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Hybrid Adaptive Event-Triggered Consensus Control with Intermittent Communication and Control Updating

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Journal of Systems Science & Complexity 2024年

作者： YUAN Shuo YU Chengpu sun jian School of Automation Beijing Institute of Technology Beijing Institute of Technology Chongqing Innovation Center

This paper studies the distributed consensus control for linear multi-agent systems under discontinuous communication and control updating. A fully distributed event-triggered adaptive control protocol with strictly positive minimum interevent time(MIET) guarantees is proposed. First, an event-triggered distributed adaptive control law without using prior global information of network topologies is presented, which achieves asymptotic consensus via discrete control updating and intermittent communication. Then, a hybrid adaptive event-triggering scheme with an internal timer is designed that is activated only when the timer decreases to zero from a specified positive value. Under the proposed triggering scheme, not only Zeno behavior is excluded but also a strictly positive MIET between any two consecutive events is guaranteed, which facilitates the physical implementation. In contrast to the existing related results, the proposed fully distributed protocol only needs low-frequency communication and control updating, while ensuring the strictly positive MIET property. Finally, a simulation example is given to illustrate the effectiveness of the theoretical results.

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Performance Analysis of an Efficient Integration System of Coal-Fired Power Plant,Solar Thermal Energy and CO2 Capture

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Journal of Thermal Science 2024年第4期33卷 1509-1522页

作者： WANG Yuhao WANG Ruilin LIU Lanhua XING Chenjian GUO Yafei YANG Qingshan YING Jiaheng sun jian LI Wenjia LIU Yuanyuan ZHAO Chuanwen School of Energy and Mechanical Engineering Nanjing Normal University China Huadian Group Co.LTD.Shanghai Branch Key Laboratory of Efficient Utilization of Low and Medium Grade Energy(Tianjin University) Ministry of Education of China Huadian Zhengzhou Mechanical Design Institute Company Limited

Coal-fired power plant is a major contributor to greenhouse gas emissions.The post-combustion capture is a promising method for CO2emission reduction but the high thermal demand is unbearable.To address this issue,solar thermal energy and CO2capture are jointly integrated into the coal-fired power plant in this study.The solar thermal energy is employed to meet the heat requirement of the CO2capture process,thereby avoiding the electricity loss caused by self-driven CO2capture.Furthermore,the heat released from the carbonation reaction of MgO adsorbent is integrated into the steam Rankine cycle.By partially substituting the extracted steam for feedwater heating,the electricity output of the power plant is further increased.According to the results from the developed model,the system could achieve a CO2capture rate of 86.5% and an electricity output enhancement of 9.8% compared to the reference system,which consists of a self-driven CO2capture coal-fired power plant and PV generation unit.The operational strategy is also optimized and the amount of CO2emission reduction on a typical day is increased by 11.06%.This work shows a way to combine fossil fuels and renewable energy for low carbon emissions and efficient power generation.

关键词： CO 2 capture parabolic trough collector solar aided coal-fired electricity generation

Effectiveness and safety of Jiawei Xiaoyao pill(加味逍遥丸)in the treatment of premenstrual syndrome(liver depression,spleen deficiency,and blood-heat syndrome):a multi-center,randomized,placebo-controlled trial

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Journal of Traditional Chinese Medicine 2024年第2期44卷 373-380页

作者： LI Xiyu YANG Yanhong sun jian NIE Quanfang LIU Lifen LI Guifen YU Junping ZHANG Zhuangjin XU Yi ZOU Ting SHI Yun Department of Gynecology Dongzhimen HospitalBeijing University of Chinese MedicineBeijing 100700China Department of Gynecology Luoyang 1st Hospital of TCMLuoyang 471099China Department of Gynecology Zaozhuang Hospital of TCMZaozhuang 277099China Department of Gynecology and Obstetrics Loudi Central HospitalLoudi 417099China Department of Gynecology and Obstetrics Yiyang 1st Hospital of TCMYiyang 413002China Department of Gynecology Harrison International Peace HospitalHengshui 053000China Department of Gynecology and Obstetrics Shanxi Fenyang HospitalFenyang 032299China Department of Gynecology and Obstetrics Hengyang Chinese Medicine HospitalHengyang 421001China Scientific Research Institute of Beijing Tongrentang Technology Development Co. Ltd.Beijing 100061China Female Reproductive and Health Medicine Research Committee of Chinese Traditional Medicine Association Beijing 100061China

