Abstract. Motivated by disease outbreaks and trade shocks, a dynamic equilibrium displacement model is calibrated for the U.S. pear industry to simulate welfare from various shocks compared to a baseline. Our contribution is assessing the impact to intermediary packers for fresh fruit and processors for processed fruit in addition to growers and consumers. The processed market is more sensitive than the fresh market generally, and supply shocks induce larger impacts on both markets than trade sanctions. Impacts to intermediaries are on par with growers, indicating that not considering them misstates the distribution of damages to the industry from a shock.

With the wide application of image fusion technology in target detection and other fields, the fusion of polarization images and other intensity images is becoming a research focus. Traditional polarization image fusion includes intensity, degree of linear polarization (DOLP), and angle of polarization (AOP). However, images of DOLP and AOP fusion cannot meet the requirements of outstanding positive characteristics. Therefore, we propose a method to calculate the polarization characteristics image that can reflect the difference of polarization characteristics of different materials. The method and process are as follows: First, the polarization detection angle is divided into several angle intervals, and the orthogonal difference characteristics (ODC) image of each interval is obtained by weighting and accumulating the AOP probability density of the angle in the interval and the correlation between images. Second, the ODC images are reconstructed in the gradient domain, and the multi-angle orthogonal differential polarization characteristics (MODPC) image is obtained. The MODPC image is fused with the visible intensity image, and the fusion results are evaluated by using image evaluation indexes such as contrast (C), average gradient (AG), image entropy (E), and peak signal-to-noise ratio (PSNR). The experimental results show that the MODPC and S 0 fusion result images are superior to the DOLP and S 0 fusion results in terms of subjective visual perception and objective indicators among the six classical fusion algorithms. The proposed MODPC image can be applied in target detection.

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