检索结果-内蒙古大学图书馆

AcWRKY28 mediated activation of AcCPK genes confers salt tolerance in pineapple(Ananas comosus)

Horticultural Plant Journal 2024年第2期10卷 398-412页

作者： Qiao Zhou Samaranayaka Vidana Gamage Nirosha Priyadarshani Rongjuan Qin Han Cheng Tiantian Luo Myat Hnin Wai Mohammad Aqa Mohammadi Yanhui Liu Chang Liu Hanyang Cai Xiaomei Wang Yeqiang Liu Yuan Qin Lulu Wang Guangxi Key Lab of Sugarcane Biology State Key Laboratory for Conservation and Utilization of Subtropical Agro-BioresourcesCollege of AgricultureGuangxi UniversityNanningGuangxi 530004China State Key Laboratory of Ecological Pest Control for Fujian and Taiwan Crops College of Life ScienceCollege of Plant ProtectionCollege of AgricultureCollege of HorticultureFujian Provincial Key Laboratory of Haixia Applied Plant Systems BiologyCenter for Genomics and BiotechnologyFujian Agriculture and Forestry UniversityFuzhouFujian 350002China Pingtan Science and Technology Research Institute of Fujian Agriculture and Forestry University PingtanFujian 350400China National Education Commission BMICHColombo00700Sri Lanka Fishery Multiplication Management Station of Lijiang River Water Supply Hub Project GuilinGuangxi 541001China Horticulture Research Institute Guangxi Academy of Agricultural SciencesNanning Investigation Station of South Subtropical Fruit TreesMinistry of AgricultureNanningGuangxi 530007China

Unfavorable environmental cues severely affect crop productivity resulting in significant economic losses to farmers. In plants, multiple regulatory genes, such as the WRKY transcription factor (TF) family, modulate the expression of defense genes. However, the role of the pineapple WRKY genes is poorly understood. Here, we studied the pineapple WRKY gene, AcWRKY28, by generating AcWRKY28 over-expressing transgenic pineapple plants. Overexpression of AcWRKY28 enhanced the salt stress resistance in transgenic pineapple lines. Comparative transcriptome analysis of transgenic and wild-type pineapple plants showed that “plant-pathogen interaction” pathway genes, including 9calcium-dependent protein kinases (CPKs), were up-regulated in AcWRKY28 over-expressing plants. Furthermore, chromatin immunoprecipitation and yeast one-hybrid assays revealed AcCPK12, AcCPK3, AcCPK8, AcCPK1, and AcCPK15 as direct targets of AcWRKY28. Consistently, the study of AcCPK12 over-expressing Arabidopsis lines showed that AcCPK12 enhances salt, drought, and disease resistance. This study shows that AcWRKY28 plays a crucial role in promoting salt stress resistance by activating the expression of AcCPK genes.

关键词： Pineapple AcWRKY AcCPK Transcription factor Salt stress ChIP

来源：评论

学校读者我要写书评

暂无评论

Call for V&VIV: Verification and Validation of Intelligent Vehicles

引用

IEEE Transactions on Intelligent Vehicles 2022年第3期7卷 401-406页

作者： Fei-Yue Wang Javier Ibanez-Guzman Yisheng Lv State Key Laboratory for Management and Control of Complex Systems Institute of Automation Chinese Academy of Sciences Beijing China Expert Autonomous Systems Artificial Intelligence Renault S.A. SIVALab CNRS Common Laboratory Chateau Renault France

Presents a summary of articles included in this issue of the publication.

关键词：

来源：评论

学校读者我要写书评

暂无评论

MetaSensing in Metaverses: See There, Be There, and Know There

引用

IEEE INTELLIGENT systems 2022年第6期37卷 7-12页

作者： Liu, Yuhang Shen, Yu Guo, Chao Tian, Yonglin Wang, Xiao Zhu, Yin Wang, Fei-Yue Univ Chinese Acad Sci Sch Artificial Intelligence Beijing 100049 Peoples R China Chinese Acad Sci State Key Lab Management & Control Complex Syst Beijing 100190 Peoples R China Chinese Acad Sci Inst Automation Beijing 100190 Peoples R China Anhui Univ Hefei 266114 Peoples R China North Automatic Control Technol Inst Taiyuan 030006 Peoples R China Macau Univ Sci & Technol Macao Inst Syst Engn Macau 999078 Peoples R China

The concept of metaverses has received extensive attention recently and cyber-physical-social systems (CPSS) is its academic foundation. In almost all the applications of metaverses, the sensing system is an essential part and intelligent sensing capacity must be provided. However, due to the insufficient consideration of human factors in most of the studies, digital twins' sensing in cyber-physical systems cannot achieve smart sensing in metaverses. For this reason, a novel framework for intelligent sensing in metaverses, MetaSensing, is proposed based on parallel intelligence in CPSS. Within the framework of MetaSensing, there are four states of sensing: physical sensing, descriptive sensing, predictive sensing, and prescriptive sensing. To protect sensors' data privacy in metaverses, DAO-based decentralized sensing is introduced as a mechanism of the operation and maintenance for smart sensing industries.

