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Chinese Journal of Chemistry 2024年第14期42卷 1571-1581页

作者： Yongjie Chen Yanwei wang Jun Nong Dan Yuan Yingming Yao Key Laboratory of Organic Synthesis of Jiangsu Province College of ChemistryChemical Engineering and Materials ScienceDushu Lake CampusSoochow UniversitySuzhouJiangsu215123 China

Eight zwitterionic rare earth metal complexes stabilized by amino-bridged tris(phenolato)ligands bearing quaternary ammonium side-arms were synthesized and *** complexes were used as single-component catalysts for the cycloaddition of CO_(2)and epoxides,and their catalytic activities are obviously higher than those of their binary *** studies revealed that the halide anions(Cl^(–),Br^(–),I^(–))and the metal complexes influenced the catalytic activity,and the lanthanum complex bearing iodide anion showed the highest catalytic activity for this addition reaction.A variety of mono-substituted epoxides were converted to cyclic carbonates in good to excellent yields(55%—99%)with high selectivity(>99%)at 30℃and 1 bar CO_(2),whereas internal epoxides required higher both reaction temperatures(60—120℃)and catalyst loading(2 mol%)for high *** catalyst was recyclable for four times without noticeable loss of catalytic *** on the results of kinetic studies and in℃situ IR reactions,a plausible reaction mechanism was proposed.

关键词： Bifunctional catalyst Carbon dioxide Cyclic carbonate Rare-earth metal Tris(phenolato)ligand Insertion Cycloaddition C1 building blocks

Afterglow Nanoprobes for In-vitro Background-free Biomarker Analysis

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Chemical Research in Chinese Universities 2024年第2期40卷 213-224页

作者： ZHENG Ting wang Ying LI Xianming LI Chenghui WU Peng Analytical&Testing Centre State Key Laboratory of Hydraulics and Mountain River EngineeringSichuan UniversityChengdu610064P.R.China School of Chemistry and Chemical Engineering Henan Normal UniversityXinxiang453007P.R.China Department of Rheumatology and Immunology West China HospitalSichuan UniversityChengdu610064P.R.China

Accurate detection of biomarkers is essential for disease *** the highly sensitive fluorescence probes are feasible for the above goal,it is typically interfered by the auto-fluorescence and light scattering of the biological *** afterglow system(consisting of photosensitizer,afterglow substrate and emitter)based on cascade photochemical reactions exhibits long-lived luminescence(seconds to hours),thus avoiding background *** the assistance of polymers,such as polystyrene microspheres,the photochemical afterglow systems have been transformed into homogeneous and water-soluble nanoparticles,and used for in-vitro biomarker ***,we summarized the principle,preparation and applications of these afterglow nanoparticles,and evaluated their performance in clinical sample testing by comparing with other nanoparticle-based ***,several problems and possible solutions of afterglow nanoparticle-based methods in biomarker determination were also mentioned.

关键词： Photochemical afterglow In-vitro analysis Background-free detection Biomarker

NFT Security Matrix:Towards Modeling NFT Ecosystem Threat

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Computer Modeling in Engineering & Sciences 2024年第6期139卷 3255-3285页

作者： Peng Liao Chaoge Liu Jie Yin Zhi wang Xiang Cui Key Laboratory of Trustworthy Distributed Computing and Service Beijing University of Posts and TelecommunicationsBeijing100876China Zhongguancun Laboratory Beijing100094China Institute of Information Engineering Chinese Academy of SciencesBeijing100085China

Digital assets have boomed over the past few years with the emergence of Non-fungible Tokens(NFTs).To be specific,the total trading volume of digital assets reached an astounding$55.5 billion in ***,numerous security concerns have been raised by the rapid expansion of the NFT *** holders are exposed to a plethora of scams and traps,putting their digital assets at risk of being ***,academic research on NFT security is scarce,and the security issues have aroused rare *** this study,the NFT ecological process is comprehensively *** process falls into five different stages encompassing the entire lifecycle of ***,the security issues regarding the respective stage are elaborated and analyzed in depth.A matrix model is proposed as a novel contribution to the categorization of NFT security *** data are collected from social networks,the Ethereum blockchain,and NFT markets to substantiate our claims regarding the severity of security concerns in the NFT *** this comprehensive dataset,nine key NFT security issues are identified from the matrix model and then subjected to qualitative and quantitative *** study aims to shed light on the severity of NFT ecosystem security *** findings stress the need for increased attention and proactive measures to safeguard the NFT ecosystem.

