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The purpose of this paper is to detect the existence of price bubbles and examine the possible contributing factors that associate with price bubble occurrences in China agricultural commodity markets.

Using recently developed rolling window right-side augmented Dickey–Fuller test, we first detect the dates of price bubbles in China's two important agricultural commodity markets, namely corn and soybeans. Then, we use a penalized maximum likelihood estimation of a multinomial logistic model to estimate the contributing factors of price bubbles in both markets, respectively.

Results from the bubble detection indicate that price bubbles account for 5.48% (3.91%) of the studied periods for corn (soybeans). More importantly, we find that market liquidity and speculation have opposite effects on the occurrences of bubbles in the corn and soybeans market. World stocks-to-use and exchange rates affect the occurrences of bubbles in a different way for each commodity, as well. Price bubbles are more likely associated with strong economic activity, high interest rates and low inflation levels.

This is the first study considering commodity-specific features into the formation of price bubbles. Through accurately identifying the bubble dates and fixing the estimation bias of rare events models, this study enables us to obtain robust results for each commodity. The results imply that China's corn and soybeans market respond differently to the speculative activity and external shocks from international markets. Therefore, future policy regulations on commodity markets should focus on more commodity-specific factors when aiming at avoiding bubble occurrences.

The purpose of this paper is to evaluate the effect of micro-nano mixed super-hydrophobic structure on corrosion resistance and mechanism of magnesium alloys.

A super-hydrophobic surface was fabricated on AZ91 and WE43 magnesium alloys by laser etching and micro-arc oxidation (MAO) with SiO₂ nanoparticles coating and low surface energy material modification. The corrosion resistance properties of the prepared super-hydrophobic surfaces were studied based on polarization curves and immersion tests.

Compared with bare substrates, the corrosion resistance of super-hydrophobic surfaces was improved significantly. The corrosion resistance of super-hydrophobic surface is related to micro-nano composite structure, static contact angle and pretreatment method. The more uniform the microstructure and the larger the static contact angle, the better the corrosion resistance of the super-hydrophobic surface. The corrosion resistance of super-hydrophobic by MAO is better than that of laser machining. Corrosion of super-hydrophobic surface can be divided into air valley action, physical shielding, pretreatment layer action and substrate corrosion.

The super-hydrophobic coatings can reduce the contact of matrix with water so that a super-hydrophobic coating would be an effective way for magnesium alloy anti-corrosion. Therefore, the corrosion resistance properties and mechanism of the prepared super-hydrophobic magnesium alloys were investigated in detail.

The purpose of this paper is to employ a fractional approach to predict the permeability of nonwoven fabrics by simulating diffusion process.

The method described here follows a similar approach to anomalous diffusion process. The relationship between viscous hydraulic permeability and electrical conductivity of porous material is applied in the derivation of fractional power law of permeability.

The presented power law predicted by fractional method is validated by the results obtained from simulation of fluid flow around a 3D nonwoven porous material by using the lattice-Boltzmann approach. A relation between the fluid permeability and the fluid content (filling fraction), namely, following the power law of the form, was derived via a scaling argument. The exponent n is predominantly a function of pore-size distribution dimension and random walk dimension of the fluid.

The fractional scheme by simulating diffusion process presented in this paper is a new method to predict wicking fluid flow through nonwoven fabrics. The forecast approach can be applied to the prediction of the permeability of other porous materials.