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基于改进simAM-YOLOv8的路面多病害识别方法
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作者 单飞 李辉 +2 位作者 孙浩 聂世刚 申忠虎 《吉林大学学报(工学版)》 北大核心 2026年第1期219-230,共12页
针对道路路面病害数据多模态和识别准确率低的问题,提出了一种基于无参数注意力机制simAM改进YOLOv8的路面多病害识别算法。利用自有路面病害数据集,在YOLOv8结构中嵌入Res2Net,在计算负载量相似的基础上增强多规模特征提取能力;采用si... 针对道路路面病害数据多模态和识别准确率低的问题,提出了一种基于无参数注意力机制simAM改进YOLOv8的路面多病害识别算法。利用自有路面病害数据集,在YOLOv8结构中嵌入Res2Net,在计算负载量相似的基础上增强多规模特征提取能力;采用simAM模块进一步调整不同尺度特征图的权重,实现对目标的检测改善;利用遗传算法提升模型自动寻参速度,使用HSV以及Mosaic等图像增强手段扩充小样本病害。实验结果表明:改进后的simAM-YOLOv8算法对沥青、水泥等不同类型路面的裂缝、破碎板、修补等病害识别结果相较原网络精确率整体提升了15.3%,召回率整体提升了13.1%,表现出了较好的智能识别效果,可在公路路况自动化检测方面发挥重要作用。 展开更多
关键词 智能交通 路面病害 识别算法 simam YOLOv8 Res2Net
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Weak Co-AB-context for G_(C)-χ-injective Modules
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作者 YANG Qiang 《数学进展》 北大核心 2026年第1期103-119,共17页
In this paper,we introduce the notion of G_(C)-X-injective modules,where X denotes a class of left S-modules and C represents a faithfully semidualizing bimodule.Under the condition that X satisfies certain hypotheses... In this paper,we introduce the notion of G_(C)-X-injective modules,where X denotes a class of left S-modules and C represents a faithfully semidualizing bimodule.Under the condition that X satisfies certain hypotheses,some properties and some equivalent characterizations of G_(C)-X-injective modules are investigated,and we also show that the triple(■,cores■,■)is a weak co-AB-context.As an application,two complete cotorsion pairs and a new model structure in Mod S are given. 展开更多
关键词 C-X-injective module G_(C)-X-injective module cotorsion pair weak co-ABcontext
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Stableδ-FA(Cs)PbI_(3)intermediate enables fabrication of large-area perovskite solar modules in ambient air
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作者 Chenyang Duan Ke Xiao +12 位作者 Yinke Wang Ye Liu Yameen Ahmed Zhentao Pang Wenjun Zhan Hongfei Sun Han Gao Haowen Luo Yuhong Zhang Xin Luo Yu Deng Makhsud I.Saidaminov Hairen Tan 《Science China Materials》 2026年第3期1456-1463,共8页
Fabrication of large-area perovskite solar modules under ambient air conditions remains a critical challenge due to air sensitivity of perovskite intermediate phases during crystallization.Here,we introduce 2-iodoimid... Fabrication of large-area perovskite solar modules under ambient air conditions remains a critical challenge due to air sensitivity of perovskite intermediate phases during crystallization.Here,we introduce 2-iodoimidazole(IIZ)into the perovskite precursor,enabling the formation of an air-stable pureδ-phase intermediate,which,upon annealing,fully transforms into a highly orientedα-phase perovskite film with reduced defects and variability.Leveraging this approach,we achieve a stabilized power conversion efficiency of 20.9%for 927.5 cm^(2)perovskite solar modules with high reproducibility.The encapsulated modules meet stringent international photovoltaic testing standards(IEC61215:2021),demonstrating excellent stability under continuous operation,thermal cycling(-40 to 85℃)and damp heat(85℃ and 85%relative humidity). 展开更多
关键词 perovskite solar modules intermediate phases ambient fabrication scalable fabrication stability
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微课驱动小学生英语自主学习能力提升的探究——以Module 5 Unit 9 Where will you go?第一课时自主学习为例
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作者 张兴 《视周刊》 2026年第1期34-35,共2页
