Optik最新文献_第3页

Variable refractive index waveguides for mid-infrared sensing 用于中红外传感的可变折射率波导

IF 3.1 3区物理与天体物理 Q2 Engineering

Optik

Pub Date : 2026-01-06 DOI: 10.1016/j.ijleo.2025.172662

Beibei Kong , Maren Anna Brandsrud , Pranish Karki , Boris Mizaikoff , Achim Kohler

Evanescent fields in attenuated total reflection (ATR) spectroscopy have enabled molecular analysis in the mid-infrared (MIR) region for decades. Recently, thin-film single-mode waveguides have been introduced, significantly improving sample interactions through evanescent fields along their surfaces. However, their implementation demands precise coupling of an infrared laser beam into a sub-wavelength-thick layer, posing design challenges. Here, we introduce gradient refractive index waveguides that achieve robust coupling, substantially enhanced evanescent fields and absorption efficiency, surpassing the performance of conventional single-mode waveguides. Using in-house Finite-Difference Time-Domain (FDTD) simulations validated against commercial software, we demonstrate that these waveguides enhance sample interactions by an order of magnitude. Moreover, their increased robustness simplifies optical system design and broadens their applicability across a wide wavelength range, making them compatible with broadband tunable lasers, LEDs (light-emitting diodes), and they have the potential to accommodate less collimated light sources, such as thermal light sources. This novel waveguide platform promises to advance mid-infrared ATR sensor technologies, particularly in lab-on-a-chip systems and compact devices targeting biomedical and environmental applications.

衰减全反射（ATR）光谱中的倏逝场已经使中红外（MIR）区域的分子分析成为可能。最近，薄膜单模波导已经被引入，通过沿其表面的倏逝场显著改善了样品的相互作用。然而，它们的实现需要将红外激光束精确耦合到亚波长厚的层中，这给设计带来了挑战。在这里，我们引入了梯度折射率波导，实现了鲁棒耦合，大大增强了倏逝场和吸收效率，超越了传统单模波导的性能。利用内部有限差分时域（FDTD）仿真验证了商业软件，我们证明了这些波导提高了一个数量级的样品相互作用。此外，它们增强的稳健性简化了光学系统的设计，拓宽了它们在宽波长范围内的适用性，使它们与宽带可调谐激光器、led（发光二极管）兼容，并且它们有可能适应较少准直的光源，如热光源。这种新型波导平台有望推进中红外ATR传感器技术，特别是在针对生物医学和环境应用的芯片实验室系统和紧凑型设备中。

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引用次数: 0

Developed a new activation function for machine learning using wavelet function for Fiber Bragg Grating sensor 利用小波函数为光纤光栅传感器开发了一种新的机器学习激活函数

IF 3.1 3区物理与天体物理 Q2 Engineering

Optik

Pub Date : 2026-01-06 DOI: 10.1016/j.ijleo.2026.172667

Sunil Kumar , Ugra Mohan , Somnath Sengupta , Yogesh K.M.

The advanced wavelet-based activation function for machine-learning applications in Fiber Bragg Grating (FBG) sensors presented in this manuscript has been developed to enhance peak-detection performance. The traditional activation function is replaced with a new activation function derived from an efficient wavelet formulation. The proposed activation function demonstrates improved response characteristics, enabling more accurate peak detection when applied to machine-learning models. A deep feedforward neural network is used to develop the machine-learning training model, which is effective for this application. The goal of the proposed technique is to reduce the dependency on the optical spectrum analyser (OSA) for measuring peak wavelengths, strain, and temperature. The wavelet-based activation function is constructed as a combination of the Gaussian wavelet function and ReLU. The developed activation function for machine-learning applications exhibits high accuracy. The proposed peak-detection technique is also verified experimentally, showing good accuracy. The mean-square error is as low as 0.0012 pm for FBG-1 and 0.0015 pm for FBG-2, with the peak-area entropy measured at approximately 1 for both FBGs.