OBJECTIVE:To investigate the effectiveness and safety of Jiawei Xiaoyao pill(加味逍遥丸,JXP)in the treatment of symptoms associated with premenstrual syndrome(PMS).METHODS:A total of 144 regularly menstruating women with PMS were recruited at 8 sites in China from August 2017 to December 2018,and randomized to receive either a JXP or a matching placebo(12 g/d,6 g twice a day)for 3 menstrual cycles.The primary indicator was the reduced Daily Record of Severity of Problems(DRSP)scores in the luteal phase after 3 months of treatment.The safety outcomes included clinical adverse events(AEs),adverse reactions(ARs),changes in vital signs,and laboratory tests.RESULTS:JXP surpassed the placebo in reducing DRSP scores(psychological/somatic dysfunction)in the luteal phase over 3 menstrual cycles of treatment(PFAS=0.002,PPPS=0.001).Additionally,there were no significant differences in the incidence of AEs,severe AEs,withdrawal due to AEs and ARs between the two groups(all P>0.05),and no clinically significant adverse medical events related to the test drug observed.CONCLUSIONS:JXP was superior to the placebo in relieving the symptoms associated with PMS,which signified that JXP may be effective,safe,and welltolerated as an alternative therapy.

关键词： premenstrual syndrome randomized controlled trial double-blind method Jiawei Xiaoyao pill

Exploring changes of precipitation extremes under climate change through global variable-resolution modeling

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Science Bulletin 2024年第2期69卷 237-247页

作者： Wei sun jian Li Rucong Yu Nina Li Yi Zhang State Key Laboratory of Severe Weather Chinese Academy of Meteorological SciencesBeijing 100081China Institute of Tibetan Plateau Meteorology China Meteorological AdministrationChengdu 610072China Department of Atmospheric Science Yunnan UniversityKunming 650091China National Meteorological Center China Meteorological AdministrationBeijing 100081China 2035 Future Laboratory PIESAT Information Technology Co.Ltd.Beijing 100105China

Understanding the responses of precipitation extremes to global climate change remains limited owing to their poor representations in models and complicated interactions with multi-scale systems.Here we take the record-breaking precipitation over China in 2021 as an example,and study its changes under three different climate scenarios through a developed pseudo-global-warming(PGW)experimental framework with 60-3 km variable-resolution global ensemble modeling.Compared to the present climate,the precipitation extreme under a warmer(cooler)climate increased(decreased)in intensity,coverage,and total amount at a range of 24.3%-37.8%(18.7%-56.1%).With the help of the proposed PGW experimental framework,we further reveal the impacts of the multi-scale system interactions in climate change on the precipitation extreme.Under the warmer climate,large-scale water vapor transport converged from double typhoons and the subtropical high marched into central China,enhancing the convective energy and instability on the leading edge of the transport belt.As a result,the mesoscale convective system(Mcs)that directly contributed to the precipitation extreme became stronger than that in the present climate.On the contrary,the cooler climate displayed opposite changing characteristics relative to the warmer climate,ranging from the large-scale systems to local environments and to the Mcs.In summary,our study provides a promising approach to scientifically assess the response of precipitation extremes to climate change,making it feasible to perform ensemble simulations while investigating the multi-scale system interactions over the globe.

关键词： Precipitation extreme Climate change Pseudo-global-warming experiment Variable-resolution modeling Multi-scale system interaction

Substrate screening for superclean graphene growth using firstprinciples calculations

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Nano Research 2024年第4期17卷 2216-2222页

作者： Zhihao Li Xiucai sun Xiaoli sun Wan-jian Yin Zhongfan Liu College of Energy Soochow Institute for Energy and Materials InnovationS(SIEMIS)and Jiangsu Provincial Key Laboratory for Advanced Carbon Materials and Wearable Energy TechnologiesSoochow UniversitySuzhou 215006China Graphene Basic Science Research Center Beijing Graphene Institute(BGI)Beijing 100095China Center for Nanochemistry Beijing Science and Engineering Center for NanocarbonsBeijing National Laboratory for Molecular ScienceCollege of Chemistry and Molecular EngineeringPeking UniversityBeijing 100871China

