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Compliant Iontronic Triboelectric Gels with Phase-Locked Structure Enabled by Competitive Hydrogen Bonding

Nano-Micro Letters 2024年第9期16卷 180-194页

作者： Guoli Du Yuzheng Shao Bin Luo Tao Liu Jiamin Zhao Ying Qin Jinlong Wang Song Zhang Mingchao Chi Cong Gao Yanhua Liu Chenchen Cai Shuangfei Wang Shuangxi Nie school of light industry and Food engineering Guangxi UniversityNanning 530004People’s Republic of China

Rapid advancements in flexible electronics technology propel soft tactile sensing devices toward high-level biointegration,even attaining tactile perception capabilities surpassing human ***,the inherent mechanical mismatch resulting from deficient biomimetic mechanical properties of sensing materials poses a challenge to the application of wearable tactile sensing devices in human-machine *** by the innate biphasic structure of human subcutaneous tissue,this study discloses a skin-compliant wearable iontronic triboelectric gel via phase separation induced by competitive hydrogen ***-nonsolvent interactions are used to construct competitive hydrogen bonding systems to trigger phase separation,and the resulting soft-hard alternating phase-locked structure confers the iontronic triboelectric gel with Young’s modulus(6.8-281.9 kPa)and high tensile properties(880%)compatible with human *** abundance of reactive hydroxyl groups gives the gel excellent tribopositive and self-adhesive properties(peel strength>70 N m^(−1)).The self-powered tactile sensing skin based on this gel maintains favorable interface and mechanical stability with the working object,which greatly ensures the high fidelity and reliability of soft tactile sensing *** strategy,enabling skin-compliant design and broad dynamic tunability of the mechanical properties of sensing materials,presents a universal platform for broad applications from soft robots to wearable electronics.

关键词： Triboelectric nanogenerator Cellulose Triboelectric gel Self-powered sensor Energy harvesting

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An Approach for Human Posture Recognition Based on the Fusion PSE-CNN-BiGRU Model

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Computer Modeling in engineering & Sciences 2024年第7期140卷 385-408页

作者： Xianghong Cao Xinyu Wang Xin Geng Donghui Wu Houru An school of Building and Environment engineering Zhengzhou University of Light IndustryZhengzhou450000China

This study proposes a pose estimation-convolutional neural network-bidirectional gated recurrent unit(PSECNN-BiGRU)fusion model for human posture recognition to address low accuracy issues in abnormal posture recognition due to the loss of some feature information and the deterioration of comprehensive performance in model detection in complex home ***,the deep convolutional network is integrated with the Mediapipe framework to extract high-precision,multi-dimensional information from the key points of the human skeleton,thereby obtaining a human posture feature ***,a double-layer BiGRU algorithm is utilized to extract multi-layer,bidirectional temporal features from the human posture feature set,and a CNN network with an exponential linear unit(ELU)activation function is adopted to perform deep convolution of the feature map to extract the spatial feature of the human ***,a squeeze and excitation networks(SENet)module is introduced to adaptively learn the importance weights of each channel,enhancing the network’s focus on important ***,comparative experiments are performed on available datasets,including the public human activity recognition using smartphone dataset(UCIHAR),the public human activity recognition 70 plus dataset(HAR70PLUS),and the independently developed home abnormal behavior recognition dataset(HABRD)created by the authors’*** results show that the average accuracy of the proposed PSE-CNN-BiGRU fusion model for human posture recognition is 99.56%,89.42%,and 98.90%,respectively,which are 5.24%,5.83%,and 3.19%higher than the average accuracy of the five models proposed in the comparative literature,including CNN,GRU,and *** F1-score for abnormal posture recognition reaches 98.84%(heartache),97.18%(fall),99.6%(bellyache),and 98.27%(climbing)on the self-builtHABRDdataset,thus verifying the effectiveness,generalization,and robustness of the proposed model in enhancing human posture rec

关键词： Posture recognition mediapipe BiGRU CNN ELU attention

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Mesoporous molecular sieve confined phase change materials with high absorption,enhanced thermal conductivity,and cooling energy charging/discharging capacity

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Frontiers of Materials Science 2024年第1期18卷 1-14页

