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A retrospective study on professor Gui-qi xuan’s experience in traditional Chinese medicine treatment on attention-deficit hyperactivity disorder: based on data mining and network pharmacology

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Life Research 2023年第3期6卷 10-24页

作者： Jue Hu Dan-Fei Chen Fang-Fang Li Nuo Chen Chun-Lu Ye Ke-Pin Yu Xiao-Bo xuan Gui-qi xuan Jian Chen First Clinical School Zhejiang Chinese Medical UniversityHangzhou 310053China Pediatrics Department of Traditional Chinese Medicine Zhejiang Provincial Hospital of Traditional Chinese MedicineHangzhou 310006China

Background:To investigate the clinical medication approach of Professor Guiqi xuan(***)in treating pediatric patients with attention-deficit hyperactivity disorder(ADHD)and the potential mechanism of the core herbal ***:Following medical record information pretreatment,the Traditional Chinese Medicine(TCM)inheritance computing platform system V3.0 was utilized to analyze the standardized *** associate rules were summarized to identify the core prescription for treating *** extracted core herbal prescription’s active compounds and potential targets were used to establish a protein-protein interaction network of active ingredient-disease *** 3.9.1 software was used to analyze the network’s topological parameters to obtain the key active ingredients and their *** Bioconductor data package of R4.0.2 was used to analyze the gene ontology biological functions and Kyoto Encyclopedia of Genes and Genomes pathways of key ***:Two hundred and twenty-seven entries derived from TCM record information were *** data mining,it was found that 62.5%of pediatric patients had short-tempered behavior,nearly half had sleep problems,and 30%-40%had picky eating and polyphagia *** highest-frequency syndrome type was kidney deficiency and liver ***,fire,phlegm,and dyspeptic food were the main pathological factors for ***’s treatment of ADHD mainly focused on replenishing kidney essence and subduing Yang(active,external,ascending,warm,bright,functional and excited pertain to Yang).The core herbal prescription for ADHD included Yuan-zhi,Yi-zhi,Gui-jia,Bai-shao,Long-chi,Ci-shi,Shi-chang-pu,Yu-jin,Fu-shen,and *** protein-protein interaction network showed that MAOA,ADRB2,FOS,MAOB,and SLC6A3 were the five key targets essential in treating ADHD with core herbal *** gene ontology biological function of crucial targets mainly involved G protein-coupled amine

关键词： Chinese traditional medicine Data mining Retrospective clinical studies Network pharmacology Attention-deficit hyperactivity disorder Mechanism of action

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Generalized Wronskian Solutions to Modified Korteweg-de Vries Equation via Its Bcklund Transformation

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Communications in Theoretical Physics 2008年第7期50卷 13-16页

作者： xuan qi-Fei ZHANG Da-Jun Department of Mathematics Shanghai University Shanghai 200444 China

In the paper we discuss the Wronskian solutions of modified Korteweg-de Vries equation （mKdV） via the Backlund transformation （BT） and a generalized Wronskian condition is given, which allows us to substitute an a... 详细信息

关键词： the modified Korteweg-de Vries equation (mKdV) generalized Wronskian solutions bilinear form Backlund transformation (BT)

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SFNet:Stellar Feature Network with CWT for Stellar Spectra Recognition

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Research in Astronomy and Astrophysics 2024年第9期24卷 260-270页

作者： Hao Fu Peng Liu xuan qi Xue Mei College of Electrical Engineering and Control Science Nanjing Tech UniversityNanjing 211816China

Stellar spectral classification is crucial in astronomical data ***,existing studies are often limited by the uneven distribution of stellar samples,posing challenges in practical *** when balancing stellar categories and their numbers,there is room for improvement in classification *** study introduces a Continuous Wavelet Transform using the Super Morlet wavelet to convert stellar spectra into wavelet images.A novel neural network,the Stellar Feature Network,is proposed for classifying these *** spectra from Large Sky Area Multi-Object Fiber Spectroscopic Telescope DR9,encompassing five equal categories(B,A,F,G,K),were *** experiments validate the effectiveness of the proposed methods and network,achieving significant improvements in classification accuracy.

