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Unraveling post-growth mechanisms of monolayer CsPbBr3 nanocubes:Laser-enhanced transformations and cathodoluminescence-electron microscopy correlations

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Journal of Energy Chemistry 2025年第1期100卷 146-156页

作者： Mingxing Li Xiaoge Wang Xiaofan Cao Zhiqun He Chunjun Liang Mingxing Chen Jing Ju Fangtian You Key Laboratory of Luminescence and Optical information Ministry of Education Institute of Optoelectronic Technology Beijing Jiaotong University Beijing National Laboratory for Molecular Sciences (BNLMS) College of Chemistry and Molecular Engineering Peking University

Lead-halide perovskite nanoparticles（LHP NPs） are highly promising materials for next-generation displays and solid-state lighting due to their exceptional optical properties. However, their inherent instability presents a significant challenge. Recent advances have demonstrated that optoelectronic devices based on monolayer nanoparticle films exhibit both high luminescence efficiency and long-term *** research demonstrates that mobility limitations and anisotropic alignments in CsPbBr3nanocube monolayer films are key to their stabilization, hindering spontaneous growth through face-to-face fusion and resulting in the formation of connecting necks in a diagonal direction. Introducing laser irradiation confirmed this by significantly accelerating nanocubes growth, increasing mobility, and enhancing local structural ordering, leading to larger and more regularly shaped nanosheets. Fourier transform infrared spectroscopy and energy dispersive spectroscopy line-scan analyses indicated that laser irradiation did not disrupt the ligand structure. transmission electron microscopy and correlative cathodoluminescence electron microscopy revealed the effects of post-growth and heterogeneous structures, including enhanced luminescence and inhomogeneous intensity in the nanosheets. These findings deepen the understanding of the post-growth mechanism of monolayer nanoparticles and the structure-emission correlation and highlight the unique role of laser irradiation in directing the formation of well-defined and regular nanostructures.

关键词： Post-growth mechanism Heterogeneous structure Single-particle spectroscopy Laser irradiation

Semantic Segmentation of Lumbar Vertebrae Using Meijering U-Net(MU-Net)on Spine Magnetic Resonance Images

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Computer Modeling in Engineering & Sciences 2025年第1期142卷 733-757页

作者： Lakshmi S V V Shiloah Elizabeth Darmanayagam Sunil Retmin Raj Cyril Department of Computer Science and Engineering College of Engineering GuindyAnna UniversityChennai600025India Department of information Technology Madras Institute of TechnologyAnna UniversityChrompetChennai600044India

Lower back pain is one of the most common medical problems in the world and it is experienced by a huge percentage of people *** to its ability to produce a detailed view of the soft tissues,including the spinal cord,nerves,intervertebral discs,and vertebrae,Magnetic Resonance Imaging is thought to be the most effective method for imaging the *** semantic segmentation of vertebrae plays a major role in the diagnostic process of lumbar *** is difficult to semantically partition the vertebrae in Magnetic Resonance Images from the surrounding variety of tissues,including muscles,ligaments,and intervertebral discs.U-Net is a powerful deep-learning architecture to handle the challenges of medical image analysis tasks and achieves high segmentation *** work proposes a modified U-Net architecture namely MU-Net,consisting of the Meijering convolutional layer that incorporates the Meijering filter to perform the semantic segmentation of lumbar vertebrae L1 to L5 and sacral vertebra ***-colour mask images were generated and used as ground truth for training the *** work has been carried out on 1312 images expanded from T1-weighted mid-sagittal MRI images of 515 patients in the Lumbar Spine MRI Dataset publicly available from Mendeley *** proposed MU-Net model for the semantic segmentation of the lumbar vertebrae gives better performance with 98.79%of pixel accuracy(PA),98.66%of dice similarity coefficient(DSC),97.36%of Jaccard coefficient,and 92.55%mean Intersection over Union(mean IoU)metrics using the mentioned dataset.

