Recent Study of Drag Embedment Plate Anchors in China

Experimental and theoretical studies of drag embedment plate anchors recently carried out in Tianjin University are summarized in this research paper, which involve a series of important topics relevant to the study of drag anchors. The techniques for measuring the trajectory and movement direction of drag anchors in soils, the techniques for measuring the moving embedment point and reverse eatenary shape of the embedded drag line, the penetration mechanism and kinematic behavior of drag anchors, the ultimate embedment depth of drag anchors, the movement direction of the anchor with an arbitrary fluke section, the reverse catenary properties of the embedded drag line, the interaetional properties between drag anchor and installation line, the kinematic model of drag anchors in seabed soils, and the analytical method for predicting the anchor trajectory in soils will all be examined. The present work remarkably reduces the uncertainties in design and analysis of drag embedment plate anchors, and is beneficial to improving the application of this new type of drag anchor in offshore engineering.

Forecasting directional movement of Forex data using LSTM with technical and macroeconomic indicators

Forex(foreign exchange)is a special financial market that entails both high risks and high profit opportunities for traders.It is also a very simple market since traders can profit by just predicting the direction of the exchange rate between two currencies.However,incorrect predictions in Forex may cause much higher losses than in other typical financial markets.The direction prediction requirement makes the problem quite different from other typical time-series forecasting problems.In this work,we used a popular deep learning tool called“long short-term memory”(LSTM),which has been shown to be very effective in many time-series forecasting problems,to make direction predictions in Forex.We utilized two different data sets—namely,macroeconomic data and technical indicator data—since in the financial world,fundamental and technical analysis are two main techniques,and they use those two data sets,respectively.Our proposed hybrid model,which combines two separate LSTMs corresponding to these two data sets,was found to be quite successful in experiments using real data.

Multi-functional Hollow Structures for Intelligent Drug Delivery

Multi-fountional hollow structures have emerged as promising platforms for intelligent drug delivery due to their unique properties,such as high loading capacities and programmed drug release.In particular,hollow multishell structures(HoMSs)with multilevel shell and space can regulate the molecular-level interaction between drugs and materials,so as to achieve the temporal-spatial order and sequential release of drugs.The anisotropic hollow structures can control the drug diffusion process by inducing the macroscopic interface flow through autonomous movement,realizing the targeted drug transport and release.In this paper,a key focus will be HoMSs with their temporal-ordered architectures and anisotropic hollow carriers with directional movement.Their synthesis mechanisms,structure-property relationships,smartly programmed drug delivery and biomedical applications will be discussed,providing insights into designing next-generation intelligent drug carriers.