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Simultaneous photocatalytic degradation and SERS detection of tetracycline with self-sustainable and recyclable ternary PI/TiO_(2)/Ag flexible microfibers

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Microsystems & Nanoengineering 2024年第2期10卷 101-113页

作者： Donglai Han Boyang Guo Yanru Li Wei Feng Keyan Liu Tianna Wu Yuchun Wan Lili Wang Ming Gao Yang Liu Lili Yang Maobin Wei Shuo Yang School of Materials Science and Engineering Changchun University of Science and Technology130022ChangchunChina College of Science Changchun University130022ChangchunChina Key Laboratory of Functional Materials Physics and Chemistry of the Ministry of Education Jilin Normal University130103ChangchunChina

Facile and efficient photocatalysts using sunlight,as well as fast and sensitive surface-enhanced Raman spectroscopy(SERS)substrates,are urgently needed for practical degradation of tetracycline(TC).To meet these requirements,a new paradigm for PI/TiO_(2)/Ag organic‒inorganic ternary flexible microfibers based on semiconducting titanium dioxide(TiO_(2)),the noble metal silver(Ag)and the conjugated polymer polyimide(PI)was developed by engineering a simple *** sunlight,the photocatalytic characteristics of the PI/TiO_(2)/Ag flexible microfibers containing varying amounts of Ag quantum dots(QDs)were evaluated with photocatalytic degradation of TC in aqueous *** results demonstrated that the amount of Ag affected the photocatalytic *** the tested samples,PI/TiO_(2)/Ag-0.07(93.1%)exhibited a higher photocatalytic degradation rate than PI/TiO_(2)(25.7%),PI/TiO_(2)/Ag-0.05(77.7%),and PI/TiO_(2)/Ag-0.09(63.3%).This observation and evaluation conducted in the present work strongly indicated a charge transfer ***,the PI/TiO_(2)/Ag-0.07 flexible microfibers exhibited highly sensitive SERS detection,as demonstrated by the observation of the Raman peaks for TC even at an extremely low concentration of 10–10 moles per *** excellent photocatalytic performance and SERS detection capability of the PI/TiO_(2)/Ag flexible microfibers arose from the Schottky barrier formed between Ag and TiO_(2)and also from the outstanding plasmonic resonance and visible light absorptivity of Ag,along with immobilization by the *** successful synthesis of PI/TiO_(2)/Ag flexible microfibers holds significant promise for sensitive detection and efficient photocatalytic degradation of antibiotics.

关键词： mechanism. photocatalytic ternary

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Denoising 1SPP Monte carlo renderings based on human visual perception 3

Denoising 1SPP Monte carlo renderings based on human visual ...

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3rd International Conference on Electronic Information engineering and Data Processing, EIEDP 2024

作者： Qi, Peili Chen, Chunyi School of the computer science and technology Changchun University of Science and Technology Changchun China School of the computer science and technology Changchun University of Science and Technology Changchun China

ISBN: (纸本)9781510680531

In traditional Monte Carlo (MC) path-tracing denoising approaches, uniform processing across all pixels often overlooks the variable importance of different image regions as perceived by human observers. This study introduces a novel denoising method tailored to 1spp (one sample per pixel) MC renderings, leveraging human visual perception to prioritize computation in visually salient areas. By classifying pixels based on visual saliency, our method efficiently allocates computational resources, enhancing quality in high-saliency regions while reducing unnecessary processing in less noticeable areas. Experimental results validate the effectiveness of our approach, demonstrating improved denoising performance with reduced computational overhead. This saliency-based strategy not only achieves high-quality denoising but also paves the way for more perception-driven approaches in real-time rendering applications. © 2024 SPIE.

关键词： Pixels

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Metarelation2vec:A Metapath-Free Scalable Representation Learning Model for Heterogeneous Networks

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Tsinghua science and technology 2024年第2期29卷 553-575页

作者： Lei Chen Yuan Li Yong Lei Xingye Deng School of Information and Electrical Engineering Hunan University of Science and TechnologyXiangtan 411201China School of Computer Science and Engineering Hunan University of Science and TechnologyXiangtan 411201China

Metapaths with specific complex semantics are critical to learning diverse semantic and structural information of heterogeneous networks(HNs)for most of the existing representation learning ***,any metapaths consisting of multiple,simple metarelations must be driven by domain *** sensitive,expensive,and limited metapaths severely reduce the flexibility and scalability of the existing models.A metapath-free,scalable representation learning model,called Metarelation2vec,is proposed for HNs with biased joint learning of all metarelations in a bid to address this ***,a metarelation-aware,biased walk strategy is first designed to obtain better training samples by using autogenerating cooperation probabilities for all metarelations rather than using expert-given ***,grouped nodes by the type,a common and shallow skip-gram model is used to separately learn structural proximity for each node ***,grouped links by the type,a novel and shallow model is used to separately learn the semantic proximity for each link ***,supervised by the cooperation probabilities of all meta-words,the biased training samples are thrown into the shallow models to jointly learn the structural and semantic information in the HNs,ensuring the accuracy and scalability of the *** experimental results on three tasks and four open datasets demonstrate the advantages of our proposed model.

