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Coordination environments build up and tune a superior synergistic “genome” toward novel trifunctional (TM-N_(x)O_(4−x))@g- C_(16)N_(3)-H_(3): High-throughput inspection of ultra-high activity for water splitting and oxygen reduction reactions

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Nano Research 2024年第4期17卷 2337-2351页

作者： Chunyao Fang Xian Wang Qiang Zhang Xihang Zhang Chenglong Shi Jingcheng Xu Mengyu Yang Department of Physics University of Shanghai for Science and TechnologyShanghai 200093China School of Materials and Chemistry University of Shanghai for Science and TechnologyShanghai 200093China

Emerging as a prominent area of focus in energy conversion and storage technologies,the development of highly active metal-based single-atom catalysts(SACs)holds great signiﬁcance in searching alternatives to replace precious metals toward the efficient,stable,and low-cost hydrogen evolution reaction(HER),as well as the oxygen evolution reaction(OER)and the oxygen reduction reaction(ORR).Combining the tremendous tunability of ligand and coordination environment with rich metal-based electrocatalysts can create breakthrough opportunities for achieving both high stability and ***,we propose a novel and stable holey graphene-like carbon nitride monolayer g-C_(16)N5(N_(4)@g-C_(16)N_(3))stoichiometries interestingly behaving as a natural substrate for constructing SACs((TM-N_(4))@g-C_(16)N_(3)),whose evenly distributed holes map rich and uniform nitrogen coordination positions with electron-rich lone pairs for anchoring transition metal(TM)***,we employed density functional theory(DFT)calculations to systematically investigate the electrocatalytic activity of(TM-N_(4))@g-C_(16)N_(3) toward HER/OER/ORR,meanwhile considering the synergistic modulation of H-loading and O-coordination((TM-N_(x)O_(4-x))@g-C_(16)N_(3)^(-)H_(3),x=0–4).Together a“four-step procedure”screening mechanism with the first-principles high-throughput calculations,we find that(Rh-N_(4))and(Ir-N_(2)O_(2)-II)distributed on g-C_(16)N_(3)^(-)H_(3) can modulate the adsorption strength of the adsorbates,thus achieving the best HER/OER/ORR performance among 216 candidates,and the lowest overpotential of 0.098/0.3/0.46 V and 0.06/0.48/0.45 V,***,the d-band center,crystal orbital Hamilton population(COHP),and molecular orbitals are used to reveal the OER/ORR activity ***,the Rh/Ir-d orbital is dramatically hybridized with the O-p orbital of the oxygenated adsorbates,so that the lone-electrons incipiently locate at the antibonding orbital pair up and popula

关键词： single atom catalysts loading and coordination hydrogen evolution reaction oxygen evolution reaction oxygen reduction reaction

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Fault diagnosis of HVAC system with imbalanced data using multi-scale convolution composite neural network

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Building Simulation 2024年第3期17卷 371-386页

作者： Rouhui Wu Yizhu Ren Mengying Tan Lei Nie School of Mechanical Engineering Hubei University of TechnologyWuhan430068China Industrial Research Institute of Xiangyang Hubei university of technology Xiangyang441100China

Accurate fault diagnosis of heating,ventilation,and air conditioning(HVAC)systems is of significant importance for maintaining normal operation,reducing energy consumption,and minimizing maintenance ***,in practical applications,it is challenging to obtain sufficient fault data for HVAC systems,leading to imbalanced data,where the number of fault samples is much smaller than that of normal ***,most existing HVAC system fault diagnosis methods heavily rely on balanced training sets to achieve high fault diagnosis ***,to address this issue,a composite neural network fault diagnosis model is proposed,which combines SMOTETomek,multi-scale one-dimensional convolutional neural networks(M1DCNN),and support vector machine(SVM).This method first utilizes SMOTETomek to augment the minority class samples in the imbalanced dataset,achieving a balanced number of faulty and normal ***,it employs the M1DCNN model to extract feature information from the augmented ***,it replaces the original Softmax classifier with an SVM classifier for classification,thus enhancing the fault diagnosis *** the SMOTETomek-M1DCNN-SVM method,we conducted fault diagnosis validation on both the ASHRAE RP-1043 dataset and experimental dataset with an imbalance ratio of 1:*** results demonstrate the superiority of this approach,providing a novel and promising solution for intelligent building management,with accuracy and F1 scores of 98.45%and 100%for the RP-1043 dataset and experimental dataset,respectively.

