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Enhancing Deepfake Detection:Proactive Forensics Techniques Using Digital Watermarking

Computers, Materials & Continua 2025年第1期82卷 73-102页

作者： Zhimao Lai Saad Arif Cong Feng Guangjun Liao Chuntao wang School of Automation Guangdong University and TechnologyGuangzhou510006China School of Immigration Administration(Guangzhou) China People’s Police UniversityGuangzhou510663China Department of Mechanical Engineering College of EngineeringKing Faisal UniversityAl Ahsa31982Saudi Arabia Cyber Police Division Guangzhou Public Security BureauGuangzhou510030China School of Forensic Science and Technology Guangdong Police CollegeGuangzhou510320China College of Mathematics and Informatics South China Agricultural UniversityGuangzhou510642China

With the rapid advancement of visual generative models such as Generative Adversarial Networks(GANs)and stable Diffusion,the creation of highly realistic Deepfake through automated forgery has significantly *** paper examines the advancements inDeepfake detection and defense technologies,emphasizing the shift from passive detection methods to proactive digital watermarking *** detection methods,which involve extracting features from images or videos to identify forgeries,encounter challenges such as poor performance against unknown manipulation techniques and susceptibility to counter-forensic *** contrast,proactive digital watermarking techniques embed specificmarkers into images or videos,facilitating real-time detection and traceability,thereby providing a preemptive defense againstDeepfake *** offer a comprehensive analysis of digitalwatermarking-based forensic techniques,discussing their advantages over passivemethods and highlighting four key benefits:real-time detection,embedded defense,resistance to tampering,and provision of legal ***,the paper identifies gaps in the literature concerning proactive forensic techniques and suggests future research directions,including cross-domain watermarking and adaptive watermarking *** systematically classifying and comparing existing techniques,this review aims to contribute valuable insights for the development of more effective proactive defense strategies in Deepfake forensics.

关键词： Deepfake proactive forensics digital watermarking traceability detection techniques

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The detection, extraction and parameter estimation of extreme-mass-ratio inspirals with deep learning

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Science China(Physics,Mechanics & Astronomy) 2025年第1期Mechanics & Astronomy) .卷 86-96页

作者： Qianyun Yun Wen-Biao Han Yi-Yang Guo He wang Minghui Du Hangzhou Institute for Advanced Study University of Chinese Academy of Sciences Shanghai Astronomical Observatory Chinese Academy of Sciences School of Physics and Astronomy Shanghai Jiao Tong University School of Astronomy and Space Science University of Chinese Academy of Sciences Taiji Laboratory for Gravitational Wave Universe (Beijing/Hangzhou) University of Chinese Academy of Sciences Lanzhou Center for Theoretical Physics Key Laboratory of Theoretical Physics of Gansu Province Key Laboratory of Quantum Theory and Applications of MoE Lanzhou University Institute of Theoretical Physics & Research Center of Gravitation Lanzhou University International Centre for Theoretical Physics Asia-Pacific (ICTP-AP) University of Chinese Academy of Sciences (UCAS) Center for Gravitational Wave Experiment National Microgravity Laboratory Institute of Mechanics Chinese Academy of Sciences

One of the primary goals of space-borne gravitational wave detectors is to detect and analyze extreme-mass-ratio inspirals(EMRIs). This task is particularly challenging because EMRI signals are complex, lengthy, and faint. In this work, we introduce a2-layer convolutional neural network(CNN) approach to detect EMRI signals for space-borne detectors, achieving a true positive rate(TPR) of 96.9% at a 1% false positive rate(FPR) for signal-to-noise ratio(SNR) from 50 to 100. Especially, the key intrinsic parameters of EMRIs such as the mass, spin of the supermassive black hole(SMBH) and the initial eccentricity of the orbit can also be inferred directly by employing a neural network. The mass and spin of the SMBH can be determined at 99% and 92% respectively. This will greatly reduce the parameter spaces and computing cost for the following Bayesian parameter *** model also has a low dependency on the accuracy of the waveform model. This study underscores the potential of deep learning methods in EMRI data analysis, enabling the rapid detection of EMRI signals and efficient parameter estimation.