作者： Qi Zhang Chongyang Liu Xuehong Wu Xueling Zhang Jun Song school of Energy and Power engineering Zhengzhou University of Light IndustryZhengzhou 450007China

The biggest challenge for organic phase change materials(PCMs)used in cold energy storage is to maintain high heat storage capacity while reducing the leakage risk of PCMs during the phase transition *** is crucial for expanding their applications in the more demanding cold storage *** this study,novel formstable low-temperature composite PCMs are prepared with mesoporous materials,namely SBA-15 and CMK-3(which are prepared using the template method),as supporting matrices and dodecane as the *** to the combined effects of capillary forces within mesoporous materials and interactions among dodecane molecules,both dodecane/SBA-15 and dodecane/CMK-3 exhibit outstanding shape stability and thermal cycling stability even after 200 heating/cooling *** comparison to those of dodecane/SBA-15,dodecane/CMK-3 exhibits superior cold storage performance and higher thermal ***,the phase transition temperature of dodecane/CMK-3 is-8.81℃ with a latent heat of 122.4 J·g^(-1).Additionally,it has a thermal conductivity of 1.21 W·m^(-1)·K^(-1),which is 9.45 times that of dodecane *** these highlight its significant potential for applications in the area of cold energy storage.

关键词： cold energy storage phase change material mesoporous molecular sieve CMK-3 SBA-15 cooling energy charging/discharging capacity

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Multimodal Sentiment Analysis Based on a Cross-Modal Multihead Attention Mechanism

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Computers, Materials & Continua 2024年第1期78卷 1157-1170页

作者： Lujuan Deng Boyi Liu Zuhe Li school of Computer and Communication engineering Zhengzhou University of Light IndustryZhengzhou450002China

Multimodal sentiment analysis aims to understand people’s emotions and opinions from diverse ***-nating or multiplying various modalities is a traditional multi-modal sentiment analysis fusion *** fusion method does not utilize the correlation information between *** solve this problem,this paper proposes amodel based on amulti-head attention ***,after preprocessing the original ***,the feature representation is converted into a sequence of word vectors and positional encoding is introduced to better understand the semantic and sequential information in the input ***,the input coding sequence is fed into the transformer model for further processing and *** the transformer layer,a cross-modal attention consisting of a pair of multi-head attention modules is employed to reflect the correlation between ***,the processed results are input into the feedforward neural network to obtain the emotional output through the classification *** the above processing flow,the model can capture semantic information and contextual relationships and achieve good results in various natural language processing *** model was tested on the CMU Multimodal Opinion Sentiment and Emotion Intensity(CMU-MOSEI)and Multimodal EmotionLines Dataset(MELD),achieving an accuracy of 82.04% and F1 parameters reached 80.59% on the former dataset.

关键词： Emotion analysis deep learning cross-modal attention mechanism

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Study on trifluoromethanesulfonic acid-promoted synthesis of daidzein: Process optimization and reaction mechanism

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Chinese Journal of Chemical engineering 2024年第7期71卷 132-139页

作者： Hai Cao Haibin Yang Yanxiong Fang Yuandi Zeng Xiaolan Cai Jingjing Ma school of Chemical engineering and light industry Guangdong University of TechnologyGuangzhou 510006China Jieyang Branch of chemistry and Chemical engineering Guangdong Laboratory(Rongjiang Laboratory) Jieyang 515200China

Daidzein has been widely used in pharmaceuticals,nutraceuticals,cosmetics,feed additives,*** preparation process and related reaction mechanism need to be further investigated.A cost-effective process for synthesizing daidzein was developed in this *** this article,a two-step synthesis of daidzein(Friedel–Crafts acylation and[5+1]cyclization)was developed via the employment of trifluoromethanesulfonic acid(TfOH)as an effective promoting *** effect of reaction conditions such as solvent,the amount of TfOH,reaction temperature,and reactant ratio on the conversion rate and the yield of the reaction,respectively,was systematically investigated,and daidzein was obtained in 74.0%isolated yield under optimal *** to the facilitating effect of TfOH,the Friedel–Crafts acylation was completed within 10 min at 90℃ and the[5+1]cyclization was completed within 180 min at 25℃.In addition,a possible reaction mechanism for this process was *** results of the study may provide useful guidance for industrial production of daidzein on a large scale.