关键词： Non-fungible token blockchain cyber security

Graph Convolutional Networks Embedding Textual Structure Information for Relation Extraction

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Computers, Materials & Continua 2024年第5期79卷 3299-3314页

作者： Chuyuan Wei Jinzhe Li Zhiyuan wang Shanshan Wan Maozu Guo School of Electrical and Information Engineering Beijing University of Civil Engineering and ArchitectureBeijing102616China

Deep neural network-based relational extraction research has made significant progress in recent years,andit provides data support for many natural language processing downstream tasks such as building knowledgegraph,sentiment analysis and question-answering ***,previous studies ignored much unusedstructural information in sentences that could enhance the performance of the relation extraction ***,most existing dependency-based models utilize self-attention to distinguish the importance of context,whichhardly deals withmultiple-structure *** efficiently leverage multiple structure information,this paperproposes a dynamic structure attention mechanism model based on textual structure information,which deeplyintegrates word embedding,named entity recognition labels,part of speech,dependency tree and dependency typeinto a graph convolutional ***,our model extracts text features of different structures from theinput *** Structure information Graph Convolutional Networks employs the dynamic structureattention mechanism to learn multi-structure attention,effectively distinguishing important contextual features invarious structural *** addition,multi-structure weights are carefully designed as amergingmechanismin the different structure attention to dynamically adjust the final *** paper combines these featuresand trains a graph convolutional network for relation *** experiment on supervised relation extractiondatasets including SemEval 2010 Task 8,TACRED,TACREV,and Re-TACED,the result significantly outperformsthe previous.

关键词： Relation extraction graph convolutional neural networks dependency tree dynamic structure attention

Advances in poly(heptazine imide)/poly(triazine imide) photocatalyst

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Chinese Chemical Letters 2024年第10期35卷 128-151页

作者： Haojie Song Laiyu Luo Siyu wang Guo Zhang Baojiang Jiang Key Laboratory of Functional Inorganic Material Chemistry Ministry of Education of the People's Republic of China School of Chemistry and Materials Science Heilongjiang University

Polymeric carbon nitride （PCN） has garnered increasing attention as a metal-free photocatalyst with a suitable band *** efforts to enhance its photocatalytic performance,researchers have examined various PCN materials,including poly（heptazine imide）(PHI) and poly（triazine imide）(PTI),two isomers within the PCN family that exhibit distinct and superior photocatalytic activity compared to other *** challenge,however,lies in the common practice among researchers to categorize PHI and PTI along with other PCN types under the overarching term“g-C3N4,”which significantly impedes optimization *** objective of this review is to provide comprehensive insights into the structural features,photoelectrochemical properties,and effective characterization methods employed for distinguishing between PHI and PTI *** review also summarizes various optimization strategies,such as crystallinity adjustments,defect engineering,morphology control,constructing heterojunction,and atomic-level metal loading dispersion,to elevate the photocatalytic activity of PHI and PTI,in addition to summarizing the history of carbon nitride ***,this review highlights the primary applications of PHI and PTI,encompassing nitrogen fixation,biomass conversion,organic synthesis,CO2reduction,pollutant degradation,H2O2production,and photocatalytic water ***,the prospects and challenges associated with further advancing PHI and PTI are thoroughly examined.