关键词： Computer aided diagnosis(CAD) magnetic resonance imaging(MRI) semantic segmentation lumbar vertebrae deep learning U-Net model

New sets of low-hit-zone frequency-hopping sequence with optimal maximum periodic partial Hamming correlation

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Science China(information Sciences) 2015年第12期58卷 162-176页

作者： WANG ChangYuan PENG DaiYuan HAN HongYu ZHOU LiMengNan Provincial Key Lab of information Coding and transmission Institute of Mobile CommunicationsSouthwest Jiaotong University

Recently, Chung et al. gave a general method to construct frequency-hopping sequence set(FHS set) with low-hit-zone(LHZ FHS set) by the Cartesian product. In their paper, Theorems 5 and 8 claim that k FHS sets whose maximum periodic Hamming correlation is 0 at the origin result in an LHZ FHS set based on the Cartesian product, and Proposition 4 presented an upper bound of the maximum periodic Hamming correlation of FHSs. However, their statements are imperfect or incorrect. In this paper, we give counterexamples and make corrections to them. Furthermore, based on the Cartesian product, we construct two classes of LHZ FHS sets with optimal maximum periodic partial Hamming correlation property. It is shown that new FHS sets are optimal by the maximum periodic partial Hamming correlation bound of LHZ FHS set.

关键词： frequency-hopping sequence maximum periodic partial Hamming correlation maximum periodic Hamming correlation low-hit-zone cartesian product

BER analysis of STBC hybrid carrier system based on WFRFT with frequency domain equalization

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Science China(information Sciences) 2018年第8期61卷 147-159页

作者： Zhenduo WANG Lin MEI Xuejun SHA Naitong ZHANG Communication Research Center Harbin Institute of Technology Science and Technology on information transmission and Dissemination in Communication Networks Laboratory

The inherent characteristic of hybrid carrier(HC) scheme based on the weighted-type fractional Fourier transform(WFRFT) is revealed. The proposed linear combination of single carrier(SC) and multicarrier’s(MC) characteristics is helpful to balance the conflicting requirements and achieve the comparative analysis of SC/MC. As an example, analytical SER/BER expressions of HC system with zero forcing(ZF)and minimum mean square error(MMSE) equalization are derived. In addition, the derived BER expressions are extended to multi-input systems. A unified framework of space time block code(STBC) HC scheme is proposed with two WFRFT modules at the transmitter or receiver, where STBC-SC and STBC-MC systems are the special cases of the novel structure.

关键词： single carrier multi-carrier weighted-type fractional Fourier transform hybrid carrier zero forcing minimum mean square error space time block code

Flex Ethernet Technology and Application in 5G Mobile Transport Network

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China Communications 2021年第2期18卷 250-258页

作者： Meng Zhang Research institute of Telecommunications transmission(RITT) China Academy of Information Communications Technology(CAICT)MIITBeijing 100191China

With the advent of 5G era,the rise of cloud services,virtual reality/virtual reality(AR/VR),vehicle networking and other technologies has put forward new requirements for the bandwidth and delay of the bearer *** Ethernet technology cannot meet the new requirements very *** Ethernet(FlexE)technology has emerged as the times *** paper introduces the background,standardization process,functional principle,application mode and technical advantages of FlexE technology,and finally analyses its application prospects and shortcomings in 5G mobile transport network.

关键词： Flex Ethernet(FlexE) 5G mobile transport network network slicing

Joint User Association and Resource Allocation for Self-Backhaul Ultra-Dense Networks

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China Communications 2016年第2期13卷 1-10页

作者： LIU Yanping FANG Xuming Provincial Key Laboratory of information Coding and transmission Southwest Jiaotong University

In order to meet the exponentially increasing demand on mobile data traffic, self-backhaul ultra-dense networks(UDNs) combined with millimeter wave(mm Wave) communications are expected to provide high spatial multiplexing gain and wide bandwidths for multi-gigabit peak data rates. In selfbackhaul UDNs, how to make the radio access rates of small cells match their backhaul rates by user association and how to dynamically allocate bandwidth for the access links and backhaul links to balance two-hop link resources are two key problems on improving the overall throughputs. Based on this, a joint scheme of user association and resource allocation is proposed in self-backhaul ultra-dense networks. Because of the combinatorial and nonconvex features of the original optimization problem, it has been divided into two subproblems. Firstly, to make the radio access rates of small base stations match their backhaul rates and maximize sum access rates per Hz of all small cells, a proportional constraint is introduced, and immune optimization algorithm(IOA) is adopted to optimize the association indicator variables and the boresight angles of between users and base stations. Then, the optimal backhaul and access bandwidths are calculated by differentiating the general expression of overall throughput. Simulation results indicatethat the proposed scheme increases the overall throughputs significantly compared to the traditional minimum-distance based association scheme.