一、微课设计:从知识传递到认知建构的范式转变1.微课定义微课是一种以短小精悍的数字视频为主要载体,围绕某个知识点、教学环节或特定教学主题而设计的结构化、情境化教学资源。其时长通常在5-10分钟之间,内容高度聚焦,重点突出,针对性... 一、微课设计:从知识传递到认知建构的范式转变1.微课定义微课是一种以短小精悍的数字视频为主要载体,围绕某个知识点、教学环节或特定教学主题而设计的结构化、情境化教学资源。其时长通常在5-10分钟之间,内容高度聚焦,重点突出,针对性强,符合学生的认知负荷与注意力特点,旨在通过精炼的内容和生动的呈现方式,激发学生学习兴趣,支持个性化、碎片化学习,促进自主探究与合作交流,是现代教育信息化背景下一种重要的教学辅助手段与课程资源形态。 展开更多
关键词 英语 module 5 Unit 9 能力提升 自主学习 微课
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An RMD-YOLOv11 Approach for Typical Defect Detection of PV Modules
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作者 Tao Geng Shuaibing Li +3 位作者 Yunyun Yun Yongqiang Kang Hongwei Li unmin Zhu 《Computers, Materials & Continua》 2026年第3期1804-1822,共19页
In order to address the challenges posed by complex background interference,high miss-detection rates of micro-scale defects,and limited model deployment efficiency in photovoltaic(PV)module defect detection,this pape... In order to address the challenges posed by complex background interference,high miss-detection rates of micro-scale defects,and limited model deployment efficiency in photovoltaic(PV)module defect detection,this paper proposes an efficient detection framework based on an improved YOLOv11 architecture.First,a Re-parameterized Convolution(RepConv)module is integrated into the backbone to enhance the model’s sensitivity to fine-grained defects—such as micro-cracks and hot spots—while maintaining high inference efficiency.Second,a Multi-Scale Feature Fusion Convolutional Block Attention Mechanism(MSFF-CBAM)is designed to guide the network toward critical defect regions by jointly modeling channel-wise and spatial attention.This mechanism effectively strengthens the specificity and robustness of feature representations.Third,a lightweight Dynamic Sampling Module(DySample)is employed to replace conventional upsampling operations,thereby improving the localization accuracy of small-scale defect targets.Experimental evaluations conducted on the PVEL-AD dataset demonstrate that the proposed RMDYOLOv11 model surpasses the baseline YOLOv11 in terms of mean Average Precision(mAP)@0.5,Precision,and Recall,achieving respective improvements of 4.70%,1.51%,and 5.50%.The model also exhibits notable advantages in inference speed and model compactness.Further validation on the ELPV dataset confirms the model’s generalization capability,showing respective performance gains of 1.99%,2.28%,and 1.45%across the same metrics.Overall,the enhanced model significantly improves the accuracy of micro-defect identification on PV module surfaces,effectively reducing both false negatives and false positives.This advancement provides a robust and reliable technical foundation for automated PV module defect detection. 展开更多
关键词 Photovoltaic(PV)modules YOLOv11 re-parameterization convolution attention mechanism dynamic upsampling
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基于SimAM注意力机制的DCN-YOLOv5水下目标检测
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作者 刘向举 刘洋 蒋社想 《重庆工商大学学报(自然科学版)》 2025年第2期63-70,共8页
目的针对水下环境复杂,水下目标因光线折射导致的目标边界模糊或外观、形状可能会发生非刚性形变,使水下目标检测困难的问题,提出了一种基于SimAM注意力机制的DCN-YOLOv5水下目标检测方法。方法首先,采用YOLOv5所使用的双向金字塔网络(B... 目的针对水下环境复杂,水下目标因光线折射导致的目标边界模糊或外观、形状可能会发生非刚性形变,使水下目标检测困难的问题,提出了一种基于SimAM注意力机制的DCN-YOLOv5水下目标检测方法。方法首先,采用YOLOv5所使用的双向金字塔网络(BiFPN,Bi-directional Feature Pyramid Network)在多个尺度上提取和融合特征信息,从而提高目标辨别的准确度;其次,针对水下目标的外观、形状变化问题,将C3模块中的CBS模块结合可变形卷积(DCN,Deformable Convolution Network),提出DBS模块并组成D3模块替换部分C3模块,以适应水下目标的外观、形状变化;同时,融入加权注意力机制(SimAM),自适应地调节模型的关注度,进一步在复杂场景下增强特征表达能力;最后,考虑目标边界模糊,为改善目标定位精度,采用WIoU(Wise-IoU)损失函数来替换交叉熵损失,能够更好地适应不同目标类型和尺寸的特点,提高算法鲁棒性。结果实验结果表明:DCN-YOLOv5可以达到87.57%的平均精度(mAP),检测效果优于YOLOv5网络和其他经典网络,平均每张图像的识别时间仅为24.5 ms。结论通过实验结果可以证明模型在检测精度明显提升的同时兼顾检测的实时性,对水下目标检测用于实际用途有着一定的参考价值。 展开更多
