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Laser capture microdissection enables cellular and molecular studies of tooth root development

International Journal of Oral Science 2012年第1期4卷 7-13页

作者： jian-xun sun Orapin V Horst Roger Bumgarner Bryce Lakely Martha J Somerman Hai Zhang State Key Laboratory of Oral Diseases Sichuan University Chengdu China Department of Periodontics University of Washington Seattle WA USA Division of Endodontics Department of Preventive and Restorative Dental SciencesUniversity of California at San FranciscoSan FranciscoCAUSA Department of Microbiology University of WashingtonSeattleWAUSA Department of Urology University of WashingtonSeattleWAUSA National Institute of Arthritis and Musculoskeletal and Skin Diseases National Institutes of HealthBethesdaMDUSA Department of Restorative Dentistry UniversitY of Washington Seattle WA USA

Epithelial-mesenchymal interactions（EMIs） are critical for tooth *** mechanisms mediating these interactions in root formation is not well *** capture microdissection（LCM） and subsequent microarray analyses enable large scale in situ molecular and cellular studies of root formation but to date have been hindered by technical challenges of gaining intact histological sections of non-decalcified mineralized teeth or jaws with well-preserved ***,we describe a new method to overcome this obstacle that permits LCM of dental epithelia,adjacent mesenchyme,odontoblasts and cementoblasts from mouse incisors and molars during root *** this method,we obtained RNA samples of high quality and successfully performed microarray *** differences in gene expression,as well as genes not previously associated with root formation,were *** of gene expression data from microarray with real-time reverse transcriptase polymerase chain reaction（RT-PCR） supported our *** genes include known markers of dental epithelia,mesenchyme,cementoblasts and odontoblasts,as well as novel genes such as those in the fibulin *** conclusion,our new approach in tissue preparation enables LCM collection of intact cells with well-preserved RNA allowing subsequent gene expression analyses using microarray and RT-PCR to define key regulators of tooth root development.

关键词： gene laser capture microdissection microarray PCR root

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ANALYTICAL MODELS OF FLOATING BRIDGES SUBJECTED BY MOVING LOADS FOR DIFFERENT WATER DEPTHS

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Journal of Hydrodynamics 2008年第5期20卷 537-546页

作者： ZHANG Jun MIAO Guo-ping LIU jian-xun sun Wen-jun The First Engineers Scientific Research Institute of the General Armaments Department Wuxi 214035 China School of Naval Architecture Ocean and Civil Engineering Shanghai Jiao Tong University Shanghai 200030China The First Engineers Scientific Research Institute of the General Armaments Department Wuxi 214035 China

There are two types of floating bridge such as discrete-pontoon floating bridges and continuous-pontoon floating bridges. Analytical models of both floating bridges subjected by raoving loads are presented to study the dynamic responses with hydrodynamic influence coefficients for different water depths. The beam theory and potential theory are introduced to produce the models. The hydrodynamic coefficients and dynamic responses of bridges are evaluated by the boundary element method and by the Galerkin method of weighted residuals, respectively. Considering causal relationship between the frequencies of the oscillation of floating bridges and the added mass coefficients, an iteration method is introduced to compute hydrodynamic frequencies. The results indicate that water depth has little influence upon the dynamic responses of both types of floating bridges, so that the effect of water depth can be neglected during the course of designing floating bridges.

关键词： floating bridge analytical model moving load water depth

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Reaction mechanism between Al_(2)O_(3)–MgO refractory materials and rare earth high-carbon heavy rail steel

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Journal of Iron and Steel Research International 2024年第5期31卷 1153-1163页

作者： Yi Wang Guang-jie Song Ping Shen jian-zhong He Da-xian Zhang jian-xun Fu Center for Advanced Solidification Technology(CAST) School of Materials Science and EngineeringState Key Laboratory of Advanced Special SteelShanghai UniversityShanghai200444China State Key Laboratory of Baiyunebo Rare Earth Resources Research and Comprehensive Utilization Baotou014030Inner MongoliaChina Inner Mongolia Baotou Steel Union Co. Ltd.Baotou014030Inner MongoliaChina

