Search

Your search keyword '"Xiang Meng"' showing total 123 results
Start Over Author "Xiang Meng" Publisher elsevier bv
123 results on '"Xiang Meng"'

10. A novel lung cancer stem cell extracellular vesicles lncRNA ROLLCSC modulate non-stemness cancer cell plasticity through miR-5623-3p and miR-217-5p targeting lipid metabolism

Author

Zhang, Yu-Han, primary, Chen, Yan, additional, Shi, Lei, additional, Han, Xue, additional, Xie, Jia-Cheng, additional, Chen, Yuting, additional, Xiang, Meng, additional, Li, Bo-Wen, additional, Li, Jie, additional, Xing, H. Rosie, additional, and Wang, Jian-Yu, additional

Published
2023
Full Text
View/download PDF

19. TWIK-related acid-sensitive K+ channel 2 promotes renal fibrosis by inducing cell-cycle arrest

Author

Zhang, Jian, primary, Chen, Jing, additional, Lu, Yufei, additional, Yang, Yan, additional, Chen, Weize, additional, Shen, Bo, additional, Hu, Jiachang, additional, Jia, Ping, additional, Xu, Sujuan, additional, Shi, Yiqin, additional, Ning, Yichun, additional, Wang, Jialin, additional, Fang, Yi, additional, Zhao, Shuan, additional, Li, Yang, additional, Dai, Yan, additional, Zhang, Xiaoyan, additional, Xiang, Meng, additional, Tian, Yang, additional, Liu, Zhichao, additional, Song, Nana, additional, and Ding, Xiaoqiang, additional

Published
2022
Full Text
View/download PDF

20. Fitness distance correlation and mixed search strategy for differential evolution

Author

Xiang Meng, Wei Li, and Ying Huang

Subjects
0209 industrial biotechnology, Mathematical optimization, Optimization problem, Fitness landscape, Computer science, Cognitive Neuroscience, Evolutionary algorithm, 02 engineering and technology, Computer Science Applications, Distance correlation, 020901 industrial engineering & automation, Local optimum, Artificial Intelligence, Differential evolution, Mutation (genetic algorithm), 0202 electrical engineering, electronic engineering, information engineering, 020201 artificial intelligence & image processing, Evolutionary dynamics
Abstract

The fitness landscape is a theory applied to the evolutionary dynamics of biological evolution to explain the behavior of evolutionary algorithms in the solution of optimization problems. With the continuous advancement of evolutionary algorithm optimization, a fitness landscape can present more abundant feature information, such as the local fitness, fitness distance correlation, and landscape roughness. These landscape features reflect the optimal solution distribution, quantity, and local unimodal topology of the optimization problem from various angles. This paper expresses the adaptability landscape features of typical optimization problems, engages in a quantitative analysis of the fitness distance correlation information, evaluates the difficulty of solving the problem within the search space, and obtains the correlation degree classification result. The search strategy adapts the mixed mutation and the fitness distance correlation for differential evolution. Empirical studies show that, the fitness distance correlation search strategy for the differential evolution algorithm can avoid falling into the local optimum, improve accuracy and convergence, and solve the single-objective optimization problem in a more comprehensive manner.

Published
2021

29. Grain refinement of Mg-3Y alloy using Mg-10Al2Y master alloy

Author

Zhong-Tao Jiang, Xiang Meng, Bin Jiang, Yongfeng Ding, Shan Jiang, Jiahong Dai, and Dong Jingren

Subjects
Number density, Materials science, Settling time, Metallurgy, Alloy, 02 engineering and technology, General Chemistry, engineering.material, 010402 general chemistry, 021001 nanoscience & nanotechnology, 01 natural sciences, 0104 chemical sciences, Geochemistry and Petrology, Phase (matter), Ultimate tensile strength, engineering, Elongation, 0210 nano-technology, Refining (metallurgy), Holding time
Abstract

The as-extruded Mg-10Al2Y master alloy was chosen as a novel grain refiner for as-cast Mg-3Y alloy. Contrast samples of cast Mg-3Y alloy added with pure Al and Mg-Zr master alloy grain refiners were prepared under the same conditions. In this study, the influence of addition amounts of Al2Y and holding time on grain refinement efficiency as well as tensile properties was investigated. And the grain refining ability of the Al2Y particles was systematically evaluated in terms of the addition amounts, number density of the Al2Y particles and holding time. The finest grains are achieved at 2 wt% Al2Y addition amount, which corresponds to number density of the polygonal Al2Y particles of 420–460 mm–2. The Mg-10Al2Y master alloy has significant refinement performance and no refining recession occurs at the holding time within 60 min, or the settling time up to 180 min. Grain refinement and the second phase strengthening of uniformly distributed Al2Y particles contribute to the simultaneous enhancement on both strength and elongation of Mg-3Y alloy.

