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Prediction of high-embankment settlement combining joint denoising technique and enhanced GWO-v-SVR method

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Journal of Rock Mechanics and Geotechnical Engineering 2024年第1期16卷 317-332页

作者： Qi Zhang Qian Su Zongyu Zhang zhixing deng De Chen School of Civil Engineering Southwest Jiaotong UniversityChengduChina MOE Key Laboratory of High Speed Railway Engineering Southwest Jiaotong UniversityChengduChina

Reliable long-term settlement prediction of a high embankment relates to mountain infrastructure *** study developed a novel hybrid model(NHM)that combines a joint denoising technique with an enhanced gray wolf optimizer(EGWO)-n-support vector regression(n-SVR)***-embankment field measurements were preprocessed using the joint denoising technique,which in-cludes complete ensemble empirical mode decomposition,singular value decomposition,and wavelet packet ***,high-embankment settlements were predicted using the EGWO-n-SVR *** this method,the standard gray wolf optimizer(GWO)was improved to obtain the EGWO to better tune the n-SVR model *** proposed NHM was then tested in two case ***,the influences of the data division ratio and kernel function on the EGWO-n-SVR forecasting performance and prediction efficiency were *** results indicate that the NHM suppresses noise and restores details in high-embankment field ***,the NHM out-performs other alternative prediction methods in prediction accuracy and *** demonstrates that the proposed NHM is effective in predicting high-embankment settlements with noisy field ***,the appropriate data division ratio and kernel function for EGWO-n-SVR are 7:3 and radial basis function,respectively.

关键词： High embankment Settlement prediction Joint denoising technique Enhanced gray wolf optimizer Support vector regression

D-BERT: Incorporating dependency-based attention into BERT for relation extraction

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CAAI Transactions on Intelligence Technology 2021年第4期6卷 417-425页

作者： Yuan Huang zhixing Li Wei deng Guoyin Wang Zhimin Lin Chongqing Key Laboratory of Computational Intelligence Chongqing University of Posts and TelecommunicationsChongqingChina Centet of Statistical Research Southwestern Univetsity of Finance and EconomicsChengduChina

Relation extraction between entity pairs is an increasingly critical area in natural language *** the pre-trained bidirectional encoder representation from transformer(BERT)performs excellendy on the text classification or sequence labelling ***,the high-level syntactic features that consider the dependency between each word and the target entities into the pre-trained language models are *** model also utilizes the intermediate layers of BERT to acquire different levels of semantic information and designs multi-granularity features for final relation *** model offers a momentous improvement over the published methods for the relation extraction on the widely used data sets.

关键词： BERT relation processing.

Computer vision-aided DEM study on the compaction characteristics of graded subgrade filler considering realistic coarse particle shapes

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Railway Engineering Science 2024年第2期32卷 194-210页

作者： Taifeng Li Kang Xie Xiaobin Chen zhixing deng Qian Su Railway Engineering Research Institute China Academy of Railway Sciences Corporation LimitedBeijing 100081China Department of Civil Engineering Central South UniversityChangsha 410075China School of Civil Engineering Southwest Jiaotong UniversityChengdu 610031China

The compaction quality of subgrade filler strongly affects subgrade *** main objective of this research is to analyze the macro-and micro-mechanical compaction characteristics of subgrade filler based on the real shape of coarse ***,an improved Viola-Jones algorithm is employed to establish a digitalized 2D particle database for coarse particle shape evaluation and discrete modeling purposes of subgrade *** indexes of 2D subgrade filler are then computed and statistically ***,numerical simulations are performed to quantitatively investigate the effects of the aspect ratio(AR)and interparticle friction coefficient(μ)on the macro-and micro-mechanical compaction characteristics of subgrade filler based on the discrete element method(DEM).The results show that with the increasing AR,the coarse particles are narrower,leading to the increasing movement of fine particles during compaction,which indicates that it is difficult for slender coarse particles to inhibit the migration of fine ***,the average displacement of particles is strongly influenced by the AR,indicating that their occlusion under power relies on particle *** dis-placement and velocity of fine particles are much greater than those of the coarse particles,which shows that compaction is primarily a migration of fine *** the cyclic load,the interparticle friction coefficientμhas little effect on the internal structure of the sample;under the quasi-static loads,however,the increase inμwill lead to a significant increase in the porosity of the *** study could not only provide a novel approach to investigate the compaction mechanism but also establish a new theoretical basis for the evaluation of intelligent subgrade compaction.

