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Transient NOE driven signal enhancement of INADEQUATE solid-state NMR spectroscopy for the structural analysis of rubbers

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Magnetic Resonance Letters 2024年第3期4卷 35-41页

作者： Zhiwei Yan Yue-Qi ye Rongchun Zhang South China Advanced Institute for Soft Matter Science and Technology(AISMST) School of Emergent Soft Matter(SESM)South China University of TechnologyGuangzhou510640China JEOL(Beijing)Co. Ltd.Haidian DistrictBeijing100190China JEOL Ltd. MusashinoAkishimaTokyo196-8558Japan Guangdong Provincial Key Laboratory of Functional and Intelligent Hybrid Materials and Devices South China University of TechnologyGuangzhou510640China

INADEQUATE(Incredible Natural Abundance DoublE QUAntum Transfer Experiment)is one of the most important techniques in revealing the carbon skeleton of organic solids in solid-state NMR ***,its use for structural analysis is quite limited due to the low natural abundance of^(13)C-^(13)C connectivity(~0.01%)and thus low ***,in semi-solids like rubbers,the sensitivity will be further significantly reduced by the inefficient cross polarization from 1H to^(13)C due to molecular motions induced averaging of^(1)H-^(13)C dipolar ***,in this study,we demonstrate that transient nuclear Overhauser effect(NOE)can be used to efficiently enhance^(13)C signals,and thus enable rapid acquisition of two-dimensional(2D)^(13)C INADEQUATE spectra of *** chlorobutyl rubber as the model system,it is found that an overall signalto-noise ratio(SNR)enhancement about 22%can be achieved,leading to significant timesaving by about 33%as compared to the direct polarization-based INADEQUATE *** experimental results on natural rubber and ethylene propylene diene monomer(EPDM)rubber are also shown to demonstrate the robust performance of transient NOE enhanced INADEQUATE experiment.

关键词： Transient NOE INADEQUATE Carbon skeleton Rubbers

Discriminatively Constrained Semi-Supervised Multi-View Nonnegative Matrix Factorization with Graph Regularization

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Big Data Mining and Analytics 2024年第1期7卷 55-74页

作者： Guosheng Cui ye Li Jianzhong Li Jianping Fan Shenzhen Institute of Advanced Technology Chinese Academy of SciencesShenzhen 518055China Joint Engineering Research Center for Health Big Data Intelligent Analysis Technology Shenzhen 518055China University of Chinese Academy of Sciences Beijing 100049China School of Computer Science and Control Engineering Shenzhen Institute of Advanced TechnologyChinese Academy of SciencesShenzhen 518055China

Nonnegative Matrix Factorization(NMF)is one of the most popular feature learning technologies in the field of machine learning and pattern *** has been widely used and studied in the multi-view clustering tasks because of its *** study proposes a general semi-supervised multi-view nonnegative matrix factorization *** algorithm incorporates discriminative and geometric information on data to learn a better-fused representation,and adopts a feature normalizing strategy to align the different *** specific implementations of this algorithm are developed to validate the effectiveness of the proposed framework:Graph regularization based Discriminatively Constrained Multi-View Nonnegative Matrix Factorization(GDCMVNMF)and Extended Multi-View Constrained Nonnegative Matrix Factorization(ExMVCNMF).The intrinsic connection between these two specific implementations is discussed,and the optimization based on multiply update rules is *** on six datasets show that the effectiveness of GDCMVNMF and ExMVCNMF outperforms several representative unsupervised and semi-supervised multi-view NMF approaches.

关键词： multi-view semi-supervised clustering discriminative information geometric information feature normalizing strategy

Evolution and Determinants of Population Agglomeration in Less Developed Metropolitan Areas:A Case Study of the Taiyuan Metropolitan Area,China

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Chinese Geographical Science 2024年第4期34卷 739-751页

作者： QIN Zhiqin LIANG ye AN Shuwei DOU Yongjing School of Economics and Management Shanxi UniversityTaiyuan 030031China School of Urban Economics and Public Affairs Capital University of Economics and BusinessBeijing 100070China School of Geography Science Taiyuan Normal UniversityJinzhong 030619China

It is of importance to enhance the urban areas'capacity for population aggregation in underdeveloped regions,aiming to rectify the imbalanced and insufficient pattern of economic development in *** the Taiyuan Metropolitan Area(TMA)in central China as a case study,this paper examines the evolutionary process and characteristics of population agglomeration from 2000 to 2020,and identifies factors associated with agglomeration and their spatial *** findings indicated that:1)against the background of sustained population shrinkage in the provincial area,the TMA showed a demographic trend of steady increase,albeit with a decelerated growth *** the metropolitan area,urban population size continued to grow rapidly,whereas the rural areas endured sustained *** in city size continued to widen,and the polarization of concentrated population in the core cities kept increasing.2)Agglomerations in both secondary and service industries had significant positive effects on local population agglomeration,with the former effect being *** economic development,government fiscal expenditure,and financial advancement all contributed to facilitating local population *** a spatial spillover perspective,service agglomeration and financial development promoted population agglomeration in surrounding ***,fiscal expenditure inhibited such *** for industrial agglomeration and regional economic development,their spatial spillover effects were *** results obtained reveal several policy implications aimed at enhancing the population agglomeration capacity of the metropolitan area in underdeveloped regions during the new era.