关键词： Application Modification Photocatalytic Poly(heptazine imide) Poly(triazine imide)

Abnormal Traffic Detection for Internet of Things Based on an Improved Residual Network

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Computers, Materials & Continua 2024年第6期79卷 4433-4448页

作者： Tingting Su Jia wang Wei Hu Gaoqiang Dong Jeon Gwanggil School of Computer Science and Technology Xinjiang UniversityUrumqi830046China School of Cyber Science and Engineering Jinling Institute of Technology CityNanjing210000China College of Information Technology Incheon National UniversityIncheon22012Korea

Along with the progression of Internet of Things(IoT)technology,network terminals are becoming continuously more *** has been widely applied in various scenarios,including urban infrastructure,transportation,industry,personal life,and other socio-economic *** introduction of deep learning has brought new security challenges,like an increment in abnormal traffic,which threatens network *** feature extraction leads to less accurate classification *** abnormal traffic detection,the data of network traffic is high-dimensional and *** data not only increases the computational burden of model training but also makes information extraction more *** address these issues,this paper proposes an MD-MRD-ResNeXt model for abnormal network traffic *** fully utilize the multi-scale information in network traffic,a Multi-scale Dilated feature extraction(MD)block is *** module can effectively understand and process information at various scales and uses dilated convolution technology to significantly broaden the model’s receptive *** proposed Max-feature-map Residual with Dual-channel pooling(MRD)block integrates the maximum feature map with the residual *** module ensures the model focuses on key information,thereby optimizing computational efficiency and reducing unnecessary information *** results show that compared to the latest methods,the proposed abnormal traffic detection model improves accuracy by about 2%.

关键词： Abnormal network traffic deep learning residual network multi-scale feature extraction max-feature-map

Identification and characterization of FpRco1 in regulating vegetative growth and pathogenicity based on T-DNA insertion in Fusarium pseudograminearum

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Journal of Integrative Agriculture 2024年第9期23卷 3055-3065页

作者： Haiyang Li Yuan Zhang Cancan Qin Zhifang wang Lingjun Hao Panpan Zhang Yongqiang Yuan Chaopu Ding Mengxuan wang Feifei Zan Jiaxing Meng Xunyu Zhuang Zheran Liu Limin wang Haifeng Zhou Linlin Chen Min wang Xiaoping Xing Hongxia Yuan Honglian Li Shengli Ding College of Plant Protection Henan Agricultural UniversityZhengzhou 450046China National Key Laboratory of Wheat and Maize Crop Science Zhengzhou 450046China Henan Plant Health Protection Technology Engineering Research Center Zhenzhou 450046China

Fusarium pseudograminearum is a devastating pathogen that causes Fusarium crown rot(FCR)in wheat and poses a significant threat to wheat production in terms of grain yield and ***,the mechanism by which *** infects wheat remains *** this study,we aimed to elucidate these mechanisms by constructing a T-DNA insertion mutant library for the highly virulent strain WZ-8A of *** screening this mutant library,we identified nine independent mutants that displayed impaired pathogenesis in barley *** these mutants,one possessed a disruption in the gene FpRCO1 that is an ortholog of Saccharomyces cerevisiae RCO1,encoding essential component of the Rpd3S histone deacetylase complex in *** further investigate the role of FpRCO1 in ***,we employed a split-marker approach to knock out FpRCO1 in *** ***1 deletion mutants exhibit reduced vegetative growth,conidium production,and virulence in wheat coleoptiles and barley leaves,whereas the complementary strain restores these ***,under stress conditions,the FpRCO1 deletion mutants exhibited increased sensitivity to NaCl,sorbitol,and SDS,but possessed reduced sensitivity to H_(2)O_(2)compared to these characteristics in the wild-type ***-seq analysis revealed that deletion of FpRCO1 affected gene expression(particularly the downregulation of TRI gene expression),thus resulting in significantly reduced deoxynivalenol(DON)*** summary,our findings highlight the pivotal role of FpRCO1 in regulating vegetative growth and development,asexual reproduction,DON production,and pathogenicity of *** study provides valuable insights into the molecular mechanisms underlying *** infection in wheat and may pave the way for the development of novel strategies to combat this devastating disease.