关键词： fault diagnosis chiller imbalanced data SMOTETomek multi-scale neural networks

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Double quantum images encryption scheme based on chaotic system

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Chinese Physics B 2024年第4期33卷 305-320页

作者：蒋社想李杨石锦张茹 School of Computer Science and Engineering Anhui University of Science and TechnologyHuainan 232001China Anhui Key Laboratory of Mine Intelligent Equipment and technology Anhui University of Science&TechnologyHuainan 232001China

This paper explores a double quantum images representation(DNEQR)model that allows for simultaneous storage of two digital images in a quantum superposition ***,a new type of two-dimensional hyperchaotic system based on sine and logistic maps is investigated,offering a wider parameter space and better chaotic behavior compared to the sine and logistic *** on the DNEQR model and the hyperchaotic system,a double quantum images encryption algorithm is ***,two classical plaintext images are transformed into quantum states using the DNEQR ***,the proposed hyperchaotic system is employed to iteratively generate pseudo-random *** chaotic sequences are utilized to perform pixel value and position operations on the quantum image,resulting in changes to both pixel values and ***,the ciphertext image can be obtained by qubit-level diffusion using two XOR operations between the position-permutated image and the pseudo-random *** corresponding quantum circuits are also *** results demonstrate that the proposed scheme ensures the security of the images during transmission,improves the encryption efficiency,and enhances anti-interference and anti-attack capabilities.

关键词： double quantum images encryption chaotic system pixel scrambling XOR operation

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Single-photon scattering and quantum entanglement of two giant atoms with azimuthal angle differences in a waveguide system

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Chinese Physics B 2024年第5期33卷 337-342页

作者：黄劲松黄红武李艳玲徐中辉 School of Information Engineering Jiangxi University of Science and TechnologyGanzhou 341000China Faculty of Science Jiangxi University of Science and TechnologyGanzhou 341000China

We theoretically investigate coherent scattering of single photons and quantum entanglement of two giant atoms with azimuthal angle differences in a waveguide *** the real-space Hamiltonian,analytical expressions are derived for the transport spectra scattered by these two giant atoms with four azimuthal ***-like resonance can be exhibited in the scattering spectra by adjusting the azimuthal angle *** concurrence of the entangled state for two atoms can be implemented in a wide angle-difference range,and the entanglement of the atomic states can be switched on/off by modulating the additional azimuthal angle differences from the giant *** suggests a novel handle to effectively control the single-photon scattering and quantum entanglement.

关键词： quantum transport quantum entanglement scattering theory optical waveguide

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WRKY11 up-regulated dirigent expression to enhance lignin/lignans accumulation in Lilium regale Wilson during response to Fusarium wilt

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Journal of Integrative Agriculture 2024年第8期23卷 2703-2722页

作者： Jie Deng Zi’e Wang Wenyun Li Xiaohua Chen Diqiu Liu Faculty of Life Science and technology Kunming University of Science and TechnologyKunming 650500China

Lilium are highly economically valuable ornamental plants that are susceptible to Fusarium wilt caused by Fusarium *** regale Wilson,a wild lily native to China,is highly resistant to *** this study,a WRKY transcription factor,WRKY11,was isolated from ***,and its function during the interaction between *** and *** was *** ectopic expression of LrWRKY11 in tobacco increased the resistance to F oxysporum,moreover,the transcriptome sequencing and UHPLC-MS/MS analysis indicated that the methyl salicylate and methyl jasmonate levels rose in LrWRKY11 transgenic tobacco,meanwhile,the expression of lignin/lignans biosynthesis-related genes including a dirigent(DiR)was *** lignin/lignans contents in LrWRKY11-transgenic tobacco also significantly increased compared with the wild-type *** addition,the resistance of *** scales in which LrWRKY11 expression was silenced by RNAi evidently decreased,and additionally,the expression of lignin/lignans biosynthesis-related genes including LrDIR1 was significantly ***,LrDIR1 and its promoter(PLrDIR1)sequence containing the W-box element were isolated from *** interaction assay indicated that LrWRKY11 specifically bound to the W-box element in PLrDIR1 and activated LrDIR1 ***,β-glucuronidase activity in the transgenic tobacco co-expressing LrWRKY11/PLrDIR1-β-glucuronidase was higher than that in transgenic tobacco expressing PLrDIR1-β-glucuronidase ***,the ectopic expression of LrDIR1 in tobacco enhanced the resistance to *** and increased the lignin/lignans *** brief,this study revealed that LrWRKY11 positively regulated *** resistance to *** through interaction with salicylic acid/jasmonic acid signaling pathways and modulating LrDIR1 expression to accumulate lignin/lignans.

