The rapid economic development and high incidence of crises in emerging economies make them play an increasingly important role in the transmission of global financial risks. As a new trend in the development of the financial industry, the development of green finance also indicates the direction of the future development of the financial industry. Faced with the increasingly concerned environmental issues, it is necessary for emerging economies, mainly represented by developing countries, to learn from the experience of developed countries in this field. In this paper, principal component analysis (PCA) and factor analysis (FPM) are applied to study the factors influencing financial fragility of emerging economies at different stages of development, and then the degree of fragility is analyzed and compared. The empirical results show that there are differences in the influencing factors of financial fragility in emerging economies at different stages of development. For middle- and low-income economies, credit security, social stability and the development of capital market are the priorities they should consider at present. For the Middle- and high-income economies, we should be alert to the malignant changes in a certain indicator. For high-income economies, macroeconomic stability is the focus of their financial security. The research results provide a basis for the emerging economies to reduce economic vulnerability according to local conditions, which is of great significance to avoid the outbreak of global financial crisis.

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In the inductive wireless power transmission, electromagnetic force, which between the primary part and the secondary part, may cause the non-contact free motion and cause bad side effects on transmission. In order to calculate the force, magnetic vector potentials differential equations, based on linear array, are built, and the expression of the electromagnetic force is produced by solving this equation system.

We modify a standard SIR epidemiological model to allow for testing and asymptomatic agents. We explore cross country variation's ability to allow for identification of key parameters of the model: the fatality rate and the evolution over time of the normalized transmission rate. We first show that as long as tests are applied only to agents who exhibit symptoms, those parameters cannot be identified. We briefly discuss which additional information may allow for identification. Finally, we also describe conditions under which the normalized transmission rate can be computed with very high accuracy, and how cross country evidence can be used to evaluate the effect of lockdowns on evolution of the effective transmission rate over time.