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Malicious Document Detection Based on GGE Visualization

Computers, Materials & Continua 2025年第1期82卷 1233-1254页

作者： Youhe Wang yi sun Yujie Li Chuanqi Zhou Henan Province Key Laboratory of Information Security Information Engineering UniversityZhengzhou450000China

With the development of anti-virus technology,malicious documents have gradually become the main pathway of Advanced Persistent Threat(APT)attacks,therefore,the development of effective malicious document classifiers has become particularly ***,detection methods based on document structure and behavioral features encounter challenges in feature engineering,these methods not only have limited accuracy,but also consume large resources,and usually can only detect documents in specific formats,which lacks versatility and *** address such problems,this paper proposes a novel malicious document detection method-visualizing documents as GGE images(Grayscale,Grayscale matrix,Entropy).The GGE method visualizes the original byte sequence of the malicious document as a grayscale image,the information entropy sequence of the document as an entropy image,and at the same time,the grayscale level co-occurrence matrix and the texture and spatial information stored in it are converted into grayscale matrix image,and fuses the three types of images to get the GGE color *** Convolutional Block Attention Module-EfficientNet-B0(CBAM-EfficientNet-B0)model is then used for classification,combining transfer learning and applying the pre-trained model on the ImageNet dataset to the feature extraction process of GGE *** shown in the experimental results,the GGE method has superior performance compared with other methods,which is suitable for detecting malicious documents in different formats,and achieves an accuracy of 99.44%and 97.39%on Portable Document Format(PDF)and office datasets,respectively,and consumes less time during the detection process,which can be effectively applied to the task of detecting malicious documents in real-time.

关键词： Malicious document visualization EfficientNet-B0 convolutional block attention module GGE image

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Exosomes:the next-generation therapeutic platform for ischemic stroke

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Neural Regeneration Research 2025年第5期20卷 1221-1235页

作者： Wenjing yin Hongyin Ma Yang Qu Jiaxin Ren yingying sun Zhen-Ni Guo yi Yang Stroke Center Department of NeurologyFirst Hospital of Jilin UniversityChangchunJilin ProvinceChina Neuroscience Research Center Department of NeurologyFirst Hospital of Jilin UniversityChangchunJilin ProvinceChina

Current therapeutic strategies for ischemic stroke fall short of the desired objective of neurological functional ***,there is an urgent need to develop new methods for the treatment of this *** are natural cell-derived vesicles that mediate signal transduction between cells under physiological and pathological *** have low immunogenicity,good stability,high delivery efficiency,and the ability to cross the blood–brain *** physiological properties of exosomes have the potential to lead to new breakthroughs in the treatment of ischemic *** rapid development of nanotechnology has advanced the application of engineered exosomes,which can effectively improve targeting ability,enhance therapeutic efficacy,and minimize the dosages *** in technology have also driven clinical translational research on *** this review,we describe the therapeutic effects of exosomes and their positive roles in current treatment strategies for ischemic stroke,including their antiinflammation,anti-apoptosis,autophagy-regulation,angiogenesis,neurogenesis,and glial scar formation reduction ***,it is worth noting that,despite their significant therapeutic potential,there remains a dearth of standardized characterization methods and efficient isolation techniques capable of producing highly purified *** optimization strategies should prioritize the exploration of suitable isolation techniques and the establishment of unified workflows to effectively harness exosomes for diagnostic or therapeutic applications in ischemic ***,our review aims to summarize our understanding of exosome-based treatment prospects in ischemic stroke and foster innovative ideas for the development of exosome-based therapies.

关键词： blood–brain barrier electroacupuncture engineering exercise exosomes ischemic stroke mesenchymal stem cells microglia neuroprotection stents

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Application of the improved dung beetle optimizer,muti-head attention and hybrid deep learning algorithms to groundwater depth prediction in the Ningxia area,China

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Atmospheric and Oceanic Science Letters 2025年第1期18卷 18-23页

作者： Jiarui Cai Bo sun Huijun Wang yi Zheng Siyu Zhou Huixin Li Yanyan Huang Peishu Zong Collaborative Innovation Center on forecast and Evaluation of Meteorological Disasters/Key Laboratory of Meteorological Disaster Ministry of Education/Joint International Research Laboratory of Climate and Environment ChangeNanjing University of Information Science and TechnologyNanjingChina Southern Marine Science and Engineering Guangdong Laboratory(Zhuhai) ZhuhaiChina China Meteorological Administration Key Laboratory of Transportation MeteorologyNanjingChina Jiangsu Meteorological Observatory NanjingChina

