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Optimal decision-making method for equipment maintenance to enhance the resilience of power digital twin system under extreme disaster

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Global Energy Interconnection 2024年第3期7卷 336-346页

作者： Song Gao Wei Wang jingyi chen Xinyu Wu Junyan Shao Electric Power Scientific Research Institute State Grid Jilin Electric Power CoLtdChangchun132000P.R.China Department of Electrical Engineering Northeast Electric Power UniversityJilin132012P.R.China

Digital twins and the physical assets of electric power systems face the potential risk of data loss and monitoring failures owing to catastrophic events,causing surveillance and energy loss.This study aims to refine maintenance strategies for the monitoring of an electric power digital twin system post disasters.Initially,the research delineates the physical electric power system along with its digital counterpart and post-disaster restoration processes.Subsequently,it delves into communication and data processing mechanisms,specifically focusing on central data processing(CDP),communication routers(CRs),and phasor measurement units(PMUs),to re-establish an equipment recovery model based on these data transmission methodologies.Furthermore,it introduces a mathematical optimization model designed to enhance the digital twin system’s post-disaster monitoring efficacy by employing the branch-and-bound method for its resolution.The efficacy of the proposed model was corroborated by analyzing an IEEE-14 system.The findings suggest that the proposed branch-and-bound algorithm significantly augments the observational capabilities of a power system with limited resources,thereby bolstering its stability and emergency response mechanisms.

关键词： Phasor measurement units Through-sequence optimization Resilience enhancement Communication networks Digital twins

Metabolic profiles and morphological characteristics of leaf tips among different sweet potato(Ipomoea batatas Lam.)varieties

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Journal of Integrative Agriculture 2024年第2期23卷 494-510页

作者： Wenqing Tan Xinbo Guo Zhangying Wang Rong Zhang Chaochen Tang Bingzhi Jiang Ruixue Jia Yuanyuan Deng Shaohai Yang jingyi chen Crops Research Institute Guangdong Academy of Agricultural Sciences/Key Laboratory of Crop Genetic Improvement of Guangdong ProvinceGuangzhou 510640China School of Food Science and Engineering South China University of TechnologyGuangzhou 510640China Sericultural&Agri-Food Research Institute Guangdong Academy of Agricultural Sciences/Key Laboratory of Functional FoodsMinistry of Agriculture and Rural Affairs/Guangdong Key Laboratory of Agricultural Products ProcessingGuangzhou 510610China

Sweet potato leaf tips have high nutritional value,and exploring the differences in the metabolic profiles of leaf tips among different sweet potato varieties can provide information to improve their qualities.In this study,a UPLC-Q-Exactive Orbitrap/MS-based untargeted metabolomics method was used to evaluate the metabolites in leaf tips of 32 sweet potato varieties.Three varieties with distinct overall metabolic profiles(A01,A02,and A03),two varieties with distinct profiles of phenolic acids(A20 and A18),and three varieties with distinct profiles of flavonoids(A05,A12,and A16)were identified.In addition,a total of 163 and 29 differentially expressed metabolites correlated with the color and leaf shape of sweet potato leaf tips,respectively,were identified through morphological characterization.Group comparison analysis of the phenotypic traits and a metabolite-phenotypic trait correlation analysis indicated that the color differences of sweet potato leaf tips were markedly associated with flavonoids.Also,the level of polyphenols was correlated with the leaf shape of sweet potato leaf tips,with lobed leaf types having higher levels of polyphenols than the entire leaf types.The findings on the metabolic profiles and differentially expressed metabolites associated with the morphology of sweet potato leaf tips can provide useful information for breeding sweet potato varieties with higher nutritional value.