关键词： Synthesis Optimal design Chemical processes Reaction mechanism

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lightweight Cross-Modal Multispectral Pedestrian Detection Based on Spatial Reweighted Attention Mechanism

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Computers, Materials & Continua 2024年第3期78卷 4071-4089页

作者： Lujuan Deng Ruochong Fu Zuhe Li Boyi Liu Mengze Xue Yuhao Cui school of Computer and Communication engineering Zhengzhou University of Light IndustryZhengzhou450002China

Multispectral pedestrian detection technology leverages infrared images to provide reliable information for visible light images, demonstrating significant advantages in low-light conditions and background occlusion scenarios. However, while continuously improving cross-modal feature extraction and fusion, ensuring the model’s detection speed is also a challenging issue. We have devised a deep learning network model for cross-modal pedestrian detection based on Resnet50, aiming to focus on more reliable features and enhance the model’s detection efficiency. This model employs a spatial attention mechanism to reweight the input visible light and infrared image data, enhancing the model’s focus on different spatial positions and sharing the weighted feature data across different modalities, thereby reducing the interference of multi-modal features. Subsequently, lightweight modules with depthwise separable convolution are incorporated to reduce the model’s parameter count and computational load through channel-wise and point-wise convolutions. The network model algorithm proposed in this paper was experimentally validated on the publicly available KAIST dataset and compared with other existing methods. The experimental results demonstrate that our approach achieves favorable performance in various complex environments, affirming the effectiveness of the multispectral pedestrian detection technology proposed in this paper.

关键词： Multispectral pedestrian detection convolutional neural networks depth separable convolution spatially reweighted attention mechanism

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A novel method for extracting and optimizing the complex permittivity of paper-based composites based on an artificial neural network model

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Science China Technological Sciences 2024年第10期67卷 3190-3204页

作者： XIA ChenBin SHEN JunYi LIAO ShaoWei WANG Yi HUANG ZhengSheng XUE Quan TANG Min LONG Jin HU Jian school of light industry and engineering South China University of Technology school of Electronic and Information engineering South China University of Technology

Measuring the complex permittivity of ultrathin, flexible materials with a high loss tangent poses a substantial challenge with precision using conventional methods, and verifying the accuracy of test results remains difficult. In this study, we introduce a methodology based on a back-propagation artificial neural network(ANN) to extract the complex permittivity of paper-based composites(PBCs). PBCs are ultrathin and flexible materials exhibiting considerable complex permittivity and dielectric loss tangent. Given the absence of mature measurement methods for PBCs and a lack of sufficient data for ANN training, a mapping relationship is initially established between the complex permittivity of honeycomb-structured microwave-absorbing materials(HMAMs, composed of PBCs) and that of PBCs using simulated data. Leveraging the ANN model, the complex permittivity of PBCs can be extracted from that of HMAMs obtained using standard measurement. Subsequently, two published methods are cited to illustrate the accuracy and advancement of the results obtained using the proposed approach. Additionally, specific error analysis is conducted, attributing discrepancies to the conductivity of PBCs, the homogenization of HMAMs, and differences between the simulation model and actual objects. Finally, the proposed method is applied to optimize the cell length parameters of HMAMs for enhanced absorption performance. The conclusion discusses further improvements and areas for extended research.

关键词： paper-based composite honeycomb complex permittivity artificial neural networks inverse modeling

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Ultra-high-rate Bi anode encapsulated in 3D lignin-derived carbon framework for sodium-ion hybrid capacitors

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Rare Metals 2024年第3期43卷 1037-1047页

作者： Ze-Hua Lin Xue-Qing Qiu Xi-Hong Zu Xiao-Shan Zhang Lei Zhong Shi-Rong Sun Shu-Hua Hao Ying-Juan Sun Wen-Li Zhang school of Chemical engineering and light industry Guangdong University of Technology(GDUT)Guangzhou510006China Jieyang Branch of chemistry and Chemical engineering Guangdong Laboratory(Rongjiang Laboratory) Jieyang515200China school of Advanced Manufacturing Institute of Green Chemistry and Advanced MaterialsGuangdong University of TechnologyJieyang515200China

