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BERD+: A Generic Sequential Recommendation Framework by Eliminating Unreliable data with Item- and Attribute-level Signals

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ACM Transactions on Information Systems 2023年第2期42卷 1-33页

作者： Sun, Yatong Yang, Xiaochun Sun, Zhu Wang, Bin School of Computer Science and Engineering Northeastern University School of Computing Macquarie University China Australia Institute of High Performance Computing Centre for Frontier AI Research A*STAR Singapore School of Computer Science and Engineering Northeastern University China National Frontiers Science Center for Industrial Intelligence and Systems Optimization China Key Laboratory of Data Analytics and Optimization for Smart Industry [Northeastern University Ministry of Education China

A preliminary work of our study was published at IJCAI’21 [47], which is substantially extended in the following aspects: (1) In Section 1, we analyze the necessity of introducing item attributes for detecting unreliable instances, together with the problems and challenges that attributes may bring in. (2) In Section 2, we add discussions about the limitations of existing attribute-aware recommender systems (Section 2.2) and denoising methods (Section 2.3) in the context of detecting unreliable instances. (3) In Section 4.2, we further conduct an in-depth analysis at the attribute level to demonstrate the capability of attributes for rectifying instance loss and uncertainty, as well as the disturbance caused by attributes. (4) We generalize BERD to a generic framework BERD+ in Section 5.1, equipped with novel modules, i.e., HU-GCN (Section 5.2) and EPE (Section 5.4), which properly incorporate item attributes while reducing their disturbance for rectifying instance uncer tainty (Section 5.5) and loss (Section 5.6). The generic BERD+ can be flexibly plugged into existing SRSs for performance enhanced recommendation via eliminating unreliable data. (5) In Section 6.2, we apply our BERD+ framework to seven state-of-the-art SRSs on five real-world datasets to illustrate its superiority. (6) To avoid unfair comparison caused by item attributes, we build and compare with the baseline that combines the original BERD and an advanced attribute-aware recommender system, KSR [19]. (7) For more comprehensive comparison, in Section 6.2.2, we compare BRED+ with two state-of-the-art denoising approaches;in Section 6.2.3, to examine the efficacy of HU-GCN and EPE, we compare HU-GCN with various attribute embedding techniques, i.e., variants of graph neural networks, and compare EPE with different attribute fusing methods, i.e., adding, concatenation, and weighted sum. (8) In Section 6.2.4, a detailed ablation study is conducted to verify the effectiveness of each module of BERD+. (

关键词： Convolution

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Dynamic Locomotion of Quadruped Robot in Sloping Terrain

Dynamic Locomotion of Quadruped Robot in Sloping Terrain

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International Symposium on Autonomous Systems (ISAS)

作者： Donglin Chen Dehong Cong Xiangman Song National Frontiers Science Center for Industrial Intelligence and Systems Optimization Northeastern University Shenyang China Key Laboratory of Data Analytics and Optimization for Smart Industry Northeastern University Ministry of Education Shenyang China Liaoning Engineering Laboratory of Data Analytics and Optimization for Smart Industry Shenyang China

In order to improve the locomotion capability of quadruped robot in the sloping terrain and enhance whose adaptability to the environment, this paper proposes a method to realize dynamic locomotion of quadruped robot in sloping terrain completely based on model predictive control (MPC) and proprioception. According to the foot contact signal and the robot body posture information measured by inertial measurement unit (IMU), quadruped robot actively changes whose body posture to adapt to different sloping terrains. This paper builds quadruped robot virtual prototype and test terrain in Webots simulation environment. The experimental results show that with this method, the roll angle fluctuation range of the quadruped robot is less than 0.05rad and the yaw angle fluctuation range is not more than 0.003rad. At the same time, when the angle of slope changes, the terrain adaptation time of the quadruped robot is less than 1.8s. The above results show that quadruped robot has excellent movement ability in sloping terrain and environmental adaptability under the condition of ensuring stability with the method proposed in this paper.