Due to the lack of accurate data and complex parameterization,the prediction of groundwater depth is a chal-lenge for numerical *** learning can effectively solve this issue and has been proven useful in the prediction of groundwater depth in many *** this study,two new models are applied to the prediction of groundwater depth in the Ningxia area,*** two models combine the improved dung beetle optimizer(DBO)algorithm with two deep learning models:The Multi-head Attention-Convolution Neural Network-Long Short Term Memory networks(MH-CNN-LSTM)and the Multi-head Attention-Convolution Neural Network-Gated Recurrent Unit(MH-CNN-GRU).The models with DBO show better prediction performance,with larger R(correlation coefficient),RPD(residual prediction deviation),and lower RMSE(root-mean-square error).Com-pared with the models with the original DBO,the R and RPD of models with the improved DBO increase by over 1.5%,and the RMSE decreases by over 1.8%,indicating better prediction *** addition,compared with the multiple linear regression model,a traditional statistical model,deep learning models have better prediction performance.

关键词： Groundwater depth Multi-head attention Improved dung beetle optimizer CNN-LSTM CNN-GRU Ningxia

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Low‑Temperature Fabrication of Stable Black‑Phase CsPbI_(3)Perovskite Flexible Photodetectors Toward Wearable Health Monitoring

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Nano-Micro Letters 2025年第3期17卷 232-245页

作者： yingjie Zhao yi.heng sun Chaoxin Pei Xing yin Xinyi Li yi Hao Mengru Zhang Meng Yuan Jinglin Zhou Yu Chen Yanlin Song College of Chemistry and Pingyuan Laboratory Zhengzhou UniversityZhengzhou 450001People’s Republic of China Key Laboratory of Green Printing Institute of ChemistryChinese Academy of SciencesBeijing 100190People’s Republic of China Key Laboratory of Bio‑Inspired Materials and Interfacial Science Technical Institute of Physics and ChemistryChinese Academy of SciencesBeijing 100190People’s Republic of China Institute of High Energy Physics Chinese Academy of SciencesBeijing 100049People’s Republic of China

Flexible wearable optoelectronic devices fabricated fromorganic–inorganic hybrid perovskites significantly accelerate the developmentof portable energy,biomedicine,and sensing fields,but their poor thermal stabilityhinders further ***,all-inorganic perovskites possessexcellent thermal stability,but black-phase all-inorganic perovskite filmusually requires high-temperature annealing steps,which increases energy consumptionand is not conducive to the fabrication of flexible wearable *** this work,an unprecedented low-temperature fabrication of stable blackphaseCsPbI3perovskite films is demonstrated by the in situ hydrolysis reactionof diphenylphosphinic chloride *** released diphenyl phosphateand chloride ions during the hydrolysis reaction significantly lower the phasetransition temperature and effectively passivate the defects in the perovskitefilms,yielding high-performance photodetectors with a responsivity of 42.1 AW−1 and a detectivity of 1.3×10^(14)***,high-fidelity imageand photoplethysmography sensors are demonstrated based on the fabricated flexible wearable *** work provides a newperspective for the low-temperature fabrication of large-area all-inorganic perovskite flexible optoelectronic devices.

关键词： In situ hydrolyzation Low-temperature processing All-inorganic perovskite Flexible photodetectors Health monitoring

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2D free-standing ultra-large ferromagnetic nanosheets via a topotactic transformation strategy

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Science China Chemistry 2025年

作者： Haofeng sun Minghao Wang Wenjie Li Yang Liu Xinyu sun Wenjie Wang Yuqiao Guo yi Xie Changzheng Wu Key Laboratory of Precision and Intelligent Chemistry University of Science&Technology of China National Synchrotron Radiation Laboratory University of Science and Technology of China

Considerable progress has been made in synthesizing two-dimensional （2D） materials by exfoliating layered ***,for tremendous non-layered inorganic materials,especially magnet solids,usually with closely packed bulk phases by strong chemical bonds,it is challenging to obtain their high-quality 2D ***,we highlighted a new structure of free-standing ferromagnetic nanosheets featuring （111） *** magnet,Fe3O4,its inversed spinel crystalline has limited abilities to exfoliate into 2D forms and rarely exists as free-standing nanosheets owing to aggregation induced by magnetic *** realized a breakthrough in achieving free-standing ferromagnetic nanosheets with dramatically surpassing size limitations via topotactic conversion from layered *** Fe3O4nanosheets exhibited a maximum width of 60μm while only～4 nm thick,prominently exposing （111） facets.2D Fe3O4behaved anisotropic magnetism,which displayed a 4.6 emu g-1moment（H=500 Oe） in the （111） plane but 2.1 emu g-1out of the （111） plane,indicating a （111） in-plane easy *** anticipated our topotactic conversion strategy would inspire the creation of 2D non-layered materials and enrich the 2D materials family.

