In the past decade, β-elemene played an important role in enhancing the effects of many anticancer drugs and was widely used in the treatment of different kinds of malignancies and in reducing the side effects of chemotherapy. Further study showed that it is also a promising anti-lung cancer drug. However, the clinical application of β-elemene was limited by its hydrophobic property, poor stability, and low bioavailability. With the development of new excipients and novel technologies, plenty of novel formulations of β-elemene have improved dramatically, which provide a positive perspective in terms of clinical application for β-elemene. Liposome as a drug delivery system shows great advantages over traditional formulations for β-elemene. In this paper, we summarize the advanced progress being made in anti-lung cancer activity and the new liposomes delivery systems of β-elemene. This advancement is expected to improve the level of pharmacy research and provide a stronger scientific foundation for further study on β-elemene.
This study investigates liner companies' timing of investment and sealing up container ships based on real option theory. The Dixit model is adopted to find out a pair of trigger prices for entry and exit with the assumption freight rate obey Geometric Brownian Motion. More new shipbuilding orders and entrants lead to lower future freight rate in the oligopoly liner shipping market. This model is tested empirically basic on the data of a 9000 TEU container ship on Far East-Europe route and the result is positive comparing to the number of ship orders. Liner companies' should make decision base on the freight of the ship in operation. Therefore, ship investment should be made at the new ship order trough and freight trough.
Abstract. When the new ship orders decline deeply and the shipbuilding capability is releasing quickly, how to guarantee the accuracy of prediction of new ship orders becomes the main target for shipbuilding corporate. This paper aims to predict the future demand of new ship with the help of combination forecast model that consist of grey system, support vector machine and artificial neural network. The result showed that combination forecast method is better than single usage of other three methods. The prediction result of new ship orders could provide some useful reference for the development of the shipbuilding industry.
This study investigates liner companies' timing of investment and sealing up container ships based on real option theory. The Dixit model is adopted to find out a pair of trigger prices for entry and exit with the assumption freight rate obey Geometric Brownian Motion. More new ship-building orders and entrants lead to lower future freight rate in the oligopoly liner shipping market. This model is tested empirically basic on the data of a 9000 TEU container ship on Far East-Europe route and the result is positive comparing to the number of ship orders. Liner companies' should make decision base on the freight of the ship in operation. Therefore, ship investment should be made at the new ship order trough and freight trough.
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