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Impacts of preferences on the emergence of cooperation

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Physical Review E 2020年第5期102卷 052414-052414页

作者： Shiping Gao Jinming Du Jinling Liang School of Mathematics Southeast University Nanjing 210096 China Institute of Industrial and Systems Engineering College of Information Science and Engineering Northeastern University Shenyang 110891 China Liaoning Engineering Laboratory of Operations Analytics and Optimization for Smart Industry Northeastern University Shenyang 110891 China Key Laboratory of Data Analytics and Optimization for Smart Industry (Northeastern University) Ministry of Education Shenyang 110891 China

Behavior decision making, where individuals can efficiently express their preferences for all options, has a great impact on cooperation. Hereby, we institute a minimal model in well-mixed populations where whether and how to sanction defectors are decided by cooperators via different decision-making mechanisms. The results illustrate that whether cooperation can outbreak depends on the cooperators' preferences for sanction and complying with the electoral outcome. We highlight the role of individuals' preferences in the emergence of cooperation and show that there exists an intermediate degree of the cooperators' preference for sanction at which the cooperators' preference for complying with the electoral outcome has a negligible impact on cooperation. We point out whether conformity facilitates the emergence of cooperation depends on the cooperators' preference for sanction. We find, compared with individual decision making, whether collective decision making is more conducive to promoting cooperation crucially depends on cooperators' preferences as well as the consensus required for employing sanction.

关键词： Evolutionary dynamics Collective behavior Evolutionary games Fitness models Stochastic analysis

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Evolution of cooperation under punishment

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Physical Review E 2020年第6期101卷 062419-062419页

Punishment has been considered as an effective mechanism for promoting and sustaining cooperation. In most existing models, punishment always comes as a third strategy alongside cooperation and defection, and it is commonly assumed to be executed based on individual decision rules rather than collective decision rules. Differently from previous works, we employ a democratic procedure by which cooperators cast votes independently and simultaneously for whether to impose punishment on defectors, and we establish a relationship between the cooperators' willingness to punish defectors (WTPD) and whether the punishment is inflicted on defectors. The results illustrate that the population can evolve to full cooperation under consensual punishment. It is noteworthy that, compared with autonomous punishment, whether consensual punishment is more in favor of cooperation crucially depends on the minimum number of votes required for punishment execution as well as the cooperators' WTPD. Our findings highlight the importance of collective decision making in the evolution of cooperation and may provide a mathematical framework for explaining the prevalence of democracy in modern societies.

关键词： Evolutionary dynamics

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Cosmology with fast radio bursts in the era of SKA

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Science China(Physics,Mechanics & Astronomy) 2023年第12期66卷 37-55页

作者： Ji-Guo Zhang Ze-Wei Zhao Yichao Li Jing-Fei Zhang Di Li Xin Zhang Department of Physics College of SciencesNortheastern UniversityShenyang 110819China Key Laboratory of Cosmology and Astrophysics(Liaoning) Northeastern UniversityShenyang 110819China National Astronomical Observatories Chinese Academy of SciencesBeijing 100101China University of Chinese Academy of Sciences Beijing 100049China Research Center for Intelligent Computing Platforms Zhejiang LaboratoryHangzhou 311100China National Frontiers Science Center for Industrial Intelligence and Systems Optimization Northeastern UniversityShenyang 110819China Key Laboratory of Data Analytics and Optimization for Smart Industry(Ministry of Education) Northeastern UniversityShenyang 110819China

We present a forecast of the cosmological parameter estimation using fast radio bursts(FRBs)from the upcoming Square Kilometre Array(SKA),focusing on the issues of dark energy,the Hubble constant,and baryon *** simulate 105and 106localized FRBs from a 10-year SKA observation,and find that:(1)using 106FRB data alone can tightly constrain dark-energy equation of state parameters better than CMB+BAO+SNe,providing an independent cosmological probe to explore dark energy;(2)combining the FRB data with gravitational-wave standard siren data from 10-year observation with the Einstein Telescope,the Hubble constant can be constrained to a sub-percent level,serving as a powerful low-redshift probe;(3)using 106FRB data can constrain the baryon density?bh to a precision of~0.1%.Our results indicate that SKA-era FRBs will provide precise cosmological measurements to shed light on both dark energy and the missing baryon problem,and help resolve the Hubble tension.

关键词： fast radio burst cosmology dark energy the Hubble constant baryon density Square Kilometre Array

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optimization of the raw material field layout for iron-steel enterprise

Optimization of the raw material field layout for iron-steel...

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作者： Wenbo Liu Yuehong Kong Department of Logistics Management Liaoning Provincial College of Communications Key Laboratory of Data Analytics and Optimization for Smart Industry(Northeastern University)

This paper studies a short-term layout optimization problem with the raw material field for iron-steel *** raw material field is a centralized storage place and distribution unit of various raw materials such as iron ore,which plays a significant role in the iron front logistics for iron and steel *** the stacking of raw materials is reasonable or not directly affects the logistics efficiency and logistics cost of raw materials for iron-steel *** on the status and basic information of the raw materials,storage space of the field shall be made full use of to allocate the optimal position for each type of raw *** achieve this goal,a mixed integer programming(MIP) model is developed,which is purposed to minimize the transportation cost and the loss of *** solution compares favorably with the current practice in the iron-steel enterprises.

