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Improved Subsynchronous Oscillation Parameter Identification with Synchrophasor Based on Matrix Pencil Method in Power Systems

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Journal of Modern Power Systems and Clean Energy 2024年第1期12卷 22-33页

作者： Xiaoxue Zhang fang Zhang Wenzhong gao Jinghan He the School of Electrical Engineering Beijing Jiaotong UniversityBeijing 100044China the Department of Electrical and Computer Engineering University of DenverDenverUSA

The subsynchronous oscillations(SSOs)related to renewable generation seriously affect the stability and safety of the power *** realize the dynamic monitoring of SSOs by utilizing the high computational efficiency and noise-resilient features of the matrix pencil method(MPM),this paper propos es an improved MPM-based parameter identification with syn *** MPM is enhanced by the angular frequency fitting equations based on the characteristic polynomial coeffi cients of the matrix pencil to ensure the accuracy of the identi fied parameters,since the existing eigenvalue solution of the MPM ignores the angular frequency conjugation constraints of the two fundamental modes and two oscillation ***,the identification and recovery of bad data are proposed by uti lizing the difference in temporal continuity of the synchropha sors before and after noise *** proposed parameter identification is verified with synthetic,simulated,and actual measured phase measurement unit(PMU)*** with the existing MPM,the improved MPM achieves better accuracy for parameter identification of each component in SSOs,better real-time performance,and significantly reduces the effect of bad data.

关键词： Subsynchronous oscillations(SSOs) synchrophasor parameter identification matrix pencil method bad data

Photocatalytic Activity Enhancement in Organic Dyes Degradation by Loading Ag Nanoparticles onto α-Fe_(2)O_(3)/ZnOs

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Journal of Wuhan University of Technology(Materials Science) 2024年第2期39卷 309-314页

作者：李保六 MENG Xinrui YUE Yifan gao fang Key laboratory of Hubei Province for Coal Conversion and New Carbon Materials Wuhan University of Science and TechnologyWuhan 430081China

Fe_(2)O_(3)/ZnO/Ag ternary composite photocatalytic material was prepared by simple hydrothermal method,and its structure and photocatalytic properties were *** experimental results show that Fe_(2)O_(3)/ZnO/Ag exhibits better photocatalytic *** two hours of UV irradiation,the degradation rates of orange Ⅱ and methyl orange reached 91.9% and 75.9%,*** design and preparation of the photocatalyst provide a theoretical basis for the practical application of photocatalytic technology.

关键词： Fe_(2)O_(3) ZnO composites photocatalysis

Cascaded four-wave mixing all-optical wavelength converter based on highly nonlinear fiber deposited graphene oxide

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Journal of Materials Science & Technology 2024年第4期171卷 10-15页

作者： Yuanhongliu gao Xiaoyu Chen Tonglei Cheng fang Wang Xin Yan College of Information Science and Engineering State Key Laboratory of Synthetical Automation for Process IndustriesNortheastern UniversityShenyang 110819China

The all-optical wavelength conversion using cascaded four-wave mixing(FWM)phenomena with graphene oxide(GO)and a highly nonlinear fiber(HNLF)device is demonstrated *** has a strong third-order nonlinear effect and is an excellent nonlinear optical material for nonlinear optical wavelength *** group velocity matching of pump and signal,HNLF,and GO amplification promote the cascaded nonlinear frequency mixing *** the experimental and analytical results,the maximum spacing between signal and pump is 21 nm,and specifically,the order of cascaded FWM light increases from order 1 to order 2 with increasing GO,and the first-order FWM conversion effi-ciency increases to a maximum of−14.5 *** the best of our knowledge,this is the first time that cascaded FWM-based all-optical wavelength conversion in HNLF-GO with wide wavelength selectivity is investigated with combined pump and signal *** findings not only provide an effective method for achieving all-optical wavelength conversion in cascaded FWM but also offer the possibility of fabricating high-performance nonlinear optical devices.

