随着网络业务的快速发展和网络技术的快速演进,人们对网络运维的要求也随之提高。当下的网络运维存在自动化程度不足、人才短缺,运维一致性差等问题。AI运维机器人基于NLP(Natural Language Processing,自然语言处理)技术,为运维人员提...随着网络业务的快速发展和网络技术的快速演进,人们对网络运维的要求也随之提高。当下的网络运维存在自动化程度不足、人才短缺,运维一致性差等问题。AI运维机器人基于NLP(Natural Language Processing,自然语言处理)技术,为运维人员提供极简的“对话式”运维操作,智能识别运维意图和操作对象,高效自动化执行任务,有效降低了运维人员的技术门槛,替代烦琐人工操作,有效提升了运维效率,实现了网络运维的提质增效。展开更多
为解决自然语言数据处理模型进行数据处理时存在效果差、资源消耗大等问题,提出一种基于多尺度特征提取和注意力机制的融合算法。通过不同尺度的特征数据提取,并在特征图上应用加权算法,从而增强对某些特定尺度特征的关注,并基于该融合...为解决自然语言数据处理模型进行数据处理时存在效果差、资源消耗大等问题,提出一种基于多尺度特征提取和注意力机制的融合算法。通过不同尺度的特征数据提取,并在特征图上应用加权算法,从而增强对某些特定尺度特征的关注,并基于该融合算法对自然语言数据处理模型进行优化。仿真实验的结果表明:该融合算法特征提取效果较好,显著提升了计算机进行数据处理的各项能力。将优化后的自然语言处理(natural language processing,NLP)数据处理模型与CSAMT数据处理模型、BETG数据处理模型和优化前的NLP数据处理模型的性能进行对比可知:经过CBAM-MS-CNN优化的NLP数据处理模型的各项性能均优于其他模型。研究结果表明:该融合算法可以满足电子化移交流程中非结构化数据管理领域中的高可靠性、智能处理等业务需求,能提升数据处理效率和数据质量,减少人工录入数据和人工复核数据的工作量。展开更多
Nitrate is the primary nitrogen source for plants and is a signaling molecule regulating various plant developmental processes.Despite its significance,limited information is available on nitrate signaling in Vitis vi...Nitrate is the primary nitrogen source for plants and is a signaling molecule regulating various plant developmental processes.Despite its significance,limited information is available on nitrate signaling in Vitis vinifera.We identified nine VvRWPeRK genes distributed across eight chromosomes using genomeewide identification and evolutionary analyses.Among these,VvNLP1e4 and VvRKD1e5 are associated with nitrate signaling and reproductive growth,respectively.To investigate their potential functions,structures,ciseacting promoter elements,functional structural domains,phylogenetic trees,spatiotemporal expression levels in different tissues at different developmental stages,potential proteineprotein interaction networks,synteny(gene content),collinearity(gene order),and threeedimensional protein structure prediction were explored.We found that longeterm nitrate application dramatically promoted grapevine plantlet development,including primary root length and leaf growth,and VvNLP1.1,VvNLP1.2,and VvNLP2 were highly expressed in‘Thompson Seedless'root tissues under nitrateeenriched conditions.To clarify the critical role of nitrate in grapevine growth,we observed that nuclear localization of VvNLP1.1 increased significantly following nitrate treatment.VvNLP1.1 was found to bind to the promoter of the primary nitrate response gene VvNRT1.1,driving its transcriptional activity.These findings indicate that VvNLP1.1 is a core transcription factor of the nitrate signaling pathway in grapevine.Nitrate molecular docking analysis revealed that VvNLP1.1 directly binds to nitrate ions,indicating its potential role as a nitrate sensor capable of directly perceiving nitrate concentration.We also discovered that shorteterm nitrate starvation impacts VvNLP1.1 promoter activity,linked to the abscisic acidebinding element(ABRE)motif in its promoter region.Our results thus provide new insights into the molecular mechanisms underlying various physiological processes in grapevine,particularly the nitrate signaling pathway,and provide a theoretical basis for improving nitrogen use efficiency(NUE)in grapevine.展开更多
