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Quantitative Green's function estimates for lattice quasi-periodic Schrodinger operators

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Science China Mathematics 2024年第5期67卷 1011-1058页

作者： Hongyi cao Yunfeng Shi Zhifei Zhang School of Mathematical Sciences Peking UniversityBeijing 100871China School of Mathematics Sichuan UniversityChengdu 610064China

In this paper,we establish quantitative Green’s function estimates for some higher-dimensional lattice quasi-periodic(QP)Schrodinger *** resonances in the estimates can be described via a pair of symmetric zeros of certain functions,and the estimates apply to the sub-exponential-type non-resonance *** the application of quantitative Green’s function estimates,we prove both the arithmetic version of Anderson localization and the finite volume version of(1/2-)-Holder continuity of the integrated density of states(IDS)for such QP Schrodinger *** gives an affirmative answer to Bourgain’s problem in Bourgain(2000).

关键词： Holder continuity of the IDS quantitative Green's function estimates quasi-periodic Schrodinger operators arithmetic Anderson localization multi-scale analysis

A Robust Framework for Multimodal Sentiment Analysis with Noisy Labels Generated from Distributed Data Annotation

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Computer Modeling in Engineering & Sciences 2024年第6期139卷 2965-2984页

作者： Kai Jiang Bin cao Jing Fan School of Computer Science and Technology Zhejiang University of TechnologyHangzhou310023China

Multimodal sentiment analysis utilizes multimodal data such as text,facial expressions and voice to detect people’s *** the advent of distributed data collection and annotation,we can easily obtain and share such multimodal ***,due to professional discrepancies among annotators and lax quality control,noisy labels might be *** research suggests that deep neural networks(DNNs)will overfit noisy labels,leading to the poor performance of the *** address this challenging problem,we present a Multimodal Robust Meta Learning framework(MRML)for multimodal sentiment analysis to resist noisy labels and correlate distinct modalities ***,we propose a two-layer fusion net to deeply fuse different modalities and improve the quality of the multimodal data features for label correction and network ***,a multiple meta-learner(label corrector)strategy is proposed to enhance the label correction approach and prevent models from overfitting to noisy *** conducted experiments on three popular multimodal datasets to verify the superiority of ourmethod by comparing it with four baselines.

关键词： Distributed data collection multimodal sentiment analysis meta learning learn with noisy labels

L_(1)-Smooth SVM with Distributed Adaptive Proximal Stochastic Gradient Descent with Momentum for Fast Brain Tumor Detection

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Computers, Materials & Continua 2024年第5期79卷 1975-1994页

作者： Chuandong Qin Yu cao Liqun Meng School of Mathematics and Information Science North Minzu UniversityYinchuan750021China Ningxia Key Laboratory of Intelligent Information and Big Data Processing Yinchuan750021China

Brain tumors come in various types,each with distinct characteristics and treatment approaches,making manual detection a time-consuming and potentially ambiguous *** tumor detection is a valuable tool for gaining a deeper understanding of tumors and improving treatment *** learning models have become key players in automating brain tumor *** descent methods are the mainstream algorithms for solving machine learning *** this paper,we propose a novel distributed proximal stochastic gradient descent approach to solve the L_(1)-Smooth Support Vector Machine(SVM)classifier for brain tumor ***,the smooth hinge loss is introduced to be used as the loss function of *** avoids the issue of nondifferentiability at the zero point encountered by the traditional hinge loss function during gradient descent ***,the L_(1) regularization method is employed to sparsify features and enhance the robustness of the ***,adaptive proximal stochastic gradient descent(PGD)with momentum,and distributed adaptive PGDwithmomentum(DPGD)are proposed and applied to the L_(1)-Smooth *** computing is crucial in large-scale data analysis,with its value manifested in extending algorithms to distributed clusters,thus enabling more efficient processing ofmassive amounts of *** DPGD algorithm leverages Spark,enabling full utilization of the computer’s multi-core *** to its sparsity induced by L_(1) regularization on parameters,it exhibits significantly accelerated convergence *** the perspective of loss reduction,DPGD converges faster than *** experimental results show that adaptive PGD withmomentumand its variants have achieved cutting-edge accuracy and efficiency in brain tumor ***-trained models,both the PGD andDPGD outperform other models,boasting an accuracy of 95.21%.