关键词 水下目标检测 simam注意力机制 可变形卷积 WIoU
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基于IEA-T和CNN-BiLSTM-SimAM的锂离子电池健康状态估计 被引量:1
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作者 张朝龙 刘梦玲 +4 位作者 张俣峰 陈阳 华国庆 谢敏 江乐阳 《武汉大学学报(理学版)》 北大核心 2025年第3期385-394,共10页
为提升锂离子电池健康状态(SOH)估计的准确性,克服现有估计方法无法全面刻画电池衰退细节的局限,提出一种融合距离交并比损失函数(DIoUloss)与无参注意力机制(SimAM)的多特征卷积神经网络-双向长短期记忆网络(CNNBiLSTM)的锂电池SOH估... 为提升锂离子电池健康状态(SOH)估计的准确性,克服现有估计方法无法全面刻画电池衰退细节的局限,提出一种融合距离交并比损失函数(DIoUloss)与无参注意力机制(SimAM)的多特征卷积神经网络-双向长短期记忆网络(CNNBiLSTM)的锂电池SOH估计方法。该方法将锂离子电池增量能量面积(IEA)和充电时长(T)组成IEA-T特征用于电池SOH的估计,将DIoUloss函数和SimAM机制融合于CNN-BiLSTM模型,建立CNN-BiLSTM-SimAM锂离子电池SOH估计模型。对锂离子电池的循环老化实验进行测试,相比起GRU、SVR、CNN-LSTM和CNN-BiLSTM等方法,本文提出的方法能更有效地表征电池健康的衰退细节,决定系数高于0.96,均方根误差低于0.020,表现出良好的准确性和效率。 展开更多
关键词 锂离子电池 健康状态(SOH) 卷积神经网络-双向长短期记忆网络(CNN-BiLSTM) 距离交并比损失(DIoUloss)函数 无参注意力机制(simam) 增量能量
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基于XMem-SimAM的半监督猪只视频分割方法
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作者 陈萌放 徐迪红 +3 位作者 李国亮 刘小磊 周明彦 黎煊 《华中农业大学学报》 北大核心 2025年第2期17-28,共12页
为解决因猪场复杂环境、猪只动态生长及体型变化等因素导致的猪只精确分割难题,以种猪性能测定过程中动态采食和生长过程的猪只为研究对象,构建一个包括234个视频序列的猪只视频数据集,提出基于XMem-SimAM的半监督猪只视频分割方法。通... 为解决因猪场复杂环境、猪只动态生长及体型变化等因素导致的猪只精确分割难题,以种猪性能测定过程中动态采食和生长过程的猪只为研究对象,构建一个包括234个视频序列的猪只视频数据集,提出基于XMem-SimAM的半监督猪只视频分割方法。通过引入SimAM注意力进行多尺度特征融合,提升模型在不同尺度下对时序信息的提取能力,捕捉猪只动态移动的时序特征;利用空间-通道注意力模块,强化模型对时序语义特征的权重提取;优化多尺度特征融合策略和上采样模块,充分利用视频序列中的时序关联信息,从细粒度层面提高视频中猪只分割精度。经过测试对比,XMem-SimAM模型在猪只视频数据集上的区域相似度Jaccard、轮廓准确度F、平均度量J&F和Dice系数分别达到96.9、95.8、98.0和98.0,优于MiVOS、STCN、DEVA、XMem++等视频对象分割方法,显示出卓越的分割性能;在推理阶段,处理速度达到58.5帧/s,内存消耗为795 MB,实现了处理效率与资源利用的良好平衡。结果表明,该方法可应用于猪场复杂环境下动态生长猪只的视频分割。 展开更多
关键词 半监督 视频分割 猪只 simam注意力
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Remaining Life Prediction Method for Photovoltaic Modules Based on Two-Stage Wiener Process 被引量:1
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作者 Jie Lin Hongchi Shen +1 位作者 Tingting Pei Yan Wu 《Energy Engineering》 EI 2025年第1期331-347,共17页
Photovoltaic (PV) modules, as essential components of solar power generation systems, significantly influence unitpower generation costs.The service life of these modules directly affects these costs. Over time, the p... Photovoltaic (PV) modules, as essential components of solar power generation systems, significantly influence unitpower generation costs.The service life of these modules directly affects these costs. Over time, the performanceof PV modules gradually declines due to internal degradation and external environmental factors.This cumulativedegradation impacts the overall reliability of photovoltaic power generation. This study addresses the complexdegradation process of PV modules by developing a two-stage Wiener process model. This approach accountsfor the distinct phases of degradation resulting from module aging and environmental influences. A powerdegradation model based on the two-stage Wiener process is constructed to describe individual differences inmodule degradation processes. To estimate the model parameters, a combination of the Expectation-Maximization(EM) algorithm and the Bayesian method is employed. Furthermore, the Schwarz Information Criterion (SIC) isutilized to identify critical change points in PV module degradation trajectories. To validate the universality andeffectiveness of the proposed method, a comparative analysis is conducted against other established life predictiontechniques for PV modules. 展开更多
关键词 Photovoltaic modules DEGRADATION stochastic processes lifetime prediction