Suppressing the formation of amorphous surface carbon and contaminants during the preparation of graphene by chemical vapor deposition remains an ongoing issue.Herein,we analyzed how substrate characteristics affect graphene quality by simulating margin extension,the nucleation process,and defect pegging configurations on mono-crystalline oriented metal substrates with the aim of enhancing graphene cleanliness.Defect formation energy and nucleation potential,which are indirect substrate–graphene interaction features,were found to appropriately evaluate graphene quality.The crystallographic orientation of the metal substrate was discovered to be critical for producing superclean graphene.A low graphene defect density and high nucleation rate on the Cu(100)facet guarantee growth of high-quality graphene,especially in terms of suppressing the formation of amorphous carbon.In addition,rapid kink growth and self-healing on the Cu(100)facet facilitate rapid graphene synthesis,which is also promoted by rapid kink splicing and margin self-repair on this facet.This study provides theoretical insight useful for the synthesis of superclean graphene.

关键词： superclean graphene defects nucleation metal substrates density functional theory calculations

Prediction of lime utilization ratio of dephosphorization in BOF steelmaking based on online sequential extreme learning machine with forgetting mechanism

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International Journal of Minerals,Metallurgy and Materials 2024年第3期31卷 508-517页

作者： Runhao Zhang jian Yang Han sun Wenkui Yang State Key Laboratory of Advanced Special Steel School of Materials Science and EngineeringShanghai UniversityShanghai 200444China

The machine learning models of multiple linear regression(MLR),support vector regression(SVR),and extreme learning ma-chine(ELM)and the proposed ELM models of online sequential ELM(OS-ELM)and OS-ELM with forgetting mechanism(FOS-ELM)are applied in the prediction of the lime utilization ratio of dephosphorization in the basic oxygen furnace steelmaking process.The ELM model exhibites the best performance compared with the models of MLR and SVR.OS-ELM and FOS-ELM are applied for sequential learning and model updating.The optimal number of samples in validity term of the FOS-ELM model is determined to be 1500,with the smallest population mean absolute relative error(MARE)value of 0.058226 for the population.The variable importance analysis reveals lime weight,initial P content,and hot metal weight as the most important variables for the lime utilization ratio.The lime utilization ratio increases with the decrease in lime weight and the increases in the initial P content and hot metal weight.A prediction system based on FOS-ELM is applied in actual industrial production for one month.The hit ratios of the predicted lime utilization ratio in the error ranges of±1%,±3%,and±5%are 61.16%,90.63%,and 94.11%,respectively.The coefficient of determination,MARE,and root mean square error are 0.8670,0.06823,and 1.4265,respectively.The system exhibits desirable performance for applications in actual industrial pro-duction.

关键词： basic oxygen furnace steelmaking machine learning lime utilization ratio dephosphorization online sequential extreme learning machine forgetting mechanism

Sustained release of vascular endothelial growth factor A and basic fibroblast growth factor from nanofiber membranes reduces oxygen/glucose deprivation-induced injury to neurovascular units

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Neural Regeneration Research 2024年第4期19卷 887-894页

作者： Yifang Wu Jun sun Qi Lin Dapeng Wang jian Hai Department of Neurosurgery Tongji HospitalSchool of MedicineTongji University Department of Pharmacy Institute of Medical SciencesShanghai Jiao Tong University School of Medicine