关键词： Lilium regale Fusarium oxysporum WRKY transcription factor dirigent

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A Review of Computing with Spiking Neural Networks

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Computers, Materials & Continua 2024年第3期78卷 2909-2939页

作者： Jiadong Wu Yinan Wang Zhiwei Li Lun Lu Qingjiang Li College of Electronic Science and technology National University of Defense TechnologyChangsha410073China

Artificial neural networks(ANNs)have led to landmark changes in many fields,but they still differ significantly fromthemechanisms of real biological neural networks and face problems such as high computing costs,excessive computing power,and so *** neural networks(SNNs)provide a new approach combined with brain-like science to improve the computational energy efficiency,computational architecture,and biological credibility of current deep learning *** the early stage of development,its poor performance hindered the application of SNNs in real-world *** recent years,SNNs have made great progress in computational performance and practicability compared with the earlier research results,and are continuously producing significant *** there are already many pieces of literature on SNNs,there is still a lack of comprehensive review on SNNs from the perspective of improving performance and practicality as well as incorporating the latest research *** from this issue,this paper elaborates on SNNs along the complete usage process of SNNs including network construction,data processing,model training,development,and deployment,aiming to provide more comprehensive and practical guidance to promote the development of ***,the connotation and development status of SNNcomputing is reviewed systematically and comprehensively from four aspects:composition structure,data set,learning algorithm,software/hardware development *** the development characteristics of SNNs in intelligent computing are summarized,the current challenges of SNNs are discussed and the future development directions are also *** research shows that in the fields of machine learning and intelligent computing,SNNs have comparable network scale and performance to ANNs and the ability to challenge large datasets and a variety of *** advantages of SNNs over ANNs in terms of energy efficiency and spatial-temporal data processing

关键词： Spiking neural networks neural networks brain-like computing artificial intelligence learning algorithm

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Unsupervised Multi-Expert Learning Model for Underwater Image Enhancement

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IEEE/CAA Journal of Automatica Sinica 2024年第3期11卷 708-722页

作者： Hongmin Liu Qi Zhang Yufan Hu Hui Zeng Bin Fan the School of Intelligence Science and technology and the Institute of Artificial Intelligence University of Science and Technology BeijingBeijing 100083China the School of Automation and Electrical Engineering University of Science and Technology BeijingBeijing 100083China IEEE

Underwater image enhancement aims to restore a clean appearance and thus improves the quality of underwater degraded *** methods feed the whole image directly into the model for ***,they ignored that the R,G and B channels of underwater degraded images present varied degrees of degradation,due to the selective absorption for the *** address this issue,we propose an unsupervised multi-expert learning model by considering the enhancement of each color ***,an unsupervised architecture based on generative adversarial network is employed to alleviate the need for paired underwater *** on this,we design a generator,including a multi-expert encoder,a feature fusion module and a feature fusion-guided decoder,to generate the clear underwater ***,a multi-expert discriminator is proposed to verify the authenticity of the R,G and B channels,*** addition,content perceptual loss and edge loss are introduced into the loss function to further improve the content and details of the enhanced *** experiments on public datasets demonstrate that our method achieves more pleasing results in vision *** metrics(PSNR,SSIM,UIQM and UCIQE) evaluated on our enhanced images have been improved obviously.

关键词： Multi-expert learning underwater image enhancement unsupervised learning

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A Video Captioning Method by Semantic Topic-Guided Generation

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Computers, Materials & Continua 2024年第1期78卷 1071-1093页

作者： Ou Ye Xinli Wei Zhenhua Yu Yan Fu Ying Yang College of Computer Science and technology Xi’an University of Science and TechnologyXi’an710054China