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基于SimAM-ResNet18的苹果病害叶片分类研究
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作者 吴文俊 陶俊 +2 位作者 隗一凡 侯顺智 袁冬华 《江汉大学学报(自然科学版)》 2025年第3期77-85,共9页
苹果病害叶片分类识别对于苹果种植业的病害监测和防治具有重要意义。针对苹果病害叶片分类识别的问题,提出了一种基于SimAM注意力机制的ResNet模型。该模型通过迁移学习和数据增强操作,结合SimAM注意力模块、Swish激活函数和熵权-Focal... 苹果病害叶片分类识别对于苹果种植业的病害监测和防治具有重要意义。针对苹果病害叶片分类识别的问题,提出了一种基于SimAM注意力机制的ResNet模型。该模型通过迁移学习和数据增强操作,结合SimAM注意力模块、Swish激活函数和熵权-FocalLoss损失函数,提高了对样本分布不均的苹果病害叶片的准确识别能力。实验结果显示,改进后的SimAM-ResNet18模型在测试集上实现了94.68%的准确率,相较于基准网络ResNet18提高了2.89%。与其他经典的卷积分类模型AlexNet、VGG16和GoogLeNet相比,该模型的准确率提高了7.02%、5.25%和4.31%。研究结果表明,基于SimAM注意力机制的ResNet模型在样本分布不均的苹果病害叶片分类识别上具有较高的潜力。 展开更多
关键词 苹果病害叶片 图像分类 迁移学习 simam注意力机制 ResNet18
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A review of encapsulation methods and geometric improvements of perovskite solar cells and modules for mass production and commercialization 被引量:1
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作者 Wending Yang Yubo Zhang +2 位作者 Chengchao Xiao Jingxuan Yang Tailong Shi 《Nano Materials Science》 2025年第6期790-809,共20页
Owing to the outstanding optoelectronic properties of perovskite materials,perovskite solar cells(PSCs)have been widely studied by academic organizations and industry corporations,with great potential to become the ne... Owing to the outstanding optoelectronic properties of perovskite materials,perovskite solar cells(PSCs)have been widely studied by academic organizations and industry corporations,with great potential to become the next-generation commercial solar cells.However,critical challenges remain in preserving high efficiency practical large-scale commercialized PSCs:a)the long-term stability of the cell materials and devices,b)lead leakage,and c)methods to scale the cells for larger area applications.This paper summarizes the prior-art strategies to address the above challenges,including the latest studies on the traditional glass-glass and thin-film encapsulation methods to better improve the reliability of PSCs,new technologies for preventing lead leakage,and geometric improvement strategies to enhance the reliability,efficiency,and performance of perovskite solar modules(PSMs).Through these strategies,the device achieved enhanced performance in long-term stability tests.The encapsulation resulted in a high lead leakage inhibition rate of up to 99%,and the PSMs possessed a geometric fill factor of 99.6%and a power conversion efficiency(PCE)of 20.7%.The dramatic improvement of efficiency and reliability of perovskite solar cells and modules indicate the great potential for mass production and commer-cialization of perovskite solar applications in the near future. 展开更多
关键词 Perovskite solar modules ENCAPSULATION Geometric improvement Stability COMMERCIALIZATION
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基于LKA和SimAM的可变形卷积用于高光谱图像分类
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作者 陈祥 张书真 严麒 《电子制作》 2025年第21期36-40,共5页
卷积神经网络(CNN)因其优异的非线性特征提取能力被广泛应用于高光谱图像分类中。然而,它的卷积层存在局部感受野限制,无法有效处理全局信息和捕捉长距离依赖关系,且对平移不变性的依赖和固定采样位置的正则卷积核,会导致信息丢失和难... 卷积神经网络(CNN)因其优异的非线性特征提取能力被广泛应用于高光谱图像分类中。然而,它的卷积层存在局部感受野限制,无法有效处理全局信息和捕捉长距离依赖关系,且对平移不变性的依赖和固定采样位置的正则卷积核,会导致信息丢失和难以适应不同尺度和形状的地物。针对这一情况,本文提出了一种基于LKA和Sim AM的可变形卷积神经网络(LSDCN)用于高光谱图像分类。具体而言,首先对原始HSI进行主成分分析(PCA)降维。然后,使用基于注意力的卷积模块进行初始特征提取。该模块结合了LKA和Sim AM增强卷积,有效解决了可变形卷积在捕获全局信息和像素之间长距离依赖关系的限制,同时减少了关键信息的损失和网络中的特征稀释。最后,以可变形卷积解决正则卷积核带来的不足,使得卷积核采样形状更接近于真实的地物覆盖形状,提高了网络的灵活几何适应性和特征提取能力。在两个广泛使用的真实HSI数据集上的实验表明,LSDCN取得了比其他方法更好的分类性能。 展开更多
关键词 高光谱图像(HSI) 大内核注意力(LKA) simam 可变形卷积(D-Conv)
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融合轻量化YOLOv5与SimAM的电力设备红外图像检测算法