Submerged entry nozzle(SEN)clogging is a major problem affecting the production quality of rare earth steel,and finding a suitable refractory outlet can significantly reduce production *** explore the relationship between refractory composition and interface interaction,unprotected coated Al_(2)O_(3)–MgO refractories and SiO2-coated Al_(2)O_(3)–MgO refractories were added to rare earth high-carbon heavy rail steel under laboratory conditions,and the Al_(2)O_(3)–MgO refractory was found to be more *** results show that,from the epoxy resin side to the refractory side,the contour of the refractory interface reaction layer can be divided into two main layers:an iron-rich reaction layer and an iron-poor reaction *** based on the spherical model suggest that the adhesion force is proportional to the size of the refractory particles and inclusions,and the same result applies to the surface *** the inclusions at a smaller size has a specific effect on alleviating the erosion of *** with the erosion mechanism of Al_(2)O_(3)–MgO refractories,the interface reaction mechanism between Al_(2)O_(3)–MgO refractories and molten steel was proposed,which provides ideas for solving SEN clogging.

关键词： Rare earth high-carbon heavy rail steel Al_(2)O_(3)-MgO refractory Adhesion Surface tension Interface interaction

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On the Quantum Cohomology of Blow-ups of Four-dimensional Quadrics

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Acta Mathematica Sinica,English Series 2024年第1期40卷 313-328页

作者： jian xun HU Hua Zhong KE Chang Zheng LI Lei SONG School of Mathematics Sun Yat-sen UniversityGuangzhou 510275P.R.China

We propose a conjecture relevant to Galkin’s lower bound conjecture,and verify it for the blow-ups of a four-dimensional quadric at a point or along a projective *** also show that Conjecture O holds in these two cases.

关键词： Quantum cohomology blow-up quadric hypersurface

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Control of GaN inverted pyramids growth on c-plane patterned sapphire substrates

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Journal of Semiconductors 2024年第6期45卷 92-96页

作者： Luming Yu xun Wang Zhibiao Hao Yi Luo Changzheng sun Bing Xiong Yanjun Han jian Wang Hongtao Li Lin Gan Lai Wang Beijing National Research Center for Information Science and Technology Department of Electronic EngineeringTsinghua UniversityBei-jing 100084China Center for Flexible Electronics Technology Tsinghua UniversityBeijing 100084China

Growth of gallium nitride(GaN)inverted pyramids on c-plane sapphire substrates is benefit for fabricating novel devices as it forms the semipolar *** this work,GaN inverted pyramids are directly grown on c-plane patterned sapphire substrates(PSS)by metal organic vapor phase epitaxy(MOVPE).The influences of growth conditions on the surface morphol-ogy are experimentally studied and explained by Wulff *** competition of growth rate among{0001},{1011},and{1122}facets results in the various surface morphologies of GaN.A higher growth temperature of 985 ℃ and a lowerⅤ/Ⅲratio of 25 can expand the area of{}facets in GaN inverted *** the other hand,GaN inverted pyramids with almost pure{}facets are obtained by using a lower growth temperature of 930℃,a higherⅤ/Ⅲratio of 100,and PSS with pattern arrangement perpendicular to the substrate primary flat.

关键词： inverted pyramids GaN MOVPE crystal growth competition model

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Substrate screening for superclean graphene growth using firstprinciples calculations

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Nano Research 2024年第4期17卷 2216-2222页

作者： Zhihao Li Xiucai sun Xiaoli sun Wan-jian Yin Zhongfan Liu College of Energy Soochow Institute for Energy and Materials InnovationS(SIEMIS)and Jiangsu Provincial Key Laboratory for Advanced Carbon Materials and Wearable Energy TechnologiesSoochow UniversitySuzhou 215006China Graphene Basic Science Research Center Beijing Graphene Institute(BGI)Beijing 100095China Center for Nanochemistry Beijing Science and Engineering Center for NanocarbonsBeijing National Laboratory for Molecular ScienceCollege of Chemistry and Molecular EngineeringPeking UniversityBeijing 100871China