关键词： Industries Data privacy Data security Organizations Human factors Maintenance engineering Real-time systems

来源：评论

学校读者我要写书评

暂无评论

A Learning Method for Feature Correspondence with Outliers 26

A Learning Method for Feature Correspondence with Outliers

引用

26th International Conference on Pattern Recognition / 8th International Workshop on Image Mining - Theory and Applications (IMTA)

作者： Yang, Xu Zeng, Shao-Feng Han, Yu Lu, Yu-Chen Liu, Zhi-Yong Chinese Acad Sci Inst Automat State Key Lab Management & Control Complex Syst Beijing Peoples R China Univ Chinese Acad Sci Beijing Peoples R China Chinese Acad Sci Hong Kong Inst Sci & Innovat Ctr Artificial Intelligence & Robot Hong Kong Peoples R China

ISBN: (数字)9781665490627

ISBN: (纸本)9781665490627

Feature correspondence is an important topic in many computer vision or robot vision tasks. Different from traditional optimization based matching method, in the last two years, researchers are finally able to solve the matching process in a learning manner. As a representative method, SuperGlue achieves superior performance in many real-world tasks, but it still has problems in dealing with outlier features. Targeting at the outlier problem, this paper improves SuperGlue by introducing a deep learning based feature correspondence method, which consists of the pruned attentional graph neural network and the improved matching layer for the outlier problem. Experiments on real world images validate the effectiveness of the proposed method.

关键词： Learning systems Deep learning Computer vision Robot vision systems Graph neural networks Pattern recognition Task analysis

来源：评论

学校读者我要写书评

暂无评论

A Collaborative Robot Torque Prediction Method Based on CNN-TCN Model

A Collaborative Robot Torque Prediction Method Based on CNN-...

引用

IEEE International Conference on Real-time Computing and Robotics (RCAR)

作者： Lina Tong Decheng Cui Chen Wang Liang Peng School of Mechanical Electronic and Information Engineering China University of Mining and Technology Beijing Beijing China State Key Laboratory of Management and Control for Complex Systems (SKLMCCS) Institute of Automation Chinese Academy of Science Beijing China

The traditional dynamical models show lower accuracy when predicting joint movement, and should be compensated. This paper proposed a model combined with the convolutional network(CNN) and temporal convolutional network(TCN) to compensate for the joint torque prediction values that are calculated from the sensing information. The experiments on the Cooperative Universal Robotic Assistant 6 DoF(CURA6) open dataset, including multi-load and multi-velocity, showed the prediction error can be reduced by 20% compared to other network models. Since there are many kinds of joint movement information, the input data form of the deep learning model should be improved. Thus, the kinetic linearization model is proposed to modify the input of sensing data. According to the different motion types of the CURA6 dataset, comparative experiments were taken, and the mean absolute error was less than 6.8%.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Sparse online kernelized actor-critic Learning in reproducing kernel Hilbert space

引用

ARTIFICIAL INTELLIGENCE REVIEW 2022年第1期55卷 23-58页

作者： Yang, Yongliang Zhu, Hufei Zhang, Qichao Zhao, Bo Li, Zhenning Wunsch, Donald C. Univ Sci & Technol Beijing Sch Automat & Elect Engn Beijing 100083 Peoples R China Chinese Acad Sci Inst Automat State Key Lab Management & Control Complex Syst Beijing 100190 Peoples R China Univ Chinese Acad Sci Beijing Peoples R China Beijing Normal Univ Sch Syst Sci Beijing 100875 Peoples R China Univ Macau State Key Lab Internet Things Smart City Taipa 59193 Macao Peoples R China Missouri Univ Sci & Technol Dept Elect & Comp Engn Rolla MO 65401 USA

