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Constraint Learning-based Optimal Power Dispatch for Active Distribution Networks with Extremely Imbalanced Data

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CSEE Journal of Power and Energy Systems 2024年第1期10卷 51-65页

作者： Yonghua song Ge Chen Hongcai Zhang State Key Laboratory of Internet of Things for Smart City and Department of Electrical and Computer Engineering University of MacaoMacao 999078China School of Electrical and Computer Engineering Purdue UniversityWest LafayetteIN 47907 USA

Transition towards carbon-neutral power systems has necessitated optimization of power dispatch in active distribution networks(ADNs)to facilitate integration of distributed renewable *** to unavailability of network topology and line impedance in many distribution networks,physical model-based methods may not be applicable to their *** tackle this challenge,some studies have proposed constraint learning,which replicates physical models by training a neural network to evaluate feasibility of a decision(i.e.,whether a decision satisfies all critical constraints or not).To ensure accuracy of this trained neural network,training set should contain sufficient feasible and infeasible ***,since ADNs are mostly operated in a normal status,only very few historical samples are ***,the historical dataset is highly imbalanced,which poses a significant obstacle to neural network *** address this issue,we propose an enhanced constraint learning ***,it leverages constraint learning to train a neural network as surrogate of ADN's ***,it introduces Synthetic Minority Oversampling Technique to generate infeasible samples to mitigate imbalance of historical *** incorporating historical and synthetic samples into the training set,we can significantly improve accuracy of neural ***,we establish a trust region to constrain and thereafter enhance reliability of the *** confirm the benefits of the proposed method in achieving desirable optimality and feasibility while maintaining low computational complexity.

关键词： Deep learning demand response distribution networks imbalanced data optimal power flow

A credible traffic prediction method based on self-supervised causal discovery

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Science China(Information Sciences) 2024年第5期67卷 244-258页

作者： Dan WANG Yingjie LIU Bin song State Key Laboratory of Integrated Services Networks Xidian University

Next-generation wireless network aims to support low-latency, high-speed data transmission services by incorporating artificial intelligence(AI) technologies. To fulfill this promise, AI-based network traffic prediction is essential for pre-allocating resources, such as bandwidth and computing power. This can help reduce network congestion and improve the quality of service(QoS) for users. Most studies achieve future traffic prediction by exploiting deep learning and reinforcement learning, to mine spatio-temporal correlated variables. Nevertheless, the prediction results obtained only by the spatio-temporal correlated variables cannot reflect real traffic changes. This phenomenon prevents the true prediction variables from being inferred, making the prediction algorithm perform poorly. Inspired by causal science, we propose a novel network traffic prediction method based on self-supervised spatio-temporal causal discovery(SSTCD). We first introduce the Granger causal discovery algorithm to build a causal graph among prediction variables and obtain spatio-temporal causality in the observed data, which reflects the real reasons affecting traffic ***, a graph neural network(GNN) is adopted to incorporate causality for traffic prediction. Furthermore,we propose a self-supervised method to implement causal discovery to to address the challenge of lacking ground-truth causal graphs in the observed data. Experimental results demonstrate the effectiveness of the SSTCD method.

关键词： wireless network traffic prediction causal discovery self-supervised

When debugging encounters artificial intelligence: state of the art and open challenges

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Science China(Information Sciences) 2024年第4期67卷 42-84页

作者： Yi song Xiaoyuan XIE Baowen XU School of Computer Science Wuhan University State Key Laboratory of Novel Software Technology Nanjing University

Both software debugging and artificial intelligence techniques are hot topics in the current field of software engineering. Debugging techniques, which comprise fault localization and program repair, are an important part of the software development lifecycle for ensuring the quality of software systems. As the scale and complexity of software systems grow, developers intend to improve the effectiveness and efficiency of software debugging via artificial intelligence(artificial intelligence for software debugging, AI4SD). On the other hand, many artificial intelligence models are being integrated into safety-critical areas such as autonomous driving, image recognition, and audio processing, where software debugging is highly necessary and urgent(software debugging for artificial intelligence, SD4AI). An AI-enhanced debugging technique could assist in debugging AI systems more effectively, and a more robust and reliable AI approach could further guarantee and support debugging techniques. Therefore, it is important to take AI4SD and SD4AI into consideration comprehensively. In this paper, we want to show readers the path, the trend, and the potential that these two directions interact with each other. We select and review a total of 165 papers in AI4SD and SD4AI for answering three research questions, and further analyze opportunities and challenges as well as suggest future directions of this cross-cutting area.

