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Effect of Dy substitution on the microstructure and magnetic properties of nanograin Nd-Fe-B single-phase alloys

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International Journal of Minerals,Metallurgy and Materials 2010年第3期17卷 335-339页

作者： zhi-an Chen Ji Luo zhi-meng Guo School of Materials Science and Engineering University of Science and Technology Beijing Beijing 100083 China

Nanocrystalline single-phase alloys with the nominal compositions （at%） of Nd12.3-xDyxFe79.7Zr0.8Nb0.8Cu0.4B6.0 （x=0, 0.5, 1.5, and 2.5） were prepared by melt-spinning and subsequent annealing. X-ray diffraction analysis shows that the as-spun ribbons were mainly com- posed of the amorphous phase. A slight content of Dy stabilizes the amorphous phase during annealing treatment. The grain size becomes smaller and the coercivity of the annealed ribbon is gradually improved with the increase of Dy content. Excessive Dy is harmful to the remanence. It is found that no intergramtlar phase exists between the grains by high-resolution transmission electron microscopy, and the grain boundaries are crystallographically coherent in the optimally annealed sample. The optimum magnetic properties of remanence （Jr=1.09 T）, coercivity （Hei=1048 kA/m）, and maximum magnetic energy product （（BH）m=169.5 kJ/m3） are obtained from the x=0.5 ribbon in a post heat-treated state （700℃, 10 min）.

关键词： NdFeB magnets dysprosium nanocrystalline amorphous grain size magnetic properties

Why over-parameterization of deep neural networks does not overfit?

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Science China(Information Sciences) 2021年第1期64卷 242-244页

作者： zhi-Hua ZHOU National Key Laboratory for Novel Software Technology Nanjing University

Deep neural networks often come with a huge number of parameters,even larger than the number of training examples,but it seems that these over-parameterized models have not suffered from *** is quite strange and why over-parameterization does not overfit?poses a fundamental question concerning the mysteries behind the success of deep neural networks.

关键词： Deep Neural Networks perspective AI Over-parameterization machine learning

First-Principles Study of the Local Magnetic Moment on a N-Doped Cu_(2)O(111)Surface

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Chinese Physics Letters 2011年第12期28卷 223-226页

作者： WANG zhi State Key Laboratory for Superlattices and Microstructures Institute of SemiconductorsChinese Academy of SciencesP.O.Box 912Beijing 100083

First-principles calculations based on density functional theory within the generalized gradient approximation are used to study on magnetism in N-doped Cu_(2)*** is interesting that nitrogen does not induce magnetism in bulk Cu_(2)O,while shows a total magnetism moment of 1.0µB at the Cu_(2)O(111)surface,which is mainly localized on the doped N *** local magnetic moment at the N−doped Cu_(2)O(111)surface can be explained in terms of the surface state.

关键词： surface Surface

Multiparameter magnetic resonance imaging-based radiomics model for the prediction of rectal cancer metachronous liver metastasis

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World Journal of Gastrointestinal Oncology 2025年第1期17卷 62-72页

作者： zhi-Da Long Xiao Yu zhi-Xiang Xing Rui Wang Department of Hepatobiliary and Pancreaticosplenic Surgery Jingzhou Hospital Affiliated to Yangtze UniversityJingzhou 434100Hubei ProvinceChina

BACKGROUND The liver,as the main target organ for hematogenous metastasis of colorectal cancer,early and accurate prediction of liver metastasis is crucial for the diagnosis and treatment of ***,this study aims to investigate the application value of a combined machine learning(ML)based model based on the multiparameter magnetic resonance imaging for prediction of rectal metachronous liver metastasis(MLM).AIM To investigate the efficacy of radiomics based on multiparametric magnetic resonance imaging images of preoperative first diagnosed rectal cancer in predicting MLM from rectal *** We retrospectively analyzed 301 patients with rectal cancer confirmed by surgical pathology at Jingzhou Central Hospital from January 2017 to December *** participants were randomly assigned to the training or validation queue in a 7:3 *** first apply generalized linear regression model(GLRM)and random forest model(RFM)algorithm to construct an MLM prediction model in the training queue,and evaluate the discriminative power of the MLM prediction model using area under curve(AUC)and decision curve analysis(DCA).Then,the robustness and generalizability of the MLM prediction model were evaluated based on the internal validation set between the validation queue *** Among the 301 patients included in the study,16.28%were ultimately diagnosed with MLM through pathological *** analysis showed that carcinoembryonic antigen,and magnetic resonance imaging radiomics were independent predictors of ***,the GLRM prediction model was developed with a comprehensive nomogram to achieve satisfactory *** prediction performance of GLRM in the training and validation queue was 0.765[95%confidence interval(CI):0.710-0.820]and 0.767(95%CI:0.712-0.822),*** with GLRM,RFM achieved superior performance with AUC of 0.919(95%CI:0.868-0.970)and 0.901(95%CI:0.850-0.952)in the training and validation queue,respect

关键词： Rectal cancer Metachronous liver metastases Magnetic resonance imaging Radiomics Machine learning

Modified constructions of binary sequences using multiplicative inverse

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Applied Mathematics(A Journal of Chinese Universities) 2008年第4期23卷 490-500页

作者： CHEN zhi-xiong LIN zhi-xing Key Laboratory of Applied Mathematics Putian University Putian 351100 China Key Laboratory of Network Security and Cryptology Fujian Normal University Fuzhou 350007China

Two new families of finite binary sequences are constructed using multiplicative inverse. The sequences are shown to have strong pseudorandom properties by using some estimates of certain exponential sums over finite fields. The constructions can be implemented fast since multiplicative inverse over finite fields can be computed in polynomial time.