Upregulation of vascular endothelial growth factor A/basic fibroblast growth factor(VEGFA/b FGF)expression in the penumbra of cerebral ischemia can increase vascular volume,reduce lesion volume,and enhance neural cell proliferation and differentiation,thereby exerting neuroprotective effects.However,the beneficial effects of endogenous VEGFA/b FGF are limited as their expression is only transiently increased.In this study,we generated multilayered nanofiber membranes loaded with VEGFA/b FGF using layer-by-layer self-assembly and electrospinning techniques.We found that a membrane containing 10 layers had an ideal ultrastructure and could efficiently and stably release growth factors for more than 1 month.This 10-layered nanofiber membrane promoted brain microvascular endothelial cell tube formation and proliferation,inhibited neuronal apoptosis,upregulated the expression of tight junction proteins,and improved the viability of various cellular components of neurovascular units under conditions of oxygen/glucose deprivation.Furthermore,this nanofiber membrane decreased the expression of Janus kinase-2/signal transducer and activator of transcription-3(JAK2/STAT3),Bax/Bcl-2,and cleaved caspase-3.Therefore,this nanofiber membrane exhibits a neuroprotective effect on oxygen/glucose-deprived neurovascular units by inhibiting the JAK2/STAT3 pathway.

关键词： brain ischemia brain microvascular endothelial cell nanofiber membrane neurovascular unit

A Method for Detecting and Recognizing Yi Character Based on Deep Learning

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Computers, Materials & Continua 2024年第2期78卷 2721-2739页

作者： Haipeng sun Xueyan Ding jian sun HuaYu jianxin Zhang School of Computer Science and Engineering Dalian Minzu UniversityDalian116600China Institute of Machine Intelligence and Bio-Computing Dalian Minzu UniversityDalian116600China 3Yi Language Research RoomChina Ethnic Languages Translation Centre Beijing100080China

Aiming at the challenges associated with the absence of a labeled dataset for Yi characters and the complexity of Yi character detection and recognition,we present a deep learning-based approach for Yi character detection and recognition.In the detection stage,an improved Differentiable Binarization Network(DBNet)framework is introduced to detect Yi characters,in which the Omni-dimensional Dynamic Convolution(ODConv)is combined with the ResNet-18 feature extraction module to obtain multi-dimensional complementary features,thereby improving the accuracy of Yi character detection.Then,the feature pyramid network fusion module is used to further extract Yi character image features,improving target recognition at different scales.Further,the previously generated feature map is passed through a head network to produce two maps:a probability map and an adaptive threshold map of the same size as the original map.These maps are then subjected to a differentiable binarization process,resulting in an approximate binarization map.This map helps to identify the boundaries of the text boxes.Finally,the text detection box is generated after the post-processing stage.In the recognition stage,an improved lightweight MobileNetV3 framework is used to recognize the detect character regions,where the original Squeeze-and-Excitation(SE)block is replaced by the efficient Shuffle Attention(SA)that integrates spatial and channel attention,improving the accuracy of Yi characters recognition.Meanwhile,the use of depth separable convolution and reversible residual structure can reduce the number of parameters and computation of the model,so that the model can better understand the contextual information and improve the accuracy of text recognition.The experimental results illustrate that the proposed method achieves good results in detecting and recognizing Yi characters,with detection and recognition accuracy rates of 97.5%and 96.8%,respectively.And also,we have compared the detection and recognition algorithms proposed in this paper with

关键词： Yi characters text detection text recognition attention mechanism deep neural network

Adversarial data splitting for domain generalization

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Science China(Information Sciences) 2024年第5期67卷 28-42页

作者： Xiang GU jian sun Zongben XU School of Mathematics and Statistics Xi'an Jiaotong University

Domain generalization aims to learn a model that is generalizable to an unseen target domain,which is a fundamental and challenging task in machine learning for out-of-distribution generalization. This paper proposes a novel domain generalization approach that enforces the learned model to be able to generalize well over the train/val subset splitting of the training dataset. This idea is modeled herein as an adversarial data splitting framework, formulated as a min-max optimization problem inspired by the metalearning approach. The min-max optimization problem is solved by iteratively splitting the training dataset into the training and val subsets to maximize the domain shift measured by the objective function and updating the model parameters to enable the model to generalize well from the training subset to the val subset by minimizing the objective function. This adversarial training approach does not assume the known domain labels of the training data; instead, it automatically investigates the “hard” splitting of the train/val subsets to learn the generalizable model. Extensive experimental results using three benchmark datasets demonstrate the superiority of this approach. In addition, we derive a generalization error bound for the theoretical understanding of our proposed approach.

关键词： domain generalization adversarial learning data splitting meta-learning out of distribution