关键词： methods data analysis-techniques image processing-stars imaging-galaxies stellar content

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Wider frequency domain for negative refraction index in a quantized composite right–left handed transmission line

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Chinese Physics B 2018年第6期27卷 468-472页

作者： qi-xuan Wu Shun-Cai Zhao Faculty of Foreign Languages and Culture Kunming University of Science and Technology Kunming 650500 China Department of Physics Faculty of Science Kunming University of Science and Technology Kunming 650500 China

The refraction index of the quantized lossy composite right-left handed transmission line（CRLH-TL） is deduced in the thermal coherence state. The results show that the negative refraction index（herein the left-handedness） can be implemented by the electric circuit dissipative factors（i.e., the resistances R and conductances G） in a higher frequency band（1.446 GHz≤ ω ≤ 15 GHz）, and flexibly adjusted by the left-handed circuit components（Cl, Ll） and the right-handed circuit components（Cr, Lr） at a lower frequency（ω = 0.995 GHz）. The flexible adjustment for left-handedness in a wider bandwidth will be significant for the microscale circuit design of the CRLH-TL and may make the theoretical preparation for its compact applications.

关键词： quantized composite right-left handed transmission line negative refraction index frequency do- main

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Effect of Spontaneously Generated Coherence and Detuning on 2D Atom Localization in Two Orthogonal Standing-Wave Fields

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Chinese Physics Letters 2014年第3期31卷 77-81页

作者： ZHAO Shun-Cai WU qi-xuan GONG Ai-Ling Department of Physics Kunming University of Science and Technology Kunming 650500 College English Department Kunming University of Science and Technology Kunming 650500

Two-dimensional （2D） atom localization via the spontaneously generated coherence （SGC） and detunings associated with the probe and standing-wave driving fields in a three-level V-type atomic system are investigated. In the gain process, two equal and tunable peak maxima of position distribution in the – plane via the detunings are observed. However, one decreasing and the other increasing peak maxima in the absorption process via the SGC are achieved in the quadrants I and III of the x–y plane. A better resolution and more novelty for the 2D atom localization in our scheme are obtained.

关键词： Atoms

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A multi-class large margin classifier

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Journal of Zhejiang University-Science A(Applied Physics & Engineering) 2009年第2期10卷 253-262页

作者： Liang TANG qi xuan Rong XIONG Tie-jun WU Jian CHU Institute of Cyber-Systems and Control Zhejiang University Hangzhou 310027 China

Currently there are two approaches for a multi-class support vector classifier(SVC). One is to construct and combine several binary classifiers while the other is to directly consider all classes of data in one optimization formulation. For a K-class problem(K>2),the first approach has to construct at least K classifiers,and the second approach has to solve a much larger op-timization problem proportional to K by the algorithms developed so far. In this paper,following the second approach,we present a novel multi-class large margin classifier(MLMC). This new machine can solve K-class problems in one optimization formula-tion without increasing the size of the quadratic programming(QP) problem proportional to K. This property allows us to construct just one classifier with as few variables in the QP problem as possible to classify multi-class data,and we can gain the advantage of speed from it especially when K is large. Our experiments indicate that MLMC almost works as well as(sometimes better than) many other multi-class SVCs for some benchmark data classification problems,and obtains a reasonable performance in face recognition application on the AR face database.

关键词： Multi-classification Support vector machine (SVM) Quadratic programming (QP) problem Large margin

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Intelligent Reflecting Surface Assisted Transmission Optimization Strategies in Wireless Networks

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China Communications 2024年第4期21卷 120-135页

作者： He Xinxin qi xuan Meng Wei Liu Wei Yin Changchuan School of Electronic Engineering Beijing University of Posts and TelecommunicationsBeijing 100876China

Wireless Power Transfer(WPT)technology can provide real-time power for many terminal devices in Internet of Things(IoT)through millimeterWave(mmWave)to support applications with large capacity and low *** the intelligent reflecting surface(IRS)can be adopted to create effective virtual links to address the mmWave blockage problem,the conventional solutions only adopt IRS in the downlink from the Base Station(BS)to the users to enhance the received signal *** practice,the reflection of IRS is also applicable to the uplink to improve the spectral *** is a challenging to jointly optimize IRS beamforming and system resource allocation for wireless energy acquisition and information *** this paper,we first design a Low-Energy Adaptive Clustering Hierarchy(LEACH)clustering protocol for clustering and data ***,the problem of maximizing the minimum system spectral efficiency is constructed by jointly optimizing the transmit power of sensor devices,the uplink and downlink transmission times,the active beamforming at the BS,and the IRS dynamic *** solve this non-convex optimization problem,we propose an alternating optimization(AO)-based joint solution *** results show that the use of IRS dynamic beamforming can significantly improve the spectral efficiency of the system,and ensure the reliability of equipment communication and the sustainability of energy supply under NLOS link.

