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Determination of Impurity Elements in Pure Cerium Oxide Product

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Journal of Rare Earths 2004年第Z1期22卷 335-336页

作者： li Peizhong Chen limin li Jie Inner Mongolia Baogang Rare Earth High Science and Technology Co. Ltd. Baotou 014010 China Inner Mongolia Baogang Rare Earth High Science and Technology Co. Ltd.Baotou 014010 China Inner Mongolia Baogang Rare Earth High Science and Technology Co. Ltd.Baotou 014010 China

Determination of the rare earth impurity in pure cerium oxide is done by *** interference and other factors which affect analytical results were *** accuracy are between 0.81% ～ 11.98% and the recoveries of standard ... 详细信息

关键词： cerium oxide inductively coupled plasma mass spectrometry pure cerium oxide product rare earths

ON NETWORK-BASED KERNEL METHODS FOR PROTEIN-PROTEIN INTERACTIONS WITH APPliCATIONS IN PROTEIN FUNCTIONS PREDICTION

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Journal of Systems Science & Complexity 2010年第5期23卷 917-930页

作者： limin li Waiki CHING Yatming CHAN Hiroshi MAMITSUKA Department of Mathematics Xi'an Jiaotong University Xi'an 710049 China Advanced Modeling and Applied Computing Laboratory Department of Mathematics The University of Hong Kong Pokfularn Road Hong Kong China Bioinformatics Center Institute for Chemical Research Kyoto University Gokasho Uji Kyoto 611-0011 Japan

Predicting protein functions is an important issue in the post-genomic era. This paper studies several network-based kernels including local linear embedding （LLE） kernel method, diffusion kernel and laplacian kernel to uncover the relationship between proteins functions and protein-protein interactions （PPI）. The author first construct kernels based on PPI networks, then apply support vector machine （SVM） techniques to classify proteins into different functional groups. The 5-fold cross validation is then applied to the selected 359 GO terms to compare the performance of different kernels and guilt-by-association methods including neighbor counting methods and Chi-square methods. Finally, the authors conduct predictions of functions of some unknown genes and verify the preciseness of our prediction in part by the information of other data source.

关键词： Diffusion kernel kernel method Laplacian kernel local linear embedding (LLE) kernel protein function prediction support vector machine.

Synthesis and Characterization of a Novel Soluble Diethoxy Phosphoryl Chitosan

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Chinese Journal of Chemistry 2012年第2期30卷 413-417页

作者： Ma,li li,Kerang li,limin liu,Pu Department of Chemistry Zhengzhou UniversityZhengzhouHenan 450001China

A simple and efficient method for the preparation of a novel soluble chitosan derivative, diethoxy phosphoryl chitosan （PH-chitosan）, has been developed. Ph-chitosan was characterized by elemental analysis, FT-IR, NMR, ICP, XRD, TG and SEM, respectively. The chemical identity of PH-chitosan was determined by FT-IR and confirmed by NMR, and those results unequivocally demonstrated that diethoxy phosphoryl groups were grafted onto the amino and hydroxyl groups of chitosan. The results of XRD indicated that the crystalline structure of chitosan was destroyed due to the incorporation of diethoxy phosphoryl group resulting in loss of hydrogen bond. The analysis of TG demonstrated that PH-chitosan was less thermal stable than chitosan. This simple synthetic method provided a new and available approach to prepare a soluble high molecule weight chitosan derivative.

关键词： chitosan diethoxy phosphoryl chitosan synthesis characterization

A review of deep learning methods for pixel-level crack detection

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Journal of Traffic and Transportation Engineering(English Edition) 2022年第6期9卷 945-968页

作者： Hongxia li Weixing Wang Mengfei Wang limin li Vivian Vimlund School of Information Engineering Chang'an UniversityXi'an 710064China School of Computer Baoji University of Arts and SciencesBaoji 721013China School of Electrical and Electronic Engineering Wenzhou UniversityWenzhou 325035China Department of Computer Science and Technology Linkoping UniversityLinköpingSweden

Cracks are a major sign of aging transportation *** detection and repair of cracks is the key to ensuring the overall safety of the transportation *** recent years,due to the remarkable success of deep learning(DL)in the field of crack detection,many researches have been devoted to developing pixel-level crack image segmentation(CIS)models based on DL to improve crack detection accuracy,but as far as we know there is no review of DL-based CIS methods *** address this gap,we present a comprehensive thematic survey of DL-based CIS *** review offers several contributions to the CIS ***,more than 40 papers of journal or top conference most published in the last three years are identified and collected based on the systematic literature review ***,according to the backbone network architecture of the models proposed in them,they are grouped into 10 topics:FCN,U-Net,encoder-decoder model,multi-scale,attention mechanism,transformer,two-stage detection,multi-modal fusion,unsupervised learning and weakly supervised learning,to be ***,our survey focuses on discussing strengths and limitations of the models in each topic so as to reveal the latest research progress in the CIS ***,publicly accessible data sets,evaluation metrics,and loss functions that can be used for pixel-level crack detection are systematically introduced and summarized to facilitate researchers to select suitable components according to their own research ***,we discuss six common problems and existing solutions to them in the field of DL-based CIS,and then suggest eight possible future research directions in this field.