关键词： workshop optimization of the raw material field layout for iron-steel enterprise

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Reynosin protects neuronal cells from microglial neuroinflammation by suppressing NLRP3 inflammasome activation mediated by NADPH oxidase

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Chinese Journal of Natural Medicines 2024年第6期22卷 486-500页

作者： YANG Yanqiu CHE Yue FANG Mingxia YAO Xiaohu ZHOU Di WANG Feng CHEN Gang LIANG Dong LI Ning HOU Yue Key Laboratory of Bioresource Research and Development of Liaoning Province College of Life and Health SciencesNorth-eastern UniversityShenyang 110000China National Frontiers Science Center for Industrial Intelligence and Systems Optimization Key Laboratory of Data Analytics and Optimization for Smart IndustryMinistry of EducationNortheastern UniversityShenyang 110000China School of Traditional Chinese Materia Medica Key Laboratory of Innovative Traditional Chinese Medicine for Major Chronic Diseases of Liaoning provinceKey Laboratory for TCM Material Basis Study and Innovative Drug Development of Shenyang CityShenyang Pharmaceutical UniversityShenyang 110000China State Key Laboratory for Chemistry and Molecular Engineering of Medicinal Resources School of Chemistry and Pharmaceutical SciencesGuangxi Normal UniversityGuilin 541000China

Neuroinflammation,mediated by the nucleotide-binding oligomerization domain-like receptor family pyrin domain-containing-3(NLRP3)inflammasome,is a significant contributor to the pathogenesis of neurodegenerative diseases(NDDs).Reynos-in,a natural sesquiterpene lactone(SL),exhibits a broad spectrum of pharmacological effects,suggesting its potential therapeutic ***,the effects and mechanism of reynosin on neuroinflammation remain *** current study explores the effects and mechanisms of reynosin on neuroinflammation using mice and BV-2 microglial cells treated with lipopolysaccharide(LPS).Our findings reveal that reynosin effectively reduces microglial inflammation in vitro,as demonstrated by decreased CD11b expression and lowered interleukin-1 beta(IL-1β)and interleukin-18(IL-18)mRNA and protein ***,in vivo,results showed a re-duction in the number of Iba-1 positive cells and alleviation of morphological alterations,alongside decreased expressions of IL-1βand *** analysis indicates that reynosin inhibits NLRP3 inflammasome activation,evidenced by reduced transcription of NLRP3 and caspase-1,diminished NLRP3 protein expression,inhibited apoptosis-associated speck-like protein containing a CARD(ASC)oli-gomerization,and decreased caspase-1 ***,reynosin curtailed the activation of nicotinamide adenine dinuc-leotide phosphate(NADPH)oxidase,demonstrated by reduced NADP^(+)and NADPH levels,downregulation of gp91^(phox) mRNA,pro-tein expression,suppression of p47^(phox) expression and translocation to the ***,reynosin exhibited a neuroprotective effect against microglial inflammation in vivo and in *** collective findings underscore reynosin’s capacity to mitigate mi-croglial inflammation by inhibiting the NLRP3 inflammasome,thus highlighting its potential as a therapeutic agent for managing neuroinflammation.

关键词： Microglia NLRP3 inflammasome Reactive oxygen species NADPH oxidase Neuron Reynosin

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Network pharmacology and single-cell transcriptomic analysis with molecular docking to elucidate the potential compounds and targets of Polygonum cuspidatum *** *** hepatocellular carcinoma

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iLIVER 2024年第3期3卷 41-51页

作者： Wenze Wu Yuzhu Shi Yongzi Wu Rui Zhang Xinyan Wu Weidi Zhao Zhiyuan Chen Gang Ye Key Laboratory of Bioresource Research and Development of Liaoning Province College of Life and Health SciencesNational Frontiers Science Center for Industrial Intelligence and Systems OptimizationKey Laboratory of Data Analytics and Optimization for Smart IndustryMinistry of EducationNortheastern UniversityShenyang 110169China College of Veterinary Medicine Sichuan Agricultural UniversityChengdu 625014China School of Physical Education Shanxi UniversityTaiyuan 030006China

