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Coating matching design is one of the important parts of ship coating process design. The selection of coating matching is influenced by various factors such as marine corrosive environment, anti-corrosion period and working conditions. There are also differences in the coating performance requirements for different ship types and different coating parts. At present, the design of coating matching in shipyards depends on the experience of technologist, which is not conducive to the scientific management of ship painting process and the macro control of ship construction cost. Therefore, this paper proposes a hybrid algorithm of fuzzy comprehensive evaluation and collaborative filtering based on user label improvement (IFCE-CF). Based on the analytic hierarchy process (AHP), the evaluation index system of coating matching is constructed, and the weight calculation process of fuzzy comprehensive evaluation is optimized by introducing the user label weight. The collaborative filtering algorithm based on matrix decomposition is used to realize the accurate recommendation of coating matching. Historical coating process data of a shipyard between 2010 and 2020 are selected to verify the recommendation ability of the method in the paper. The results show that using the coating matching intelligent recommendation algorithm proposed in this paper, the root mean square error is

This study aimed to evaluate in vitro probiotic characteristics of Pediococcus pentosaceus strain L1 from pickled radish and investigate its impacts on inflammatory responses in porcine intestinal epithelial cells (IEC) to enterotoxigenic Escherichia coli (ETEC) F4+. The abilities of P. pentosaceus L1 to tolerate gastrointestinal conditions and to antagonize ETEC F4+ growth were determined. Adhesion of P. pentosaceus L1 and its effect on ETEC F4+ adhesion to porcine IPEC-J2 IEC were evaluated. Furthermore, the effects of this strain on proinflammatory gene expression and cytokines/chemokine production in porcine IPEC-J2 IEC induced by ETEC F4+ were determined. P. pentosaceus L1 showed good tolerance to the medium adjusted at pH 2.5 and consequently supplemented with 0.3% oxgall. Reduction of ETEC F4+ growth in co-culture with L1 was found. Effective adhesion of L1 to porcine. IPEC-J2 IEC was observed under these conditions. P. pentosaceus L1 decreased the adhesion of ETEC F4+ to IPEC-J2 IEC and the extent of inhibition of ETEC F4+ adhesion depended on the timing of L1 addition. Further analysis revealed down-regulation of expression of ETEC F4+-induced proinflammatory genes encoding interleukin-6 (IL-6), tumor necrosis factor-α (TNF-α), and interleukin-8 (IL-8) in IPEC-J2 IEC. Expression of the genes involved in NF-κB pathway, including RELA and NFKB1, were also repressed, as was production of IL-6, TNF-α, and IL-8. These results indicate that P. pentosaceus L1 may have potential as a probiotic for control of ETEC infection in pigs.

This study aimed to investigate the probiotic potential of lactic acid bacteria (LAB) strains isolated from De'ang pickled tea, a traditional food consumed by the De'ang nationality of Yunnan, China. Twenty-six LAB strains isolated from De'ang pickled tea were subjected to identification based on 16S rRNA gene sequence analysis. Twenty-four belonged to Lactobacillus plantarum, one belonged to Enterococcus casseliflavus, and one belonged to Lactobacillus acidophilus. Eighteen out of 26 LAB strains which showed a higher capability to tolerate simulated gastrointestinal juices were chosen to further evaluate their probiotic properties. Varied adhesive abilities and auto-aggregative capacities of selected LAB strains were dependent on species and even strains. All tested LAB strains were resistant to kanamycin, streptomycin, gentamycin, and vancomycin and sensitive to tetracycline and chloramphenicol. Ten out of the 18 strains are resistant to ampicillin, and the remaining strains are sensitive to ampicillin; 4 out of the 18 strains showed resistance to erythromycin. Compared to reference strain Lactobacillus rhamnosus strain GG, these LAB strains had a greater or comparative antimicrobial activity against Salmonella typhimurium or Escherichia coli. In contrast, eight out of the 18 strains suppressed growth of Shigella flexneri. Two L. plantarum strains, ST and STDA10, not only exhibited good probiotic properties but also showed a good ability of scavenging DPPH and ABTS+. This study suggests that L. plantarum ST and STDA10 could be used as potential probiotics applied in functional foods.