In this paper, we develop a novel non-parametric online actor-critic reinforcement learning (RL) algorithm to solve optimal regulation problems for a class of continuous-time affine nonlinear dynamical systems. To deal with the value function approximation (VFA) with inherent nonlinear and unknown structure, a reproducing kernel Hilbert space (RKHS)-based kernelized method is designed through online sparsification, where the dictionary size is fixed and consists of updated elements. In addition, the linear independence check condition, i.e., an online criteria, is designed to determine whether the online data should be inserted into the dictionary. The RHKS-based kernelized VFA has a variable structure in accordance with the online data collection, which is different from classical parametric VFA methods with a fixed structure. Furthermore, we develop a sparse online kernelized actor-critic learning RL method to learn the unknown optimal value function and the optimal control policy in an adaptive fashion. The convergence of the presented kernelized actor-critic learning method to the optimum is provided. The boundedness of the closed-loop signals during the online learning phase can be guaranteed. Finally, a simulation example is conducted to demonstrate the effectiveness of the presented kernelized actor-critic learning algorithm.

关键词： Reproducing kernel Hilbert space Actor-critic learning Value function approximation Online sparsification Non-parametric learning

来源：评论

学校读者我要写书评

暂无评论

Spatio-Temporal Causal Transformer for Multi-Grained Surgical Phase Recognition 44

Spatio-Temporal Causal Transformer for Multi-Grained Surgica...

引用

44th Annual International Conference of the IEEE-Engineering-in-Medicine-and-Biology-Society (EMBC)

作者： Chen, Hua-Bin Li, Zhen Fu, Pan Ni, Zhen-Liang Bian, Gui-Bin Chinese Acad Sci Inst Automat State Key Lab Management & Control Complex Syst Beijing 100190 Peoples R China Univ Chinese Acad Sci Sch Artificial Intelligence Beijing 100049 Peoples R China Beijing Informat Sci & Technol Univ Sch Automat Beijing 100101 Peoples R China

ISBN: (数字)9781728127828

ISBN: (纸本)9781728127828

Automatic surgical phase recognition plays a key role in surgical workflow analysis and overall optimization in clinical work. In the complicated surgical procedures, similar inter-class appearance and drastic variability in phase duration make this still a challenging task. In this paper, a spatio-temporal transformer is proposed for online surgical phase recognition with different granularity. To extract rich spatial information, a spatial transformer is used to model global spatial dependencies of each time index. To overcome the variability in phase duration, a temporal transformer captures the multi-scale temporal context of different time indexes with a dual pyramid pattern. Our method is thoroughly validated on the public Cholec80 dataset with 7 coarse-grained phases and the CATARACTS2020 dataset with 19 fine-grained phases, outperforming state-of-the-art approaches with 91.4% and 84.2% accuracy, taking only 24.5M parameters.

关键词： Surgery Color Transformers Biology Indexes Data mining Task analysis

来源：评论

学校读者我要写书评

暂无评论

Parallel System-Based Predictive control for Traffic Signals in Large-Scale Road Networks 26

Parallel System-Based Predictive Control for Traffic Signals...

引用

IEEE 26th International Conference on Intelligent Transportation systems (ITSC)

作者： Dai, Xingyuan Zhang, Yan Tang, Yiqing Chen, Hongrui Sun, Jiaming Cong, Fei Lu, Yanan Lv, Yisheng Univ Chinese Acad Sci Sch Artificial Intelligence Beijing 100049 Peoples R China Chinese Acad Sci State Key Lab Management & Control Complex Syst Inst Automat Beijing 100190 Peoples R China China Telecom Digital City Technol Co Ltd Xiongan 071700 Peoples R China China Univ Geosci Beijing Sch Informat Engn Beijing 100083 Peoples R China

ISBN: (纸本)9798350399462

This paper proposes a parallel system-based predictive control (PPC) method to address the problem of active traffic signal control in large-scale urban road networks. The method leverages simulated artificial transportation systems to infer the short-term future operating states of the real transportation system. During the inference process, an efficient predictive learning-based multi-agent reinforcement learning (RL) algorithm is employed to optimize the cooperative control policies. The optimized policies are then deployed to the real transportation system at fixed intervals to adapt to the real-time and dynamic traffic flow. Experimental results demonstrate that PPC outperforms traditional traffic control methods and some multi-agent RL benchmarks in large-scale road network control scenarios with nearly two hundred intersections, showcasing superior generalization capabilities.