关键词： population agglomeration population shrinkage spatial spillover effects Taiyuan Metropolitan Area(TMA) China

Social Robot Detection Method with Improved Graph Neural Networks

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Computers, Materials & Continua 2024年第2期78卷 1773-1795页

作者： Zhenhua Yu Liangxue Bai Ou ye Xuya Cong Institute of Systems Security and Control College of Computer Science and TechnologyXi’an University of Science and TechnologyXi’an710054China

Social robot accounts controlled by artificial intelligence or humans are active in social networks,bringing negative impacts to network security and social *** social robot detection methods based on graph neural networks suffer from the problem of many social network nodes and complex relationships,which makes it difficult to accurately describe the difference between the topological relations of nodes,resulting in low detection accuracy of social *** paper proposes a social robot detection method with the use of an improved neural ***,social relationship subgraphs are constructed by leveraging the user’s social network to disentangle intricate social relationships ***,a linear modulated graph attention residual network model is devised to extract the node and network topology features of the social relation subgraph,thereby generating comprehensive social relation subgraph features,and the feature-wise linear modulation module of the model can better learn the differences between the ***,user text content and behavioral gene sequences are extracted to construct social behavioral features combined with the social relationship subgraph ***,social robots can be more accurately identified by combining user behavioral and relationship *** carrying out experimental studies based on the publicly available datasets TwiBot-20 and Cresci-15,the suggested method’s detection accuracies can achieve 86.73%and 97.86%,*** with the existing mainstream approaches,the accuracy of the proposed method is 2.2.and 1.35%higher on the two *** results show that the method proposed in this paper can effectively detect social robots and maintain a healthy ecological environment of social networks.

关键词： Social robot detection social relationship subgraph graph attention network feature linear modulation behavioral gene sequences

Studying the effect of surfactant assisted low-salinity water flooding on clay-rich sandstones

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Petroleum 2024年第2期10卷 306-318页

作者： Saeed Khezerloo-ye Aghdam Alireza Kazemi Mohammad Ahmadi Department of Petroleum Engineering Amirkabir University of Technology(AUT)TehranIran Department of Petroleum and Chemical Engineering College of EngineeringSultan Qaboos UniversityMuscatOman

Sandstone reservoirs often contain clay particles that can cause damage and reduce permeability during low-salinity water *** this study,the effect of surfactants on fine migration in clay-rich sandstones and its impact on oil recovery was ***,the impact of surfactants on interparticle forces in fine-matrix,fine-fine,and oil-matrix systems was *** results showed that both CTAB(cetyltrimethyl ammonium bromide)and QS(quillaja saponin)cause EDL compaction,weakening the repulsive ***,SDS(sodium dodecyl sulfate)and TX(triton X-100)do not affect the ***,the effect of surfactants on IFT reduction and wettability alteration was experimentally *** surfactants reduced IFT due to the surface excessive concentration *** wettability alteration experiment illustrated that although QS and CTAB compact EDL around oil and matrix particles leading to attraction force augmentation,they both alter wettability through adsorption on matrix and carboxylic groups present in crude oil,*** aqueous solutions were then injected into various clay-rich sandstone sanpacks,which resulted in increased oil ***,the mechanisms leading to enhanced oil recovery variedby surfactant *** increased recovery by 10%through IFT reduction and wettability alteration,while SDS and TX increased recovery by 12.and 9%,respectively,through wettability alteration and extreme fine *** contrast,partial fine migration in the QS flooding experiment reached a recovery increase of 18%.Permeability trends through experiments were also *** CTAB injection,permeability did not reduce,while QS aqueous solution reduced rock permeability to 5 m *** and TX reduced the magnitude of permeability to 2 m *** conclusion,this study demonstrates that surfactants can effectively improve oil recovery in clay-rich sandstones by altering the interparticle forces,reducing IFT,and changing *** results

关键词： Surfactant flooding Smart water Fine migration Recovery factor

A Blockchain and CP-ABE Based Access Control Scheme with Fine-Grained Revocation of Attributes in Cloud Health

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Computers, Materials & Continua 2024年第2期78卷 2787-2811页

作者： ye Lu Tao Feng Chunyan Liu Wenbo Zhang School of Computer&Communication Lanzhou University of TechnologyLanzhou730000China School of Economics&Management Lanzhou University of TechnologyLanzhou730000China School of Computer Science Baoji University of Arts and ScienceBaoji721000China

