To better understand the variation properties of marine aerosol during transport, single particle aerosol mass spectrometer (SPAMS) was applied for the first time during a comprehensive ocean experiment over the South Yellow Sea in November 2012. Two parallel sections influenced by marine air masses with constant wind direction from ocean to land (Section 1), and continental air masses with constant wind direction from land to ocean (Section 2), respectively, were selected to study the variation of chemical characteristics of marine aerosol. The results showed that the average particle count in Section 2 was around 3.5 times higher than that in Section 1, which might be ascribed to the influence of continental air masses, accompanied with high wind speed in Section 2. Particle counts of major components (SO42-, NO3-, NH4+, OC and EC) containing particles in Section 1 and Section 2 (excluding NO3-) gradually decreased by 58%-74% and 34%-53%, and the reductions in Section 1 were greater than that in Section 2. Secondary aerosol contributed to the highest fraction (42%) of the total particles in Section 2, while sea-salt aerosol contributed to the highest (>30%) in Section 1. The contribution of secondary and other anthropogenic aerosols (including biomass burning, Soot-like and Pb-containing aerosols) in both sections were significant. It indicated that the contribution of anthropogenic air pollutants to marine aerosol could not be ignored over the South Yellow Sea.
To effectively solve the glyph generation and glyph description problem, a dynamical glyph generation method of Xiangxi folk Hmong characters is proposed. According to this method, the glyph generation process can be described as a combination arithmetic expression. Hmong characters component acts as the operand, and the location relationship between the components decides the operator. Glyphs in different structure can be dynamically generated by combination of two or three components. Further, if combination arithmetic expression is converted to ideographic description sequence (IDS), the proposed method can be implemented with the help of the IDS explain mechanism of operation system. Test results illustrate that, the Xiangxi Hmong characters glyph, which generated by the mapping script based on the proposed method, can meet practical requirements.
The limited semantic knowledge is used in the phrase-based statistical machine translation (SMT), which causes that the translation quality of long-distance verb and its object is low. A selectional preference based translation model is proposed, which inducts the semantic constraints that a verb imposes on its object to select the proper argument-head word for the predicate with long distance. The authors train the corpus to obtain the conditional probability based selectional preferences for verb, and integrate the selectional preferences into a phrase-based translation system and evaluate on a Chinese-to-English translation task with large-scale training data. Experiment results show that the integration of selectional preference into SMT can effectively capture the long-distance semantic dependencies and improve the translation quality.