关键词： stream cipher binary sequence multiplicative inverse pseudorandomness exponential sum

A GAN-based temporally stable shading model for fast animation of photorealistic hair

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Computational Visual Media 2021年第1期7卷 127-138页

作者： zhi Qiao Takashi Kanai Department of General Systems Studies Graduate School of Arts and SciencesThe University of TokyoTokyoJapan

We introduce an unsupervised GANbased model for shading photorealistic hair *** model is much faster than previous rendering algorithms and produces fewer artifacts than other neural image translation *** main idea is to extend the Cycle-GAN structure to avoid semitransparent hair appearance and to exactly reproduce the interaction of the lights with the *** use two constraints to ensure temporal coherence and highlight *** approach outperforms and is computationally more efficient than previous methods.

关键词： hair animation fast shading neural networks

Hierarchical Management Scheme by Local Fields

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Acta Mathematica Sinica,English Series 2011年第1期27卷 155-168页

作者： zhi Hong YUE Mao zhi XU School of Mathematical Sciences Peking University Beijing 100871 P. R. China Key Laboratory of Network and Software Security Assurance School of Mathematical Sciences Peking University Beijing 100871 P. R. China

In the present paper we propose a new hierarchical management scheme within suitable extensions of 2-adic numbers, in which the subfields are treated as classes, and the communications are realized by computation on elliptic curves. The security of our system is much stronger than that of the traditional public key cryptographic systems.

关键词： Hierarchical management local fields elliptic curves

Digital microstructure insights to phase evolution and thermal flow properties of hydrates by X-ray computed tomography

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Science China(Technological Sciences) 2021年第1期64卷 187-202页

作者： ZHAO zhi ZHOU XiaoPing School of Civil Engineering Chongqing UniversityChongqing 400045China

Natural gas-hydrates are valuable energy resource with rich deposits,and their thermal transport and thermal dynamic mechanical behaviors significantly affect the long-term production process and phase change-based thermal energy storage characteristics of these energy *** paper aims to propose novel relations to predict the thermophysical properties,to investigate the hydrate phase evolution in microstructures,and to study the thermal transport and thermal dynamic mechanical *** formation experiments in sandpack samples and ultrasonic wave tests are conducted with the aid of X-ray CT *** microstructures models and variables are defined to describe the hydrate phase evolution,and novel relations are proposed to accurately predict the thermophysical properties based on the microporosity and ultrasonic wave *** thermal transport and thermal dynamic mechanical properties in microstructures with hydrate,water,residuary pore and grain phases are *** show that the average errors of porosity,P-wave and S-wave velocities between the experimental data and computed results by the proposed relations are less than 5%,indicating the accuracy and reliability of the proposed *** temperature fraction decreases with increasing underground temperature and decreasing hydrate *** thermal stress and thermal displacement increase as temperature and hydrate saturation *** are strong anisotropy for the temperature fraction,thermal stress and thermal displacement during the thermal transport of hydrates.

关键词： X-ray computed tomography imaging hydrate phase evolution transport properties effective thermal conductivity thermal-mechanical properties

Parameter feature extraction for hyperspectral detection of the shallow underwater target

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Science China(Technological Sciences) 2021年第5期64卷 1092-1100页

作者： XIA zhi GU YanFeng Acoustic Science and Technology Laboratory Harbin Engineering UniversityHarbin 150001China College of Underwater Acoustic Engineering Harbin Engineering UniversityHarbin 150001China School of Electronics and Information Engineering Harbin Institute of TechnologyHarbin 150001China

For the detection of shallow underwater targets by the hyperspectrum, the information of the target is carried in the water-leaving radiation. However, the differences between the water-leaving radiation of the underwater target and the ocean background radiation are not significant, and the spectrum of the water-leaving radiation is sensitive to the changes of the marine environment. Therefore, taking the spectrum as the feature is not stable for hyperspectral detection of the underwater target. In this paper, we propose a parameter feature extraction method for hyperspectral detection of the shallow underwater target. The presence of an underwater target would change the optical properties of seawater in a local place. Based on that, a quasianalytical model of the water-leaving radiation is adopted to inverse the properties of the marine environment from the radiated spectrum. Then the inversed water depth and bottom reference reflectance are taken as the features. Simulation results show that the samples which belong to the water-leaving radiation of underwater target have higher inversed depth and reference reflectance than that belong to the ocean background radiation. Furthermore, these two kinds of samples can be separated significantly and stably in a 2-dimension feature space.

关键词： hyperspectral imaging underwater technology feature extraction