关键词： software debugging fault localization program repair artificial intelligence machine learning

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学校教育空间的现代性表征、生产逻辑及其必要改造

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当代教育科学 2024年第5期 9-19页

作者：宋岭杭州师范大学中国教育现代化研究院杭州311121

空间塑造着主体,而主体与空间的交互又再造了空间。现代学校教育空间基本延续了工业时代的特征,其标准化、封闭性和分割性的特征服务于个体的客观知识增长这一教育生产目的。它顺应了工业社会对批量人才的需求,促进了教育的制度化发展... 详细信息

空间塑造着主体,而主体与空间的交互又再造了空间。现代学校教育空间基本延续了工业时代的特征,其标准化、封闭性和分割性的特征服务于个体的客观知识增长这一教育生产目的。它顺应了工业社会对批量人才的需求,促进了教育的制度化发展和现代化进步,但也造成了割裂、限制和规训等问题。而当下功利和异化的教育观念与目的也凭借空间再生产出针对性的制度与规范;这些制度与规范在空间中运行发挥其管理学功能,并通过空间得以管控空间主体的身体及其行为,使规训得以实现,异化的权力关系也得以形成。传统学校教育空间的沿用已经阻碍了新教育理念的落实,亦限制了新型教育空间样态的产生。学校教育空间的改造,需要在满足必要的标准和基本生理学与教育学保障的基础上,努力寻求更多的开放性、动态交互性与多样化的发展,以满足当下教与学的本真需要,真正推进教育改革、促进学生的学习与发展。

关键词：学校教育空间现代性教育生产身体作用机制

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A Least-squares-based Iterative Method with Better Convergence for PF/OPF in Integrated Transmission and Distribution Networks

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CSEE Journal of Power and Energy Systems 2024年第3期10卷 953-962页

作者： Kunjie Tang Shufeng Dong Yonghua song College of Electrical Engineering Zhejiang UniversityHangzhou 310027China State Key Laboratory of Internet of Things for Smart City and Department of Electrical and Computer Engineering University of MacaoMacao SARChina IEEE

The limitations of the conventional master-slavesplitting(MSS)method,which is commonly applied to power flow and optimal power flow in integrated transmission and distribution(I-T&D)networks,are first *** that the MSS method suffers from a slow convergence rate or even divergence under some circumstances,a least-squares-based iterative(LSI)method is *** with the MSS method,the LSI method modifies the iterative variables in each iteration by solving a least-squares problem with the information in previous iterations.A practical implementation and a parameter tuning strategy for the LSI method are ***,a LSI-PF method is proposed to solve I-T&D power flow and a LSIheterogeneous decomposition(LSI-HGD)method is proposed to solve optimal power *** experiments demonstrate that the proposed LSI-PF and LSI-HGD methods can achieve the same accuracy as the benchmark ***,these LSI methods,with appropriate settings,significantly enhance the convergence and efficiency of conventional ***,in some cases,where conventional methods diverge,these LSI methods can still converge.

关键词： Fixed-point theory integrated transmission and distribution networks least-squares-based iterative method master-slave-splitting method optimal power flow power flow

Adaptive Consensus of Uncertain Multi-Agent Systems With Unified Prescribed Performance

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IEEE/CAA Journal of Automatica Sinica 2024年第5期11卷 1310-1312页

作者： Kun Li Kai Zhao Yongduan song The authors are with the School of Automation Chongqing UniversityChongqing 400044China

Dear Editor,An adaptive consensus control algorithm for uncertain multi-agent systems(MAS),capable of guaranteeing unified prescribed performance,is presented in this *** many existing prescribed performance related works,the developed control exhibits some ***,a distributed prescribed time observer is introduced so that not only each follower is able to estimate the leader’s signal within a predetermined time,but also the control design for each agent is independent with its neighbors.

关键词： agent prescribed Uncertain

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Open-Shell Oligomers and Polymers: Theory, Characterization Methods, Molecular Design, and Applications

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Chinese Journal of Polymer Science 2024年第4期42卷 417-436页

作者： Xue-Qing Wang Cheng song Ting Lei Key Laboratory of Polymer Chemistry and Physics(Ministry of Education) School of Materials Science and EngineeringPeking UniversityBeijing100871China

Open-shell oligomers and polymers have exhibited intriguing electronic and magnetic properties, making them highly desirable for a wide range of applications, including ambipolar organic field-effect transistors (OFETs), photodetectors, organic thermoelectrics, and spintronics. Although open-shell ground states have been observed in certain small molecules and doped organic semiconductors, the exploration of open-shell ground-state conjugated polymers is still limited, and the strategies for designing these polymers remain obscure. This review aims to briefly introduce the theory and characterization methods of open-shell conjugated polymers, along with an overview of recent progress and applications. The objective is to stimulate further advancements and investigations in this promising area by shedding light on the potential of open-shell conjugated polymers and the challenges that lie ahead.

