A series of biodegradable Mg-Cu alloys is designed to induce osteogenesis, stimulate angiogenesis, and provide long-lasting antibacterial performance at the same time. The Mg-Cu alloys with precipitated Mg2Cu intermetallic phases exhibit accelerated degradation in the physiological environment due to galvanic corrosion and the alkaline environment combined with Cu release endows the Mg-Cu alloys with prolonged antibacterial effects. In addition to no cytotoxicity towards HUVECs and MC3T3-E1 cells, the Mg-Cu alloys, particularly Mg-0.03Cu, enhance the cell viability, alkaline phosphatase activity, matrix mineralization, collagen secretion, osteogenesis-related gene and protein expressions of MC3T3-E1 cells, cell proliferation, migration, endothelial tubule forming, angiogenesis-related gene, and protein expressions of HUVECs compared to pure Mg. The favorable osteogenesis and angiogenesis are believed to arise from the release of bioactive Mg and Cu ions into the biological environment and the biodegradable Mg-Cu alloys with osteogenesis, angiogenesis, and long-term antibacterial ability are very promising in orthopedic applications.
Ontology mapping is the key point to reach interoperability over ontologies. In semantic web environment, ontologies are usually distributed and heterogeneous and thus it is necessary to find the mapping between them before processing across them. Many efforts have been conducted to automate the discovery of ontology mapping. However, some problems are still evident. In this paper, ontology mapping is formalized as a problem of decision making. In this way, discovery of optimal mapping is cast as finding the decision with minimal risk. An approach called RiMOM (Risk Minimization based Ontology Mapping) is proposed, which automates the process of discoveries on 1:1, n:1, 1:null and null:1 mappings. Based on the techniques of normalization and NLP, the problem of instance heterogeneity in ontology mapping is resolved to a certain extent. To deal with the problem of name conflict in mapping process, we use thesaurus and statistical technique. Experimental results indicate that the proposed method can significantly outperform the baseline methods, and also obtains improvement over the existing methods.
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