关键词： gravitational wave EMRIs deep-learing

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Enhanced post-combustion CO2 capture and direct air capture by plasma surface functionalization of graphene adsorbent

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Journal of Energy Chemistry 2025年第1期100卷 653-664页

作者： Rahul Navik Eryu wang Xiao Ding Huang Yunyi Yiyu Liu Jia Li Guangdong-Hong Kong Joint Laboratory for Carbon Neutrality Jiangmen Laboratory of Carbon and Science and Technology Guangzhou HKUST Fok Ying Tung Research Institute The Hong Kong University of Science and Technology (Guangzhou) Carbon Neutrality and Climate Change Thrust Society Hub The Hong Kong University of Science and Technology (Guangzhou) Stoddart Institute of Molecular Science Department of Chemistry Zhejiang University

Graphene has enormous potential to capture CO2due to its unique properties and ***,graphene-based adsorbents have drawbacks of lower CO2adsorption capacity and poor *** work demonstrates a one-step rapid and sustainable N2/H2plasma treatment process to prepare graphene-based sorbent material with enhanced CO2adsorption *** treatment directly enriches amine species,increases surface area,and improves textural *** CO2adsorption capacity increases from 1.6 to 3.3 mmol/g for capturing flue gas,and from 0.14 to 1.3 mmol/g for direct air capture （DAC）.Importantly,the electrothermal property of the plasma-modified aerogels has been significantly improved,resulting in faster heating rates and significantly reducing energy consumption compared to conventional external heating for regeneration of *** aerogels display improved selectivity of 42 and 87 after plasma modification for 5 and 10 min,*** plasma-treated aerogels display minimal loss between 17%and 19% in capacity after 40 adsorption/desorption cycles,rendering excellent *** N2/H2plasma treatment of adsorbent materials would lower energy expenses and prevent negative effects on the global economy caused by climate change.

关键词： Carbon neutrality CO 2 capture Climate change Plasma treatment Graphene aerogel

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The Internet of Things under Federated Learning:A Review of the Latest Advances and Applications

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Computers, Materials & Continua 2025年第1期82卷 1-39页

作者： Jinlong wang Zhenyu Liu Xingtao Yang Min Li Zhihan Lyu School of Information and Control Engineering Qingdao University of TechnologyQingdao260043China Anhui Province Key Laboratory of Intelligent Building&Building Energy Saving Anhui Jianzhu UniversityHefei230000China Department of Game Design Uppsala UniversityUppsala75310Sweden

With the rapid development of artificial intelligence,the Internet of Things(IoT)can deploy various machine learning algorithms for network and application *** the IoT environment,many sensors and devices generatemassive data,but data security and privacy protection have become a serious *** learning(FL)can achieve many intelligent IoT applications by training models on local devices and allowing AI training on distributed IoT devices without data *** review aims to deeply explore the combination of FL and the IoT,and analyze the application of federated learning in the IoT from the aspects of security and privacy *** this paper,we first describe the potential advantages of FL and the challenges faced by current IoT systems in the fields of network burden and privacy ***,we focus on exploring and analyzing the advantages of the combination of FL on the Internet,including privacy security,attack detection,efficient communication of the IoT,and enhanced learning *** also list various application scenarios of FL on the ***,we propose several open research challenges and possible solutions.