关键词： Four-wave mixing Graphene oxide Highly nonlinear fiber Optical wavelength conversion

Förster resonance energy transfer reveals phillygenin and swertiamarin concurrently target AKT on different binding domains to increase the anti-inflammatory effect

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Chinese Chemical Letters 2024年第5期35卷 207-212页

作者： Xiaoyao Ma Jinling Zhang Ge fang He gao Jie gao Li Fu Yuanyuan Hou Gang Bai State Key Laboratory of Medicinal Chemical Biology College of Pharmacy and Tianjin Key Laboratory of Molecular Drug ResearchNankai UniversityTianjin 300000China College of Life Health Dalian UniversityDalian 116622China Dalian Fusheng Pharmaceutical Co. Ltd.Dalian 116000China

The clinical benefit of combination therapy is significant,but it is not easy to define the mechanism of complexity and *** studies illustrate that phillygenin(Phi)binds in the allosteric inhibit pocket of protein kinase B(AKT),and swertiamarin(Swe)acts on the pleckstrin homology(PH)domain of ***,the combined synergistic effect of relieving the inflammatory response has yet to be *** on high sensitivity,specificity and fast-responsibility fluorescent sensors,the Förster resonance energy transfer(FRET)technique offers a route to provide clear insights into physiological and pathological *** the study,molecular docking,the fluorescent probes of Phi and Swe for FRET were designed and *** analysis shown that Swe and Phi concurrently acted on the PH domain and allosterically inhibited pocket of AKT,*** combination of Swe and Phi significantly increased the heat stability of AKT and decreased protease-induced *** lipopolysaccharides(LPS)-induced mice and cells,the combination arrested AKT activation,nuclear factor kappa-B(NF-κB)phosphorylation,and the expression of tumor necrosis factor-α(TNF-α),interleukin(IL)-6 and *** conclusion,FRET revealed Phi and Swe concurrently targeted AKT on different domains and the combination of Phi and Swe enhanced the anti-inflammatory effect.

关键词： FRET Swertiamarin Phillygenin AKT Anti-inflammation Combinatorial drug

Seasonal variation of mesoscale eddy intensity in the global ocean

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Acta Oceanologica Sinica 2024年第1期43卷 48-58页

作者： Yongcan Zu Yue fang Shuangwen Sun Libao gao Yang Yang Guijun Guo First Institute of Oceanography/Key Laboratory of Marine Science and Numerical Modeling Ministry of Natural ResourcesQingdao 266061China Laboratory for Regional Oceanography and Numerical Modeling Laoshan LaboratoryQingdao 266237China Shandong Key Laboratory of Marine Science and Numerical Modeling Qingdao 266061China

Mesoscale eddies are a prominent oceanic phenomenon that plays an important role in oceanic mass transport and energy *** by rotational speed,the eddy intensity is one of the most fundamental properties of an ***,the seasonal spatiotemporal variation in eddy intensity has not been examined from a global ocean *** this study,we unveil the seasonal spatiotemporal characteristics of eddy intensity in the global ocean by using the latest satellite-altimetry-derived eddy trajectory data *** results suggest that the eddy intensity has a distinct seasonal variation,reaching a peak in spring while attaining a minimum in autumn in the Northern Hemisphere and the opposite in the Southern *** seasonal variation of eddy intensity is more intense in the tropical-subtropical transition zones within latitudinal bands between 15°and 30°in the western Pacific Ocean,the northwestern Atlantic Ocean,and the eastern Indian Ocean because baroclinic instability in these areas changes *** analysis found that the seasonal variation of baroclinic instability precedes the eddy intensity by a phase of 2–3 months due to the initial perturbations needing time to grow into mesoscale eddies.