关键词： sweet potato leaf tips phenotypic traits metabolic profile differentially expressed metabolites polyphenols

FGF7 enhances the expression of ACE2 in human islet organoids aggravating SARS-CoV-2 infection

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Signal Transduction and Targeted Therapy 2024年第5期9卷 2260-2274页

作者： Hao Meng Zhiying Liao Yanting Ji Dong Wang Yang Han Chaolin Huang Xujuan Hu jingyi chen Hengrui Zhang Zonghong Li Changliang Wang Hui Sun Jiaqi Sun Lihua chen Jiaxiang Yin Jincun Zhao Tao Xu Huisheng Liu School of Biomedical Engineering Guangzhou Medical UniversityGuangzhou 511495 GuangdongChina Guangzhou National Laboratory Guangzhou 510320 GuangdongChina State Key Laboratory of Respiratory Disease National Clinical Research Center for Respiratory DiseaseGuangzhou Institute of Respiratory HealthThe First Affiliated Hospital of Guangzhou Medical UniversityGuangzhou 510120China Center for Translational Medicine Wuhan Jinyintan HospitalWuhan 430023 HubeiChina School of Biomedical Sciences and Engineering South China University of TechnologyGuangzhou 510006 GuangdongChina

The angiotensin-converting enzyme 2(ACE2)is a primary cell surface viral binding receptor for SARS-CoV-2,so finding new regulatory molecules to modulate ACE2 expression levels is a promising strategy against COVID-19.In the current study,we utilized islet organoids derived from human embryonic stem cells(hESCs),animal models and COVID-19 patients to discover that fibroblast growth factor 7(FGF7)enhances ACE2 expression within the islets,facilitating SARS-CoV-2 infection and resulting in impaired insulin secretion.Using hESC-derived islet organoids,we demonstrated that FGF7 interacts with FGF receptor 2(FGFR2)and FGFR1 to upregulate ACE2 expression predominantly inβcells.This upregulation increases both insulin secretion and susceptibility ofβcells to SARS-CoV-2 infection.Inhibiting FGFR counteracts the FGF7-induced ACE2 upregulation,subsequently reducing viral infection and replication in the islets.Furthermore,retrospective clinical data revealed that diabetic patients with severe COVID-19 symptoms exhibited elevated serum FGF7 levels compared to those with mild symptoms.Finally,animal experiments indicated that SARS-CoV-2 infection increased pancreatic FGF7 levels,resulting in a reduction of insulin concentrations in situ.Taken together,our research offers a potential regulatory strategy for ACE2 by controlling FGF7,thereby protecting islets from SARS-CoV-2 infection and preventing the progression of diabetes in the context of COVID-19.

关键词： ACE2 FGF7 islet

A software defect prediction method with metric compensation based on feature selection and transfer learning

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Frontiers of Information Technology & Electronic Engineering 2022年第5期23卷 715-731页

作者： Jinfu chen Xiaoli WANG Saihua CAI Jiaping XU jingyi chen Haibo chen School of Computer Science and Communication Engineering Jiangsu UniversityZhenjiang 212013China Jiangsu Key Laboratory of Security Technology for Industrial Cyberspace Jiangsu UniversityZhenjiang 212013China

Cross-project software defect prediction solves the problem of insufficient training data for traditional defect prediction,and overcomes the challenge of applying models learned from multiple different source projects to target project.At the same time,two new problems emerge:(1)too many irrelevant and redundant features in the model training process will affect the training efficiency and thus decrease the prediction accuracy of the model;(2)the distribution of metric values will vary greatly from project to project due to the development environment and other factors,resulting in lower prediction accuracy when the model achieves cross-project prediction.In the proposed method,the Pearson feature selection method is introduced to address data redundancy,and the metric compensation based transfer learning technique is used to address the problem of large differences in data distribution between the source project and target project.In this paper,we propose a software defect prediction method with metric compensation based on feature selection and transfer learning.The experimental results show that the model constructed with this method achieves better results on area under the receiver operating characteristic curve(AUC)value and F1-measure metric.