关键词： Support vector machine proximal stochastic gradient descent brain tumor detection distributed computing

Curve Classification Based onMean-Variance Feature Weighting and Its Application

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Computers, Materials & Continua 2024年第5期79卷 2465-2480页

作者： Zewen Zhang Sheng Zhou Chunzheng cao School of Mathematics and Statistics Nanjing University of Information Science and TechnologyNanjing210044China Center for Applied Mathematics of Jiangsu Province Nanjing University of Information Science and TechnologyNanjing210044China

The classification of functional data has drawn much attention in recent *** main challenge is representing infinite-dimensional functional data by finite-dimensional features while utilizing those features to achieve better classification *** this paper,we propose a mean-variance-based(MV)feature weighting method for classifying functional data or functional *** the feature extraction stage,each sample curve is approximated by B-splines to transfer features to the coefficients of the spline *** that,a feature weighting approach based on statistical principles is introduced by comprehensively considering the between-class differences and within-class variations of the *** also introduce a scaling parameter to adjust the gap between the weights of *** new feature weighting approach can adaptively enhance noteworthy local features while mitigating the impact of confusing *** algorithms for feature weighted K-nearest neighbor and support vector machine classifiers are both ***,the new approach can be well integrated into existing functional data classifiers,such as the generalized functional linear model and functional linear discriminant analysis,resulting in a more accurate *** performance of the mean-variance-based classifiers is evaluated by simulation studies and real *** results show that the newfeatureweighting approach significantly improves the classification accuracy for complex functional data.

关键词： Functional data analysis classification feature weighting B-splines

Advances in non-invasive imaging of proteinopathies in animal models of neurodegenerative diseases

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Neural Regeneration Research 2024年第10期19卷 2115-2116页

作者： Lei cao Bin Ji Ruiqing Ni Changes Technology Corporation Ltd. ShanghaiChina Fudan University ShanghaiChina School of Pharmacy Fudan UniversityShanghaiChina Institute for Biomedical Engineering University of Zurich&ETH Zurich Institute for Regenerative MedicineUniversity of ZurichZurichSwitzerland

Neurodegenerative diseases,including Alzheimer's disease(AD),frontotemporal dementia,Parkinson's disease,and dementia with Lewy bodies,represent tremendous unmet clinical needs.A common feature of these diseases is the aberrant cerebral accumulation of pathological protein aggregates,affecting selectively vulnerable circuits in a disease-specific *** studies have established a relationship between abnormal aggregation and neuronal dysfunction or loss,suggesting multifactorial pathogenesis mechanisms in these neurodegenerative disorders.

关键词： diseases degenerative clinical

In Situ Atomic Reconstruction Engineering Modulating Graphene-Like MXene-Based Multifunctional Electromagnetic Devices Covering Multi-Spectrum

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Nano-Micro Letters 2024年第9期16卷 247-261页

作者： Ting‑Ting Liu Qi Zheng Wen‑Qiang cao Yu‑Ze Wang Min Zhang Quan‑Liang Zhao Mao‑Sheng cao School of Materials Science and Engineering Beijing Institute of TechnologyBeijing 100081People’s Republic of China Department of Physics Beijing Technology and Business UniversityBeijing 100048People’s Republic of China School of Mechanical and Materials Engineering North China University of TechnologyBeijing 100144People’s Republic of China

With the diversified development of big data,detection and precision guidance technologies,electromagnetic(EM)functional materials and devices serving multiple spectrums have become a hot *** the multispectral response of materials is a challenging and meaningful scientific *** this study,MXene/TiO_(2)hybrids with tunable conduction loss and polarization relaxation are fabricated by in situ atomic reconstruction *** importantly,MXene/TiO_(2)hybrids exhibit adjustable spectral responses in the GHz,infrared and visible spectrums,and several EM devices are constructed based on *** antenna array provides excellent EM energy harvesting in multiple microwave bands,with|S11|up to−63.2 dB,and can be tuned by the degree of *** ultra-wideband bandpass filter realizes a passband of about 5.4 GHz and effectively suppresses the transmission of EM signals in the *** infrared stealth device has an emissivity of less than 0.2 in the infrared spectrum at wavelengths of 6-14μ*** work can provide new inspiration for the design and development of multifunctional,multi-spectrum EM devices.

关键词： Graphene-like MXene hybrids Multi-spectral response Multi-function antenna Ultra-wideband bandpass filter Electromagnetic device

Multidimensional hollow SiO_(2)/C nanofibers modified by magnetic nanocrystals for electromagnetic energy conversion and lithium battery storage

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Nano Research 2024年第8期17卷 7301-7314页

作者： Chen Han Qi Zheng Juncheng Jin Jiajia Zhang Wen-Qiang cao Kun Xiang Min Zhang Mao-Sheng cao Anhui Provincial Laboratory of Biomimetic Sensor and Detecting Technology College of Materials and Chemical EngineeringWest Anhui UniversityLu’an 237012China School of Materials Science and Engineering Beijing Institute of TechnologyBeijing 100081China Department of Physics Beijing Technology and Business UniversityBeijing 100048China