关键词： Roads and streets

来源：评论

学校读者我要写书评

暂无评论

Adaptively temporal graph convolution model for epidemic prediction of multiple age groups

引用

Fundamental Research 2022年第2期2卷 311-320页

作者： Yuejiao Wang Dajun Daniel Zeng Qingpeng Zhang Pengfei Zhao Xiaoli Wang Quanyi Wang Yin Luo Zhidong Cao The State Key Laboratory of Management and Control for Complex Systems Institute of AutomationChinese Academy of SciencesBeijingChina School of Artificial Intelligence University of Chinese Academy of SciencesBeijingChina Shenzhen Artificial Intelligence and Data Science Institute(Longhua) ShenzhenChina School of Data Science City University of Hong Kong-Hong Kong SARChina Institute for Infectious Disease and Endemic Disease Control Beijing Center for Disease Prevention and Control BeijingChina

Introduction:Multivariate time series prediction of infectious diseases is significant to public health,and the deep learning method has attracted increasing attention in this research *** and methods:An adaptively temporal graph convolution(ATGCN)model,which leams the contact patterns of multiple age groups in a graph-based approach,was proposed for COVID-19 and influenza *** compared ATGCN with autoregressive models,deep sequence learning models,and experience-based ATGCN models in short-term and long-term prediction ***:Results showed that the ATGCN model performed better than the autoregressive models and the deep sequence learning models on two datasets in both short-term(12.5%and 10%improvements on RMSE)and longterm(12.4%and 5%improvements on RMSE)prediction *** the RMSE of ATGCN predictions fluctuated least in different age groups of COVID-19(0.029±0.003)and influenza(0.059±0.008).Compared with the Ones-ATGCN model or the Pre-ATGCN model,the ATGCN model was more robust in performance,with RMSE of 0.0293 and 0.06 on two datasets when horizon is ***:Our research indicates a broad application prospect of deep learning in the field of infectious disease *** characteristics and domain knowledge of infectious diseases should be further applied to the design of deep learning models and feature ***:The ATGCN model addressed the multivariate time series forecasting in a graph-based deep learning approach and achieved robust prediction on the confirmed cases of multiple age groups,indicating its great potentials for exploring the implicit interactions of multivariate variables.

关键词： Graph convolution model Infectious disease prediction Multiple age group Multivariate time series Public health

来源：评论

学校读者我要写书评

暂无评论

iMAPeM: A New Paradigm for Implementing Intelligent Mining With Humans in the Loop

引用

IEEE TRANSACTIONS ON systems MAN CYBERNETICS-systems 2024年第12期54卷 7536-7547页

作者： Ai, Yunfeng Teng, Siyu Yang, Qingyuan Wu, Ye Li, Yuchen Gao, Yu Meng, Feng Yang, Shengli Tian, Bin Chen, Long Wang, Fei-Yue Univ Chinese Acad Sci Artificial Intelligence Dept Beijing 100049 Peoples R China Waytous Inc Qingdao 266109 Peoples R China Hong Kong Baptist Univ Dept Comp Sci Hong Kong Peoples R China Guoneng Baorishile Energy Co Ltd Hulunbuir 021000 Peoples R China CHN Energy Investment Grp Co Ltd Beijing 100190 Peoples R China Chinese Acad Sci Inst Automat State Key Lab Management & Control Complex Syst Beijing 100045 Peoples R China Univ Chinese Acad Sci Sch Artificial Intelligence Beijing 100190 Peoples R China

Since the 1990s, the automated process within open-pit mines has been rapidly advanced. However, mineral transportation, as the most costly and dangerous production process, has not witnessed efficient achievements. Adverse weather conditions and complex work environments are two critical bottlenecks that impede the development and deployment of autonomous transportation of open-pit mines. To alleviate this issue, this research proposes a novel paradigm, named IMAPeM, designed to enable safe and efficient autonomous transportation with humans in the loop. IMAPeM includes three categories of miners: 1) biological miners;2) digital miners;and 3) robotic miners, as well as three operational modes: 1) autonomous model (AM);2) parallel model (PM);and 3) expert/emergency model (EM). IMAPeM employs these miners and modes depend on the complexity of the task, optimizing the utilization of digital and robotic miners while reducing the workload for biological miners. In addition, we developed the YUGONG system based on IMAPeM. The empirical implementation demonstrates the exceptional performance of the YUGONG system in autonomous transportation across diverse open-pit mines. This system contributes to the advancement of sustainable mining practices, which also carries profound significance for achieving long-term environmentally responsible mining operations.

关键词： Autonomous transportation intelligent mining parallel driving operating system parallel systems theory

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：