本文中提出的用于光纤布拉格光栅（FBG）传感器中机器学习应用的先进的基于小波的激活函数已经开发出来，以提高峰值检测性能。传统的激活函数被一种新的激活函数所取代，该激活函数是由一种有效的小波公式推导出来的。提出的激活函数展示了改进的响应特性，当应用于机器学习模型时，可以更准确地检测峰值。采用深度前馈神经网络建立机器学习训练模型，有效地解决了这一问题。该技术的目标是减少对光谱分析仪（OSA）测量峰值波长、应变和温度的依赖。基于小波的激活函数由高斯小波函数和ReLU组合而成。开发的用于机器学习应用的激活函数具有很高的准确性。实验结果表明，所提出的峰值检测技术具有良好的准确性。FBG-1的均方误差低至0.0012 pm， FBG-2的均方误差低至0.0015 pm，两种fbg的峰面积熵测量值约为1。

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引用次数: 0

Multi-image encryption based on DCT coefficients and random vortex lattice 基于DCT系数和随机涡格的多图像加密

IF 3.1 3区物理与天体物理 Q2 Engineering

Optik

Pub Date : 2026-01-04 DOI: 10.1016/j.ijleo.2026.172666

Rahul Kumar , Sonu Kumar Rao , Naveen K. Nishchal , Ayman Alfalou

The secure transmission and storage of information have become increasingly critical in this technological era. While traditional image encryption techniques, such as double random phase encoding and its variants, offer robust security for single or paired images, they face significant challenges when applied to large-scale, multi-image scenarios. The challenges include high storage and computational complexity, inefficient processing, and difficult key management. To address these limitations, this study proposes an efficient and scalable method for multi-image encryption. The approach begins by applying the discrete cosine transform to each image, followed by cropping the transformed data. The cropped images are then assembled into a composite image of the original input size to prevent spectral overlap. Additional security is achieved through the application of the Arnold transform and the use of a random array-structured phase mask, generated by the random topological charges of a vortex lattice. The proposed method significantly reduces the storage and computational overhead, simplifies key management, and maintains high encryption quality. Numerical simulations demonstrate its effectiveness, robustness against various attacks, and suitability for securing multiple images.

在这个技术时代，信息的安全传输和存储变得越来越重要。虽然传统的图像加密技术，如双随机相位编码及其变体，为单个或成对图像提供了强大的安全性，但它们在应用于大规模、多图像场景时面临着重大挑战。挑战包括高存储和计算复杂性、低效的处理和困难的密钥管理。为了解决这些限制，本研究提出了一种高效且可扩展的多图像加密方法。该方法首先对每个图像应用离散余弦变换，然后裁剪变换后的数据。然后将裁剪后的图像组装成原始输入大小的合成图像，以防止光谱重叠。额外的安全性是通过应用阿诺德变换和使用随机阵列结构的相位掩模来实现的，该掩模是由涡流晶格的随机拓扑电荷产生的。该方法显著降低了存储和计算开销，简化了密钥管理，并保持了较高的加密质量。数值仿真结果表明，该算法对各种攻击具有较强的鲁棒性，适合于多图像的安全保护。

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引用次数: 0

Image deconvolution using adapted cauchy method 采用自适应柯西方法进行图像反卷积

IF 3.1 3区物理与天体物理 Q2 Engineering

Optik

Pub Date : 2026-01-02 DOI: 10.1016/j.ijleo.2026.172665

Zohair Al-Ameen

Generating clearer artifact-suppressed images is vital in various real-world scenarios, where hardware and software limitations often introduce blur. Image deconvolution (ID) aims to reverse this degradation, where prevailing methods vary in intricacy and frequently struggle to maintain stability and acuity across iterations. Driven by the need for non-complex and expeditious solutions, this study explores the use of the classical Cauchy method for ID, a method that, to the best of my knowledge, has not been previously investigated. Accordingly, two contributions are proposed based on this principle. First, the classical Cauchy method (CCM) is modified by embedding the blurring kernel into the iterative update structure, allowing CCM to work as an ID method. Second, an adapted Cauchy method (ACM) is introduced based on CCM. ACM further improves stability and suppresses artifacts better by utilizing a gradient reblurring formulation and an optimized step length rule. ACM is implemented and tested with images of real-life scenes, compared with six existing algorithms, and evaluated using four measures. Experimental results demonstrated that ACM showed a strong ability to restore diverse images while suppressing artifacts, surpassing existing methods in this field. This study showed that a non-complex method can achieve competitive and distinguished results, making it a valuable tool for image deconvolution. The related source codes are available at: https://github.com/qi-zohair/ACM.