Suppressing the formation of amorphous surface carbon and contaminants during the preparation of graphene by chemical vapor deposition remains an ongoing ***,we analyzed how substrate characteristics affect graphene quality by simulating margin extension,the nucleation process,and defect pegging configurations on mono-crystalline oriented metal substrates with the aim of enhancing graphene *** formation energy and nucleation potential,which are indirect substrate–graphene interaction features,were found to appropriately evaluate graphene *** crystallographic orientation of the metal substrate was discovered to be critical for producing superclean graphene.A low graphene defect density and high nucleation rate on the Cu(100)facet guarantee growth of high-quality graphene,especially in terms of suppressing the formation of amorphous *** addition,rapid kink growth and self-healing on the Cu(100)facet facilitate rapid graphene synthesis,which is also promoted by rapid kink splicing and margin self-repair on this *** study provides theoretical insight useful for the synthesis of superclean graphene.

关键词： superclean graphene defects nucleation metal substrates density functional theory calculations

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Prediction of lime utilization ratio of dephosphorization in BOF steelmaking based on online sequential extreme learning machine with forgetting mechanism

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International Journal of Minerals,Metallurgy and Materials 2024年第3期31卷 508-517页

作者： Runhao Zhang jian Yang Han sun Wenkui Yang State Key Laboratory of Advanced Special Steel School of Materials Science and EngineeringShanghai UniversityShanghai 200444China

The machine learning models of multiple linear regression(MLR),support vector regression(SVR),and extreme learning ma-chine(ELM)and the proposed ELM models of online sequential ELM(OS-ELM)and OS-ELM with forgetting mechanism(FOS-ELM)are applied in the prediction of the lime utilization ratio of dephosphorization in the basic oxygen furnace steelmaking *** ELM model exhibites the best performance compared with the models of MLR and ***-ELM and FOS-ELM are applied for sequential learning and model *** optimal number of samples in validity term of the FOS-ELM model is determined to be 1500,with the smallest population mean absolute relative error(MARE)value of 0.058226 for the *** variable importance analysis reveals lime weight,initial P content,and hot metal weight as the most important variables for the lime utilization *** lime utilization ratio increases with the decrease in lime weight and the increases in the initial P content and hot metal weight.A prediction system based on FOS-ELM is applied in actual industrial production for one *** hit ratios of the predicted lime utilization ratio in the error ranges of±1%,±3%,and±5%are 61.16%,90.63%,and 94.11%,*** coefficient of determination,MARE,and root mean square error are 0.8670,0.06823,and 1.4265,*** system exhibits desirable performance for applications in actual industrial pro-duction.

关键词： basic oxygen furnace steelmaking machine learning lime utilization ratio dephosphorization online sequential extreme learning machine forgetting mechanism

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A Method for Detecting and Recognizing Yi Character Based on Deep Learning

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Computers, Materials & Continua 2024年第2期78卷 2721-2739页

作者： Haipeng sun Xueyan Ding jian sun HuaYu jianxin Zhang School of Computer Science and Engineering Dalian Minzu UniversityDalian116600China Institute of Machine Intelligence and Bio-Computing Dalian Minzu UniversityDalian116600China 3Yi Language Research RoomChina Ethnic Languages Translation Centre Beijing100080China