Published
2021

38. Multipopulation cooperative particle swarm optimization with a mixed mutation strategy

Author

Xiang Meng, Ying Huang, Wei Li, and Zhang-Hua Fu

Subjects
Mathematical optimization, Information Systems and Management, Optimization problem, Speedup, Computer science, 05 social sciences, 050301 education, Particle swarm optimization, 02 engineering and technology, Computer Science Applications, Theoretical Computer Science, Operator (computer programming), Artificial Intelligence, Control and Systems Engineering, Position (vector), Mutation (genetic algorithm), 0202 electrical engineering, electronic engineering, information engineering, Benchmark (computing), 020201 artificial intelligence & image processing, 0503 education, Software, Coevolution
Abstract

The traditional particle swarm optimization algorithm learns from the two best experiences: the best position previously learned by the particle itself and the best position learned by the entire population to date. This learning strategy is simple and ordinary, but when addressing high-dimensional optimization problems, it is unable to quickly find the global optimal solution due to its low efficiency. This paper proposes a multipopulation cooperative particle swarm optimization (MPCPSO) algorithm with a dynamic segment-based mean learning strategy and a multidimensional comprehensive learning strategy. In MPCPSO, the dynamic segment-based mean learning strategy (DSMLS), which is employed to construct learning exemplars, achieves information sharing and coevolution between populations. The multidimensional comprehensive learning strategy (MDCLS) is employed to speed up convergence and improve the accuracy of MPCPSO solutions. Additionally, a differential mutation operator is introduced to increase the population diversity and enhance the global exploration ability of MPCPSO. Sixteen benchmark functions and seven well-known PSO variants are employed to verify the advantages of MPCPSO. The comparison results indicate that MPCPSO has a faster convergence speed, obtains more accurate solutions, and is more robust.

Published
2020

39. Self-supported yttria-stabilized zirconia ripple-shaped electrolyte for solid oxide fuel cells application by digital light processing three-dimension printing

Author

Shuyue Gao, Zhe Zhao, Xiang Meng, Bohang Xing, Weiming Zhao, Yongxia Yao, and Minhao Shen

Subjects
010302 applied physics, Materials science, business.industry, Mechanical Engineering, Metals and Alloys, Oxide, 3D printing, 02 engineering and technology, Electrolyte, 021001 nanoscience & nanotechnology, Condensed Matter Physics, Electrochemistry, 01 natural sciences, chemistry.chemical_compound, chemistry, Mechanics of Materials, 0103 physical sciences, General Materials Science, Cubic zirconia, Digital Light Processing, Composite material, 0210 nano-technology, business, Yttria-stabilized zirconia, Power density
Abstract

In this work, 8mol% yttria-stabilized zirconia (8YSZ) ripple-shaped electrolytes have been prepared by digital light processing (DLP) 3D printing and their electrochemical performances have been investigated. The total conductivities of flat samples printed at different angles were tested firstly to confirm that there is no huge influence on the electrochemical performance from the printing itself. Then, by using ripple-shaped electrolytes, primary cells were assembled and their electrochemical performance were investigated. Compared with the reference flat cell, an improvement of ~32% was achieved in the power density for the same thickness of the electrolyte (~200 µm) at 800 °C.

Published
2020

40. Robust Control Optimization for Quantum Approximate Optimization Algorithms

Author

Xiang Meng, Yulong Dong, K. Birgitta Whaley, Lin Lin, and Robert L. Kosut

Subjects
0209 industrial biotechnology, Optimization algorithm, Computer science, media_common.quotation_subject, 020208 electrical & electronic engineering, Robust optimization, Fidelity, Scale (descriptive set theory), 02 engineering and technology, 020901 industrial engineering & automation, Control and Systems Engineering, Robustness (computer science), 0202 electrical engineering, electronic engineering, information engineering, State (computer science), Robust control, Quantum, Algorithm, media_common
Abstract

Quantum variational algorithms have garnered significant interest recently, due to their feasibility of being implemented and tested on noisy intermediate scale quantum (NISQ) devices. We examine the robustness of the quantum approximate optimization algorithm (QAOA), which can be used to solve certain quantum control problems, state preparation problems, and combinatorial optimization problems. We demonstrate that the error of QAOA simulation can be significantly reduced by robust control optimization techniques, specifically, by sequential convex programming (SCP), to ensure error suppression in situations where the source of the error is known but not necessarily its magnitude. We show that robust optimization improves both the objective landscape of QAOA as well as overall circuit fidelity in the presence of coherent errors and errors in initial state preparation.

Published
2020

Catalog

Books, media, physical & digital resources
See catalog results