在各种现实场景中，生成更清晰的伪影抑制图像是至关重要的，硬件和软件的限制通常会导致模糊。图像反卷积（ID）旨在扭转这种退化，其中流行的方法在复杂性上各不相同，并且经常难以在迭代中保持稳定性和敏锐性。由于需要非复杂和快速的解决方案，本研究探索了经典柯西方法在ID中的使用，据我所知，这是一种以前没有研究过的方法。因此，根据这一原则提出了两项建议。首先，对经典柯西方法（CCM）进行改进，将模糊核嵌入到迭代更新结构中，使CCM可以作为ID方法使用。其次，介绍了一种基于CCM的自适应柯西方法（ACM）。ACM进一步提高了稳定性，并通过利用梯度重模糊公式和优化的步长规则更好地抑制伪影。ACM使用真实场景的图像进行了实现和测试，与六种现有算法进行了比较，并使用四种度量进行了评估。实验结果表明，ACM在抑制伪影的同时表现出较强的复原多种图像的能力，超越了该领域现有的方法。该研究表明，一种不复杂的方法可以获得具有竞争性和显著性的结果，使其成为一种有价值的图像反卷积工具。相关源代码可从https://github.com/qi-zohair/ACM获得。

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引用次数: 0

Fabrication approaches for THz metasurfaces: A comprehensive review 太赫兹元表面的制备方法综述

IF 3.1 3区物理与天体物理 Q2 Engineering

Optik

Pub Date : 2025-12-30 DOI: 10.1016/j.ijleo.2025.172664

Meraline Selvaraj, Sreeja B S

Over the past decade, metamaterials have emerged as a revolutionary class of engineered materials, capturing significant attention across diverse scientific domains. Metasurfaces, composed of two-dimensional arrays of engineered meta-atoms, offer precise control over electromagnetic wave amplitude, phase, and polarization at subwavelength scales. This capability makes them an ideal platform for the design of ultra-compact, high-performance components in the THz regime. A critical challenge in transitioning these innovations to practical applications lies in the scalable fabrication of large-area, uniform, and high-resolution micro/nanostructures compatible with THz operation. This review explores the current state-of-the-art fabrication techniques for THz metasurfaces, including lithography, two-photon polymerization, 3D printing, and other advanced fabrication techniques. Each technique’s applicability, advantages, and limitations in achieving structural precision and optimal performance are highlighted. Additionally, challenges in the THz metasurface fabrication are addressed, along with potential solutions to guide future advancements in high-performance THz devices.

在过去的十年里，超材料已经成为一种革命性的工程材料，在不同的科学领域引起了极大的关注。由工程元原子的二维阵列组成的超表面可以精确控制电磁波的振幅、相位和亚波长尺度的极化。这种能力使它们成为设计超紧凑、高性能太赫兹波段组件的理想平台。将这些创新转化为实际应用的一个关键挑战在于，如何可扩展地制造与太赫兹操作兼容的大面积、均匀和高分辨率微/纳米结构。这篇综述探讨了目前最先进的太赫兹超表面的制造技术，包括光刻、双光子聚合、3D打印和其他先进的制造技术。强调了每种技术在实现结构精度和最佳性能方面的适用性、优点和局限性。此外，还解决了太赫兹超表面制造中的挑战，以及指导高性能太赫兹器件未来发展的潜在解决方案。

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引用次数: 0

MAPbBr3-2D material based on ultrahigh efficiency urine glucose detection SPR sensor 基于MAPbBr3-2D材料的超高效尿糖检测SPR传感器

IF 3.1 3区物理与天体物理 Q2 Engineering

Optik

Pub Date : 2025-12-30 DOI: 10.1016/j.ijleo.2025.172655

Alagu Vibisha G , Senthilkumar V , Priyadharsini N , Habibur Rahman S.M. , Jaroszewic Z , Rajesh K.B.