关键词： Federated learning Internet of Things sensors machine learning privacy security

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Occluded Gait Emotion Recognition Based on Multi-Scale Suppression Graph Convolutional Network

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Computers, Materials & Continua 2025年第1期82卷 1255-1276页

作者： Yuxiang Zou Ning He Jiwu Sun Xunrui Huang Wenhua wang Beijing Key Laboratory of Information Service Engineering Beijing Union UniversityBeijing100101China College of Smart City Beijing Union UniversityBeijing100101China

In recent years,gait-based emotion recognition has been widely applied in the field of computer ***,existing gait emotion recognition methods typically rely on complete human skeleton data,and their accuracy significantly declines when the data is *** enhance the accuracy of gait emotion recognition under occlusion,this paper proposes a Multi-scale Suppression Graph ConvolutionalNetwork(MS-GCN).TheMS-GCN consists of three main components:Joint Interpolation Module(JI Moudle),Multi-scale Temporal Convolution Network(MS-TCN),and Suppression Graph Convolutional Network(SGCN).The JI Module completes the spatially occluded skeletal joints using the(K-Nearest Neighbors)KNN interpolation *** MS-TCN employs convolutional kernels of various sizes to comprehensively capture the emotional information embedded in the gait,compensating for the temporal occlusion of gait *** SGCN extracts more non-prominent human gait features by suppressing the extraction of key body part features,thereby reducing the negative impact of occlusion on emotion recognition *** proposed method is evaluated on two comprehensive datasets:Emotion-Gait,containing 4227 real gaits from sources like BML,ICT-Pollick,and ELMD,and 1000 synthetic gaits generated using STEP-Gen technology,and ELMB,consisting of 3924 gaits,with 1835 labeled with emotions such as“Happy,”“Sad,”“Angry,”and“Neutral.”On the standard datasets Emotion-Gait and ELMB,the proposed method achieved accuracies of 0.900 and 0.896,respectively,attaining performance comparable to other ***,on occlusion datasets,the proposedmethod significantly mitigates the performance degradation caused by occlusion compared to other methods,the accuracy is significantly higher than that of other methods.

关键词： KNN interpolation multi-scale temporal convolution suppression graph convolutional network gait emotion recognition human skeleton

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Revealing and predicting the long-term biomechanical response of orthokeratology by developing a patient-specific computational model

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Science China(Physics,Mechanics & Astronomy) 2025年第1期Mechanics & Astronomy) .卷 156-168页

作者： Yifeng Li Zhuoran Yang Ziming Yan Huibin Shi Zhanli Liu Kaijie wang Department of Engineering Mechanics School of Aerospace Engineering Tsinghua University Beijing Tongren Eye Center Beijing Tongren Hospital Capital Medical University Beijing Ophthalmology & Visual Sciences Key Lab

Orthokeratology(OK) is widely used for effective myopia correction and control. However, the incomplete understanding of its biomechanical mechanisms makes OK lens fitting rely heavily on clinician judgment, complicating accurate predictions of treatment outcomes. In this paper, we performed clinical experiments and numerical analysis to study corneal deformation modes and long-term changes in central corneal thickness. Clinical experiments were conducted on 194 Chinese myopic patients under OK treatment for 3 months. Based on the experimental data, a patient-specific computational biomechanical model for OK was established and validated. Specifically, the anisotropic mechanical properties of the cornea were incorporated into the model to describe the significant difference between its shear modulus(29.5 kPa) and tensile modulus(768.4 kPa). Additionally, a viscohyperelastic material model with a prolonged corneal relaxation time of 5.6 h was developed to capture the long-term deformation response. The results show that corneal thickness reduction in OK is primarily due to out-of-plane shear deformation,influenced by the cornea's low shear resistance. Modeling the extended corneal relaxation time is crucial for predicting long-term biomechanical responses. The computational model effectively captures long-term changes in central corneal thickness, potentially improving OK lens fitting accuracy.