Aiming at the challenges associated with the absence of a labeled dataset for Yi characters and the complexity of Yi character detection and recognition,we present a deep learning-based approach for Yi character detection and *** the detection stage,an improved Differentiable Binarization Network(DBNet)framework is introduced to detect Yi characters,in which the Omni-dimensional Dynamic Convolution(ODConv)is combined with the ResNet-18 feature extraction module to obtain multi-dimensional complementary features,thereby improving the accuracy of Yi character ***,the feature pyramid network fusion module is used to further extract Yi character image features,improving target recognition at different ***,the previously generated feature map is passed through a head network to produce two maps:a probability map and an adaptive threshold map of the same size as the original *** maps are then subjected to a differentiable binarization process,resulting in an approximate binarization *** map helps to identify the boundaries of the text ***,the text detection box is generated after the post-processing *** the recognition stage,an improved lightweight MobileNetV3 framework is used to recognize the detect character regions,where the original Squeeze-and-Excitation(SE)block is replaced by the efficient Shuffle Attention(SA)that integrates spatial and channel attention,improving the accuracy of Yi characters ***,the use of depth separable convolution and reversible residual structure can reduce the number of parameters and computation of the model,so that the model can better understand the contextual information and improve the accuracy of text *** experimental results illustrate that the proposed method achieves good results in detecting and recognizing Yi characters,with detection and recognition accuracy rates of 97.5%and 96.8%,*** also,we have compared the detection and re

关键词： Yi characters text detection text recognition attention mechanism deep neural network

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Adversarial data splitting for domain generalization

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Science China(Information Sciences) 2024年第5期67卷 28-42页

作者： Xiang GU jian sun Zongben XU School of Mathematics and Statistics Xi'an Jiaotong University

Domain generalization aims to learn a model that is generalizable to an unseen target domain,which is a fundamental and challenging task in machine learning for out-of-distribution generalization. This paper proposes a novel domain generalization approach that enforces the learned model to be able to generalize well over the train/val subset splitting of the training dataset. This idea is modeled herein as an adversarial data splitting framework, formulated as a min-max optimization problem inspired by the metalearning approach. The min-max optimization problem is solved by iteratively splitting the training dataset into the training and val subsets to maximize the domain shift measured by the objective function and updating the model parameters to enable the model to generalize well from the training subset to the val subset by minimizing the objective function. This adversarial training approach does not assume the known domain labels of the training data; instead, it automatically investigates the “hard” splitting of the train/val subsets to learn the generalizable model. Extensive experimental results using three benchmark datasets demonstrate the superiority of this approach. In addition, we derive a generalization error bound for the theoretical understanding of our proposed approach.

关键词： domain generalization adversarial learning data splitting meta-learning out of distribution

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Co-doped Ni_(3)S_(2) nanosheet array: A high-efficiency electrocatalyst for alkaline seawater oxidation

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Nano Research 2024年第3期17卷 1050-1055页

作者： Meng Yue xun He Shengjun sun Yuntong sun Mohamed S.Hamdy Mhamed Benaissa Alsamani A.M.Salih Jun Liu Xuping sun College of Chemistry Chemical Engineering and Materials ScienceShandong Normal UniversityJinan 250014China Institute of Fundamental and Frontier Sciences University of Electronic Science and Technology of ChinaChengdu 610054China Department of Chemistry College of ScienceKing Khalid UniversityP.O.Box 9004Abha 61413Saudi Arabia Department of Chemical Engineering College of EngineeringUniversity of Ha’ilP.O.Box 2440Ha’il 81441Saudi Arabia Department of Otolaryngology-Head&Neck Surgery West China HospitalSichuan UniversityChengdu 610041China

Developing efficient and durable oxygen evolution reaction(OER)catalysts holds great promise for green hydrogen production via seawater electrolysis,but remains a ***,we report a Co-doped Ni_(3)S_(2) nanosheet array on Ni foam(Co-Ni_(3)S_(2)/NF)as a high-efficiency OER electrocatalyst for *** alkaline conditions,Co-Ni_(3)S_(2)/NF requires an overpotential of only 368 mV to drive 100 mA·cm^(–2),superior to Ni_(3)S_(2)/NF(385 mV).Besides,it exhibits at least 50-h continuous electrolysis.

关键词： Co doping Ni_(3)S_(2)nanosheet array oxygen evolution reaction seawater electrolysis electrocatalyst

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