关键词： Crack image segmentation Crack detection Convolutional neural networks Deep learning Systematic literature review

On Using Physico-Chemical Properties of Amino Acids in String Kernels for Protein Classification via Support Vector Machines

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Journal of Systems Science & Complexity 2015年第2期28卷 504-516页

作者： li limin AOKI-KINOSHITA Kiyoko F CHING Wai-Ki JIANG Hao Institute of Information and System Science Xi'an Jiaotong University Department of Bioinformatics Faculty of EngineeringSoka University Advanced Modeling and Applied Computing Laboratory Department of MathematicsThe University of Hong Kong Department of Mathematics School of InformationRenmin University of China

String kernels are popular tools for analyzing protein sequence data and they have been successfully applied to many computational biology problems. The traditional string kernels assume that different substrings are independent. However, substrings can be highly correlated due to their substructure relationship or common physico-chemical properties. This paper proposes two kinds of weighted spectrum kernels： The correlation spectrum kernel and the AA spectrum kernel. We evMuate their performances by predicting glycan-binding proteins of 12 glycans. The results show that the correlation spectrum kernel and the AA spectrum kernel perform significantly better than the spectrum kernel for nearly all the 12 glycans. By comparing the predictive power of AA spectrum kernels constructed by different physico-chemical properties, the authors can also identify the physico- chemical properties which contributes the most to the glycan-protein binding. The results indicate that physico-chemical properties of amino acids in proteins play an important role in the mechanism of glycamprotein binding.

关键词： AAindex AA spectrum kernel correlation spectrum kernel physico-chemical properties string kernel weighted spectrum kernel.

Optimized Binary Neural Networks for Road Anomaly Detection:A TinyML Approach on Edge Devices

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Computers, Materials & Continua 2024年第7期80卷 527-546页

作者： Amna Khatoon Weixing Wang Asad Ullah limin li Mengfei Wang School of Information Engineering Chang’an UniversityXi’an710064China School of Information Engineering Xi’an Eurasia UniversityXi’an710065China School of Electrical and Electronic Engineering Wenzhou UniversityWenzhou325035China

Integrating Tiny Machine Learning(TinyML)with edge computing in remotely sensed images enhances the capabilities of road anomaly detection on a broader *** devices efficiently implement a Binary Neural Network(BNN)for road feature extraction,utilizing quantization and compression through a pruning *** modifications resulted in a 28-fold decrease in memory usage and a 25%enhancement in inference speed while only experiencing a 2.5%decrease in *** showcases its superiority over conventional detection algorithms in different road image *** constrained by computer resources and training datasets,our results indicate opportunities for future research,demonstrating that quantization and focused optimization can significantly improve machine learning models’accuracy and operational *** Cortex-M0 gives practical feasibility and substantial benefits while deploying our optimized BNN model on this low-power device:Advanced machine learning in edge *** analysis work delves into the educational significance of TinyML and its essential function in analyzing road networks using remote sensing,suggesting ways to improve smart city frameworks in road network assessment,traffic management,and autonomous vehicle navigation systems by emphasizing the importance of new technologies for maintaining and safeguarding road networks.

关键词： Edge computing remote sensing TinyML optimization BNNs road anomaly detection quantization model compression

Efficacy of combined inhibition of mTOR and ERK/MAPK pathways in treating a tuberous sclerosis complex cell model

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Journal of Genetics and Genomics 2009年第6期36卷 355-361页

作者： Ruifang Mi Jianhui Ma Dechang Zhang limin li Hongbing Zhang Department of Physiology Institute of Basic Medical Sciences and School of Basic Medicine Chinese Academy of Medical Sciences and Peking Union Medical College Beijing 100005 China Department of Pathology Institute of Basic Medical Sciences and School of Basic Medicine Chinese Academy of Medical Sciences and Peking Union Medical College Beijing 100005 China Department of Pharmacology Institute of Basic Medical Sciences and School of Basic Medicine Chinese Academy of Medical Sciences and Peking Union Medical College Beijing 100005 China