关键词： Subgrade filler particles Deep learning particle Shape analysis Particle library Compaction characteristics Discrete element method(DEM)

Physical modeling of long-term dynamic characteristics of the subgrade for medium-low-speed maglevs

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Railway Engineering Science 2023年第3期31卷 293-308页

作者： Minqi Dong Wubin Wang Chengjin Wang Zhichao Huang Zhaofeng Ding zhixing deng Qian Su School of Civil Engineering Southwest Jiaotong UniversityChengdu 610031China National Engineering Research Center of Geological Disaster Prevention Technology in Land Transportation Southwest Jiaotong UniversityChengdu 611756China China Railway Maglev Transportation Investment Construction China Railway Construction Corporation LimitedWuhan 430000China

To investigate the dynamic characteristics and long-term dynamic stability of the new subgrade structure of medium-low-speed(MLS)maglevs,cyclic vibration tests were performed under natural and rainfall conditions,and the dynamic response of the subgrade structure was *** dynamic response attenuation characteristics along the depth direction of the subgrade were compared,and the distribution characteristics of the dynamic stress on the surface of the subgrade along the longitudinal direction of the line were *** critical dynamic stress and cumulative deformation were used as indicators to evaluate the long-term dynamic stability of the *** show that water has a certain effect on the dynamic characteristics of the subgrade,and the dynamic stress and acceleration increase with the water *** the dowel steel structure set between the rail-bearing beams,stress concentration at the end of the loaded beam can be prevented,and the diffusion distance of the dynamic stress along the longitudinal direction *** dynamic stress measured in the subgrade bed range is less than 1/5 of the critical dynamic *** postconstruction settlement of the subgrade after similarity ratio conversion is 3.94 mm and 7.72 mm under natural and rainfall conditions,respectively,and both values are less than the 30 mm limit,indicating that the MLS maglev subgrade structure has good long-term dynamic stability.

关键词： Medium-low-speed maglev Subgrade Dynamic characteristics Long-term dynamic stability Model test

Preparation of low cobalt-doped LiNiO2 materials by the spray pyrolysis method

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Progress in Natural Science:Materials International 2023年第4期33卷 425-432页

作者： Bianzheng You zhixing Wang Ding Wang Gui luo Duo deng Guochun Yan Huajun Guo Xinhai Li Wenjie Peng Mingxia Dong Jiexi Wang National Key Laboratory of Energy Metal Resources and New Materials Engineering Research Center of the Ministry of Education for Advanced Battery Materials Hunan Provincial Key Laboratory of Nonferrous Value-Added Metallurgy School of Metallurgy and Environment Central South University National and Local Joint Engineering Laboratory for Lithium-ion Batteries and Materials Preparation Technology Key Laboratory of Advanced Battery Materials of Yunnan Province Faculty of Metallurgical and Energy Engineering Kunming University of Science and Technology Research Institute BASF Shanshan Battery Materials Co LTD.

LiNiO2(LNO) is recognized as the most promising cathode material for next-generation lithium-ion batteries owing to its highest energy density and economic benefit in the layered oxide cathode materials ***, severe cation disordering, multiple phase transformations and poor lithium-ion diffusion kinetics,which result in rapid degradation of cycling stabilities and rate properties, hinder its further practical applications. Cobalt doping is an effective strategy to address such issues, but the influences of cobalt on LNO materials have not been figured out completely yet. Hence, a systematical investigation of cobalt doping for LiNiO2cathode materials prepared by spray pyrolysis is conducted. The addition of cobalt enhances the stabilities of layered structures and suppresses the cation disordering effectively. The multiple-phase transformations during cycling are also alleviated significantly. Furthermore, cobalt doping can decrease charge transfer resistances and improve lithium-ion diffusion kinetics, especially at high de-lithiation states. As a result, the electrochemical performances are improved comprehensively after cobalt doping. The LNO with optimal doping amount exhibits an improved capacity retention of 78.0% after 100 cycles as compared with 64.9% for pristine LNO, and an outstanding rate performance of 167.2 mA h g-1with the current density of 5 C(1 C = 200 mA g-1).

