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Distributions Characteristics of Nutrients and Corresponding Ecological Effects in Dongting Lake
LIN Jie, LI Bin, CHEN Qian
Acta Scientiarum Naturalium Universitatis Pekinensis    2024, 60 (2): 341-349.   DOI: 10.13209/j.0479-8023.2024.008
Abstract39)   HTML    PDF(pc) (1709KB)(20)       Save
Based on monitoring data of monthly average COD, TN, and TP concentrations at Chenglingji hydrological station in Dongting Lake from 1990 to 2015, the intra-annual variation, inter-annual variation patterns of nutrients in the water column of Dongting Lake were systematically studied by trend analysis, and further revealed their stoichiometric ratio characteristics and discussed the effects of nutrient concentrations and structure on algal growth. The findings showed that the intra-annual variation patterns of average COD, TN, and TP were similar, indicating that the nutrient content in dry season was higher than that in wet season. However, as for multi-year trend, the annual average COD, TN, and TP in Dongting Lake showed a significant increase since 1990, while C:N and C:P ratios decreased and N:P ratio increased over time. The average C:N:P ratio in the water column of Chenglingji station in Dongting Lake was 13:18:1, and redundancy analysis showed that nutrient concentrations and stoichiometry ratios in the water would affect algae growth, with C:N, C:P and COD playing a dominant role. During the study period, the overall nitrogen and phosphorus content of the water column in Chenglingji station was generally high and has already met the algae growth demand. In order to avoid adverse ecological consequences such as harmful algal bloom events, external nitrogen and phosphorus inputs should be controlled to maintain the stoichiometric ratio balance in the water column of Dongting Lake.
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Hybrid Neural Network for Recognition of the “de” Structure with Semantic Ellipsis
SHI Bingqing, DAI Rubing, QU Weiguang, GU Yanhui, ZHOU Junsheng, LI Bin, XU Ge, SHI Shengwang
Acta Scientiarum Naturalium Universitatis Pekinensis    2019, 55 (1): 75-83.   DOI: 10.13209/j.0479-8023.2018.058
Abstract771)   HTML    PDF(pc) (893KB)(148)       Save

To slove the classification of the “de” structure containing the usage of semantic ellipsis, a hybrid neural network is built. Firstly, the network uses a bidirectional LSTM (long short-term memory) neural network to learn more syntactic and semantic information of the “de” structure. Then, the network employs a Max-pooling
layer or GRU (gated recurrent unit) based multiple attention layers to capture features of ellipsis of the “de” structure by which the network can recognize the “de” structure containing the usage of semantic ellipsis. Experiments on CTB8.0 corpus show that the proposed approach can achieve accurate results efficiently, the F1 value is 96.67%.

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Research on the Sense Guessing of Chinese Unknown Words Based on “Semantic Knowledge-base of Modern Chinese”
SHANG Fenfen, GU Yanhui, DAI Rubing, LI Bin, ZHOU Junsheng, QU Weiguang
Acta Scientiarum Naturalium Universitatis Pekinensis    2016, 52 (1): 10-16.   DOI: 10.13209/j.0479-8023.2016.009
Abstract1707)   HTML    PDF(pc) (396KB)(818)       Save

Based on the research issue of sense guessing of Chinese unknown words, different levels of semantic dictionary were introduced by applying “Semantic Knowledge-base of Modern Chinese”. Models have constructed for sense guessing by using these dictionary. Each model was intergrated to predict the unknown words and obtained better performance. Based on each model, semantic prediction and annotation of the unknown words in People’s Daily which published in 2000 were evaluated. Finally, corpus resources with the sense annotation of unknown words were obtained.

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Expression of Photosynthetic Gene psaC of Cyanobacteria in Saccharomyces cerevisiae
LI Bin,LI Tao,TONG Xuemei,WANG Donghui,ZHAO Jindong,WU Guangyao
Acta Scientiarum Naturalium Universitatis Pekinensis   
Abstract668)            Save
The psaC Gene of Synechococcus sp. PCC 7002 encodes the FA/FB aprotein of photosystem I, a protein with a molecular weight of 8.9 kD containing two 4Fe-4S centers. The expression vector of psaC gene was constructed, and transformed into Saccharoromyces cerevisiae.Southern blotting confirmed that psaC gene had been successfully transformed and Tris-Tricine-PAGE revealed that psaC gene had been highly expressed after incubating the transformed strains in the inducing culture.
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