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With the rising labor costs and increasing resource and environmental constraints in China, coupled with geopolitical conflicts, related industries or production processes are shifting to emerging economies such as Southeast Asia, South Asia, and Mexico. Among these, India's development potential has garnered significant attention, and the "China-to-India Industrial Transfer Model" in the global industrial chain poses a greater impact and threat to China. This paper constructs a quantitative model to measure the impact of industrial transfer on the home country. It designs three scenarios-ultra-long-term, medium-to-long-term, and short-to-medium- term-and uses counterfactual analysis to assess the impact of India's absorption of China's industrial transfer on China's GDP and employment under different scenarios. The research results indicate that the transfer of industries from China to India will generate significant socio-economic shocks. In the ultra-long-term, this industrial transfer could lead to a 15.6% reduction in China's GDP, a 16.8% decrease in the overall income of the workforce, and a reduction in the number of employed people by 110 million. The impacts are also substantial in the medium- to-long-term and short-to-medium-term scenarios. By sectors, the relocation of low and medium-low R&D intensity manufacturing sectors has a significant impact on the Chinese economy in both the short-to-medium and medium-to-long term perspectives. The relocation of high R&D intensity manufacturing sectors, represented by the computer industry, also causes considerable negative effects on the Chinese economy in the ultra-long-term perspective. This quantitative analysis helps anticipate the economic impact of future changes in industrial layout on China's economy and facilitates the development of preemptive strategies. Based on the medium-to-long-term international economic outlook and the characteristics of domestic regional and industrial economic development, we propose three policy implications. [ABSTRACT FROM AUTHOR]

This paper proposes a novel kernel‐based generalized random interval multilayer perceptron (KG‐iMLP) method for predicting high‐volatility interval‐valued returns of crude oil. The KG‐iMLP model is constructed by utilizing the DK distance based on a kernel function, which outperforms the conventional Euclidean distance. Additionally, the optimal kernel function is estimated using the variance–covariance matrix of the prediction error, contributing to a better understanding of the overall characteristics of interval‐valued data. The introduction of the kernel function renders the algorithms used for estimating machine learning parameters ineffective. Therefore, this paper further proposes a backward DK distance of accumulative error propagation algorithm to estimate both the kernel function and model parameters, which provides a feasible approach for utilizing kernel function in interval neural networks. In the empirical analysis of weekly and daily returns of WTI crude oil, the superior predictive performance of the proposed method is demonstrated, enabling stable and accurate predictions for both point values and interval values. The model exhibits consistent outstanding performance across different network structures, showcasing the potential of KG‐iMLP for crude oil price forecasting. [ABSTRACT FROM AUTHOR]

Modified polyvinylidene chloride (PVDC) resin was prepared using octafluoropentyl methacrylate and trimethylolpropane trimethacrylate as modifying monomers through seeded emulsion polymerization. The successful incorporation of octafluoropentyl methacrylate into the PVDC resin was confirmed by Fourier transform infrared spectroscopy (FTIR) and X‐ray photoelectron spectroscopy (XPS) analyses. Scanning electron microscopy (SEM), energy dispersive spectroscopy (EDS) and XPS were utilized to investigate the element distribution in the modified monomer emulsion and the mechanism of monomer modification. The results demonstrated that the fluorine monomer was reacted in the resin, and mainly concentrated on the surface of the resin. The addition of octafluoropentyl methacrylate and trimethylolpropane trimethacrylate improved the water resistance of the resin. Compared to unmodified PVDC resin, the contact angle of the modified PVDC resin increased from 89.46° to 109.51°, and the water resistance at room temperature increased from 120 to 500 h. Furthermore, the modified resin exhibited excellent mechanical properties, thermal stability, and storage stability. [ABSTRACT FROM AUTHOR]