关键词： Defect prediction Feature selection Transfer learning Metric compensation

Two-Stage Lesion Detection Approach Based on Dimension-Decomposition and 3D Context

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Tsinghua Science and Technology 2022年第1期27卷 103-113页

作者： Jiacheng Jiao Haiwei Pan Chunling chen Tao Jin Yang Dong jingyi chen the College of Computer Science and Technology Harbin Engineering UniversityHarbin 150001China the School of Software Tsinghua UniversityBeijng 100084China

Lesion detection in Computed Tomography(CT) images is a challenging task in the field of computer-aided diagnosis.An important issue is to locate the area of lesion accurately.As a branch of Convolutional Neural Networks(CNNs),3D Context-Enhanced(3DCE) frameworks are designed to detect lesions on CT scans.The False Positives(FPs) detected in 3DCE frameworks are usually caused by inaccurate region proposals,which slow down the inference time.To solve the above problems,a new method is proposed,a dimension-decomposition region proposal network is integrated into 3DCE framework to improve the location accuracy in lesion detection.Without the restriction of "anchors" on ratios and scales,anchors are decomposed to independent "anchor strings".Anchor segments are dynamically combined in accordance with probability,and anchor strings with different lengths dynamically compose bounding boxes.Experiments show that the accurate region proposals generated by our model promote the sensitivity of FPs and spend less inference time compared with the current methods.

关键词： lesion detection Computed Tomography(CT) dimension-decomposition 3D context computer-aided diagnosis

Time-varying road network design for urban hazmat transportation

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Journal of Management Science and Engineering 2023年第4期8卷 558-569页

作者： jingyi chen Qiuchen Gu Hanwen Yu Wei Zhou Tijun Fan School of Business East China University of Science and TechnologyShanghai 200237China Information&Operations Management Department ESCP Business SchoolParis 75015France School of Economics and Management Minjiang UniversityFuzhou 350108China

Hazmat transportation in cities faces significant risks that may cause catastrophic losses to humans.From the perspective of the regulator,the main responsibility is to mitigate hazmat transport risk by determining the availability of road networks to hazmat carriers.Based on the time-variant population distribution,the hazmat transport risk was assessed via the total population exposure associated with the resident and variable populations at different times.We propose a risk-minimizing urban hazmat road network design model for multiple types of hazmats,considering time-varying traffic.The model was applied to a realistic case study of hazmat transportation in a densely populated urban area with complex traffic in Shanghai,China.

关键词： Hazmat transport Roadclosure Time-varying traffic Network design Population exposure Urbanenvironment

Accuracy controlling and mechanical behaviors of precursor-derived ceramic SiOC microlattices by projection micro stereolithography(PμSL)3D printing

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Journal of Advanced Ceramics 2023年第11期12卷 2134-2147页

作者： Ruyue Su jingyi chen Xueqin Zhang Xiong Gao Wenqing Wang Ying Li Rujie He State Key Laboratory of Explosion Science and Technology Beijing Institute of TechnologyBeijing 100081China Beijing Key Laboratory of Lightweight Multi-functional Composite Materials and Structure Institute of Advanced Structure TechnologyBeijing Institute of TechnologyBeijing 100081China

Precursor-derived ceramic SiOC(PDC-SiOC)microlattices exhibit excellent oxidation resistance,high-temperature stability,and superior mechanical properties.However,the printing accuracy of the PDC-SiOC microlattices by 3D printing is still limited,and mechanical properties of the PDC-SiOC microlattices have not been studied systematically.Here,PDC-SiOC octet microlattices were fabricated by projection micro stereolithography(PμSL)3D printing,and photoabsorber(Sudan III)’s effect on the accuracy was systematically analyzed.The results showed that the addition of Sudan III improved the printing accuracy significantly.Then,the ceramization process of the green body was analyzed in detail.The order of the green body decreased,and most of their chemical bonds were broken during pyrolysis.After that,the PDC-SiOC microlattices with different truss diameters in the range of 52–220μm were fabricated,and their mechanical properties were investigated.The PDC-SiOC microlattices with a truss diameter of 52μm exhibited higher compression strength(31 MPa)than those with bigger truss diameters.The size effect among the PDC-SiOC microlattices was analyzed.Our work provides a deeper insight into the manufacturing of PDC-SiOC micro-scaled architectures by 3D printing and paves a path to the research of the size effect in ceramic structures.