关键词： seasonal variation mesoscale eddy intensity baroclinic instability global ocean

Unlocking efficient energy storage via regulating ion and electron-active subunits:an(SbS)_(1.15)TiS_(2)superlattice for large and fast Na^(+)storage

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Science China Chemistry 2024年第1期67卷 336-342页

作者： Baixin Peng Tianxun Cai Shaoning Zhang Yuqiang fang Zhuoran Lv Yusha gao Fuqiang Huang State Key Laboratory of High Performance Ceramics and Superfine Microstructure Shanghai Institute of CeramicsChinese Academy of SciencesShanghai 200050China Center of Materials Science and Optoelectronics Engineering University of Chinese Academy of SciencesBeijing 100049China School of Physical Science and Technology ShanghaiTech UniversityShanghai 200031China Beijing National Laboratory for Molecular Sciences State Key Laboratory of Rare Earth Materials Chemistry and ApplicationsCollege of Chemistry and Molecular EngineeringPeking UniversityBeijing 100871China

Alloying-type metal sulfides with high sodiation activity and theoretical capacity are promising anode materials for high energy density sodium ion ***,the large volume change and the migratory and aggregation behavior of metal atoms will cause severe capacity decay during the charge/discharge ***,a robust and conductive TiS_(2)framework is integrated with a high-capacity SbS layer to construct a single phase(SbS)_(1.15)TiS_(2)superlattice for both high-capacity and fast Na^(+)*** metallic TiS_(2)sublayer with high electron activity acts as a robust and conductive skeleton to buffer the volume expansion caused by conversion and alloying reaction between Na+and SbS ***,high capacity and high rate capability can be synergistically realized in a single phase(SbS)_(1.15)TiS_(2)*** novel(SbS)_(1.15)TiS_(2)anode has a high charge capacity of 618 mAh g^(-1)at 0.2 C and superior rate performance and cycling stability(205 mAh g^(-1)at 35 C after 2,000 cycles).Furthermore,in situ and ex situ characterizations are applied to get an insight into the multi-step reaction *** integrity of robust Na-Ti-S skeleton during(dis)charge process can be *** superlattice construction idea to integrate the Na^(+)-active unit and electron-active unit would provide a new avenue for exploring high-performance anode materials for advanced sodium-ion batteries.

关键词： (SbS)_(1.15)TiS_(2) sulfides sodium ion battery superlattice fast-charging

MUS Model:A Deep Learning-Based Architecture for IoT Intrusion Detection

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Computers, Materials & Continua 2024年第7期80卷 875-896页

作者： Yu Yan Yu Yang Shen fang Minna gao Yiding Chen College of Information Engineering University of Engineering of the Chinese People’s Armed Police Force(PAP)Xi’an710000China College of Missile Engineering Rocket Force Engineering UniversityXi’an710000China

In the face of the effective popularity of the Internet of Things(IoT),but the frequent occurrence of cybersecurity incidents,various cybersecurity protection means have been proposed and *** them,Intrusion Detection System(IDS)has been proven to be stable and ***,traditional intrusion detection methods have shortcomings such as lowdetection accuracy and inability to effectively identifymalicious *** address the above problems,this paper fully considers the superiority of deep learning models in processing highdimensional data,and reasonable data type conversion methods can extract deep features and detect classification using advanced computer vision techniques to improve classification *** TransformField(MTF)method is used to convert 1Dnetwork traffic data into 2D images,and then the converted 2D images are filtered by UnsharpMasking to enhance the image details by sharpening;to further improve the accuracy of data classification and detection,unlike using the existing high-performance baseline image classification models,a soft-voting integrated model,which integrates three deep learning models,MobileNet,VGGNet and ResNet,to finally obtain an effective IoT intrusion detection architecture:the MUS *** types of experiments are conducted on the publicly available intrusion detection dataset CICIDS2018 and the IoT network traffic dataset N_BaIoT,and the results demonstrate that the accuracy of attack traffic detection is greatly improved,which is not only applicable to the IoT intrusion detection environment,but also to different types of attacks and different network environments,which confirms the effectiveness of the work done.