关键词： orthokeratology computational biomechanical model long-term viscoelasticity myopia correction

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Boosting bidirectional sulfur conversion enabled by introducing boron-doped atoms and phosphorus vacancies in Ni2P for lithium-sulfur batteries

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Journal of Energy Chemistry 2025年第1期100卷 760-769页

作者： Lin Peng Yu Bai Hang Li Meixiu Qu Zhenhua wang Kening Sun Advanced Research Institute of Multidisciplinary Science Beijing Institute of Technology Beijing Key Laboratory of Chemical Power Source and Green Catalysis School of Chemistry and Chemical Engineering Beijing Institute of Technology

Lithium-sulfur （Li-S） batteries have gained great attention due to the high theoretical energy density and low cost,yet their further commercialization has been obstructed by the notorious shuttle effect and sluggish redox ***,we supply a strategy to optimize the electron structure of Ni2P by concurrently introducing B-doped atoms and P vacancies in Ni2P （Vp-B-Ni2P）,thereby enhancing the bidirectional sulfur *** study indicates that the simultaneous introduction of B-doped atoms and P vacancies in Ni2P causes the redistribution of electron around Ni atoms,bringing about the upward shift of d-band center of Ni atoms and effective d-p orbital hybridization between Ni atoms and sulfur species,thus strengthening the chemical anchoring for lithium polysulfides （LiPSs） as well as expediting the bidirectional conversion kinetics of sulfur ***,theoretical calculations reveal that the incorporation of B-doped atoms and P vacancies in Ni2P selectively promotes Li2S dissolution and nucleation ***,the Li-S batteries with Vp-B-Ni2P-separators present outstanding rate ability of 777 m A h g-1at 5 C and high areal capacity of 8.03 mA h cm-2under E/S of 5μL mg-1and sulfur loading of 7.20 mg *** work elucidates that introducing heteroatom and vacancy in metal phosphide collaboratively regulates the electron structure to accelerate bidirectional sulfur conversion.

关键词： Lithium sulfur batteries

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Enhancing anion conductivity in a highly alkali-stable eta topologic Cu(Ⅰ) framework via strong electrostatic repulsion

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Science China Chemistry 2025年

作者： Xiaolu wang Shaohui Guo Chao Suo Fuqiang Zhang Junhao wang Wenjing wang Daqiang Yuan Linfeng Liang Xianming Zhang College of Chemistry Taiyuan University of Technology Institute of Crystalline Materials Shanxi University School of Chemistry and Materials Science Shanxi Normal University State Key Laboratory of Structural Chemistry Fujian Institute of Research on the Structure of Matter Chinese Academy of Sciences

Metal-organic frameworks （MOFs） based on anion exchange membranes （AEMs） have garnered considerable interest,particularly for their potential to enhance ion conductivity by pre-introducing anions into *** approach is recognized as straightforward and effective for improving ion ***,developing high-performance AEMs is limited by the inherent instability and low resistance of *** study presents a novel 1,3,5-triazineμ3-bridged neutral Cu（I） framework,designated SXU-120 （where SXU represents Shanxi University）.This framework is synthesized using melamine,a widely available industrial product,as the starting material,achieving a high space-time yield exceeding 1.1 kg *** organic ligands and metal ions in SXU-120 are 3-connected,forming a rare eta topology with the point symbol 8～***-120 exhibits exceptional stability,even in a 10 M KOH solution,due to its high density of uncoordinated–NH2and carbonyl ***,the framework’s unique one-dimensional channels,characterized by their electronegativity,interact electrostatically with OH-ions,thereby accelerating OH-ion transfer along these ***,the OH-conductivity of this material reaches an impressive 0.49 S cm-1at 90°C under full humidity for 100 h,representing the highest OH-conductivity reported for MOF-based conductors to *** properties make SXU-120 a promising candidate for efficient AEM materials in next-generation industrial applications.

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DDoS Attack Autonomous Detection Model Based on Multi-Strategy Integrate Zebra Optimization Algorithm

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Computers, Materials & Continua 2025年第1期82卷 645-674页

作者： Chunhui Li Xiaoying wang Qingjie Zhang Jiaye Liang Aijing Zhang School of Information Engineering Institute of Disaster PreventionLangfang065201China Langfang Key Laboratory of Network Emergency Protection and Network Security Langfang065201China

