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Building Simulation 2024年第4期17卷 639-655页

作者： Shanshuo Xing Jili zhang song Mu Dalian University of Technology Dalian116024China Guangdong Airport Baiyun Information Technology Co. Ltd.Guangzhou510000China

Optimization for the multi-chiller system is an indispensable approach for the operation of highly efficient chiller *** optima obtained by model-based optimization algorithms are dependent on precise and solvable objective *** classical neural networks cannot provide convex input-output mappings despite capturing impressive nonlinear fitting capabilities,resulting in a reduction in the robustness of model-based *** this paper,we leverage the input convex neural networks(ICNN)to identify the chiller model to construct a convex mapping between control variables and the objective function,which enables the NN-based OCL as a convex optimization problem and apply it to multi-chiller optimization for optimal chiller loading(OCL).Approximation performances are evaluated through a four-model comparison based on an experimental data set,and the statistical results show that,on the premise of retaining prior convexities,the proposed model depicts excellent approximation power for the data set,especially the unseen ***,the ICNN model is applied to a typical OCL problem for a multi-chiller system and combined with three types of optimization *** with conventional and meta-heuristic methods,the numerical results suggest that the gradient-based BFGS algorithm provides better energy-saving ratios facing consecutive cooling load inputs and an impressive convergence speed.

关键词： chiller plant input convex neural network optimal load distribution convex optimization

Efficiently simulating the work distribution of multiple identical bosons with boson sampling

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Frontiers of physics 2024年第3期19卷 197-206页

作者： Wen-qiang Liu zhang-qi Yin Center for Quantum Technology Research and Key Laboratory of Advanced Optoelectronic Quantum Architecture and Measurements(MOE) School of PhysicsBeijing Institute of TechnologyBeijing 100081China

Boson sampling has been theoretically proposed and experimentally demonstrated to show quantum computational ***,it still lacks the deep understanding of the practical applications of boson *** we propose that boson sampling can be used to efficiently simulate the work distribution of multiple identical *** link the work distribution to boson sampling and numerically calculate the transition amplitude matrix between the single-boson eigenstates in a one-dimensional quantum piston system,and then map the matrix to a linear optical network of boson *** work distribution can be efficiently simulated by the output probabilities of boson sampling using the method of the grouped probability *** scheme requires at most a polynomial number of the samples and the optical *** work opens up a new path towards the calculation of complex quantum work distribution using only photons and linear optics.

关键词： quantum simulation quantum work distribution boson sampling linear optic

Deciphering and integrating invariants for neural operator learning with various physical mechanisms

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National Science Review 2024年第4期11卷 111-122页

作者： Rui zhang qi Meng Zhi-Ming Ma Academy of Mathematics and Systems Science Chinese Academy of Sciences(CAS) Microsoft Research

Neural operators have been explored as surrogate models for simulating physical systems to overcome the limitations of traditional partial differential equation(PDE) solvers. However, most existing operator learning methods assume that the data originate from a single physical mechanism, limiting their applicability and performance in more realistic scenarios. To this end, we propose the physical invariant attention neural operator(PIANO) to decipher and integrate the physical invariants for operator learning from the PDE series with various physical mechanisms. PIANO employs self-supervised learning to extract physical knowledge and attention mechanisms to integrate them into dynamic convolutional *** to existing techniques, PIANO can reduce the relative error by 13.6%–82.2% on PDE forecasting tasks across varying coefficients, forces or boundary conditions. Additionally, varied downstream tasks reveal that the PI embeddings deciphered by PIANO align well with the underlying invariants in the PDE systems, verifying the physical significance of PIANO.

关键词： neural operator PDE solver contrastive learning physical invariants

Cobalt(Ⅲ)hydride HAT mediated enantioselective intramolecular hydroamination access to chiral pyrrolidines

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Science China Chemistry 2024年第6期67卷 2002-2008页

作者： qi Meng Tao qin Huanran Miao Ge zhang qian zhang Jilin Province Key Laboratory of Organic Functional Molecular Design&Synthesis Department of ChemistryNortheast Normal UniversityChangchun130024China State Key Laboratory of Organometallic Chemistry Shanghai Institute of Organic ChemistryChinese Academy of SciencesShanghai200032China

Enantioenriched pyrrolidines and derivatives are ubiquitous substructures in compounds of importance to medicinal and biological ***,we report an efficient cobalt-catalyzed intramolecular asymmetric hydroamination reaction that produces chiral pyrrolidines with good to excellent yield and *** with previously reported radicalinvolved methodologies for enantioenriched pyrrolidines,these conditions feature two elegant versatilities,enabling(1)the use of cobalt-catalyzed hydrogen atom transfer(HAT)to generate organocobalt intermediates that bring radical reaction to organometallic chemistry,and(2)enantioselective intramolecular C-N bond forging through an S_(N)2-like displacement involving dynamic kinetic resolution(DKR).This approach provides a new alternative and efficient methodology for enantioselective radical-involved C-N bond construction that can be used in the synthesis of both chiral pyrrolidines and homologous nitrogen heterocycles.