关键词： metarelation random walk heterogeneous network metapath representation learning

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Deep learning-based software engineering: progress,challenges, and opportunities

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science China(Information sciences) 2025年第1期68卷 57-144页

作者： Xiangping CHEN Xing HU Yuan HUANG He JIANG Weixing JI Yanjie JIANG Yanyan JIANG Bo LIU Hui LIU Xiaochen LI Xiaoli LIAN Guozhu MENG Xin PENG Hailong SUN Lin SHI Bo WANG Chong WANG Jiayi WANG Tiantian WANG Jifeng XUAN Xin XIA Yibiao YANG Yixin YANG Li ZHANG Yuming ZHOU Lu ZHANG School of Journalism and Communication Sun Yat-sen University School of Software Technology Zhejiang University School of Software Engineering Sun Yat-sen University School of Software Dalian University of Technology School of Computer Science and Technology Beijing Institute of Technology Key Laboratory of High Confidence Software Technologies (Peking University) Ministry of EducationSchool of Computer Science Peking University State Key Laboratory for Novel Software Technology Nanjing University School of Computer Science and Engineering Beihang University Institute of Information Engineering Chinese Academy of Sciences School of Computer Science Fudan University State Key Laboratory of Complex & Critical Software Environment (CCSE) School of Software Beihang University School of Computer and Information Technology Beijing Jiaotong University School of Computer Science and Technology Harbin Institute of Technology School of Computer Science Wuhan University Huawei Technologies

Researchers have recently achieved significant advances in deep learning techniques, which in turn has substantially advanced other research disciplines, such as natural language processing, image processing, speech recognition, and software engineering. Various deep learning techniques have been successfully employed to facilitate software engineering tasks, including code generation, software refactoring, and fault localization. Many studies have also been presented in top conferences and journals, demonstrating the applications of deep learning techniques in resolving various software engineering tasks. However,although several surveys have provided overall pictures of the application of deep learning techniques in software engineering,they focus more on learning techniques, that is, what kind of deep learning techniques are employed and how deep models are trained or fine-tuned for software engineering tasks. We still lack surveys explaining the advances of subareas in software engineering driven by deep learning techniques, as well as challenges and opportunities in each subarea. To this end, in this study, we present the first task-oriented survey on deep learning-based software engineering. It covers twelve major software engineering subareas significantly impacted by deep learning techniques. Such subareas spread out through the whole lifecycle of software development and maintenance, including requirements engineering, software development, testing, maintenance, and developer collaboration. As we believe that deep learning may provide an opportunity to revolutionize the whole discipline of software engineering, providing one survey covering as many subareas as possible in software engineering can help future research push forward the frontier of deep learning-based software engineering more systematically. For each of the selected subareas,we highlight the major advances achieved by applying deep learning techniques with pointers to the available datasets i

关键词： deep learning software engineering software benchmark software artifact representation survey

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The etching strategy of zinc anode to enable high performance zinc-ion batteries

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Journal of Energy Chemistry 2024年第1期88卷 125-143,I0004页

作者： Xueqing Fu Gaopeng Li Xinlu Wang Jinxian Wang Wensheng Yu Xiangting Dong Dongtao Liu School of Chemistry and Environmental Engineering Changchun University of Science and TechnologyChangchun 130022JilinChina Department of Chemistry Northeast Normal UniversityChangchun 130024JilinChina

Zinc-ion batteries(ZIBs)are considered to be one of the most promising candidates to replace lithium-ion batteries(LIBs)due to the high theoretical capacity,low cost and intrinsic ***,zinc dendrites,hydrogen evolution reaction,surface passivation and other side reactions will inevitably occur during the charging and discharging process of Zn anode,which will seriously affect the cycle stability of the battery and hinder its practical *** etching strategy of Zn anode has attracted wide attention because of its simple operation and broad commercial prospects,and the etched Zn anode can effectively improve its electrochemical ***,there is no comprehensive review of the etching strategy of Zn *** review first summarizes the challenges faced by Zn anode,then puts forward the etching mechanisms and properties of acid,salt and other ***,based on the above discussion,the challenges and opportunities of Zn anode etching strategy are proposed.