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Nanoimprint lithography-assisted block copolymer self-assembly for hyperfine fabrication of magnetic patterns based on L10-FePt nanoparticles

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Science China Chemistry 2025年

作者： Jie Zhang yi Chen Guijun Li Zelin sun Zhengong Meng Wai-Yeung Wong Department of Applied Biology and Chemical Technology and Research Institute for Smart Energy The Hong Kong Polytechnic University The Hong Kong Polytechnic University Shenzhen Research Institute Division of Integrative Systems and Design and Department of Electronic and Computer Engineering The Hong Kong University of Science and Technology School of Flexible Electronics (Future Technology) and Institute of Advanced Materials (IAM) Nanjing Tech University

L10-FePt-type bit-patterned media has provided a promising alternative for ultrahigh-density magnetic recording systems in the current digital era, but rapid fabrication of magnetic patterns with hyperfine bit islands is still challenging, especially with the target for miniaturization and scalable production simultaneously. Herein, Fe,Pt-containing block copolymers were utilized as single-source precursors for solution-processable patterning and subsequent generation of the demanding magnetic FePt dots by in situ pyrolysis. High-throughput nanoimprint lithography was initially employed to fabricate the predefined bit cells precisely,and then the intrinsic self-assembly of phase-separated block copolymers further drove the formation of accurate bit *** from the synergistic effect of top-down lithographic approach and bottom-up self-assembly, the customizable patterns could be achieved for large-scale mass production in targeted areas, but high-density isolated dots could also be accurately aligned along the patterned features after subsequent self-assembly. This reliable strategy would provide a good avenue to precisely construct ultrahigh-density magnetic data storage devices.

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Inter‑Skeleton Conductive Routes Tuning Multifunctional Conductive Foam for Electromagnetic Interference Shielding,Sensing and Thermal Management

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Nano-Micro Letters 2025年第3期17卷 19-36页

作者： Xufeng Li Chunyan Chen Zhenyang Li Peng yi Haihan Zou Gao Deng Ming Fang Junzhe He Xin sun Ronghai Yu Jianglan Shui Caofeng Pan Xiaofang Liu School of Materials Science and Engineering Beihang UniversityBeijing 100191People’s Republic of China Institute of Atomic Manufacturing Beihang UniversityBeijing 100191People’s Republic of China Tianmushan Laboratory Xixi Octagon CityYuhang DistrictHangzhou 310023People’s Republic of China Science and Technology On Electromagnetic Scattering Laboratory Beijing Institute of Environmental FeaturesBeijing 100854People’s Republic of China

Conductive polymer foam(CPF)with excellent compressibility and variable resistance has promising applications in electromagnetic interference(EMI)shielding and other integrated functions for wearable ***,its insufficient change amplitude of resistance with compressive strain generally leads to a degradation of shielding performance during ***,an innovative loading strategy of conductive materials on polymer foam is proposed to significantly increase the contact probability and contact area of conductive components under *** inter-skeleton conductive films are constructed by loading alginate-decorated magnetic liquid metal on the polymethacrylate films hanged between the foam skeleton(denoted as AMLM-PM foam).Traditional point contact between conductive skeletons under compression is upgraded to planar contact between conductive ***,the resistance change of AMLM-PM reaches four orders of magnitude under ***,the inter-skeleton conductive films can improve the mechanical strength of foam,prevent the leakage of liquid metal and increase the scattering area of EM ***-PM foam has strain-adaptive EMI shielding performance and shows compression-enhanced shielding effectiveness,solving the problem of traditional CPFs upon *** upgrade of resistance response also enables foam to achieve sensitive pressure sensing over a wide pressure range and compression-regulated Joule heating function.

