Rare earth (RE) elements have large solid solubility in magnesium and are widely used to regulate the microstructure and property of advanced magnesium alloys. However, different kinds of RE elements have different effects on microstructure and property of the alloy. In this study, a Mg-Zn-Y alloy and a Mg-Zn-Gd alloy with alloying elements of the same atomic percentage were designed to clarify the effect of yttrium (Y) and gadolinium (Gd) on the corrosion behavior of as-cast MgZn 2 Y 2.66 and MgZn 2 Gd 2.66 alloys. The results show that the MgZn 2 Y 2.66 alloy is mainly composed of α-Mg phase and long period stacking ordered (LPSO) phase, while MgZn 2 Gd 2.66 alloy is mainly composed of α-Mg phase and (Mg, Gd) 3 Zn phase (W phase). Generally speaking, the corrosion phenomena of the two alloys in 3.5 wt% NaCl solution are similar. In the early stages of exposure, the alloys underwent uniform corrosion at a relatively low corrosion rate. With prolonged exposure, localized corrosion became dominated and the corrosion rate was greatly increased. However, the corrosion rate of the MgZn 2 Y 2.66 alloy, in terms of the corrosion current density, is about one order of magnitude lower than that of the MgZn 2 Gd 2.66 alloy. The high corrosion resistance of the MgZn 2 Y 2.66 alloy is mainly attributed to the presence of LPSO phase in form of continuous networks and the relatively high corrosion resistance of the corrosion product layer on the alloy.

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In this paper, we established a computer vision system for missing tablets detection in pharmaceutical industry during the manufacturing process. The images of blister pack with tablets in RGB color format were acquired by using a CCD industrial color camera on the industrial assembly line in real time. In order to reduce the effect of environmental brightness, the obtained RGB format images were transformed into HSI color format. According to the threshold of the hue and saturation, the image segmentation was carried out. Then, the tablets could be identified and determined. The Canny edge detection and Hough circle detection was used to mark the locations of tablets. Based on the locations and number of circles, the location of the missing tablets was obtained. This computer vision system could boost efficiency, reduce the cost of labor, and guarantee the safety of drug consumers.