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作者 李文 翁天天 +1 位作者 包海斌 周轶喆 《国外电子测量技术》 2025年第5期63-68,共6页
提出一种融合轻量化YOLOv5与SimAM注意力机制的电力设备红外图像检测算法,旨在提高电力设备故障检测的精度和效率。首先,利用高分辨率红外相机采集电力设备的红外图像,构建包含具有问题的训练数据集。然后,采用轻量化YOLOv5模型进行训练... 提出一种融合轻量化YOLOv5与SimAM注意力机制的电力设备红外图像检测算法,旨在提高电力设备故障检测的精度和效率。首先,利用高分辨率红外相机采集电力设备的红外图像,构建包含具有问题的训练数据集。然后,采用轻量化YOLOv5模型进行训练,从而对图像进行检测。为进一步提升检测性能,引入了SimAM注意力机制改进ECA(Efficient Channel Attention)模块,增强了对小目标和异常发热区域的检测能力。实验结果表明:该算法在变压器数据集中表现出色,精确率和召回率分别达到97.1%和95.2%,显著优于其他算法。在实际应用中,该算法对电力设备红外图像故障检测的有效精度在96%以上。该算法提升了设备图像检测精度和效率,有助于保障电力设备的安全运行。 展开更多
关键词 红外图像检测 simam注意力机制 电力设备 轻量化YOLOv5 故障检测
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EL-DenseNet:Mushroom Recognition Based on Erasing Module Using DenseNet
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作者 WANG Yaojun ZHAO Weiting +1 位作者 BIE Yuhui JIA Lu 《农业机械学报》 北大核心 2025年第9期628-637,共10页
Target occlusion poses a significant challenge in computer vision,particularly in agricultural applications,where occlusion of crops can obscure key features and impair the model’s recognition performance.To address ... Target occlusion poses a significant challenge in computer vision,particularly in agricultural applications,where occlusion of crops can obscure key features and impair the model’s recognition performance.To address this challenge,a mushroom recognition method was proposed based on an erase module integrated into the EL-DenseNet model.EL-DenseNet,an extension of DenseNet,incorporated an erase attention module designed to enhance sensitivity to visible features.The erase module helped eliminate complex backgrounds and irrelevant information,allowing the mushroom body to be preserved and increasing recognition accuracy in cluttered environments.Considering the difficulty in distinguishing similar mushroom species,label smoothing regularization was employed to mitigate mislabeling errors that commonly arose from human observers.This strategy converted hard labels into soft labels during training,reducing the model’s overreliance on noisy labels and improving its generalization ability.Experimental results showed that the proposed EL-DenseNet,when combined with transfer learning,achieved a recognition accuracy of 96.7%for mushrooms in occluded and complex backgrounds.Compared with the original DenseNet and other classic models,this approach demonstrated superior accuracy and robustness,providing a promising solution for intelligent mushroom recognition. 展开更多
关键词 mushroom recognition erase module label smoothing DenseNet
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Hydrophobic surface release and energy-level alignment of PTAA enables stable flexible perovskite solar modules
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作者 Hua Zhong Jianxing Xia +2 位作者 Hao Tian Chuanxiao Xiao Fei Zhang 《Journal of Energy Chemistry》 2025年第10期448-454,共7页
The fabrication of efficient and stable flexible perovskite solar modules(F-PSMs)using poly[bis(4-phenyl)(2,4,6-trimethylphenyl)amine](PTAA)remains a significant challenge due to its hydrophobic properties and the mis... The fabrication of efficient and stable flexible perovskite solar modules(F-PSMs)using poly[bis(4-phenyl)(2,4,6-trimethylphenyl)amine](PTAA)remains a significant challenge due to its hydrophobic properties and the mismatch in interface energy-level alignment.Here,we introduced[2-(3,6-dimethoxy-9H-carba zol-9-yl)ethyl]phosphonic acid(MeO-2PACz)to modify the PTAA layer,which effectively suppressed surface potential fluctuations and aligned energy levels