Previous studies have shown that deep learning is very effective in detecting known ***,when facing unknown attacks,models such as Deep Neural Networks(DNN)combined with Long Short-Term Memory(LSTM),Convolutional Neural Networks(CNN)combined with LSTM,and so on are built by simple stacking,which has the problems of feature loss,low efficiency,and low ***,this paper proposes an autonomous detectionmodel for Distributed Denial of Service attacks,Multi-Scale Convolutional Neural Network-Bidirectional Gated Recurrent Units-Single Headed Attention(MSCNN-BiGRU-SHA),which is based on a Multistrategy Integrated Zebra Optimization Algorithm(MI-ZOA).The model undergoes training and testing with the CICDDoS2019 dataset,and its performance is evaluated on a new GINKS2023 *** hyperparameters for Conv_filter and GRU_unit are optimized using the Multi-strategy Integrated Zebra Optimization Algorithm(MIZOA).The experimental results show that the test accuracy of the MSCNN-BiGRU-SHA model based on the MIZOA proposed in this paper is as high as 0.9971 in the CICDDoS 2019 *** evaluation accuracy of the new dataset GINKS2023 created in this paper is *** to the MSCNN-BiGRU-SHA model based on the Zebra Optimization Algorithm(ZOA),the detection accuracy on the GINKS2023 dataset has improved by 5.81%,precisionhas increasedby 1.35%,the recallhas improvedby 9%,and theF1scorehas increasedby 5.55%.Compared to the MSCNN-BiGRU-SHA models developed using Grid Search,Random Search,and Bayesian Optimization,the MSCNN-BiGRU-SHA model optimized with the MI-ZOA exhibits better performance in terms of accuracy,precision,recall,and F1 score.

关键词： Distributed denial of service attack intrusion detection deep learning zebra optimization algorithm multi-strategy integrated zebra optimization algorithm

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Unraveling brain aging through the lens of oral microbiota

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Neural Regeneration Research 2025年第7期20卷 1930-1943页

作者： Qinchao Hu Si wang Weiqi Zhang Jing Qu Guang-Hui Liu State Key Laboratory of Membrane Biology Institute of ZoologyChinese Academy of SciencesBeijingChina Hospital of Stomatology Guanghua School of StomatologyGuangdong Provincial Key Laboratory of StomatologySun Yat-sen UniversityGuangzhouGuangdong ProvinceChina Advanced Innovation Center for Human Brain Protection and National Clinical Research Center for Geriatric Disorders Xuanwu HospitalCapital Medical UniversityBeijingChina Aging Translational Medicine Center International Center for Aging and CancerBeijing Municipal Geriatric Medical Research CenterXuanwu HospitalCapital Medical UniversityBeijingChina CAS Key Laboratory of Genomic and Precision Medicine Beijing Institute of GenomicsChinese Academy of Sciences and China National Center for BioinformationBeijingChina University of Chinese Academy of Sciences BeijingChina Institute for Stem Cell and Regeneration Chinese Academy of SciencesBeijingChina Aging Biomarker Consortium BeijingChina State Key Laboratory of Stem Cell and Reproductive Biology Institute of ZoologyChinese Academy of SciencesBeijingChina Beijing Institute for Stem Cell and Regenerative Medicine BeijingChina

The oral cavity is a complex physiological community encompassing a wide range of *** of oral microbiota can lead to various oral infectious diseases,such as periodontitis and tooth decay,and even affect systemic health,including brain aging and neurodegenerative *** studies have highlighted how oral microbes might be involved in brain aging and neurodegeneration,indicating potential avenues for intervention *** this review,we summarize clinical evidence demonstrating a link between oral microbes/oral infectious diseases and brain aging/neurodegenerative diseases,and dissect potential mechanisms by which oral microbes contribute to brain aging and *** also highlight advances in therapeutic development grounded in the realm of oral microbes,with the goal of advancing brain health and promoting healthy aging.

关键词： Alzheimer's disease brain aging multiple sclerosis neurodegeneration neurodegenerative diseases oral microbiota Parkinson's disease periodontitis bacteria Porphyromonas gingivalis

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