关键词： Lithium nickel oxides Spray pyrolysis Cobalt doping Phase transformations Lithium-ion diffusion kinetics

Step-edge controlled fast growth of wafer-scale MoSe_(2)films by MOCVD

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Nano Research 2023年第7期16卷 9577-9583页

作者： Rui Ji Jing Liao Lintao Li Rongji Wen Mengjie Liu Yifeng Ren Jianghua Wu Yunrui Song Minru Qi zhixing Qiao Liwei Liu Chengbing Qin Yu deng Yongtao Tian Suotang Jia Yufeng Hao Key Laboratory of Material Physics of Ministry of Education School of Physics and MicroelectronicsZhengzhou UniversityZhengzhou 450052China National Laboratory of Solid State Microstructures College of Engineering and Applied SciencesJiangsu Key Laboratory of Artificial Functional Materialsand Collaborative Innovation Center of Advanced MicrostructuresNanjing UniversityNanjing 210023China State Key Laboratory of Quantum Optics and Quantum Optics Devices Institute of Laser SpectroscopyShanxi UniversityTaiyuan 030006China Collaborative Innovation Center of Extreme Optics Shanxi UniversityTaiyuan 030006China College of Medical Imaging Shanxi Medical UniversityTaiyuan 030001China MIIT Key Laboratory for Low-Dimensional Quantum Structure and Devices School of Integrated Circuits and ElectronicsBeijing Institute of TechnologyBeijing 100081China

Two-dimensional(2D)transition metal dichalcogenides(TMDCs),due to their unique physical properties,have a wide range of applications in the next generation of electronics,optoelectronics,and ***-scale preparation of high-quality TMDCs films is critical to realize these potential *** we report a study on metal-organic chemical vapor deposition(MOCVD)growth of wafer-scale MoSe_(2)films guided by the crystalline step edges of miscut sapphire *** established that the nucleation density and growth rate of MoSe_(2)films were positively correlated with the step-edge density and negatively with the growth *** a certain temperature,the MoSe_(2)domains on the substrate with high step-edge density grow faster than that with low *** a result,wafer-scale and continuous MoSe_(2)films can be formed in a short duration(30 min).The MoSe_(2)films are of high crystalline quality,as confirmed by systematic Raman and photoluminescence(PL)*** results provide an important methodology for the rapid growth of wafer-scale TMDCs,which may promote the application of 2D semiconductors.

关键词： MoSe_(2) nucleation density transition metal dichalcogenides metal-organic chemical vapor deposition(MOCVD) waferscale two-dimensional(2D)semiconductor

Catalytic performance enhancement by alloying Pd with Pt on ordered mesoporous manganese oxide for methane combustion

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Chinese Journal of Catalysis 2017年第1期38卷 92-105页

作者： Peng Xu zhixing Wu Jiguang deng Yuxi Liu Shaohua Xie Guangsheng Guo Hongxing Dai Beijing Key Laboratory for Green Catalysis and Separation Key Laboratory of Beijing on Regional Air Pollution Control Key Laboratory of Advanced Functional Materials Education Ministry of China and Laboratory of Catalysis Chemistry and Nanoscience Department of Chemistry and Chemical Enginee