关键词： Cyberspace security intrusion detection deep learning Markov Transition Fields(MTF) soft voting integration

Enhancing personalized exercise recommendation with student and exercise portraits

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Journal of Electronic Science and Technology 2024年第2期22卷 91-109页

作者： Wei-Wei gao Hui-fang Ma Yan Zhao Jing Wang Quan-Hong Tian College of Computer Science and Engineering Northwest Normal UniversityLanzhou730070China Computer Center of Gansu Province Lanzhou730070China

The exercise recommendation system is emerging as a promising application in online learning scenarios,providing personalized recommendations to assist students with explicit learning *** solutions generally follow a collaborative filtering paradigm,while the implicit connections between students(exercises)have been largely *** this study,we aim to propose an exercise recommendation paradigm that can reveal the latent connections between student-student(exercise-exercise).Specifically,a new framework was proposed,namely personalized exercise recommendation with student and exercise portraits(PERP).It consists of three sequential and interdependent modules:Collaborative student exercise graph(CSEG)construction,joint random walk,and recommendation list ***,CSEG is created as a unified heterogeneous graph with students’response behaviors and student(exercise)***,a joint random walk to take full advantage of the spectral properties of nearly uncoupled Markov chains is performed on CSEG,which allows for full exploration of both similar exercises that students have finished and connections between students(exercises)with similar ***,we propose to optimize the recommendation list to obtain different exercise *** analyses of two public datasets,the results demonstrated that PERP can satisfy novelty,accuracy,and diversity.

关键词： Educational data mining Exercise recommend Joint random walk Nearly uncoupled Markov chains Optimization Personalized learning

An improved transfer learning strategy for short-term cross-building energy prediction usingdata incremental

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Building Simulation 2024年第1期17卷 165-183页

作者： Guannan Li Yubei Wu Chengchu Yan Xi fang Tao Li Jiajia gao Chengliang Xu Zixi Wang School of Urban Construction Wuhan University of Science and TechnologyWuhan 430065China Anhui Province Key Laboratory of Intelligent Building and Building Energy-saving Anhui Jianzhu UniversityHefei 230601China State Key Laboratory of Green Building in Western China Xi'an University of Architecture and TechnologyXi'an 710055China College of Urban Construction Nanjing Tech UniversityNo.200North Zhongshan RoadNanjing 210009China Key Laboratory of Low-grade Energy Utilization Technologies and Systems(Chongqing University) Ministry of Education of ChinaChongqing UniversityChongqing 400044China College of Civil Engineering Hunan UniversityChangsha 410082China Hubei Provincial Engineering Research Center of Urban Regeneration Wuhan University of Science and TechnologyWuhan 430065China

The available modelling data shortage issue makes it difficult to guarantee the performance of data-driven building energy prediction(BEP)models for both the newly built buildings and existing information-poor *** knowledge transfer learning(KTL)and data incremental learning(DIL)can address the data shortage issue of such *** new building scenarios with continuous data accumulation,the performance of BEP models has not been fully investigated considering the data accumulation ***,which can learn dynamic features from accumulated data adapting to the developing trend of new building time-series data and extend BEP model's knowledge,has been rarely *** studies have shown that the performance of KTL models trained with fixed data can be further improved in scenarios with dynamically changing ***,this study proposes an improved transfer learning cross-BEP strategy continuously updated using the coarse data incremental(CDI)*** hybrid KTL-DIL strategy(LSTM-DANN-CDI)uses domain adversarial neural network(DANN)for KLT and long short-term memory(LSTM)as the Baseline BEP *** evaluation is conducted to systematically qualify the effectiveness and applicability of KTL and improved ***-world data from six-type 36 buildings of six types are adopted to evaluate the performance of KTL and KTL-DIL in data-driven BEP tasks considering factors like the model increment time interval,the available target and source building data *** with LSTM,results indicate that KTL(LSTM-DANN)and the proposed KTL-DIL(LSTM-DANN-CDI)can significantly improve the BEP performance for new buildings with limited *** with the pure KTL strategy LSTM-DANN,the improved KTL-DIL strategy LSTM-DANN-CDI has better prediction performance with an average performance improvement ratio of 60%.

关键词： building energy prediction(BEP) cross-building data incremental learning(DIL) domain adversarial neural network(DANN) knowledge transfer learning(KTL)