In the video captioning methods based on an encoder-decoder,limited visual features are extracted by an encoder,and a natural sentence of the video content is generated using a ***,this kind ofmethod is dependent on a single video input source and few visual labels,and there is a problem with semantic alignment between video contents and generated natural sentences,which are not suitable for accurately comprehending and describing the video *** address this issue,this paper proposes a video captioning method by semantic topic-guided ***,a 3D convolutional neural network is utilized to extract the spatiotemporal features of videos during the ***,the semantic topics of video data are extracted using the visual labels retrieved from similar video *** the decoding,a decoder is constructed by combining a novel Enhance-TopK sampling algorithm with a Generative Pre-trained Transformer-2 deep neural network,which decreases the influence of“deviation”in the semantic mapping process between videos and texts by jointly decoding a baseline and semantic topics of video *** this process,the designed Enhance-TopK sampling algorithm can alleviate a long-tail problem by dynamically adjusting the probability distribution of the predicted ***,the experiments are conducted on two publicly used Microsoft Research Video Description andMicrosoft Research-Video to Text *** experimental results demonstrate that the proposed method outperforms several state-of-art ***,the performance indicators Bilingual Evaluation Understudy,Metric for Evaluation of Translation with Explicit Ordering,Recall Oriented Understudy for Gisting Evaluation-longest common subsequence,and Consensus-based Image Description Evaluation of the proposed method are improved by 1.2%,0.1%,0.3%,and 2.4% on the Microsoft Research Video Description dataset,and 0.1%,1.0%,0.1%,and 2.8% on the Microsoft Research-Video to Text dataset

关键词： Video captioning encoder-decoder semantic topic jointly decoding Enhance-TopK sampling

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RepDNet:A re-parameterization despeckling network for autonomous underwater side-scan sonar imaging with prior-knowledge customized convolution

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Defence technology（防务技术） 2024年第5期35卷 259-274页

作者： Zhuoyi Li Zhisen Wang Deshan Chen Tsz Leung Yip Angelo P.Teixeira Department of Logistics and Maritime Studies The Hong Kong Polytechnic UniversityChina State Key Laboratory of Maritime technology and Safety Wuhan University of TechnologyChina School of Transportation and Logistics Engineering Wuhan University of TechnologyChina National Engineering Research Center for Water Transport Safety Wuhan University of TechnologyChina Centre for Marine technology and Ocean Engineering(CENTEC) Instituto Superior TecnicoUniversidade de LisboaPortugal

Side-scan sonar(SSS)is now a prevalent instrument for large-scale seafloor topography measurements,deployable on an autonomous underwater vehicle(AUV)to execute fully automated underwater acoustic scanning imaging along a predetermined ***,SSS images often suffer from speckle noise caused by mutual interference between echoes,and limited AUV computational resources further hinder noise *** approaches for SSS image processing and speckle noise reduction rely heavily on complex network structures and fail to combine the benefits of deep learning and domain *** address the problem,Rep DNet,a novel and effective despeckling convolutional neural network is *** DNet introduces two re-parameterized blocks:the Pixel Smoothing Block(PSB)and Edge Enhancement Block(EEB),preserving edge information while attenuating speckle *** training,PSB and EEB manifest as double-layered multi-branch structures,integrating first-order and secondorder derivatives and smoothing *** inference,the branches are re-parameterized into a 3×3 convolution,enabling efficient inference without sacrificing *** DNet comprises three computational operations:3×3 convolution,element-wise summation and Rectified Linear Unit *** on benchmark datasets,a real SSS dataset and Data collected at Lake Mulan aestablish Rep DNet as a well-balanced network,meeting the AUV computational constraints in terms of performance and latency.

关键词： Side-scan sonar Sonar image despeckling Domain knowledge Re-parameterization

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Structure and dynamical properties during solidification of liquid aluminum induced by cooling and compression

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Chinese Physics B 2024年第7期33卷 476-481页

作者：吴旻杨永琪王垚 College of Materials Science and Engineering Zhejiang University of TechnologyHangzhou 310014China Shaoxing Research Institute Zhejiang University of TechnologyShaoxing 312000China

The structural transformation from a liquid into a crystalline solid is an important subject in condensed matter physics and materials science. In the present study, first-principles molecular dynamics calculations are performed to investigate the structure and properties of aluminum during the solidification which is induced by cooling and compression. In the cooling process and compression process, it is found that the icosahedral short-range order is initially enhanced and then begin to decay, the face-centered cubic short-range order eventually becomes dominant before it transforms into a crystalline solid.

关键词： first-principles method molecular dynamics short-range order liquid aluminum

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