The deep learning methods based on syntactic dependency tree have achieved great success on Aspect-based Sentiment Analysis(ABSA).However,the accuracy of the dependency parser cannot be determined,which may keep aspec...The deep learning methods based on syntactic dependency tree have achieved great success on Aspect-based Sentiment Analysis(ABSA).However,the accuracy of the dependency parser cannot be determined,which may keep aspect words away from its related opinion words in a dependency tree.Moreover,few models incorporate external affective knowledge for ABSA.Based on this,we propose a novel architecture to tackle the above two limitations,while fills up the gap in applying heterogeneous graphs convolution network to ABSA.Specially,we employ affective knowledge as an sentiment node to augment the representation of words.Then,linking sentiment node which have different attributes with word node through a specific edge to form a heterogeneous graph based on dependency tree.Finally,we design a multi-level semantic heterogeneous graph convolution network(Semantic-HGCN)to encode the heterogeneous graph for sentiment prediction.Extensive experiments are conducted on the datasets SemEval 2014 Task 4,SemEval 2015 task 12,SemEval 2016 task 5 and ACL 14 Twitter.The experimental results show that our method achieves the state-of-the-art performance.展开更多
Benzophenones （BPs） are a class of widely used UV filters, which have been frequently detected within multiple environmental matrices. Disinfection is a necessary process in water treatment processes. The transforma...Benzophenones （BPs） are a class of widely used UV filters, which have been frequently detected within multiple environmental matrices. Disinfection is a necessary process in water treatment processes. The transformation behaviors and toxicity changes of 14 BP-type UV filters during chlorination disinfection treatment were investigated in this study. A new index, the acute toxicity formation potential, was proposed to evaluate the toxicity changes and potential risks of BP-type UV filters during chlorination treatment. It was found that 13 of 14 BP-type UV filters exhibited toxicity decreases in the chlorination disinfection process, more or less, while one showed a toxicity increase. The toxicity changes were dependent on substitution effects, such that 2,4-di-hydroxylated or 3-hydroxylated BPs exhibited significant toxicity decreases after chlorination treatment due to the ready cleavage of the aromatic ring. Importantly, the acute toxicity changes could be duplicated in an ambient water matrix.展开更多
基金supported by the National Natural Science Foundation of China(Grant Nos.62276073,61966004)Guangxi Natural Science Foundation(No.2019GXNSFDA245018)+2 种基金Innovation Project of Guangxi Graduate Education(No.YCSW2022155)Guangxi“Bagui Scholar”Teams for Innovation and Research ProjectGuangxi Collaborative Innovation Center of Multi-source Information Integration and Intelligent Processing.
文摘The deep learning methods based on syntactic dependency tree have achieved great success on Aspect-based Sentiment Analysis(ABSA).However,the accuracy of the dependency parser cannot be determined,which may keep aspect words away from its related opinion words in a dependency tree.Moreover,few models incorporate external affective knowledge for ABSA.Based on this,we propose a novel architecture to tackle the above two limitations,while fills up the gap in applying heterogeneous graphs convolution network to ABSA.Specially,we employ affective knowledge as an sentiment node to augment the representation of words.Then,linking sentiment node which have different attributes with word node through a specific edge to form a heterogeneous graph based on dependency tree.Finally,we design a multi-level semantic heterogeneous graph convolution network(Semantic-HGCN)to encode the heterogeneous graph for sentiment prediction.Extensive experiments are conducted on the datasets SemEval 2014 Task 4,SemEval 2015 task 12,SemEval 2016 task 5 and ACL 14 Twitter.The experimental results show that our method achieves the state-of-the-art performance.
基金supported by the National Natural Science Foundation of China (No. 21377143, 21077123 and 20877090)
文摘Benzophenones （BPs） are a class of widely used UV filters, which have been frequently detected within multiple environmental matrices. Disinfection is a necessary process in water treatment processes. The transformation behaviors and toxicity changes of 14 BP-type UV filters during chlorination disinfection treatment were investigated in this study. A new index, the acute toxicity formation potential, was proposed to evaluate the toxicity changes and potential risks of BP-type UV filters during chlorination treatment. It was found that 13 of 14 BP-type UV filters exhibited toxicity decreases in the chlorination disinfection process, more or less, while one showed a toxicity increase. The toxicity changes were dependent on substitution effects, such that 2,4-di-hydroxylated or 3-hydroxylated BPs exhibited significant toxicity decreases after chlorination treatment due to the ready cleavage of the aromatic ring. Importantly, the acute toxicity changes could be duplicated in an ambient water matrix.