The Access control scheme is an effective method to protect user data *** access control scheme based on blockchain and ciphertext policy attribute encryption(CP–ABE)can solve the problems of single—point of failure and lack of trust in the centralized ***,it also brings new problems to the health information in the cloud storage environment,such as attribute leakage,low consensus efficiency,complex permission updates,and so *** paper proposes an access control scheme with fine-grained attribute revocation,keyword search,and traceability of the attribute private key distribution *** technology tracks the authorization of attribute private *** credit scoring method improves the Raft protocol in consensus ***,the interplanetary file system(IPFS)addresses the capacity deficit of *** the premise of hiding policy,the research proposes a fine-grained access control method based on users,user attributes,and file *** optimizes the data-sharing *** the same time,Proxy Re-Encryption(PRE)technology is used to update the access *** proposed scheme proved to be *** analysis and experimental results show that the proposed scheme has higher efficiency and more *** can meet the needs of medical institutions.

关键词： Blockchain access-control CP-ABE cloud health

Energy-information trade-off induces continuous and discontinuous phase transitions in lateral predictive coding

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Science China(Physics,Mechanics & Astronomy) 2024年第6期67卷 79-85页

作者： Zhen-ye Huang Ruyi Zhou Miao Huang Hai-Jun Zhou Key Laboratory for Theoretical Physics Institute of Theoretical PhysicsChinese Academy of SciencesBeijing 100190China School of Physical Sciences University of Chinese Academy of SciencesBeijing 100049China School of Optics and Photonics Beijing Institute of TechnologyBeijing 100081China Minjiang Collaborative Center for Theoretical Physics Minjiang UniversityFuzhou 350108China

Lateral predictive coding is a recurrent neural network that creates energy-efficient internal representations by exploiting statistical regularity in sensory ***,we analytically investigate the trade-off between information robustness and energy in a linear model of lateral predictive coding and numerically minimize a free energy *** observed several phase transitions in the synaptic weight matrix,particularly a continuous transition that breaks reciprocity and permutation symmetry and builds cyclic dominance and a discontinuous transition with the associated sudden emergence of tight balance between excitatory and inhibitory *** optimal network follows an ideal gas law over an extended temperature range and saturates the efficiency upper bound of energy *** results provide theoretical insights into the emergence and evolution of complex internal models in predictive processing systems.

关键词： predictive coding recurrent neural network phase transition internal model free energy

Degradation-adaptive neural network for jointly single image dehazing and desnowing

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Frontiers of Computer Science 2024年第2期18卷 247-249页

作者： Erkang CHEN Sixiang CHEN Tian ye Yun LIU School of Ocean Information Engineering Jimei UniversityXiamen 361021 China College of Artificial Intelligence Southwest UniversityChongqing 400715 China

1 Introduction In harsh winter scenes,the captured images often suffer from hazeand snowdegradationssimultaneously,which significantly affect the performance of high-level computer vision ***,most existing dehazing methods[1-4]and desnowing methods[5-7]are specialized to address only one type of weather-related degradation,and they struggle to effectively handle multiple types of degradations.

关键词： neural handle computer

Impact and prediction of pollutant on mangrove and carbon stocks:A machine learning study based on urban remote sensing data

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Geoscience Frontiers 2024年第3期15卷 401-418页

作者： Mengjie Xu Chuanwang Sun Yanhong Zhan ye Liu Institute of Artificial Intelligence Xiamen UniversityXiamen 361005FujianChina China Center for Energy Economics Research School of EconomicsXiamen UniversityXiamen 361005FujianChina Laboratory of Smart Energy and Green Economy Institute of Artificial IntelligenceXiamen UniversityXiamen 361005FujianChina Department of Public Finance School of EconomicsXiamen UniversityXiamen 361005China

Mangrove ecosystems have important ecological and economic values,especially their ability to store ***,in recent years,human disturbance has accelerated mangrove *** them,the emission of pollutants cannot be *** is of great significance for carbon emission reduction and ecological protection to study the impacts of different pollutants on mangroves and their carbon *** on the remote sensing data of coastal areas south of the Yangtze River in China's Mainland,this paper builds the ensemble learning model Random Forest(RF)and Gradient Boosting Regression(GBR)to empirically analyse the relationship between industrial wastewater,industrial sulfur dioxide(SO2),PM2.5 and mangrove *** results show that the pollutant concentration of meteorological normalisation is more *** importance of pollutants presents regional *** area of mangroves in different cities and the corresponding total carbon stocks show different trends with the increase or decrease of pollutants,and there is a dynamic balance between urban pollutant discharge and mangrove growth in some *** research in this paper provides an analysis and explanation from the perspective of machine learning to explore the relationship between mangroves and pollutants and at the same time,provides scientific suggestions for the formulation of future pollutant emission policies in different cities.

关键词： Mangrove forests Pollutants Machine learning model Carbon stocks Regional heterogeneity