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Application of aluminum industry solid waste in asphalt mixtures and its impact on performance:Current research and future perspectives
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作者 Tianyi yan Yongjun Meng +3 位作者 Xiaowan Luo Jinbin Chen keyu yan Dawei Wang 《Journal of Road Engineering》 2025年第4期554-571,共18页
Aluminum industrial solid waste represents a highly abundant yet underutilized resource.Its incorporation into asphalt pavement applications can effectively reduce the exploitation of natural resources and mitigate en... Aluminum industrial solid waste represents a highly abundant yet underutilized resource.Its incorporation into asphalt pavement applications can effectively reduce the exploitation of natural resources and mitigate environmental issues caused by waste accumulation.This paper focuses on typical solid waste resources generated by the aluminum industry,summarizing the latest research progress in their application within the asphalt pavement industry and proposing key directions for future attention.The physicochemical properties of red mud(RM),spent aluminum electrolytic cathode materials,and secondary aluminum dross(SAD)are reviewed.The effects and mechanisms of RM,spent aluminum electrolytic cathode materials,and SAD on the performance of asphalt and its mixtures are elaborated.RM significantly enhances the aging resistance of asphalt,the hightemperature rheological properties of asphalt mastic,and the rutting resistance of asphalt mixtures.Spent aluminum electrolytic cathode materials require the removal of fluorides and cyanides before further application in asphalt pavement.SAD effectively improves the dynamic stability of asphalt mixtures.This review presents the first systematic summary of key scientific challenges and technical bottlenecks in the application of aluminum industrial solid waste in asphalt pavements.It clarifies that future research should prioritize waste pretreatment technologies,performance regulation mechanisms,and life cycle environmental impact assessments.These contributions provide essential theoretical foundations and technical guidance for advancing the resource utilization of aluminum industrial solid waste,holding substantial significance for promoting the development of green transportation infrastructure. 展开更多
关键词 Aluminum industry solid waste Asphalt mastic Asphalt mixtures Red mud Spent aluminum electrolytic cathode materials Secondary aluminum dross
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知识图谱驱动的图卷积神经网络谣言检测模型 被引量:9
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作者 徐凡 李明昊 +3 位作者 黄琪 鄢克雨 王明文 周国栋 《中国科学:信息科学》 CSCD 北大核心 2023年第4期663-681,共19页
社交媒体谣言以极低的成本在互联网中被快速扩散,给社会带来显著的负面影响.传统的谣言检测模型主要考虑传播模式、写作风格、用户信用和世界知识等信息.然而,谣言的传播模式通常难以被捕捉,写作风格却容易被模仿,由元数据(如职业、家... 社交媒体谣言以极低的成本在互联网中被快速扩散,给社会带来显著的负面影响.传统的谣言检测模型主要考虑传播模式、写作风格、用户信用和世界知识等信息.然而,谣言的传播模式通常难以被捕捉,写作风格却容易被模仿,由元数据(如职业、家乡、学历、年龄等)构成的用户信息也容易被伪造.本文提出了一种新颖的知识驱动的图卷积神经网络谣言检测模型.该模型首先将社交媒体文本表示成一种语义–实体无向图结构,其中节点包含原社交媒体文本中的词语,利用世界知识库扩展的实体词语,以及利用语言知识库扩展的语义词语,边包含三类节点的6种有效组合.该语义–实体图可以有效地增强任意两种节点的共现性,从而丰富了原社交媒体文本的表示,从一定程度上缓解数据稀疏共现问题.语言知识利用了HowNet (义原和同义词)以及WordNet (上义词、下义词和同义词)分别对中英文社交媒体文本的主题词进行扩充.并成功地将语言知识和实体知识通过图卷积神经网络框架有效集成.在4个国际基准中英文谣言语料库上的实验结果和可视化分析表明了本文模型的有效性. 展开更多
关键词 语言知识 世界知识 主题模型 图卷积神经网络 谣言检测
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