关键词： asymmetric catalysis radical hydroamination cobalt catalysis hydrogen atom transfer

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Mechanical behaviors of warm and ice-rich frozen soil stabilized with sulphoaluminate cement

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Journal of Mountain Science 2024年第1期21卷 335-345页

作者： WANG Honglei zhang Hu zhang Jianming zhang qi YIN Zhenhua State Key Laboratory of Frozen Soil Engineering Northwest Institute of Eco-Environment and ResourcesChinese Academy of SciencesLanzhou 730000China University of Chinese Academy of Sciences Beijing 100049China School of Civil Engineering and Transportation Northeast Forestry UniversityHarbin 150040China National Key Laboratory of Green and Long-Life Road Engineering in Extreme Environment CCCC First Highway Consultants Co.LtdXi'an 710065China Railway Engineering Research Institute China Academy of Railway Sciences Corporation LimitedBeijing 100081China

The warm and ice-rich frozen soil is characterized by high unfrozen water content, low shear strength and large compressibility, which is unreliable to meet the stability requirements of engineering infrastructures and foundations in permafrost regions. In this study, a novel approach for stabilizing the warm and ice-rich frozen soil with sulphoaluminate cement was proposed based on chemical stabilization. The mechanical behaviors of the stabilized soil, such as strength and stress-strain relationship, were investigated through a series of triaxial compression tests conducted at -1.0℃, and the mechanism of strength variations of the stabilized soil was also explained based on scanning electron microscope test. The investigations indicated that the strength of stabilized soil to resist failure has been improved, and the linear Mohr-Coulomb criteria can accurately reflect the shear strength of stabilized soil under various applied confining pressure. The increase in both curing age and cement mixing ratio were favorable to the growth of cohesion and internal friction angle. More importantly, the strength improvement mechanism of the stabilized soil is attributed to the formation of structural skeleton and the generation of cementitious hydration products within itself. Therefore, the investigations conducted in this study provide valuable references for chemical stabilization of warm and ice-rich frozen ground, thereby providing a basis for in-situ ground improvement for reinforcing warm and ice-rich permafrost foundations by soil-cement column installation.

关键词： Permafrost regions Frozen soil Mechanical behavior Chemical stabilization Ground improvement Ground modification

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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

Dynamic Scene Graph Generation of Point Clouds with Structural Representation Learning

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Tsinghua Science and Technology 2024年第1期29卷 232-243页

作者： Chao qi Jianqin Yin Zhicheng zhang Jin Tang School of Artificial Intelligence Beijing University of Posts and TelecommunicationsBeijing 100876China Standard and Metrology Research Institute China Academy of Railway Sciences Corporation LimitedBeijing 100081China

Scene graphs of point clouds help to understand object-level relationships in the 3D *** graph generation methods work on 2D structured data,which cannot be used for the 3D unstructured point cloud *** point-cloud-based methods generate the scene graph with an additional graph structure that needs labor-intensive manual *** address these problems,we explore a method to convert the point clouds into structured data and generate graphs without given ***,we cluster points with similar augmented features into groups and establish their relationships,resulting in an initial structural representation of the point ***,we propose a Dynamic Graph Generation Network(DGGN)to judge the semantic labels of targets of different *** dynamically splits and merges point groups,resulting in a scene graph with high *** show that our methods outperform other baseline *** output reliable graphs describing the object-level relationships without additional manual labeled data.

关键词： scene graph generation structural representation point cloud

Uncertain knowledge graph embedding:an effective method combining multi-relation and multi-path

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Frontiers of Computer Science 2024年第3期18卷 73-89页

作者： qi LIU qinghua zhang Fan ZHAO Guoyin WANG Key Laboratory of Tourism Multisource Data Perception and Decision Ministry of Culture and TourismChongqing University of Posts and TelecommunicationsChongqing 400065China Chongqing Key Laboratory of Computational Intelligence Chongqing University of Posts and TelecommunicationsChongqing 400065China Chongqing Key Laboratory of Big Data Intelligent Computing Chongqing University of Posts and TelecommunicationsChongqing 400065China

Uncertain Knowledge Graphs(UKGs)are used to characterize the inherent uncertainty of knowledge and have a richer semantic structure than deterministic knowledge *** research on the embedding of UKG has only recently begun,Uncertain Knowledge Graph Embedding(UKGE)model has a certain effect on solving this ***,there are still unresolved *** the one hand,when reasoning the confidence of unseen relation facts,the introduced probabilistic soft logic cannot be used to combine multi-path and multi-step global information,leading to information *** the other hand,the existing UKG embedding model can only model symmetric relation facts,but the embedding problem of asymmetric relation facts has not be *** address the above issues,a Multiplex Uncertain Knowledge Graph Embedding(MUKGE)model is proposed in this ***,to combine multiple information and achieve more accurate results in confidence reasoning,the Uncertain ResourceRank(URR)reasoning algorithm is ***,the asymmetry in the UKG is *** embed asymmetric relation facts of UKG,a multi-relation embedding model is ***,experiments are carried out on different datasets via 4 tasks to verify the effectiveness of *** results of experiments demonstrate that MUKGE can obtain better overall performance than the baselines,and it helps advance the research on UKG embedding.

关键词： knowledge representation uncertain knowledge graph multi-relation embedding uncertain reasoning

DeciLS-PBO: an effective local search method for pseudo-Boolean optimization

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Frontiers of Computer Science 2024年第2期18卷 239-241页

作者： Luyu JIANG Dantong OUYANG qi zhang Liming zhang College of Computer Science and Technology Jilin UniversityChangchun 130012China Key Laboratory of Symbolic Computation and Knowledge Engineering(Ministry of Education) Jilin UniversityChangchun 130012China

1 Introduction Local search method is a rising star for solving combinatorial optimization problems in recent years,and the state-of-the-art local search-based incomplete Maximum Satisfiability(MaxSAT)solversshowpromi... 详细信息

关键词： Max optimization local

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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