Promptly and accurately dealing with the equipment breakdown is very important in terms of enhancing reliability and decreasing downtime. A novel fault diagnosis method PSO-RVM based on relevance vector machines (RVM) with particle swarm optimization (PSO) algorithm for plunger pump in truck crane is proposed. The particle swarm optimization algorithm is utilized to determine the kernel width parameter of the kernel function in RVM, and the five two-class RVMs with binary tree architecture are trained to recognize the condition of mechanism. The proposed method is employed in the diagnosis of plunger pump in truck crane. The six states, including normal state, bearing inner race fault, bearing roller fault, plunger wear fault, thrust plate wear fault, and swash plate wear fault, are used to test the classification performance of the proposed PSO-RVM model, which compared with the classical models, such as back-propagation artificial neural network (BP-ANN), ant colony optimization artificial neural network (ANT-ANN), RVM, and support vectors, machines with particle swarm optimization (PSO-SVM), respectively. The experimental results show that the PSO-RVM is superior to the first three classical models, and has a comparative performance to the PSO-SVM, the corresponding diagnostic accuracy achieving as high as 99.17% and 99.58%, respectively. But the number of relevance vectors is far fewer than that of support vector, and the former is about 1/12–1/3 of the latter, which indicates that the proposed PSO-RVM model is more suitable for applications that require low complexity and real-time monitoring.

In the first essay, we study mutual funds' voting on compensation-related proposals initiated by corporate management. Compared with proposals on other topics, proposals on compensation issues are more likely to be challenged by mutual funds. Consistent with active institutional influence, mutual funds are more likely to vote against management at portfolio firms that make more excess CEO pay or depict other symptoms of poor governance such as bad performance and CEO entrenchment. Both active and passive funds' votes are significant drivers of the voting outcome of a proposal. Failed proposals are associated with lower CEO pay, especially excess pay, in the following year. Say-on-pay proposals opposed by more mutual funds are also followed by lower excess CEO pay. Collectively, evidence in this paper suggests that institutions (including passive institutions) play an important role in setting CEO pay through the voting channel. The second essay examines the equity loan supply for short selling. Using detailed stock lending data, we show that active equity funds, on average, are informed, stock lenders. The stocks they lend outperform those that they do not. The stocks they recall and sell perform worse in the future than those that remain on loan. These funds avoid lending stocks when lending fees are extremely high and use the shorting market's signals to form stock-selling decisions. Our findings help explain why institutional investors lend stocks. They also highlight a new source of short-sale constraints arising from the informed loan supply. Doctor of Philosophy Shareholders of a firm are expected to monitor executive compensation. Among all share-holders, institutional investors such as mutual funds play an important role in setting pay practices for executives. However, do they vote on related proposals at annual meetings or simply "vote by feet"? The first essay strives to answer the question using mutual fund proposal vote records data. Our findings suggest that mutual funds can affect CEO compensation in the future by voting against management-initiated pay proposals and the effect is both statistically and economically significant. Institutional investors such as mutual funds also participate in lending business on otherwise idle shares in their portfolio. While they are often considered passive and not informed in the equity loan market, their behavior has been much less investigated. We study the extent to which mutual funds exploit information in lending their shares using the first detailed stock lending dataset obtained from SEC filings. We find that mutual funds are informed lenders and important to market efficiency.

This dissertation consists of three essays. The first essay focuses on idiosyncratic volatility as a primary arbitrage cost for short sellers. Previous studies document (i) negative abnormal returns for high relative short interest (RSI) stocks, and (ii) positive abnormal returns for low RSI stocks. We examine whether these market inefficiencies can be explained by arbitrage limitations, especially firms' idiosyncratic risk. Consistent with limits to arbitrage hypothesis, we document an abnormal return of -1.74% per month for high RSI stocks (>=95th percentile) with high idiosyncratic volatility. However, for similar level of high RSI, abnormal returns are economically and statistically insignificant for stocks with low idiosyncratic volatility. For stocks with low RSI, the returns are positively related to idiosyncratic volatility. These results imply that idiosyncratic risk is a potential reason for the inability of arbitrageurs to extract returns from high and low RSI portfolios. The second essay investigates market efficiency in the absence of limits to arbitrage on short selling. Theoretical predictions and empirical results are ambiguous about the effect of short sale constraints on security prices. Since these constraints cannot be eliminated in equity markets, we use trades from futures markets where there is no distinction between short and long positions. With no external constraints on short positions, we document a weekend effect in futures markets which is a result of asymmetric risk between long and short positions around weekends. The premium is higher in periods of high volatility when short sellers are unwilling to accept higher levels of risk. On the other hand, riskiness of long positions does not seem to have a similar impact on prices. The third essay studies investor behaviors that generate mispricing by examining relationship between stock price and future returns. Based on traditional finance theory, valuation should not depend on nominal stock prices. However, recent literature documents that preference of retail investors for low price stocks results in their overvaluation. Motivated by this preference, we re-examine the relationship between stock price and expected return for the entire U.S. stock market. We find that stock price and expected returns are positively related if price is not confounded with size. Results in this paper show that, controlled for size, high price stocks significantly outperform low price stocks by an abnormal 0.40% per month. This return premium is attributed to individual investors' preference for low price stocks. Consistent with costly arbitrage, the return differential between high and low price stocks is highest for the stocks which are difficulty to arbitrage. The results are robust to price cut-off of $5, and in different sub-periods. Ph. D.