Ordered mesoporous Mn2O3 (meso‐Mn2O3) and meso‐Mn2O3‐supported Pd, Pt, and Pd‐Pt alloy x(PdyPt)/meso‐Mn2O3; x = (0.10?1.50) wt%; Pd/Pt molar ratio (y) = 4.9?5.1 nanocatalysts were prepared using KIT‐6‐templated and poly(vinyl alcohol)‐protected reduction methods, *** meso‐Mn2O3 had a high surface area, i.e., 106 m2/g, and a cubic crystal structure. Noble‐metalnanoparticles (NPs) of size 2.1?2.8 nm were uniformly dispersed on the meso‐Mn2O3 surfaces. AlloyingPd with Pt enhanced the catalytic activity in methane combustion; 1.41(Pd5.1Pt)/meso‐Mn2O3gave the best performance; T10%, T50%, and T90% (the temperatures required for achieving methaneconversions of 10%, 50%, and 90%) were 265, 345, and 425 °C, respectively, at a space velocity of20000 mL/(g?h). The effects of SO2, CO2, H2O, and NO on methane combustion over1.41(Pd5.1Pt)/meso‐Mn2O3 were also examined. We conclude that the good catalytic performance of1.41(Pd5.1Pt)/meso‐Mn2O3 is associated with its high‐quality porous structure, high adsorbed oxygen species concentration, good low‐temperature reducibility, and strong interactions between Pd‐Pt alloy NPs and the meso‐Mn2O3 support.

关键词： Ordered mesoporous manganese oxide Pd‐Pt alloy nanoparticle Supported noble metal catalyst Strong metal‐support interaction Methane combustion

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人工智能在抗癌肽研发中的应用与挑战

中国药科大学学报 2024年第3期55卷 347-356页

作者：张志星邓华唐贇华东理工大学药学院上海市新药设计重点实验室上海200237

抗癌肽(anticancer peptides,ACPs)因其高效低毒和高选择性优势成为研究焦点,而基于人工智能的ACPs识别和设计方法较传统实验方法成本低廉、成功率高且能够探索更广阔的序列空间。本文重点介绍了人工智能技术在ACPs生成和识别过程中的应... 详细信息

抗癌肽(anticancer peptides,ACPs)因其高效低毒和高选择性优势成为研究焦点,而基于人工智能的ACPs识别和设计方法较传统实验方法成本低廉、成功率高且能够探索更广阔的序列空间。本文重点介绍了人工智能技术在ACPs生成和识别过程中的应用,包括深度生成模型探索新型ACPs设计以及基于机器学习和深度学习的ACPs识别方法。此外,文章还讨论了当前研究中存在的模型可复现性和可解释性不足、缺乏经过实验验证的阴性数据等挑战,并对未来研究方向提出展望,以期为ACPs的研发提供新思路。

关键词：抗癌肽人工智能机器学习深度学习

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分数间隔采样的并行均衡新算法

清华大学学报（自然科学版） 2005年第1期45卷 13-16页

作者：邓拥军杨知行郭兴波清华大学电子工程系微波与数字通信技术国家重点实验室北京100084

由于模拟接收机在宽带条件下的性能不稳定等缺点,全数字接收机逐渐引起了人们的兴趣。针对一种全数字并行接收机结构(APRX),提出了一种分数间隔的并行均衡新算法(PFSE)。该算法基于恒模算法(CMA),充分利用了APRX中的数据重叠特点,实现... 详细信息

由于模拟接收机在宽带条件下的性能不稳定等缺点,全数字接收机逐渐引起了人们的兴趣。针对一种全数字并行接收机结构(APRX),提出了一种分数间隔的并行均衡新算法(PFSE)。该算法基于恒模算法(CMA),充分利用了APRX中的数据重叠特点,实现了与上述APRX结构的完美结合。此外,还分析了由于该并行均衡器的引入,对APRX环路稳定性、环路噪声带宽等性能所产生的影响。仿真结果表明:该并行分数间隔均衡器的性能相对于波特间隔采样的均衡器具有明显的优势,而且相对于串行分数间隔均衡器,就消除串扰能力而言,该并行算法基本上没有带来损失。

关键词：微波通信恒模算法并行分数间隔均衡器全数字并行接收机