at the interface of PTAA/perovskite.Additionally,MeO-2PACz enhanced the hydrophilicity of PTAA,facilitating the fabrication of dense,uniform,and pinhole-free perovskite films on large-area flexible substrates.As a result,we achieved an F-PSM with a power conversion efficiency(PCE)of 16.6% and an aperture area of 64 cm^(2),which is the highest reported value among F-PSMs with an active area exceeding 35 cm^(2)based on PTAA.Moreover,the encapsulated module demonstrated outstanding long-term operational stability,retaining 90.2% of its initial efficiency after 1000 bending cycles(5 mm radius),87.2% after 1000 h of continuous illumination,and 80.3% under combined thermal and humid conditions(85℃ and 85% relative humidity),representing one of the most stable F-PSMs reported to date. 展开更多
关键词 FLEXIBLE Perovskite solar modules STABILITY
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Two-tailed modification module tuned steric-hindrance effect enabling high therapeutic efficacy of paclitaxel prodrug nanoassemblies
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作者 Wenfeng Zang Yixin Sun +9 位作者 Jingyi Zhang Yanzhong Hao Qianhui Jin Hongying Xiao Zuo Zhang Xianbao Shi Jin Sun Zhonggui He Cong Luo Bingjun Sun 《Chinese Chemical Letters》 2025年第5期453-459,共7页
Self-assembled prodrug nanomedicine has emerged as an advanced platform for antitumor therapy,mainly comprise drug modules,response modules and modification modules.However,existing studies usually compare the differe... Self-assembled prodrug nanomedicine has emerged as an advanced platform for antitumor therapy,mainly comprise drug modules,response modules and modification modules.However,existing studies usually compare the differences between single types of modification modules,neglecting the impact of steric-hindrance effect caused by chemical structure.Herein,single-tailed modification module with low-steric-hindrance effect and two-tailed modification module with high-steric-hindrance effect were selected to construct paclitaxel prodrugs(P-LA_(C18)and P-BAC18),and the in-depth insights of the sterichindrance effect on prodrug nanoassemblies were explored.Notably,the size stability of the two-tailed prodrugs was enhanced due to improved intermolecular interactions and steric hindrance.Single-tailed prodrug nanoassemblies were more susceptible to attack by redox agents,showing faster drug release and stronger antitumor efficacy,but with poorer safety.In contrast,two-tailed prodrug nanoassemblies exhibited significant advantages in terms of pharmacokinetics,tumor accumulation and safety due to the good size stability,thus ensuring equivalent antitumor efficacy at tolerance dose.These findings highlighted the critical role of steric-hindrance effect of the modification module in regulating the structureactivity relationship of prodrug nanoassemblies and proposed new perspectives into the precise design of self-assembled prodrugs for high-performance cancer therapeutics. 展开更多
关键词 Prodrug nanoassemblies Two-tailed modification module Steric-hindrance PACLITAXEL Anticancer
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Simple Yetter-Drinfeld Modules over a Non-Pointed Hopf Algebra
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作者 Ruifang YANG Shilin YANG 《Journal of Mathematical Research with Applications》 2025年第6期716-734,共19页