关键词： intelligent reflecting surface(IRS) joint optimization millimeter wave wireless information transmission(WIT) wireless power transfer(WPT)

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A Fast Evolutionary Learning to Optimize CNN

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Chinese Journal of Electronics 2020年第6期29卷 1061-1073页

作者： CHEN Jinyin LIN Xiang GAO Shangtengda XIONG Hui ZHANG Longyuan LIU Yi xuan qi College of Information Engineering Zhejiang University of Technology NESA Lab Zhejiang University

Deep neural networks(DNNs) show great performance in lots of *** neural network(CNN) is one of the classic DNNs,and various modified CNNs have been brought up,such as DenseNet,GoogleNet,ResNet,*** diverse tasks,a unique structure of CNN may show its ***,how to design an effective CNN model for a practical task is a *** this paper,we model the architecture optimization of CNN as an optimization problem and design a Genetic network programming based Fast evolutionary learning(GNP-FEL) to optimize ***-FEL contains three main ideas:First GNP is adopted to optimize CNN architecture and hyperparameters,which can build diverse network structures and make network parameters selfevolve;Second multi-objective optimization is designed by balancing both CNN model efficiency and structure compactness;Last a novel incremental training method is proposed to train offspring CNN models in GNP,which is capable of reducing time complexity *** have validated that GNP-FEL can quickly evolve a CNN classifier with a sufficiently compact *** the classifier has a comparable classification effect to state-ofthe-art CNN model.

关键词： Optimisation techniques CNN classifier Other topics in statistics multiobjective optimization architecture optimization optimize CNN Combinatorial mathematics DNN GNP-FEL genetic network programming diverse network structures structure compactness network parameters state-ofthe-art CNN model deep neural networks optimization problem CNN model genetic algorithms diverse tasks convolutional neural nets offspring CNN models neural net architecture practical task convolutional neural network Neural computing techniques learning (artificial intelligence) Knowledge engineering techniques fast evolutionary learning

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DGEPN-GCEN2V: a new framework for mining GGI and its application in biomarker detection

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Science China(Information Sciences) 2019年第9期62卷 199-201页

作者： Jinyin CHEN Haibin ZHENG Hui XIONG Yangyang WU Xiang LIN Shiyan YING qi xuan College of Information Engineering Zhejiang University of Technology

Dear editor,Deep learning is widely applied in various fields [1,2] recently. In the field of bioinformatics, deep learning also attracts many attentions of researchers. Danaee et al.[3] extracted depth functional features from high-dimensional gene expression profile by stacked denoising automatic encoder and identified a set of highly interacting genes for cancer biomarkers detection. Chen et al.[4] proposed a novel spectral clustering with automatic cluster number determination, which

关键词： BCS DGEPN-GCEN2V a new framework for mining GGI and its application in biomarker detection

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Classifying multiclass relationships between ASes using graph convolutional network

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Frontiers of Engineering Management 2022年第4期9卷 653-667页

作者： Songtao PENG Xincheng SHU Zhongyuan RUAN Zegang HUANG qi xuan Institute of Cyberspace Security College of Information EngineeringZhejiang University of TechnologyHangzhou 310023China Department of Electrical Engineering City University of Hong KongHong KongChina

Precisely understanding the business relationships between autonomous systems(ASes)is essential for studying the Internet *** date,many inference algorithms,which mainly focus on peer-to-peer(P2P)and provider-to-customer(P2C)binary classification,have been proposed to classify the AS relationships and have achieved excellent ***,business-based sibling relationships and structure-based exchange relationships have become an increasingly nonnegligible part of the Internet market in recent *** algorithms are often difficult to infer due to the high similarity of these relationships to P2P or P2C *** this study,we focus on multiclassification of AS relationship for the first *** first summarize the differences between AS relationships under the structural and attribute features,and the reasons why multiclass relationships are difficult to be *** then introduce new features and propose a graph convolutional network(GCN)framework,AS-GCN,to solve this multiclassification problem under complex *** proposed framework considers the global network structure and local link features *** on real Internet topological data validate the effectiveness of our method,that is,*** proposed method achieves comparable results on the binary classification task and outperforms a series of baselines on the more difficult multiclassification task,with an overall metrics above 95%.

关键词： autonomous system multiclass relationship graph convolutional network classification algorithm Internet topology

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