关键词： Inter-skeleton conductive films Conductive polymer foam Liquid metal Electromagnetic interference shielding

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Joint Feature Encoding and Task Alignment Mechanism for Emotion-Cause Pair Extraction

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Computers, Materials & Continua 2025年第1期82卷 1069-1086页

作者： Shi Li Didi sun College of Computer and Control Engineering Northeast Forestry UniversityHarbin150040China

With the rapid expansion of social media,analyzing emotions and their causes in texts has gained significant ***-cause pair extraction enables the identification of causal relationships between emotions and their triggers within a text,facilitating a deeper understanding of expressed sentiments and their underlying *** comprehension is crucial for making informed strategic decisions in various business and societal ***,recent research approaches employing multi-task learning frameworks for modeling often face challenges such as the inability to simultaneouslymodel extracted features and their interactions,or inconsistencies in label prediction between emotion-cause pair extraction and independent assistant tasks like emotion and cause *** address these issues,this study proposes an emotion-cause pair extraction methodology that incorporates joint feature encoding and task alignment *** model consists of two primary components:First,joint feature encoding simultaneously generates features for emotion-cause pairs and clauses,enhancing feature interactions between emotion clauses,cause clauses,and emotion-cause ***,the task alignment technique is applied to reduce the labeling distance between emotion-cause pair extraction and the two assistant tasks,capturing deep semantic information interactions among *** proposed method is evaluated on a Chinese benchmark corpus using 10-fold cross-validation,assessing key performance metrics such as precision,recall,and F1 *** results demonstrate that the model achieves an F1 score of 76.05%,surpassing the state-of-the-art by 1.03%.The proposed model exhibits significant improvements in emotion-cause pair extraction(ECPE)and cause extraction(CE)compared to existing methods,validating its *** research introduces a novel approach based on joint feature encoding and task alignment mechanisms,contributing to advancements in emotion-c

关键词： Emotion-cause pair extraction interactive information enhancement joint feature encoding label consistency task alignment mechanisms

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Microstructure and Wear/corrosion Resistance of Stainless Steel Laser-alloyed with Mn+W_(2)C, Mn+NiWC and Mn+SiC

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Journal of Wuhan University of Technology(Materials Science) 2025年第1期40卷 283-294页

作者： ZHOU Rui DIAO Xiaogang sun yixin School of Metallurgical Engineering Jiangsu University of Science and TechnologyZhangjiagang 215600China CITIC Heavy Cast Iron Industry Co. Ltd.Luoyang 417039China

In-situ formed high Mn steel coating reinforced by carbides was formed by laser surface alloying(LSA).Laser alloyed layers on 1Cr18Ni9Ti steel with Mn+W_(2)C(specimen A),Mn+NiWC(specimen B)and Mn+SiC(specimen C)powders were fabricated to improve the wear and corrosion behavior of 1Cr18Ni9Ti steel blades in high speed *** evolution,phases,element distribution,microhardness,wear and corrosion behavior of the laser alloyed layers were *** indicated that high Mn steel matrix composites with undissolved W_(2)C,WC and other in-situ formed carbides were formed by LSA with Mn+W_(2)C and Mn+NiWC while SiC totally dissolved into the high Mn matrix when adding Mn+*** as the binding phase in Ni-WC powder decreased the crack sensitivity of the alloyed layer as compared with the addition of W_(2)C *** improvement in average microhardness was achieved in the matrix in specimen A,B and C,with the value of 615,602 and 277 HV_(0.5),while that of the substrate was 212 HV_(0.5).The increase of microhardness,wear and corrosion resistance is highly corelated to microstructure,formed phases,type and content of carbides,micro-hardness and toughness of the alloyed layers.

关键词： laser surface alloying stainless steel carbide type microstructure wear and corrosion resistance

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Traffic safety helmet wear detection based on improved YOLOv5 network

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Optoelectronics Letters 2025年第1期21卷 35-42页

作者： GUI Dongdong sun Bo College of Software Southeast University Quanzhou Equipment Research Centre Haixi Institute Chinese Academy of Sciences

Aiming at the problem that the current traffic safety helmet detection model can't balance the accuracy of detection with the size of the model and the poor generalization of the model, a method based on improving you only look once version 5(YOLOv5) is proposed. By incorporating the lightweight Ghost Net module into the YOLOv5 backbone network, we effectively reduce the model size. The addition of the receptive fields block(RFB) module enhances feature extraction and improves the feature acquisition capability of the lightweight model. Subsequently, the high-performance lightweight convolution, GSConv, is integrated into the neck structure for further model size compression. Moreover, the baseline model's loss function is substituted with efficient insertion over union(EIoU), accelerating network convergence and enhancing detection precision. Experimental results corroborate the effectiveness of this improved algorithm in real-world traffic scenarios.

关键词： Traffic control

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