关键词： ultra-dense networks user association mmWave communications self-backhaul

Efficient link scheduling with joint power control and successive interference cancellation in wireless networks

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Science China Earth Sciences 2016年第12期59卷 19-33页

作者： Xuan LI Yan SHI Xijun WANG Chao XU Min SHENG State Key Laboratory of Integrated Services Networks Information Science InstituteXidian UniversityXi'an 710071China Science and Technology on information transmission and Dissemination in Communication Networks Laboratory Shijiazhuang 050081China

Existing works have addressed the interference mitigation by any two of the three approaches: link scheduling, power control, and successive interference cancellation(SIC). In this paper, we integrate the above approaches to further improve the spectral efficiency of the wireless networks and consider the max-min fairness to guarantee the transmission demand of the worst-case link. We formulate the link scheduling with joint power control and SIC(PCSIC) problem as a mixed-integer non-linear programming(MINLP), which has been proven to be NP-complete. Consequently, we propose an iterative algorithm to tackle the problem by decomposing it into a series of linear subproblems, and then the analysis shows that the algorithm has high complexity in the worst case. In order to reduce the computational complexity, we have further devised a two-stage algorithm with polynomial-time complexity. Numerical results show the performance improvements of our proposed algorithms in terms of the network throughput and power consumption compared with the link scheduling scheme only with SIC.

关键词： successive interference cancellation power control mathematical optimization fairness cross-layerlink scheduling framework

Regularization by Multiple Dual Frames for Compressed Sensing Magnetic Resonance Imaging With Convergence Analysis

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IEEE/CAA Journal of Automatica Sinica 2023年第11期10卷 2136-2153页

作者： Baoshun Shi Kexun Liu School of information Science and Engineering Yanshan University the Hebei Key Laboratory of information transmission and Signal Processing Qinhuangdao 066004China IEEE

Plug-and-play priors are popular for solving illposed imaging inverse problems. Recent efforts indicate that the convergence guarantee of the imaging algorithms using plug-andplay priors relies on the assumption of bounded denoisers. However, the bounded properties of existing plugged Gaussian denoisers have not been proven explicitly. To bridge this gap, we detail a novel provable bounded denoiser termed as BMDual,which combines a trainable denoiser using dual tight frames and the well-known block-matching and 3D filtering(BM3D)denoiser. We incorporate multiple dual frames utilized by BMDual into a novel regularization model induced by a solver. The proposed regularization model is utilized for compressed sensing magnetic resonance imaging(CSMRI). We theoretically show the bound of the BMDual denoiser, the bounded gradient of the CSMRI data-fidelity function, and further demonstrate that the proposed CSMRI algorithm converges. Experimental results also demonstrate that the proposed algorithm has a good convergence behavior, and show the effectiveness of the proposed algorithm.

关键词： Bounded denoiser compressed sensing magnetic resonance imaging(CSMRI) dual frames plug-and-play priors regularization

Adaptive Neighboring Selection Algorithm Based on Curvature Prediction in Manifold Learning

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Journal of Harbin institute of Technology(New Series) 2013年第3期20卷 119-123页

作者： Lin Ma Cai-Fa Zhou Xi Liu Yu-Bin Xu Communication Research Center Harbin Institute of Technology Science and Technology on information transmission and Dissemination in Communication Networks Laboratory

Recently manifold learning algorithm for dimensionality reduction attracts more and more interests, and various linear and nonlinear,global and local algorithms are proposed. The key step of manifold learning algorithm is the neighboring region selection. However,so far for the references we know,few of which propose a generally accepted algorithm to well select the neighboring region. So in this paper,we propose an adaptive neighboring selection algorithm,which successfully applies the LLE and ISOMAP algorithms in the test. It is an algorithm that can find the optimal K nearest neighbors of the data points on the manifold. And the theoretical basis of the algorithm is the approximated curvature of the data point on the manifold. Based on Riemann Geometry,Jacob matrix is a proper mathematical concept to predict the approximated curvature. By verifying the proposed algorithm on embedding Swiss roll from R3 to R2 based on LLE and ISOMAP algorithm,the simulation results show that the proposed adaptive neighboring selection algorithm is feasible and able to find the optimal value of K,making the residual variance relatively small and better visualization of the results. By quantitative analysis,the embedding quality measured by residual variance is increased 45. 45% after using the proposed algorithm in LLE.

关键词： manifold learning curvature prediction adaptive neighboring selection residual variance