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Influence of carbides and pores on the localized deformation of nickel-based single-crystal superalloys

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Progress in Natural Science:Materials International 2024年第3期34卷 562-568页

作者： Rengeng Li Yu Zhang Haoyi niu Hao Wang Hao Wu Key Laboratory for Light-weight Materials Nanjing Tech University College of Materials Science and Engineering Chongqing University CRRC Qishuyan Institute Co.Ltd.

The carbides and pores play a critical role in the cracking tendencies of nickel-based single-crystal superalloys during deformation. In the present study, the deformation mechanism and local strain evolution behavior around carbides and pores were studied through in-situ tensile deformation experiments. The findings indicate that multiple slip systems are easily activated during tensile deformation in single-crystal alloys. Furthermore, the strain localization in carbides is influenced by their morphology, with rod-like and flake-like carbides demonstrating an increased likelihood of cracking during deformation. The strain localization adjacent to pores is markedly more intense, rendering these areas particularly susceptible to cracking. Our work therefore offers a theoretical foundation for enhancing the mechanical properties of nickel-based single-crystal superalloys by controlling carbide morphology and pore formation.

关键词： Carbides In-situ tensile Nickel-based single-crystal Pores Strain evolution

A unified pre-training and adaptation framework for combinatorial optimization on graphs

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Science China Mathematics 2024年第6期67卷 1439-1456页

作者： Ruibin Zeng Minglong Lei Lingfeng niu Lan Cheng School of Computer Science and Technology University of Chinese Academy of SciencesBeijing100049China Faculty of Information Technology Beijing University of TechnologyBeijing100124China School of Economics and Management University of Chinese Academy of SciencesBeijing100190China School of Mathematics and Statistics Central South UniversityChangsha410075China

Combinatorial optimization(CO)on graphs is a classic topic that has been extensively studied across many scientific and industrial fields.Recently,solving CO problems on graphs through learning methods has attracted great attention.Advanced deep learning methods,e.g.,graph neural networks(GNNs),have been used to effectively assist the process of solving COs.However,current frameworks based on GNNs are mainly designed for certain CO problems,thereby failing to consider their transferable and generalizable abilities among different COs on graphs.Moreover,simply using original graphs to model COs only captures the direct correlations among objects,which does not consider the mathematical logicality and properties of COs.In this paper,we propose a unified pre-training and adaptation framework for COs on graphs with the help of the maximum satisfiability(Max-SAT)problem.We first use Max-SAT to bridge different COs on graphs since they can be converted to Max-SAT problems represented by standard formulas and clauses with logical information.Then we further design a pre-training and domain adaptation framework to extract the transferable and generalizable features so that different COs can benefit from them.In the pre-training stage,Max-SAT instances are generated to initialize the parameters of the model.In the fine-tuning stage,instances from CO and Max-SAT problems are used for adaptation so that the transferable ability can be further improved.Numerical experiments on several datasets show that features extracted by our framework exhibit superior transferability and Max-SAT can boost the ability to solve COs on graphs.

关键词： combinatorial optimization graph neural networks domain adaptation maximum satisfiability problem

On traceable iterated line graph and hamiltonian path index

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Applied Mathematics(A Journal of Chinese Universities) 2024年第2期39卷 239-252页

作者： niu Zhao-hong XIONG Li-ming YANG Wei-hua School of Mathematical Sciences Shanxi UniversityTaiyuan 030006China School of Mathematics and Statistics Beijing Key Laboratory on MCAACIBeijing Institute of TechnologyBeijing 100081China Department of Mathematics Taiyuan University of TechnologyTaiyuan 030024China

Xiong and Liu[21]gave a characterization of the graphs G for which the n-iterated line graph L^(n)(G)is hamiltonian,for n≥2.In this paper,we study the existence of a hamiltonian path in L^(n)(G),and give a characterization of G for which L^(n)(G)has a hamiltonian path.As applications,we use this characterization to give several upper bounds on the hamiltonian path index of a graph.