Let D(n)be the finite dimensional non-pointed and non-semisimple Hopf algebra,which is a quotient of a prime Hopf algebras of GK-dimension one for an odd number n>1.In this paper,we investigate the structure of Yet... Let D(n)be the finite dimensional non-pointed and non-semisimple Hopf algebra,which is a quotient of a prime Hopf algebras of GK-dimension one for an odd number n>1.In this paper,we investigate the structure of Yetter-Drinfeld simple modules over D(n)and give iso-classes of them. 展开更多
关键词 Hopf algebra Yetter-Drinfeld module Nichols algebra
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Wood-derived catalysts for green and stable Fenton-like chemistry:From basic mechanisms to catalytic modules and future inspiration
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作者 Xiaoyun Lei Hanghang Zhao +2 位作者 Chao Bai Longlong Geng Xing Xu 《Chinese Chemical Letters》 2025年第10期212-225,共14页
Most carbon-based catalysts utilized in Fenton-like systems face challenges such as structural instability,susceptibility to deactivation,and a tendency to disperse during operation.Wood-derived catalysts have garnere... Most carbon-based catalysts utilized in Fenton-like systems face challenges such as structural instability,susceptibility to deactivation,and a tendency to disperse during operation.Wood-derived catalysts have garnered considerable attention due to their well-defined structures,extensive pipeline networks,superior mechanical strength,and adaptability for device customization.However,there remains a paucity of research that systematically summarizes Fenton-like systems based on wood-derived catalysts.In this review,we first summarize the structural designs of wood-derived catalysts based on nano-metal sites and single-atom sites,while also outlining their advantages and limitations applied in Fenton-like systems.Furthermore,we evaluate catalytic modules of wood-derived catalysts for scale-up and continuous Fenton-like systems.Additionally,wood-inspired catalytic materials utilizing commercial textures and their applications in Fenton-like processes are also discussed.This paper aims to comprehensively explore the fundamental mechanisms(e.g.,characteristics of catalytic sites,catalytic performance,and mechanisms)of wood-based catalysts in Fenton-like chemistry,as well as their equipment designs and application scenarios,as well as providing the insights into future developments. 展开更多
关键词 Wood-derive catalysts Nano-metal Fenton-like chemistry Scale-up application Catalytic modules
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A Two-Stage Wiener Degradation Model-Based Approach for Visual Maintenance of Photovoltaic Modules
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作者 Jie Lin Hongchi Shen +1 位作者 Tingting Pei Yan Wu 《Energy Engineering》 2025年第6期2449-2463,共15页
This study proposes a novel visual maintenance method for photovoltaic(PV)modules based on a two-stage Wiener degradation model,addressing the limitations of traditional PV maintenance strategies that often result in ... This study proposes a novel visual maintenance method for photovoltaic(PV)modules based on a two-stage Wiener degradation model,addressing the limitations of traditional PV maintenance strategies that often result in insufficient or excessive maintenance.The approach begins by constructing a two-stage Wiener process performance degradation model and a remaining life prediction model under perfect maintenance conditions using historical degradation data of PV modules.This enables accurate determination of the optimal timing for postfailure corrective maintenance.To optimize the maintenance strategy,the study establishes a comprehensive cost model aimed at minimizing the long-term average cost rate.The model considers multiple cost factors,including