关键词： precursor-derived ceramic(PDC) microlattice projection micro stereolithography(PμSL) accuracy mechanical behaviors

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改进哈里斯鹰算法的仓储机器人路径规划研究

系统仿真学报 2024年第5期36卷 1081-1092页

作者：雷旭陈静夷陈潇阳长安大学电子与控制工程学院陕西西安710064

为提高静态环境下仓储移动机器人路径规划效率,解决传统哈里斯鹰(Harris Hawks optimization, HHO)算法在路径规划中存在收敛速度慢且易陷入局部最优的问题,提出了一种基于Tent混沌映射融合柯西反学习变异的哈里斯鹰优化算法(HHO algori... 详细信息

为提高静态环境下仓储移动机器人路径规划效率,解决传统哈里斯鹰(Harris Hawks optimization, HHO)算法在路径规划中存在收敛速度慢且易陷入局部最优的问题,提出了一种基于Tent混沌映射融合柯西反学习变异的哈里斯鹰优化算法(HHO algorithmbasedon Tentchaotic mapping hybrid Cauchy mutation and inverse learning, TCLHHO)。通过Tent混沌映射增加种群多样性,以提高算法的收敛速度;提出指数型的猎物逃逸能量更新策略,以平衡算法的全局搜索和局部开发能力;通过柯西反学习变异策略对最优个体进行扰动,扩大算法的搜索范围,增强全局搜索能力。根据真实仓储环境搭建二维栅格环境模型,并在Matlab中进行仿真对比实验。结果表明:该算法的规划速度、最优路径长度以及最优路径转折次数较对比算法具有较好的效果,验证了应用于智能仓储环境下改进的HHO路径规划问题的可行性和鲁棒性。

关键词：移动机器人路径规划哈里斯鹰优化算法栅格地图多策略改进

Heterogenous glucose-stimulated insulin secretion at single islet level

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Engineered Regeneration

Engineered Regeneration 2023年第4期4卷 387-395页

作者： Jiaxiang Yin Hao Meng Haopeng Lin Meijun Mo Jingfang Lin jingyi chen Lihua chen Xiaojun Xu Zonghong Li Wei Ji Tao Xu Huisheng Liu School of Biomedical Engineering Guangzhou Medical UniversityGuangzhouChina Guangzhou National Laboratory GuangzhouGuangdongChina Bioland Laboratory GuangzhouGuangdongChina National Laboratory of Biomacromolecules CAS Center for Excellence in BiomacromoleculesInstitute of BiophysicsChinese Academy of SciencesBeijingChina School of Biomedical Sciences and Engineering South China University of TechnologyGuangzhou International CampusGuangzhouChina

Insulin secretion by pancreatic islets plays a vital role in regulating blood glucose levels.Nevertheless,the mech-anism responsible for this dynamic insulin secretion has not been completely understood,particularly at the single islet level.In this study,we have successfully developed an easy microfluidic platform that allows for the exploration of dynamic glucose-stimulated insulin secretion(GSIS)at the single islet level.With the utilization of this platform,we evaluated dynamic GSIS from single islets isolated from both normal and diabetic rats.Our results demonstrate that islets can be categorized into three types based on their dynamic GSIS:Type Ⅰ exhibits a biphasic GSIS profile with a fast first phase and flat second phase;Type Ⅱ also has a biphasic GSIS profile with a fast first phase but a slow increased second phase;Type Ⅲ displays only a slowly increased second phase and lacks a fast first phase.RNA sequencing analysis demonstrated that the cell type and exocytosis-specific genes are consistent with the proportion of cells and insulin release kinetics among the three types of islets,respectively.Moreover,our findings suggest that high expression of Atp5pb is anti-correlated with the first phase of insulin secretion.Furthermore,we revealed that diabetic islets exhibit only the type Ⅰ GSIS response,indicating a deliberate impairment of the second phase of insulin secretion.Together,this device serves as a crucial tool in the research field of islets and diabetes,allowing researchers to investigate islet functional heterogeneity and identity at the single islet level.

关键词： Islet-on-a-chip Single islet Glucose-stimulated insulin secretion Heterogeneity Diabetes