关键词： Conjugated polymers Open-shell molecules High-spin ground state Donor-acceptor(D-A)polymers Optoelectronic and magnetic properties

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Glioma-derived ANXA1 suppresses the immune response to TLR3 ligands by promoting an anti-inflammatory tumor microenvironment

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Cellular & Molecular Immunology 2024年第1期21卷 47-59页

作者： Yu Zheng Haihui Jiang Naixue Yang Shaoping Shen Daosheng Huang Lemei Jia Jing ling Longchen Xu Mingxiao Li Kefu Yu Xiaohui Ren Yong Cui Xun Lan song Lin Xin Lin Institute for Immunology and School of Medicine Tsinghua UniversityBeijing100084China Department of Neurosurgery Beijing Tiantan HospitalCapital Medical UniversityChina.National Clinical Research Center for Neurological DiseasesCenter of Brain TumorBeijing Institute for Brain Disorders and Beijing Key Laboratory of Brain TumorBeijing100070China Department of Neurosurgery Peking University Third HospitalPeking UniversityBeijing100191China Tsinghua-Peking Center for Life Sciences Beijing100084China

A highly immunosuppressive tumor microenvironment(TME)and the presence of the blood‒brain barrier are the two major obstacles to eliciting an effective immune response in patients with high-grade glioma(HGG).Here,we tried to enhance the local innate immune response in relapsed HGG by intracranially injecting poly(I:C)to establish a robust antitumor immune response in this registered clinical trial(NCT03392545).During the follow-up,12/27(44.4%)patients who achieved tumor control concomitant with survival benefit were regarded as responders in our *** found that the T-cell receptor(TCR)repertoire in the TME was reshaped after poly(I:C)*** on the RNA-seq analysis of tumor samples,the expression of annexin A1(ANXA1)was significantly upregulated in the tumor cells of nonresponders,which was further validated at the protein *** vitro and in vivo experiments showed that ANXA1 could induce the production of M2-like macrophages and microglia via its surface receptor formyl peptide receptor 1(FPR1)to establish a Treg cell-driven immunosuppressive TME and suppress the antitumor immune response facilitated by poly(I:C).The ANXA1/FPR1 signaling axis can inhibit the innate immune response of glioma patients by promoting an anti-inflammatory and Treg-driven ***,ANXA1 could serve as a reliable predictor of response to poly(I:C),with a notable predictive accuracy rate of 92.3%.In light of these notable findings,this study unveils a new perspective of immunotherapy for gliomas.

关键词： glioma ANXA1 TLR3 poly(I:C) immunotherapy

Bactericidal bissulfone B7 targets bacterial pyruvate kinase to impair bacterial biology and pathogenicity in plants

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Science China(Life Sciences) 2024年第2期67卷 391-402页

作者： Awei Zhang Haizhen Zhang Ronghua Wang Hongfu He Baoan song Runjiang song National Key Laboratory of Green Pesticide Key Laboratory of Green Pesticide and Agricultural BioengineeringMinistry of EducationCenter for R&D of Fine Chemicals of Guizhou UniversityGuiyang 550025China

The prevention and control of rice bacterial leaf blight(BLB)disease has not yet been achieved due to the lack of effective agrochemicals and available ***,we develop a series of novel bissulfones and a novel target with a unique mechanism to address this *** developed bissulfones can control Xanthomonas oryzae ***(Xoo),and 2-(bis(methylsulfonyl)methylene)-N-(4-chlorophenyl)hydrazine-1-carboxamide(B_(7))is more effective than the commercial drugs thiodiazole copper(TC)and bismerthiazol(BT).Pyruvate kinase(PYK)in Xoo has been identified for the first time as the target protein of our bissulfone B_(7).PYK modulates bacterial virulence via a CRP-like protein(Clp)/two-component system regulatory protein(reg R)*** elucidation of this pathway facilitates the use of B_(7)to reduce PYK expression at the transcriptional level,block PYK activity at the protein level,and impair the interaction within the PYK-Clp-reg R complex via competitive inhibition,thereby attenuating bacterial biology and *** study offers insights into the molecular and mechanistic aspects underlying anti-Xoo strategies that target *** believe that these valuable discoveries will be used for bacterial disease control in the future.

关键词： 2-bissulfone-N-phenylhydrazine-1-carboxamide derivatives Xoo antibacterial activities pyruvate kinase regulatory mechanism

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