Background and aims:Polygonum cuspidatum *** Zucc.(***)and its active components have been clinically proven to have anti-hepatocellular carcinoma ***,the potential targets of *** for these effects have not yet been ***:We used network pharmacology and single-cell transcriptomic analysis with molecular docking to elucidate the active components and targets of *** for hepatocellular ***:CDK1,ESR1,HSP90A11,and MAPK1 were shown to be the key targets of *** for hepatocellular *** was found to be likely correlated with the improved abnormal expression of CDK1 and ESR1 and the poor prognosis of HSP90AA1 and ***1 was identified as the most potential antihepatocellular carcinoma target of *** the active components of ***,physcion diglucoside was found to have the most potential to treat hepatocellular carcinoma by targeting ***:Our study provides novel insights into the anti-hepatocellular carcinoma pharmacological effects of ***,which could serve as a scientific basis for its development as a medicinal resource and the targeting of CDK1 for hepatocellular carcinoma treatment.

关键词： Hepatocellular carcinoma Network pharmacology Molecular dynamics simulation Molecular docking Polygonum cuspidatum Single-cell transcriptomic analysis

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An Improved MOEA/D Algorithm for the Carbon Black Production Line Static and Dynamic Multiobjective Scheduling Problem

An Improved MOEA/D Algorithm for the Carbon Black Production...

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Congress on Evolutionary Computation

作者： Yao Wang Zhiming Dong Tenghui Hu Xianpeng Wang Key Laboratory of Data Analytics and Optimization for Smart Industry (Northeastern University) Ministry of Education China Liaoning Engineering Laboratory of operation Analytics and Optimization for Smart Industry Northeastern University Shenyang China Liaoning Key Laboratory of Manufacturing System and Logistics Northeastern University Shenyang China Institute of Industrial & Systems Engineering Northeastern University Shenyang China

ISBN: (数字)9781728169293

ISBN: (纸本)9781728169309

The make-to-order (MTO) manufacturers generally make production plans based on orders, which can help enterprises effectively avoid market risks, reduce market pressure and improve competitiveness. However, due to the characteristics of MTO production mode, the order static scheduling problem and rush order dynamic rescheduling problem have become more and more important for these MTO manufacturers. Therefore, in this paper, we take the packaging production line of a typical carbon black production enterprise as the research background to study the carbon black production line static and dynamic multiobjective scheduling problem. Firstly, multiobjective optimization models of both order static scheduling and rush order dynamic rescheduling are established. Then the improved MOEA/D algorithm combined the heuristic algorithm based on heuristic rules and discrete dynamic local search is developed to solve these two models. Based on the actual production data, eight instances of order static scheduling problems of different scales and four instances of rush order dynamic rescheduling problems of different scales are constructed respectively. Experimental results illustrate that the improved MOEA/D is effective and superior in solving these two problems.

关键词： Dynamic scheduling Job shop scheduling Mathematical model Heuristic algorithms Delays

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MOEA/D With Spatial-Temporal Topological Tensor Prediction for Evolutionary Dynamic Multiobjective optimization

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IEEE Transactions on Evolutionary Computation 2024年 1-1页

作者： Wang, Xianpeng Zhao, Yumeng Tang, Lixin Yao, Xin Ministry of Education Shenyang China Liaoning Engineering Laboratory of Data Analytics and Optimization for Smart Industry Liaoning Key Laboratory of Manufacturing System and Logistics Optimization Shenyang China National Frontiers Science Center for Industrial Intelligence and Systems Optimization Shenyang China Lingnan University Hong Kong China

When solving dynamic multiobjective optimization problems, most evolutionary algorithms attempt to predict the initial population in a new environment by mining the relationships between solutions during historical environment changes. However, the complex relationships between solutions and the limited amount of available data often make it difficult to extract useful information efficiently, which may deteriorate the prediction accuracy. To address this problem, this paper proposes a spatial-temporal topological tensor-based prediction method to generate the initial population in a new environment under the decomposition framework of MOEA/D. The method relies on the idea that the population distribution in each environment has topological similarity along the time dimension in the objective space, which makes it efficient to represent the population distribution in terms of a tensor and predict new solutions along each decomposition axis in a new environment by an improved tensor-based multi-short time series prediction method. Experimental results on various benchmark problems and a real-world problem show that the proposed method is competitive or even superior to state-of-the-art dynamic multiobjective evolutionary algorithms based on prediction strategies. IEEE

关键词： Tensors

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