This study presents a high-performance surface plasmon resonance (SPR) biosensor employing a novel hybrid Kretschmann configuration for non-invasive urine glucose monitoring in diabetes management. The sensor integrates a CaF₂ prism, an optimized Cu-Ni bimetallic layer, a MAPbBr₃ perovskite sensitivity-enhancer, and a 2D nanomaterial interface to facilitate biomolecular interactions. Comprehensive numerical modeling via the transfer matrix method demonstrates exceptional performance, revealing a progressive angular sensitivity increase (330–615.1°/RIU) across clinically relevant glucose concentrations (0.625–10gdL^-¹). Achieved figures of merit (151.6–186.9RIU^-¹) confirm the platform's analytical precision. Featuring cost-effective fabrication potential, remarkable stability, and superior sensitivity, this SPR biosensor offers significant promise for developing practical non-invasive diabetes monitoring solutions.

本研究提出了一种高性能表面等离子体共振（SPR）生物传感器，采用一种新型的混合Kretschmann配置，用于糖尿病管理中的无创尿糖监测。该传感器集成了一个CaF2棱镜、一个优化的Cu-Ni双金属层、一个MAPbBr3钙钛矿灵敏度增强剂和一个二维纳米材料界面，以促进生物分子相互作用。通过传递矩阵方法进行的综合数值模拟显示了卓越的性能，揭示了在临床相关葡萄糖浓度（0.625-10gdL -¹）下，角敏感性逐渐增加（330-615.1°/RIU）。获得的优异值（151.6-186.9RIU -¹）证实了平台的分析精度。具有成本效益的制造潜力，卓越的稳定性和卓越的灵敏度，这种SPR生物传感器为开发实用的非侵入性糖尿病监测解决方案提供了重要的希望。

引用次数: 0

Evaluating short term financial marketing bitcoin prediction: A comparative analysis of large-kernel attention graph convolutional networks across various prediction horizon 评估短期金融营销比特币预测：跨不同预测范围的大核注意图卷积网络的比较分析

IF 3.1 3区物理与天体物理 Q2 Engineering

Optik

Pub Date : 2025-12-29 DOI: 10.1016/j.ijleo.2025.172663

Mohideen AbdulKader M , Sudhansu Sekhar Nanda , K. Sampath , D. Barani

One of the most popular investment assets nowadays is Bitcoin. The financial market volatility of bitcoin's price has drawn the attention of researchers and investors alike to the ways in which its price fluctuates. The paper proposes an evaluation of Short Term Financial Marketing Bitcoin Prediction: A Comparative Analysis of Large-Kernel Attention Graph Convolutional Networks across Various Prediction Horizons (BP-ST-LAGCN-NOA) for short-term Bitcoin market prediction. Then, pre-processed data are fed to the Large-kernel Attention Graph Convolutional Network (LAGCN) to effectively predict the bitcoin market in the short term. LAGCN does not express adaptive optimization strategies to determine optimal factors to effectively predict the Bitcoin market. Hence, the Nutcracker Optimization Algorithm (NOA) is employed to optimize the weight parameter of the Large-kernel Attention Graph Convolutional Network to predict the bitcoin market. Then the proposed BP-ST-LAGCN-NOA is implemented in Python, and the performance metrics like Accuracy, Precision, Recall, Specificity, F1-score, and ROC are analysed. The BP-ST-LAGCN-NOA model achieves 99.64 % accuracy, 99.21 % precision, 99.18 % recall, 98.14 % F1-Score and 98.47 % specificity, outperforming all baseline methods. The BP-ST-LAGCN-NOA model demonstrates superior accuracy and robustness in short-term Bitcoin market prediction, outperforming existing machine learning (ML) and deep learning (DL) approaches.