关键词： Zinc-ion batteries Zn anode Etching 3D structures Dendrite-free

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A self-standing dual-electric field synergistic Janus nanofibre piezoelectric photocatalyst with degradation of antibiotics:Performances,DFT calculation and mechanism unveiling

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材料科学技术（英文版） 2025年第5期208卷 278-291页

作者： Feng Sun Da Xu Jingcheng Xu Yunrui Xie Haina Qi Feng Liu Hong Shao Hui Yu Wensheng Yu Xiangting Dong Key Laboratory of Applied Chemistry and Nanotechnology at Universities of Jilin Province School of Chemistry and Environmental EngineeringChangchun University of Science and TechnologyChangchun 130022China School of Materials and Chemistry University of Shanghai for Science and TechnologyShanghai 200093China

A self-standing dual-electric field synergistic[TiO2/polyvinylidene fluoride(PVDF)]//[g-C3N4 tube/PVDF]Janus nanofibres(named as[TP]//[CTP]JNs)S-scheme heterostructure piezoelectric photocatalyst is de-signed and constructed via conjugative ***-fields of built-in electric fields supplied by S-scheme heterostructure and piezoelectric field formed by PVDF jointly boost separation and transfer of photo-induced *** a case study,piezoelectric photocatalytic efficiency of[TP]//[CTP]JNs for tetracycline hydrochloride(TCH)under ultrasonic united with simulated sunlight illumination is 93.35％(40 min),which is 1.39 times of the photocatalytic efficiency(light illumination only)and 5.32 times of piezoelectric catalytic efficiency(applying ultrasonic only),proving the advantages of the synergistic ef-fect of piezoelectric catalysis and photocatalysis on contaminant *** dynamic behaviors of photocatalysis and photo-generated charges are deeply revealed through fs-TA and TRPL decay spectra,and the degradation pathways of antibiotics are reasonably speculated by combining LCMS spectra with Fukui *** the degradation ability,COMSOL simulation and DFT calculation,the structural advantage of Janus nanofibers is fully verified,and S-scheme charge transfer mechanism is confirmed by combining a series of sound ample experiments with theoretical ***,the construction mecha-nism of Janus nanofibers is proposed,and corresponding construction technique is established.

关键词： Janus nanofibre piezoelectric photocatalyst Dual-electric field S-scheme heterostructure Self-standing Degradation of antibiotic

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A Global-Local Parallel Dual-Branch Deep Learning Model with Attention-Enhanced Feature Fusion for Brain Tumor MRI Classification

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computers, Materials & Continua 2025年第4期83卷 739-760页

作者： Zhiyong Li Xinlian Zhou School of Computer Science and Engineering Hunan University of Science and TechnologyXiangtan411100China

Brain tumor classification is crucial for personalized treatment *** deep learning-based Artificial Intelligence(AI)models can automatically analyze tumor images,fine details of small tumor regions may be overlooked during global feature ***,we propose a brain tumor Magnetic Resonance Imaging(MRI)classification model based on a global-local parallel dual-branch *** global branch employs ResNet50 with a Multi-Head Self-Attention(MHSA)to capture global contextual information from whole brain images,while the local branch utilizes VGG16 to extract fine-grained features from segmented brain tumor *** features from both branches are processed through designed attention-enhanced feature fusion module to filter and integrate important ***,to address sample imbalance in the dataset,we introduce a category attention block to improve the recognition of minority *** results indicate that our method achieved a classification accuracy of 98.04%and a micro-average Area Under the Curve(AUC)of 0.989 in the classification of three types of brain tumors,surpassing several existing pre-trained Convolutional Neural Network(CNN)***,feature interpretability analysis validated the effectiveness of the proposed *** suggests that the method holds significant potential for brain tumor image classification.

关键词： Deep learning attention mechanism feature fusion dual-branch structure brain tumor MRI classification

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Analyzing topics in social media for improving digital twinning based product development

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Digital Communications and Networks 2024年第2期10卷 273-281页

作者： Wenyi Tang Ling Tian Xu Zheng Ke Yan School of Computer Science and Engineering University of Electronic Science and Technology of ChinaChengdu611731China

Digital twinning enables manufacturers to create digital representations of physical entities,thus implementing virtual simulations for product *** efforts of digital twinning neglect the decisive consumer feedback in product development stages,failing to cover the gap between physical and digital *** work mines real-world consumer feedbacks through social media topics,which is significant to product *** specifically analyze the prevalent time of a product topic,giving an insight into both consumer attention and the widely-discussed time of a *** primary body of current studies regards the prevalent time prediction as an accompanying task or assumes the existence of a preset ***,these proposed solutions are either biased in focused objectives and underlying patterns or weak in the capability of generalization towards diverse *** this end,this work combines deep learning and survival analysis to predict the prevalent time of *** propose a specialized deep survival model which consists of two *** first module enriches input covariates by incorporating latent features of the time-varying text,and the second module fully captures the temporal pattern of a rumor by a recurrent network ***,a specific loss function different from regular survival models is proposed to achieve a more reasonable *** experiments on real-world datasets demonstrate that our model significantly outperforms the state-of-the-art methods.