关键词： iterated line graph traceable hamiltonian index hamiltonian path index

Development of a cell adhesion-based prognostic model for multiple myeloma:Insights into chemotherapy response and potential reversal of adhesion effects

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Oncology Research 2024年第4期32卷 753-768页

作者： QIAN HU MENGYAO WANG JINJIN WANG YALI TAO TING niu Department of Hematology West China HospitalSichuan UniversityChengdu610041China

Multiple myeloma(MM)is a hematologic malignancy notorious for its high relapse rate and development of drug resistance,in which cell adhesion-mediated drug resistance plays a critical role.This study integrated four RNA sequencing datasets(CoMMpass,GSE136337,GSE9782,and GSE2658)and focused on analyzing 1706 adhesionrelated genes.Rigorous univariate Cox regression analysis identified 18 key prognosis-related genes,including KIF14,TROAP,FLNA,MSN,LGALS1,PECAM1,and ALCAM,which demonstrated the strongest associations with poor overall survival(OS)in MM patients.To comprehensively evaluate the impact of cell adhesion on MM prognosis,an adhesion-related risk score(ARRS)model was constructed using Lasso Cox regression analysis.The ARRS model emerged as an independent prognostic factor for predicting OS.Furthermore,our findings revealed that a heightened cell adhesion effect correlated with tumor resistance to DNA-damaging drugs,protein kinase inhibitors,and drugs targeting the PI3K/Akt/mTOR signaling pathway.Nevertheless,we identified promising drug candidates,such as tirofiban,pirenzepine,erlotinib,and bosutinib,which exhibit potential in reversing this resistance.In vitro,experiments employing NCIH929,RPMI8226,and AMO1 cell lines confirmed that MM cell lines with high ARRS exhibited poor sensitivity to the aforementioned candidate drugs.By employing siRNA-mediated knockdown of the key ARRS model gene KIF14,we observed suppressed proliferation of NCIH929 cells,along with decreased adhesion to BMSCs and fibronectin.This study presents compelling evidence establishing cell adhesion as a significant prognostic factor in MM.Additionally,potential molecular mechanisms underlying adhesion-related resistance are proposed,along with viable strategies to overcome such resistance.These findings provide a solid scientific foundation for facilitating clinically stratified treatment of MM.

关键词： Cell adhesion Bioinformatics Prognosis Multiple myeloma CAM-DR

UAV-assisted cooperative offloading energy efficiency system for mobile edge computing

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Digital Communications and Networks 2024年第1期10卷 16-24页

作者： Xue-Yong Yu Wen-Jin niu Ye Zhu Hong-Bo Zhu Jiangsu Key Laboratory of Wireless Communications Nanjing University of Posts and Telecommunications Nanjing210003China Engineering Research Centerof Health Service System Based on Ubiquitous Wireless Nework Ministyof EducationNanjng Universityof Posts and Telecommunication Nanjing210003China

Reliable communication and intensive computing power cannot be provided effectively by temporary hot spots in disaster areas and complex terrain ground infrastructure.Mitigating this has greatly developed the application and integration of UAV and Mobile Edge Computing(MEC)to the Internet of Things(loT).However,problems such as multi-user and huge data flow in large areas,which contradict the reality that a single UAV is constrained by limited computing power,still exist.Due to allowing UAV collaboration to accomplish complex tasks,cooperative task offloading between multiple UAVs must meet the interdependence of tasks and realize parallel processing,which reduces the computing power consumption and endurance pressure of terminals.Considering the computing requirements of the user terminal,delay constraint of a computing task,energy constraint,and safe distance of UAV,we constructed a UAV-Assisted cooperative offloading energy efficiency system for mobile edge computing to minimize user terminal energy consumption.However,the resulting optimization problem is originally nonconvex and thus,difficult to solve optimally.To tackle this problem,we developed an energy efficiency optimization algorithm using Block Coordinate Descent(BCD)that decomposes the problem into three convex subproblems.Furthermore,we jointly optimized the number of local computing tasks,number of computing offloaded tasks,trajectories of UAV,and offloading matching relationship between multi-UAVs and multiuser terminals.Simulation results show that the proposed approach is suitable for different channel conditions and significantly saves the user terminal energy consumption compared with other benchmark schemes.