如今最受欢迎的投资资产之一是比特币。比特币价格在金融市场上的波动引起了研究人员和投资者对其价格波动方式的关注。本文提出了短期金融营销比特币预测的评价：跨不同预测视界的大核注意图卷积网络（BP-ST-LAGCN-NOA）对短期比特币市场预测的比较分析。然后，将预处理后的数据输入到大核注意图卷积网络（LAGCN）中，有效预测比特币短期市场走势。LAGCN没有表达自适应优化策略来确定最优因素，从而有效地预测比特币市场。因此，采用胡桃夹子优化算法（NOA）对大核注意图卷积网络的权重参数进行优化，预测比特币市场。然后用Python实现了BP-ST-LAGCN-NOA，并对准确率、精密度、召回率、特异性、F1-score和ROC等性能指标进行了分析。BP-ST-LAGCN-NOA模型准确率为99.64 %，精密度为99.21 %，召回率为99.18 %，F1-Score为98.14 %，特异性为98.47 %，优于所有基线方法。BP-ST-LAGCN-NOA模型在短期比特币市场预测中表现出卓越的准确性和鲁棒性，优于现有的机器学习（ML）和深度学习（DL）方法。

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引用次数: 0

Optical radiation forces on Rayleigh spheres produced by focused vortex higher-order cosine-hyperbolic-Gaussian beams 聚焦涡高阶余弦双曲高斯光束对瑞利球产生的光辐射力

IF 3.1 3区物理与天体物理 Q2 Engineering

Optik

Pub Date : 2025-12-27 DOI: 10.1016/j.ijleo.2025.172654

Abdellah Ahlane, Salma Chib, Zoubir Hricha, Abdelmajid Belafhal

We present a theoretical investigation of the optical radiation forces exerted by highly focused vortex higher-order cosine-hyperbolic-Gaussian beams (vHOChGBs) on Rayleigh dielectric spheres. Analytical expressions for the focused vHOChGBs field and the resulting gradient and scattering forces are derived, explicitly revealing their dependence on key beam parameters (decentering b, beam order N, topological charge m), particle characteristics, and the environment medium. Numerical results show that the structured intensity profiles of vHOChGBs enable simultaneous trapping of low and high-index particles. High-index particles localize in bright focal regions, while low-index particles are confined into inter-lobe minima. Stability analysis establishes that gradient forces dominate scattering and thermal effects across parameter spaces, with beam waist ω₀ and topological charge m critically governing trapping potential depths. This parametric flexibility could allow precision assembly of micro/nanostructures and non-invasive biological specimen handling, advancing vHOChGBs as versatile tools for optical tweezers and biophotonics applications.

本文从理论上研究了高聚焦涡旋高阶余弦双曲高斯光束在瑞利介质球上施加的光辐射力。推导了聚焦vHOChGBs场及其梯度和散射力的解析表达式，明确揭示了它们与关键光束参数（离心b、光束阶数N、拓扑电荷m）、粒子特性和环境介质的依赖关系。数值结果表明，vhochgb的结构强度分布可以同时捕获低指数和高指数粒子。高折射率粒子集中在明亮的焦点区域，而低折射率粒子则局限在瓣间极小值区域。稳定性分析表明，梯度力在参数空间中的散射和热效应占主导地位，束腰ω0和拓扑电荷m对捕获电位深度起关键控制作用。这种参数灵活性可以实现微/纳米结构的精确组装和非侵入性生物标本处理，使vhochgb成为光学镊子和生物光子学应用的多功能工具。

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引用次数: 0

Generation of quantum coherence in a magnomechanical system 磁力学系统中量子相干性的产生

IF 3.1 3区物理与天体物理 Q2 Engineering

Optik

Pub Date : 2025-12-23 DOI: 10.1016/j.ijleo.2025.172653

Mulugeta Tadesse Bedore , Tesfay Gebremariam Tesfahannes , Tewodros Yirgashewa Darge , Menisha Alemu Tufa , Abdelkader Hidki , Habtamu Dagnaw Mekonnen , Muhdin Abdo Wodedo , Philippe Djorwe

We investigate macroscopic quantum coherence in a hybrid magnomechanical system consisting of a microwave cavity with a yttrium iron garnet (YIG) sphere coupled to an auxiliary microwave cavity. By solving the Lyapunov equation and analyzing the steady-state mean values, we use the magnetic dipole interaction between the cavity mode and the magnon mode, as well as the magnetostrictive interaction between the magnon mode and the mechanical vibrations of the YIG sphere, to generate and transfer Gaussian quantum coherence across different subsystems. Our results reveal that significant quantum coherence can be realized between various bipartitions, even at high temperatures. We identify optimal parameter regimes that enhance coherence, offering insights into the robust generation and control of quantum correlations in macroscopic systems. These findings contribute to the advancement of macroscopic quantum technologies and highlight promising directions for quantum information processing.