Bismuth(Bi),as an alloy-based anode material,has attracted much atte ntion in the developme nt of sodiumion hybrid capacitors(SIHCs)due to its high theoretical ***,the volume expansion of the Bi-based anode during the sodiation/desodiation process results in limited rate *** the present work,a porous Bi-based composite was constructed by a one-step hydrothermal method,and Bi was encapsulated in ligninderived nitrogen-doped porous carbon(Bi@LNPC)after *** obtained Bi nanoparticles could effectively adapt to the strain and shorten the diffusion distance of Na^(+).In addition,porous carbon skeleton provides a rigid conductive network for electronic ***,the assembled sodium-ion half-cell with Bi@LNPC anode shows ultra-high-rate *** the current density was enhanced from 0.1 to 50 A·g^(-1),the specific capacity decreased slightly from 351.5 to 342.8 mAh·g^(-1).Even at an extremely high current density of 200 A·g^(-1),it retains 81.3%capacity retention when compared to a current density of 1 A·g^(-1).The SIHCs assembled by Bi@LNPC show a high energy density of 63 Wh·kg^(-1).This work provides an effective method for developing high-rate Bi anode materials for sodium-ion hybrid capacitors(SIHCs)and sodium-ion batteries(SIBs).

关键词： Bismuth Lignin Sodium-ion batteries Sodium-ion hybrid capacitors Rate Porous carbon

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Fabrication of surface passivated two-dimensional MFI zeolite for alkylation between toluene with methanol

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Frontiers of Chemical Science and engineering 2024年第4期18卷 115-124页

作者： Zhenyuan Zou Shengzhi Gan Ting Pu Xingxing Zeng Yi Huang Baoyu Liu school of Chemical engineering and light industry Guangdong University of TechnologyGuangzhou 510006China school of engineering Institute for Materials&Processesthe University of EdinburghEdinburgh EH93FBUnited Kingdom

The fabrication of suitable MFI zeolites to effectively produce para-xylene through the alkylation between toluene and methanol is highly ***,the two-dimensional pillared MFI zeolite was modified by silicalite-1,and its morphology and structure were systematically investigated by tuning the concentration of Si species during the secondary crystallization *** MFI zeolites were characterized by X-ray diffraction,transmission electron microscopy,pyridine-infrared and N_(2) adsorption-desorption *** characterization results showed that the external Brønsted acid sites of surface passivated P-MFI-x samples have been successfully ***,the P-MFI-23 showed long lifetime and high selectivity of para-xylene(about 35%)based on the cooperation between opened interlamellar structure and passivated silicalite-1 *** was found that the accumulated hard coke in the interior of MFI zeolites not only blocked the channels of zeolites but also covered the acidic sites,resulting in the deactivation of ***,the highest selectivity of para-xylene(about 48%)can be achieved for P-MFI-30 under harsh reaction condition,which also exhibited excellent regeneration property in the alkylation reaction between toluene and *** strategy described in present research may open a window for the design of other advanced materials.

关键词： alkylation MFI nanosheets catalysis

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A Review of Deep Learning-Based Vulnerability Detection Tools for Ethernet Smart Contracts

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Computer Modeling in engineering & Sciences 2024年第7期140卷 77-108页

作者： Huaiguang Wu Yibo Peng Yaqiong He Jinlin Fan school of Computer Science and Technology Zhengzhou University of Light IndustryZhengzhou450001China

In recent years,the number of smart contracts deployed on blockchain has ***,the issue of vulnerability has caused incalculable *** to the irreversible and immutability of smart contracts,vulnerability detection has become particularly *** the popular use of neural network model,there has been a growing utilization of deep learning-based methods and tools for the identification of vulnerabilities within smart *** paper commences by providing a succinct overview of prevalent categories of vulnerabilities found in smart ***,it categorizes and presents an overview of contemporary deep learning-based tools developed for smart contract *** tools are categorized based on their open-source status,the data format and the type of feature extraction they *** we conduct a comprehensive comparative analysis of these tools,selecting representative tools for experimental validation and comparing them with traditional tools in terms of detection coverage and ***,Based on the insights gained from the experimental results and the current state of research in the field of smart contract vulnerability detection tools,we suppose to provide a reference standard for developers of contract vulnerability detection ***,forward-looking research directions are also proposed for deep learning-based smart contract vulnerability detection.

关键词： Smart contract vulnerability detection deep learning

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