关键词： Computation offloading Internet of things(IoT) Mobile edge computing(MEC) Block coordinate descent(BCD)

Enhancing cut selection through reinforcement learning

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Science China Mathematics 2024年第6期67卷 1377-1394页

作者： Shengchao Wang Liang Chen Lingfeng niu Yu-Hong Dai Academy of Mathematics and Systems Science Chinese Academy of SciencesBeijing100190China Research Center on Fictitious Economy and Data Science Chinese Academy of SciencesBeijing100190China

With the rapid development of artificial intelligence in recent years,applying various learning techniques to solve mixed-integer linear programming(MILP)problems has emerged as a burgeoning research domain.Apart from constructing end-to-end models directly,integrating learning approaches with some modules in the traditional methods for solving MILPs is also a promising direction.The cutting plane method is one of the fundamental algorithms used in modern MILP solvers,and the selection of appropriate cuts from the candidate cuts subset is crucial for enhancing efficiency.Due to the reliance on expert knowledge and problem-specific heuristics,classical cut selection methods are not always transferable and often limit the scalability and generalizability of the cutting plane method.To provide a more efficient and generalizable strategy,we propose a reinforcement learning(RL)framework to enhance cut selection in the solving process of MILPs.Firstly,we design feature vectors to incorporate the inherent properties of MILP and computational information from the solver and represent MILP instances as bipartite graphs.Secondly,we choose the weighted metrics to approximate the proximity of feasible solutions to the convex hull and utilize the learning method to determine the weights assigned to each metric.Thirdly,a graph convolutional neural network is adopted with a self-attention mechanism to predict the value of weighting factors.Finally,we transform the cut selection process into a Markov decision process and utilize RL method to train the model.Extensive experiments are conducted based on a leading open-source MILP solver SCIP.Results on both general and specific datasets validate the effectiveness and efficiency of our proposed approach.

关键词： reinforcement learning mixed-integer linear programming cutting plane method cut selection

Sliding behaviors of the trapezoidal roof rock block under a lateral dynamic disturbance

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Journal of Rock Mechanics and Geotechnical Engineering 2024年第3期16卷 741-760页

作者： Feng Dai Wancheng Zhu Min Ren Shunchuan Wu Leilei niu Faculty of Land Resources Engineering Kunming University of Science and TechnologyKunming650093China Center for Rock Instability and Seismicity Research Department of Mining EngineeringSchool of Resource and Civil EngineeringNortheastern UniversityShenyang110819China

The surrounding rock of underground space is always affected by external dynamic disturbance from the side position,such as blasting vibration from a stope at the same level or seismic waves from adjacent strata.A series of laboratory tests,numerical simulations and theoretical analyses were carried out in this study to disclose the sliding mechanism of roof rock blocks under lateral disturbance.Firstly,the experiments on trapezoidal key block under various clamping loads and disturbance were conducted,followed by numerical simulations using the fast Lagrangian analysis of continua(FLAC3D).Then,based on the conventional wave propagation model and the classical shear-slip constitutive model,a theoretical model was proposed to capture the relative displacement between blocks and the sliding displacement of the key block.The results indicate that the sliding displacement of the key block increased linearly with the disturbance energy and decreased exponentially with the clamping load when the key block was disturbed to slide(without instability).Meanwhile,when the key block was disturbed to fall,two types of instability process may appear as immediate type or delayed type.In addition,the propagation of stress waves in the block system exhibited obvious low-velocity and lowfrequency characteristics,resulting in the friction reduction effect appearing at the contact interface,which is the essential reason for the sliding of rock blocks.The results can be applied to practical underground engineering and provide valuable guidance for the early detection and prevention of rockfalling disasters.