Tuberous sclerosis complex （TSC） is an autosomal dominant tumor syndrome which afflicts multiple organs and for which there is no cure, such that TSC patients may develop severe mental retardation and succumb to renal or respiratory failure. TSC derives from inacti- vating mutations of either the TSC1 or TSC2 tumor suppressor gene, and the resulting inactivation of the TSC1/TSC2 protein complex causes hyperactivation of the mammalian target of rapamyein （mTOR）, leading to uncontrolled cell growth and proliferation. Recent clinical trials of targeted suppression of mTOR have yielded only modest success in TSC patients. It was proposed that abrogation of a newly identified mTOR-mediated negative feedback regulation on extracellular signal-regulated kinase/mitogen-activated protein kinase （ERK/MAPK） signaling pathway and on the well-documented RTK-PI3K-AKT signaling cascade could limit the efficacy of mTOR inhibitors in the treatment of TSC patients. Therefore, we speculate that dual inhibition of mTOR and ERK/MAPK pathways may overcome the disadvantage of single agent therapies and boost the efficacy of mTOR targeted therapies for TSC patients. Investigation of this hypothesis in a TSC cell model revealed that mTOR suppression with an mTOR inhibitor, rapamycin （sirolimus）, led to up-regulation of ERK/MAPK signaling in mouse Tsc2 knockout cells and that this augmented signaling was attenuated by concurrent administration of a MEK1/2 inhibitor, PD98059. When compared with monotherapy, combinatorial application of rapamycin and PD98059 had greater inhibitory effects on Tsc2 deficient cell proliferation, suggesting that combined suppression of mTOR and ERK/MAPK signaling pathways may have advantages over single mTOR inhibition in the treatment of TSC patients.

关键词： TSC mTOR ERK/MAPK rapamycin PD98059

Corrosion Behavior of Graphene Nanosheets Reinforced Magnesium Matrix Composites in Simulated Body Fluids

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Acta Metallurgica Sinica(English Letters) 2024年第3期37卷 525-536页

作者： liwen Chen Jianhui Jing Lulu Zhang Jing li Weipeng Chen limin li Yuan Zhao Hua Hou Yuhong Zhao School of Materials Science and Engineering Collaborative Innovation Center of Ministry of Education and Shanxi Province for High-Performance Al/Mg Alloy MaterialsNorth University of ChinaTaiyuan 030051China Shanxi Key Laboratory of Advanced Manufacturing Technology School of Mechanical EngineeringNorth University of ChinaTaiyuan 030051China School of Materials Science and Engineering Taiyuan University of Science and TechnologyTaiyuan 030024China Beijing Advanced Innovation Center for Materials Genome Engineering University of Science and Technology BeijingBeijing 100083China Institute of Materials Intelligent Technology Liaoning Academy of MaterialsShenyang 110004China

Magnesium(Mg)alloy is considered as a promising biodegradable implant material but restricted to rapid ***,the new strategies based on thixomolding process had been explored to utilize the outstanding anti-permeability of graphene nanosheets(GNPs)while inhibit its galvanic corrosion with the matrix,so as to improve the corrosion resistance of *** agglomerate of GNPs with 0.9 wt%content is the main reason for the deterioration of corrosion performance due to the formation of micro-galvanic *** grain refinement of composites with 0.6 wt%content had positive effects on the better corrosion *** process adjusting,the unique distributions of GNPs along grain boundaries play a vital role in improving the corrosion *** can be ascribed to the following mechanisms:(I)The barriers can be established between the Mg matrix and corrosive medium,hence blocking the charge transfer at the interface;(II)The GNPs can effectively promote apatite deposition on the Mg matrix,leading to form dense apatite layers and prevent the further invasion of SBF;(III)The GNPs acting as reinforcements exists in the corrosion layer and apatite layer,impede the apatite layer falling off from the Mg *** findings broaden the horizon for biomedical applications in Mg matrix composites to realize desired performances.

关键词： Magnesium matrix composite Graphene nanosheets Corrosion resistance

A rate-dependent Prandtl-lshlinskii model for piezoelectric actuators using the dynamic envelope function based play operator

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Frontiers of Mechanical Engineering 2015年第1期10卷 37-42页

作者： Meiju YANG Chunxia li Guoying GU limin ZHU State Key Laboratory of Mechanical System and Vibration School ofMechanical Engineering Shanghai Jiao Tong University Shanghai200240 China

In this paper, a novel rate-dependent Prandtl- Ishlinskii （P-I） model is proposed to characterize the rate- dependent hysteresis nonlinearity of piezoelectric actua- tors. The new model is based on a modified rate-dependent play operator, in which a dynamic envelope function is introduced to replace the input function of the classical play operator. Moreover, a dynamic density function is utilized in the proposed P-I model. The parameters of the proposed model are identified by a modified particle swarm optimization algorithm. Finally, experiments are conducted on a piezo-actuated nanopositioning stage to validate the proposed P-I model under the sinusoidal inputs. The experimental results show that the developed rate-dependent P-I model precisely characterize the rate- dependent hysteresis loops up to 1000 Hz.

关键词： piezoelectric actuators hysteresis Prandtl-Ishlinskii rate-dependent