Multifunctional materials are powerful tools to support the advancement of energy conversion *** with prominent electromagnetic and electrochemical properties can realize the conversion of electromagnetic energy and solve the subsequent storage ***,an electrospinning-thermal reduction method is employed to construct ultrafine nickel nanoparticle modified porous SiO_(2)/C(Ni-SiO_(2)/C)hollow nanofibers as promising materials for applications in both electromagnetic wave absorption(EMA)and lithium-ion ***,when used as an EMA material,the reflection loss(RL)of Ni-SiO_(2)/C can reach−47.8 dB at 15.8 GHz with a matching thickness of 2.2 *** excellent microwave absorption performance can be attributed to the enhanced conduction loss,polarization relaxation,synergistic magnetic loss,and preferred impedance matching,which result from multi-component magnetic/dielectric synergy and the unique interconnected multidimensional hollow ***,the electronic conductivity and electrochemical activity of the samples are significantly enhanced due to the uniform distribution of ultrafine Ni nanoparticles in the amorphous SiO_(2)/C ***,the hierarchical hollow porous structure provides sufficient free space for volume change during lithiation/delithiation ***,the Ni-SiO_(2)/C nanocomposite exhibits a high reversible capacity of 917.6 mAh·g^(−1)at 0.1 A·g^(−1).At a high current density of 2 A·g^(−1),a capacity of 563.9 mAh·g^(−1)can be maintained after 300 *** energy conversion-storage device is designed to store waste electromagnetic energy in the form of useful electrical *** work inspires the development of high-performance bifunctional materials.

关键词： Ni-SiO_(2)/C nanofiber electromagnetic absorption lithium-ion storage electrospinning multidimensional structure

Genome wide investigation of Hsf gene family in Phoebe bournei:identification,evolution,and expression after abiotic stresses

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Journal of Forestry Research 2024年第5期35卷 201-215页

作者： Wenhai Liao Xinghao Tang Jingshu Li Qiumian Zheng Ting Wang Shengze Cheng Shiping Chen Shijiang cao Guangqiu cao College of Forestry Fujian Agriculture and Forestry UniversityFuzhou 350002People’s Republic of China University Key Laboratory of Forest Stress Physiology Ecology and Molecular Biology of Fujian ProvinceFuzhou 350002People’s Republic of China Fujian Academy of Forestry Sciences Fuzhou 350002People’s Republic of China College of Plant Protection Fujian Agriculture and Forestry UniversityFuzhou 350002People’s Republic of China

Heat shock transcription factors(Hsfs)have important roles during plant growth and development and responses to abiotic *** identification and func-tion of Hsf genes have been thoroughly studied in various herbaceous plant species,but not woody species,especially Phoebe bournei,an endangered,unique species in *** this study,17 members of the Hsf gene family were identi-fied from *** using bioinformatic ***-netic analysis indicated that PbHsf genes were grouped into three subfamilies:A,B,and *** motifs,three-dimensional structure,and physicochemical properties of the PbHsf proteins were also *** structure of the PbHsf genes varied in the number of exons and ***-diction of cis-acting elements in the promoter region indi-cated that PbHsf genes are likely involved in responses to plant hormones and stresses.A collinearity analysis dem-onstrated that expansions of the PbHsf gene family mainly take place via segmental *** expression levels of PbHsf genes varied across different plant *** the basis of the expression profiles of five representative PbHsf genes during heat,cold,salt,and drought stress,PbHsf pro-teins seem to have multiple functions depending on the type of abiotic *** systematic,genome-wide investigation of PbHsf genes in *** and their expression patterns provides valuable insights and information for further func-tional dissection of Hsf proteins in this endangered,unique species.

关键词： Phoebe bournei Hsf gene family Evolutionary analysis Expression mechanism Abiotic stresses

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氮氧自由基类有机磁体的研究与展望

材料导报 2009年第3期23卷 102-105页

作者：曹雪琴李战雄陈国强苏州大学材料工程学院苏州215021

氮氧自由基因其结构优势已成为有机磁体的重要构件。从纯氮氧自由基类有机磁体和含金属的氮氧自由基类有机磁体两方面综述了氮氧自由基类有机磁体的结构、种类及发展历史。分析指出氮氧自由基类有机磁体目前存在的主要问题是转换温度Tc... 详细信息

氮氧自由基因其结构优势已成为有机磁体的重要构件。从纯氮氧自由基类有机磁体和含金属的氮氧自由基类有机磁体两方面综述了氮氧自由基类有机磁体的结构、种类及发展历史。分析指出氮氧自由基类有机磁体目前存在的主要问题是转换温度Tc较低及磁构关系不明确,但由于其具有诸多的优越性能而将得到大力研发。

关键词：氮氧自由基纯有机磁体含金属的有机磁体转换温度磁构关系