关键词： Lateral dynamic disturbance Trapezoidal rock block system Low-velocity and low-frequency wave Friction reduction effect Instability mode

Spatial Differentiation and Convergence Trend of High-quality Development Level of China’s Tourism Economy

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Chinese Geographical Science 2024年第2期34卷 230-249页

作者： CAO Shanshan HE Zhaoli niu Jinlan WANG Songmao ZHAO Lei School of Geography and Ocean Science Nanjing UniversityNanjing 210046China School of Business Administration Nanjing University of Finance and EconomicsNanjing 210046China School of Economics and Management Shandong Agricultural Uni-versityTai’an 271018China School of Hotel Management Shanghai Business SchoolShanghai 201400China School of Man-agement Zhejiang University of TechnologyHangzhou 310014China

This paper aims to interpret the connotation of high-quality development of tourism economy(HQTE)from the perspective of the new development concepts of innovation,coordination,green,openness and sharing,and then to evaluate the spatial differenti-ation of China’s HQTE based on provincial panel data from 2009 to 2018.Specifically,we employ the spatial convergence model to ex-plore the absolute and conditionalβconvergence trends of HQTE in the whole country and the eastern,central and western regions of China.Our empirical results reveal that:1)within the decade,from 2009 to 2018,regions of China with the highest HQTE index is its eastern region followed by the central region and then the western region,but the fastest growing one is the western region of China fol-lowed by the central region and then the eastern region.2)Whether or not the spatial effect is included,there are absolute and condition-alβconvergence in HQTE in the whole country and aforementioned three regions.3)The degree of government attention as well as the level of economic development and location accessibility are the positive driving factors for the convergence of HQTE in the whole country and the three regions.The degree of marketization and human capital have not passed the significance test either in the whole country or in the three regions.The above conclusions could deepen the understanding of the regional imbalance and spatial conver-gence characteristics of HQTE,clarify the primary development objects,and accomplish the goal of China’s HQTE.

关键词： new development concepts high-quality development of tourism economy(HQTE) spatial convergence China

Sustainable Intensification and Large-scale Operation of Cultivated Land Use at the Farmers’ Scale:A Case Study of Shandong Province,China

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Chinese Geographical Science 2024年第1期34卷 149-167页

作者： LI Li LYU Xiao ZHANG Anlu niu Shandong PENG Wenlong School of Public Administration Huazhong Agricultural UniversityWuhan430070China Department of Geography University of ZurichZurich8057Switzerland School of Humanities and Law Northeastern UniversityShenyang110169China School of Geography and Tourism Qufu Normal UniversityRizhao276800China

Sustainable intensification of cultivated land use(SICLU) and large-scale operations(LSO) are widely acknowledged strategies for enhancing agricultural performance.However,the existing literature has faced challenges in precisely defining SICLU and constructing comprehensive indicators,which has hindered the exploration of factors influencing LSO within the SICLU framework.To address this gap,we integrated self-efficacy theory into the design of an index framework for evaluating SICLU.We subsequently employed econometric models to analyze the significant factors that impact LSO.Our findings reveal that SICLU can be divided into four key dimensions:intensive management,efficient output,resource conservation,and ecological environment optimization.Furthermore,it is crucial to incorporate belief-based cognitive factors into the index system,as farmers’ understanding of fertilizer and pesticide application significantly influences their willingness to engage in LSO.Moreover,we identify grain market turnover as the most influential factor in promoting LSO,with single-factor contribution rates reaching 70.9% for cultivated land transfer willingness and 62.5% for the total planting areas.Interestingly,unlike irrigation and agricultural machinery inputs,increased labor inputs correspond to larger planting areas for farmers.This trend may be attributed to reduced labor availability because of rural labor migration,whereas the reduction in irrigation and agricultural input is contingent on innovations in production practices and the transfer of cultivated land management rights.Importantly,SICLU dynamically influences LSO,with each index related to SICLU having an optimal range that fosters LSO.These insights offer valuable guidance for policymakers,emphasizing farmers as their central focus,with the adjustment of input and output factors as a means to achieve LSO as the ultimate goal.In conclusion,we propose research avenues for further enriching the SICLU framework to ensure that it aligns with the specific characteristi

关键词： sustainable intensification of cultivated land use(SICLU) self-efficacy status quo bias input and output Boosted Regression Tree willingness to transfer cultivated land cultivated land planting areas Shandong,China