decisions and consumption behavior, this study employs both the difference-in differences with multiple periods and groups ( D I D M ) model and the two-way fixed effects model. The results show that the average consumption expenditure of households with housing debt is 14% higher than those without. A 1% increase in housing debt size correlates with a 0.011% rise in consumption. Moreover, this positive effect is more pronounced among low-income households and those with older household heads, as well as those owning multiple properties. Compared to non-durable consumption, the impact of housing debt is more substantial on durable consumption. Further mechanism analysis reveals that the effect of housing debt on household consumption is primarily driven by an increase in housing assets, spurred by the rising housing prices. This study underscores the importance of integrating housing debt management within the framework of sustainable urban development, which not only ensures equitable access to housing but also fosters the promotion of sustainable consumption. [ABSTRACT FROM AUTHOR]