关键词： Digital twinning Product development Topic analysis Social media

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Robust video question answering via contrastive cross-modality representation learning

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science China(Information sciences) 2024年第10期67卷 211-226页

作者： Xun YANG Jianming ZENG Dan GUO Shanshan WANG Jianfeng DONG Meng WANG School of Information Science and Technology University of Science and Technology of China Institute of Artificial Intelligence Hefei Comprehensive National Science Center School of Computer Science and Information Engineering Hefei University of Technology Institutes of Physical Science and Information Technology Anhui University School of Computer Science and Technology Zhejiang Gongshang University

Video question answering(VideoQA) is a challenging yet important task that requires a joint understanding of low-level video content and high-level textual semantics. Despite the promising progress of existing efforts, recent studies revealed that current VideoQA models mostly tend to over-rely on the superficial correlations rooted in the dataset bias while overlooking the key video content, thus leading to unreliable results. Effectively understanding and modeling the temporal and semantic characteristics of a given video for robust VideoQA is crucial but, to our knowledge, has not been well investigated. To fill the research gap, we propose a robust VideoQA framework that can effectively model the cross-modality fusion and enforce the model to focus on the temporal and global content of videos when making a QA decision instead of exploiting the shortcuts in datasets. Specifically, we design a self-supervised contrastive learning objective to contrast the positive and negative pairs of multimodal input, where the fused representation of the original multimodal input is enforced to be closer to that of the intervened input based on video perturbation. We expect the fused representation to focus more on the global context of videos rather than some static keyframes. Moreover, we introduce an effective temporal order regularization to enforce the inherent sequential structure of videos for video representation. We also design a Kullback-Leibler divergence-based perturbation invariance regularization of the predicted answer distribution to improve the robustness of the model against temporal content perturbation of videos. Our method is model-agnostic and can be easily compatible with various VideoQA backbones. Extensive experimental results and analyses on several public datasets show the advantage of our method over the state-of-the-art methods in terms of both accuracy and robustness.

关键词： video question answering cross-modality fusion contrastive learning cross-media reasoning

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Improving long-term thermal stability in twin-roll cast Al-Mg-Si-Cu alloys by optimizing Mg/Si ratios

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材料科学技术（英文版） 2025年第3期206卷 164-175页

作者： Shao-You Zhang Yuan-Ting Mo Zhen-Ming Hua Xu Liu Ze-Tian Liu Hui-Yuan Wang School of Material Science and Engineering Hebei University of TechnologyTianjin 300130PR China Key Laboratory of Automobile Materials of Ministry of Education & School of Materials Science and Engineering Jilin UniversityNanling CampusChangchun 130025PR China International Center of Future Science Jilin UniversityChangchun 130012PR China School of Material Science and Engineering Hebei University of TechnologyTianjin 300130PR China School of Materials Science and Engineering Inner Mongolia University of TechnologyHohhot 010051PR China School of Material Science and Engineering Hebei University of TechnologyTianjin 300130PR China Key Laboratory of Automobile Materials of Ministry of Education & School of Materials Science and Engineering Jilin UniversityNanling CampusChangchun 130025PR China International Center of Future Science Jilin UniversityChangchun 130012PR China

Achieving high thermal stability in the 6xxx series alloys remains a challenging task,which limits their engineering ***,Al-Mg-Si-Cu alloys with various Mg/Si ratios(0.5,1,2,and 4)were fab-ricated by twin-roll casting(TRC),and the microstructure evolution and mechanical properties during long-term thermal exposure of 150 ℃/1000 h were *** results disclosed that alloys with a high Mg/Si ratio exhibited better thermal *** alloys with the Mg/Si ratio of 2(Mg/Si～2)achieved a stable high yield strength of～330 MPa and meanwhile maintained a satisfactory fracture elongation(＞10％)throughout the thermal exposure *** excellent thermal stability can be attributed to the microstructure consisting of high-density L phases and fine α-AlFeSi phases,which was related to the optimized Mg/Si ***,L phases were dominated in peak-aged Mg/Si～2 alloys,while the counterparts in alloys with the Mg/Si ratio of 1(Mg/Si～1)were β"and Q'*** the thermal exposure process,the L phases remained stable without coarsening,which was mainly due to the high coherence and low interfacial energy of the L-matrix ***,the main Fe-containing phases in Mg/Si～2 and Mg/Si～1 alloys were fine near-spheroidal α-AlFeSi and large-size needle-like β-AlFeSi,re-spectively,which lead to a better ductility of Mg/Si～2 *** work may provide a strategy for the preparation of 6xxx series alloys with high thermal stability.

关键词： Aluminum alloy Twin-roll casting Thermal stability Microstructure evolution Mechanical properties

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