我们研究了一个由钇铁石榴石球耦合到辅助微波腔的微波腔组成的混合磁力学系统中的宏观量子相干性。通过求解Lyapunov方程和分析稳态平均值，我们利用腔模式和磁振子模式之间的磁偶极相互作用，以及磁振子模式和YIG球的机械振动之间的磁致伸缩相互作用，在不同子系统之间产生和传递高斯量子相干性。我们的研究结果表明，即使在高温下，不同双分频之间也可以实现显著的量子相干性。我们确定了增强相干性的最佳参数制度，为宏观系统中量子相关性的鲁棒生成和控制提供了见解。这些发现有助于宏观量子技术的进步，并突出了量子信息处理的有前途的方向。

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引用次数: 0

An automated measurement method for dendritic structures in laser cladding coatings using deep learning 基于深度学习的激光熔覆层枝晶结构自动测量方法

IF 3.1 3区物理与天体物理 Q2 Engineering

Optik

Pub Date : 2025-12-19 DOI: 10.1016/j.ijleo.2025.172643

Fang Guo , Longmei Luo , Xueming Zhang , Mengsi Zhang , Youji Zhan , Guofu Lian

To enhance the efficiency of intelligent recognition of the microstructure of laser cladding coatings and optimize the evaluation methods for coating performance and quality, we introduce an image segmentation model called DendriticNet and develops an automated measurement method for the dendritic structure images of laser cladding coatings. The DendriticNet model enables precise pixel-level segmentation and recognition of three types of dendritic structures—dendritic, bulk, and equiaxed crystals—effectively overcoming the limitations of traditional metallographic recognition methods. This provides efficient and accurate technical support for the microstructural analysis of laser cladding coatings. The DendriticNet model combines transfer learning with the Res_CSP attention mechanism module, enabling accurate recognition in complex scenarios involving varying scales and overlapping dendritic structures. Additionally, it achieves qualitative characterization of dendritic microstructures at the micron scale. Experimental results demonstrate that the DendriticNet model achieves an mIoU of 80.31 %, an MPA of 88.43 %, and an accuracy of 93.01 %. By integrating the predicted images produced by the DendriticNet model with the automatic measurement method for dendritic microstructure images of laser cladding coatings, quantitative analysis is conducted to automatically calculate the density ratios of various dendritic structures. Experimental results demonstrate that the measurement accuracy for the total dendritic density ratio exceeds 96.6 %, confirming the feasibility and effectiveness of this automatic measurement method. This approach not only enables the quantitative characterization of dendritic structures at the micron scale but also offers an innovative solution for exploring the relationship between the microstructure and macroscopic performance of coatings.

为了提高激光熔覆涂层微观结构的智能识别效率，优化涂层性能和质量的评价方法，我们引入了一种名为DendriticNet的图像分割模型，并开发了一种用于激光熔覆涂层树枝状结构图像的自动测量方法。DendriticNet模型能够精确的像素级分割和识别三种类型的枝晶结构-枝晶，块状和等轴晶体-有效地克服了传统金相识别方法的局限性。这为激光熔覆涂层的显微组织分析提供了高效、准确的技术支持。DendriticNet模型将迁移学习与Res_CSP注意机制模块相结合，能够在涉及不同规模和重叠树突结构的复杂场景中进行准确识别。此外，它还实现了微米尺度上枝晶微观结构的定性表征。实验结果表明，该模型的mIoU为80.31 %，MPA为88.43 %，准确率为93.01 %。将DendriticNet模型生成的预测图像与激光熔覆涂层枝晶微观结构图像自动测量方法相结合，进行定量分析，自动计算出各种枝晶结构的密度比。实验结果表明，总枝晶密度比的测量精度超过96.6% %，验证了该自动测量方法的可行性和有效性。这种方法不仅能够在微米尺度上定量表征树枝状结构，而且为探索涂层微观结构与宏观性能之间的关系提供了一种创新的解决方案。

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引用次数: 0