This study presents a systematic review of applications of artificial intelligence(abbreviated as AI)and blockchain in supply chain provenance traceability and legal forensics cover five sectors:integrated circuits(ab...This study presents a systematic review of applications of artificial intelligence(abbreviated as AI)and blockchain in supply chain provenance traceability and legal forensics cover five sectors:integrated circuits(abbreviated as ICs),pharmaceuticals,electric vehicles(abbreviated as EVs),drones(abbreviated as UAVs),and robotics—in response to rising trade tensions and geopolitical conflicts,which have heightened concerns over product origin fraud and information security.While previous literature often focuses on single-industry contexts or isolated technologies,this reviewcomprehensively surveys these sectors and categorizes 116 peer-reviewed studies by application domain,technical architecture,and functional objective.Special attention is given to traceability control mechanisms,data integrity,and the use of forensic technologies to detect origin fraud.The study further evaluates real-world implementations,including blockchain-enabled drug tracking systems,EV battery raw material traceability,and UAV authentication frameworks,demonstrating the practical value of these technologies.By identifying technological challenges and policy implications,this research provides a comprehensive foundation for future academic inquiry,industrial adoption,and regulatory development aimed at enhancing transparency,resilience,and trust in global supply chains.展开更多
The global automotive sector is moving towards zero-emission transportation,which has led to the rapid growthof the electric vehidles(EVs)market,projected to reach USD1,318 billion in 2028.However,behind the booming d...The global automotive sector is moving towards zero-emission transportation,which has led to the rapid growthof the electric vehidles(EVs)market,projected to reach USD1,318 billion in 2028.However,behind the booming develop-ment of the electric vehicle market,its safety issues havealways been the focal point of consumers'concern and alsothe cornerstone for the sustained and healthy developmentof the new energy vehicle industry.展开更多
目的:比较TIPSS和EVS治疗食管静脉曲张破裂出血的疗效,治疗前后两组患者肝功能的变化和术后患者的死亡原因方法:回顾性分析两组各18例经TIPSS和EVS治疗的食管静脉曲张破裂出血患者在治疗后不同时间的死亡率,再出血率及治疗前后血浆白蛋...目的:比较TIPSS和EVS治疗食管静脉曲张破裂出血的疗效,治疗前后两组患者肝功能的变化和术后患者的死亡原因方法:回顾性分析两组各18例经TIPSS和EVS治疗的食管静脉曲张破裂出血患者在治疗后不同时间的死亡率,再出血率及治疗前后血浆白蛋白和胆红素的变化。结果:TIPSS组在术后30 d的死亡率略低于硬化剂治疗组(16.67％ vs 22.22％),术后1a,两组的死亡率比较有显著差异(22.22％ vs 44.44％);术后2a,TIPSS组仍略低于EVS组(38.89％ vs 50.00％),但差异无显著性,在术后2a的随诊期内,EVS组的再出血率高于TIPSS组。与EVS组比较,TIPSS组患者术后肝功能的降低更明显。结论:TIPSS治疗的近期疗效优于EVS治疗,中远期疗效的对比尚需进一步的观察。TIPSS术后肝功能的衰竭是本组患者治疗后死亡的主要原因,而EVS组患者的术后死亡与再出血密切相关。展开更多
聚类方法的核心是如何度量事物间的邻近性。介绍了邮件特征的向量表示形式、构建了邮件特征矩阵,并使用变形后的极值分布函数模型拟合了邮件间通信特征信息;在此基础上提出了一个新的邻近性度量方法(ex-treme value distribution simila...聚类方法的核心是如何度量事物间的邻近性。介绍了邮件特征的向量表示形式、构建了邮件特征矩阵,并使用变形后的极值分布函数模型拟合了邮件间通信特征信息;在此基础上提出了一个新的邻近性度量方法(ex-treme value distribution similarity,EVS),用以指导邮件社区划分;使用微聚类-宏聚类邮件社区划分算法验证了该方法的有效性。实验表明,在测试数据集上,相比余弦、PCC等经典的邻近性度量方法,以EVS作为划分依据的邮件社区划分算法能够更加有效地发现高质量的邮件社区。展开更多
文摘This study presents a systematic review of applications of artificial intelligence(abbreviated as AI)and blockchain in supply chain provenance traceability and legal forensics cover five sectors:integrated circuits(abbreviated as ICs),pharmaceuticals,electric vehicles(abbreviated as EVs),drones(abbreviated as UAVs),and robotics—in response to rising trade tensions and geopolitical conflicts,which have heightened concerns over product origin fraud and information security.While previous literature often focuses on single-industry contexts or isolated technologies,this reviewcomprehensively surveys these sectors and categorizes 116 peer-reviewed studies by application domain,technical architecture,and functional objective.Special attention is given to traceability control mechanisms,data integrity,and the use of forensic technologies to detect origin fraud.The study further evaluates real-world implementations,including blockchain-enabled drug tracking systems,EV battery raw material traceability,and UAV authentication frameworks,demonstrating the practical value of these technologies.By identifying technological challenges and policy implications,this research provides a comprehensive foundation for future academic inquiry,industrial adoption,and regulatory development aimed at enhancing transparency,resilience,and trust in global supply chains.
文摘The global automotive sector is moving towards zero-emission transportation,which has led to the rapid growthof the electric vehidles(EVs)market,projected to reach USD1,318 billion in 2028.However,behind the booming develop-ment of the electric vehicle market,its safety issues havealways been the focal point of consumers'concern and alsothe cornerstone for the sustained and healthy developmentof the new energy vehicle industry.
文摘目的:比较TIPSS和EVS治疗食管静脉曲张破裂出血的疗效,治疗前后两组患者肝功能的变化和术后患者的死亡原因方法:回顾性分析两组各18例经TIPSS和EVS治疗的食管静脉曲张破裂出血患者在治疗后不同时间的死亡率,再出血率及治疗前后血浆白蛋白和胆红素的变化。结果:TIPSS组在术后30 d的死亡率略低于硬化剂治疗组(16.67％ vs 22.22％),术后1a,两组的死亡率比较有显著差异(22.22％ vs 44.44％);术后2a,TIPSS组仍略低于EVS组(38.89％ vs 50.00％),但差异无显著性,在术后2a的随诊期内,EVS组的再出血率高于TIPSS组。与EVS组比较,TIPSS组患者术后肝功能的降低更明显。结论:TIPSS治疗的近期疗效优于EVS治疗,中远期疗效的对比尚需进一步的观察。TIPSS术后肝功能的衰竭是本组患者治疗后死亡的主要原因,而EVS组患者的术后死亡与再出血密切相关。
文摘聚类方法的核心是如何度量事物间的邻近性。介绍了邮件特征的向量表示形式、构建了邮件特征矩阵,并使用变形后的极值分布函数模型拟合了邮件间通信特征信息;在此基础上提出了一个新的邻近性度量方法(ex-treme value distribution similarity,EVS),用以指导邮件社区划分;使用微聚类-宏聚类邮件社区划分算法验证了该方法的有效性。实验表明,在测试数据集上,相比余弦、PCC等经典的邻近性度量方法,以EVS作为划分依据的邮件社区划分算法能够更加有效地发现高质量的邮件社区。
