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This paper considers the problem of how to construct the optimal multi-period portfolio for investors with loss aversion in fuzzy environment. Firstly, we regard the return rates of the risky assets as fuzzy numbers and use the value function in prospect theory to transform the return rate of a portfolio into perceived value, which can reflect investors' loss aversion. Moreover, due to the fact that investors' perception level toward risk may vary with the loss aversion degree, we propose a new risk measure based on the perceived value. Then, we formulate the objectives of maximizing the cumulative expected perceived value and minimizing the cumulative perceived risk and propose a multi-period portfolio selection model with diversification constraint. Furthermore, to solve the proposed model, we design a multiple particle swarm optimization algorithm with respect to its specific situation. Finally, using the data from real financial market, we construct a real case to illustrate the effectiveness of the model and algorithm. The results show that loss aversion has an important effect on investors' investment decisions, and the proposed model could provide more reasonable strategies for investors with different loss aversion degrees. [ABSTRACT FROM AUTHOR]

Aiming at the problems like many locations to be detected and complex texture background for automobile calipers, a detection method combining gray average algorithm, wavelet denoising and LBP operator is proposed. First, the region of interest is extracted from the caliper sample and the wavelet denoising is preprocessed. The gray-to-average ratio of the genuine template and the sample at each position is calculated, then a suitable threshold is set to remove the defective maps with large differences of the ratios. ff the gray-to-average ratio is within the indistinguishable range M, the feature is extracted by the LBP operator. Finally, the template feature is compared with the image feature to be detected in the M range to measure the caliper defect. The experimental results show that the proposed method has real-time characteristics and reliability for the detection of automobile calipers, which can be well applied to the detection of actual products. [ABSTRACT FROM AUTHOR]

The receptor for activated C kinase 1 (RACK1) is one member of the most important WD repeat–containing family of proteins found in all eukaryotes and is involved in multiple signaling pathways. However, compared with the progress in the area of mammalian RACK1, our understanding of the functions and molecular mechanisms of RACK1 in the regulation of plant growth and development is still in its infancy. In the present study, we investigated the roles of rice RACK1A gene (OsRACK1A) in controlling seed germination and its molecular mechanisms by generating a series of transgenic rice lines, of which OsRACK1A was either over-expressed or under-expressed. Our results showed that OsRACK1A positively regulated seed germination and negatively regulated the responses of seed germination to both exogenous ABA and H2O2. Inhibition of ABA biosynthesis had no enhancing effect on germination, whereas inhibition of ABA catabolism significantly suppressed germination. ABA inhibition on seed germination was almost fully recovered by exogenous H2O2 treatment. Quantitative analyses showed that endogenous ABA levels were significantly higher and H2O2 levels significantly lower in OsRACK1A-down regulated transgenic lines as compared with those in wildtype or OsRACK1A-up regulated lines. Quantitative real-time PCR analyses showed that the transcript levels of OsRbohs and amylase genes, RAmy1A and RAmy3D, were significantly lower in OsRACK1A-down regulated transgenic lines. It is concluded that OsRACK1A positively regulates seed germination by controlling endogenous levels of ABA and H2O2 and their interaction. [ABSTRACT FROM AUTHOR]