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Aspect-based sentiment analysis is a fine-grained sentiment analysis task, which aims to align aspects with the corresponding emotion words for aspect specific emotion polarity reasoning. In recent years, the graph neural network sentiment classification method based on syntactic dependent information has become a research hotspot in this field. However, due to the flexibility of comment sentences in content expression and syntactic structure, the modeling method using only syntactic dependent information still has some shortcomings. In order to enhance the comment sentences by affective knowledge and structural semantic information, a convolutional network model(DualSyn-GCN) of two channel knowledge enhancement graph is proposed. On one hand, the syntactic dependency adjacency matrix is enhanced according to the implicit relationship between aspect and aspect as well as aspect and context. On the other hand, the emotional dependency of aspect is learned from external emotional knowledge, and then the two different enhanced representations are fused to realize the sharing and complementarity between different representations. The experimental results show that, compared with the classical aspect based graph convolutional network model (ASGCN), this model improves the accuracy and MF1 value on LAP14 data set by 2.34% and 3.26% respectively. [ABSTRACT FROM AUTHOR]

Aspect-level sentiment classification aims to discriminate the sentiment polarity of a specific aspect in a sentence. Although attention-based recurrent neural network models perform well among existing solutions, they are not ideal for processing "semantically ambiguous" sentences that are short and contain many neologisms and polysemous words. Therefore, this paper proposes a neural network model based on knowledge graph and attention mechanism. The basic idea is to use a knowledge base to obtain a relevant concept set of aspect words and integrate external information to enhance the semantic representation of the text. Firstly, the output of bidirectional long short-term memory network is combined with self-attention mechanism to generate context representation. Then, the upper and lower context representations are combined to use dual attention to obtain external knowledge from the knowledge graph and obtain knowledge vectors related to aspect words. Finally, the two parts of content are input together into a fully connected network to calculate the aspect-level sentiment tendency. Experimental results show that compared with other models, the proposed model significantly improves classification performance. [ABSTRACT FROM AUTHOR]

The construction of operation mode and materialized operation of Shaanxi Alliance is an important exploration of the reform of agricultural science and technology system and mechanism innovation, an effective way to improve the innovation system of agricultural science and technology in Shaanxi Province, and an important measure to implement the strategy of high-quality agricultural development and rural revitalization. This paper is based on Shaanxi alliance management system and operation characteristics, with agricultural science and technology collaborative innovation as the goal. The paper learns from the operation mode of China’s industrial technology innovation alliance, the operation mode of agricultural science and technology innovation benchmark alliance and the collaborative innovation mode of Shaanxi agricultural science and technology project of Shaanxi Alliance, and scientifically summarizes the current operation mode of Shaanxi Alliance. At the same time, combining with the existing problems and instability in the operation of the Shaanxi alliance, the future operation mode of the Shaanxi alliance is innovatively constructed from the strategic positioning of the materialized operation of the alliance. In order to run the materialized Shaanxi alliance, this paper envisions three paths of the materialized operation of the Shaanxi Alliance. [ABSTRACT FROM AUTHOR]

Objective: To explore the clinical curative effect of trimetazidine or Shengmai decoction combined with astragalus injection in the treatment of acute viral myocarditis(AVMC). Methods: A total of 140 patients with AVMC, who were treated in Sichuan Provincial People’s Hospital from April 2013 to April 2016, were selected and randomly divided into control group(n=45), Qu Huang group(n=46) and Sheng Huang group(n=49). The control group received routine drug treatment.On the basis of the control group’s therapy, the Qu Huang group received trimetazidine combined with astragalus injection and the Sheng Huang group received Shengmai decoction combined with astragalus injection. The serum creatine kinase-MB(CK-MB), cardiac troponin I(cTnI), electrocardiogram indexs, clinical total effective rate, improvement of clinical symptoms and adverse reaction were compared among the three groups.Results: After treatment, the total effective rate in the Qu Huang group and Sheng Huang group was significantly higher than that in the control group,and the total effective rate in the Qu Huang group was higher than that in the Sheng Huang group(P<0.05). The incidence of heart palpitations and chest pain in the Qu Huang group and the Sheng Huang group were lower than that in the control group,the differences were statistically significant(P<0.05). The levels of serum CK-MB and cTnI in the Qu Huang group and the Sheng Huang group were lower than those in the control group, and the levels of above indexes in the Qu Huang group was lower than that in the Sheng Huang group(P<0.05). The incidence of atrioventricular heart-block, ST-T change,premature ventricular contractions in the Qu Huang group were lower than those in the control group(P<0.05).There was no significant difference in the incidence of adverse reactions among the three groups(P>0.05). Conclusion: In the treatment of patients with AVCM. The total effective rate of trimetazidine combined with astragalus injection is higher than that of Shengmai decoction combined with astragalus injection. It can reduce the degree of myocardial injury and improve clinical symptoms,without serious adverse reactions, which is worthy of clinical application. [ABSTRACT FROM AUTHOR]