文摘随着网络业务的快速发展和网络技术的快速演进,人们对网络运维的要求也随之提高。当下的网络运维存在自动化程度不足、人才短缺,运维一致性差等问题。AI运维机器人基于NLP(Natural Language Processing,自然语言处理)技术,为运维人员提供极简的“对话式”运维操作,智能识别运维意图和操作对象,高效自动化执行任务,有效降低了运维人员的技术门槛,替代烦琐人工操作,有效提升了运维效率,实现了网络运维的提质增效。
文摘为解决自然语言数据处理模型进行数据处理时存在效果差、资源消耗大等问题,提出一种基于多尺度特征提取和注意力机制的融合算法。通过不同尺度的特征数据提取,并在特征图上应用加权算法,从而增强对某些特定尺度特征的关注,并基于该融合算法对自然语言数据处理模型进行优化。仿真实验的结果表明:该融合算法特征提取效果较好,显著提升了计算机进行数据处理的各项能力。将优化后的自然语言处理(natural language processing,NLP)数据处理模型与CSAMT数据处理模型、BETG数据处理模型和优化前的NLP数据处理模型的性能进行对比可知:经过CBAM-MS-CNN优化的NLP数据处理模型的各项性能均优于其他模型。研究结果表明:该融合算法可以满足电子化移交流程中非结构化数据管理领域中的高可靠性、智能处理等业务需求,能提升数据处理效率和数据质量,减少人工录入数据和人工复核数据的工作量。
基金supported by the National Natural Science Foundation of China(Grant Nos.32260727,32472670,and 32371924)the Natural Science Foundation of Ningxia(Grant Nos.2024AAC02039 and 2022AAC02024)+2 种基金the Key Research and Development Program of Xinjiang Province(Grant No.2022B02034-3)the Key Research and Development Program of Ningxia Province(Grant No.2024BBF01003)the Science and Technology Plan Project of Xi'an City(Grant No.23NYGG0028).
文摘Nitrate is the primary nitrogen source for plants and is a signaling molecule regulating various plant developmental processes.Despite its significance,limited information is available on nitrate signaling in Vitis vinifera.We identified nine VvRWPeRK genes distributed across eight chromosomes using genomeewide identification and evolutionary analyses.Among these,VvNLP1e4 and VvRKD1e5 are associated with nitrate signaling and reproductive growth,respectively.To investigate their potential functions,structures,ciseacting promoter elements,functional structural domains,phylogenetic trees,spatiotemporal expression levels in different tissues at different developmental stages,potential proteineprotein interaction networks,synteny(gene content),collinearity(gene order),and threeedimensional protein structure prediction were explored.We found that longeterm nitrate application dramatically promoted grapevine plantlet development,including primary root length and leaf growth,and VvNLP1.1,VvNLP1.2,and VvNLP2 were highly expressed in‘Thompson Seedless'root tissues under nitrateeenriched conditions.To clarify the critical role of nitrate in grapevine growth,we observed that nuclear localization of VvNLP1.1 increased significantly following nitrate treatment.VvNLP1.1 was found to bind to the promoter of the primary nitrate response gene VvNRT1.1,driving its transcriptional activity.These findings indicate that VvNLP1.1 is a core transcription factor of the nitrate signaling pathway in grapevine.Nitrate molecular docking analysis revealed that VvNLP1.1 directly binds to nitrate ions,indicating its potential role as a nitrate sensor capable of directly perceiving nitrate concentration.We also discovered that shorteterm nitrate starvation impacts VvNLP1.1 promoter activity,linked to the abscisic acidebinding element(ABRE)motif in its promoter region.Our results thus provide new insights into the molecular mechanisms underlying various physiological processes in grapevine,particularly the nitrate signaling pathway,and provide a theoretical basis for improving nitrogen use efficiency(NUE)in grapevine.