关键词： Fusarium pseudograminearum T-DNA insertion Rpd3S complex FpRCO1 pathogenicity DON production

Rethinking multi-spatial information for transferable adversarial attacks on speaker recognition systems

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CAAI Transactions on Intelligence Technology 2024年第3期9卷 620-631页

作者： Junjian Zhang Hao Tan Le wang Yaguan Qian Zhaoquan Gu Guangzhou University GuangzhouChina Department of New Networks Peng Cheng LaboratoryShenzhenChina Harbin Institute of Technology(Shenzhen) ShenzhenChina Zhejiang University of Science and Technology HangzhouChina

Adversarial attacks have been posing significant security concerns to intelligent systems,such as speaker recognition systems(SRSs).Most attacks assume the neural networks in the systems are known beforehand,while black-box attacks are proposed without such information to meet practical *** black-box attacks improve trans-ferability by integrating multiple models or training on multiple datasets,but these methods are *** by the optimisation strategy with spatial information on the perturbed paths and samples,we propose a Dual Spatial Momentum Iterative Fast Gradient Sign Method(DS-MI-FGSM)to improve the transferability of black-box at-tacks against ***,DS-MI-FGSM only needs a single data and one model as the input;by extending to the data and model neighbouring spaces,it generates adver-sarial examples against the integrating *** reduce the risk of overfitting,DS-MI-FGSM also introduces gradient masking to improve *** authors conduct extensive experiments regarding the speaker recognition task,and the results demonstrate the effectiveness of their method,which can achieve up to 92%attack success rate on the victim model in black-box scenarios with only one known model.

关键词： speaker recognition spoofing attacks

Deep Broad Learning for Emotion Classification in Textual Conversations

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Tsinghua Science and Technology 2024年第2期29卷 481-491页

作者： Sancheng Peng Rong Zeng Hongzhan Liu Lihong Cao Guojun wang Jianguo Xie Center for Linguistics and Applied Linguistics and Laboratory of Language Engineering and ComputingGuangdong University of Foreign StudiesGuangzhou 510006China Guangdong Provincial Key Laboratory of Nanophotonic Functional Materials and Devices South China Normal UniversityGuangzhou 510006China School of Computer Science and Cyber Engineering Guangzhou UniversityGuangzhou 510006China Modern Education Technology Center Guangdong University of Foreign StudiesGuangzhou 510006China

Emotion classification in textual conversations focuses on classifying the emotion of each utterance from textual *** is becoming one of the most important tasks for natural language processing in recent ***,it is a challenging task for machines to conduct emotion classification in textual conversations because emotions rely heavily on textual *** address the challenge,we propose a method to classify emotion in textual conversations,by integrating the advantages of deep learning and broad learning,namely *** aims to provide a more effective solution to capture local contextual information(i.e.,utterance-level)in an utterance,as well as global contextual information(i.e.,speaker-level)in a conversation,based on Convolutional Neural Network(CNN),Bidirectional Long Short-Term Memory(Bi-LSTM),and broad *** experiments have been conducted on three public textual conversation datasets,which show that the context in both utterance-level and speaker-level is consistently beneficial to the performance of emotion *** addition,the results show that our proposed method outperforms the baseline methods on most of the testing datasets in weighted-average F1.

关键词： emotion classification textual conversation Convolutional Neural Network(CNN) Bidirectional Long Short-Term Memory(Bi-LSTM) broad learning

Attack based on data: a novel perspective to attack sensitive points directly

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Cybersecurity 2024年第3期7卷 111-123页

作者： Yuyao Ge Zhongguo Yang Lizhe Chen Yiming wang Chengyang Li School of Information Science and Technology North China University of TechnologyBeijingChina Bejing Key Laboratory on Integration and Analysis of Large-Scale Stream Data North China University of TechnologyBeijingChina School of Computer Science Peking UniversityBeijingChina

Adversarial attack for time-series classification model is widely explored and many attack methods are *** there is not a method of attack based on the data *** this paper,we innovatively proposed a black-box sparse attack method based on data *** method directly attack the sensitive points in the time-series data accord-ing to statistical features extract from the *** frst,we have validated the transferability of sensitive points among DNNs with different ***,we use the statistical features extract from the dataset and the sensi-tive rate of each point as the training set to train the predictive ***,predicting the sensitive rate of test set by predictive ***,perturbing according to the sensitive *** attack is limited by constraining the LO norm to achieve one-point *** conduct experiments on several datasets to validate the effectiveness of this method.

关键词： Black-box adversarial attack Time series classification Data mining