inspection costs,preventive maintenance costs,restorative maintenance costs,and penalty costs associated with delayed fault detection.Through this optimization framework,the method determines both the optimal maintenance threshold and the ideal timing for predictive maintenance actions.Comparative analysis demonstrates that the twostage Wiener model provides superior fitting performance compared to conventional linear and nonlinear degradation models.When evaluated against traditional maintenance approaches,including Wiener process-based corrective maintenance strategies and static periodic maintenance strategies,the proposed method demonstrates significant advantages in reducing overall operational costs while extending the effective service life of PV components.The method achieves these improvements through effective coordination between reliability optimization and economic benefit maximization,leading to enhanced power generation performance.These results indicate that the proposed approach offers a more balanced and efficient solution for PV system maintenance. 展开更多
关键词 Photovoltaic module remaining life maintenance strategy Wiener modeling
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Modified Near‑Infrared Annealing Enabled Rapid and Homogeneous Crystallization of Perovskite Films for Efficient Solar Modules
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作者 Qing Chang Peng He +10 位作者 Haosong Huang Yingchen Peng Xiao Han Yang Shen Jun Yin Zhengjing Zhao Ye Yang Binghui Wu Zhiguo Zhao Jing Li Nanfeng Zheng 《Nano-Micro Letters》 2025年第11期236-250,共15页
Currently,perovskite solar cells have achieved commendable progresses in power conversion efficiency(PCE)and operational stability.However,some conventional laboratory-scale fabrication methods become challenging when... Currently,perovskite solar cells have achieved commendable progresses in power conversion efficiency(PCE)and operational stability.However,some conventional laboratory-scale fabrication methods become challenging when scaling up material syntheses or device production.Particularly,the prolonged high-temperature annealing process for the crystallization of perovskites requires a substantial amount of energy consumption and impact the modules’throughput.Here,we report a modified near-infrared annealing(NIRA)process,which involves the excess PbI_(2)engineered crystallization,efficiently reduces the preparation time for perovskite active layer to within 20 s compared to dozens of min in conventional hot plate annealing(HPA)process.The study showed that the incorporated PbI_(2)promoted the consistent nucleation of the perovskite film,leading to the subsequent rapid and homogeneous crystallization at the NIRA stage.Thus,highly crystalized perovskite film was realized with even better crystallization performance than conventional HPA-based film.Ultimately,efficient perovskite solar modules of 36 and 100 cm^(2)were readily fabricated with the optimal PCEs of 22.03%and 20.18%,respectively.This study demonstrates,for the first time,the successful achievement of homogeneous and high-quality crystallization in large-area perovskite films through rapid NIRA processing.This approach not only significantly reduces energy consumption during production,but also substantially shortens the manufacturing cycle,paving a new path toward the commercial-scale application of perovskite solar modules. 展开更多
关键词 Near-infrared annealing Homogeneous crystallization Blade coating Perovskite solar modules
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