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Nano Research 2024年第5期17卷 4089-4099页

作者： Taili Du Dianlong Shen Ziyue Xi Hongyong Yu Fangyang Dong Cong Zhao Meixian Zhu Yongjiu Zou Peiting Sun Minyi Xu Dalian Key Laboratory of marine Micro/Nano Energy and Self-powered systems Marine Engineering CollegeDalian Maritime UniversityDalian 116026China Collaborative Innovation Research institute of Autonomous Ship Dalian Maritime UniversityDalian 116026China

An enormous number of wireless sensing nodes(WSNs)are of great significance for the Internet of Things(IoT).It is tremendously prospective to realize the in-situ power supply of WSNs by harvesting unutilized mechanical vibration energy.A harmonic silicone rubber triboelectric nanogenerator(HSR-TENG)is developed focusing on ubiquitous constant working frequency *** unique design of the strip serving as a flexible resonator realizes both soft contact and high and broadband *** significant factors influencing the 1^(st)-order vibration mode of the strip are developed for realizing the harmonic frequency adaptation to external *** surface treatment of the strip improves the output performance of HSR-TENG by 49.1%as well as eliminates the adhesion *** HSR-TENG is able to achieve a voltage output bandwidth of 19 Hz under a vibration strength of 3.0,showing its broadband *** peak power density of 153.9 W/m^(3)is achieved and 12×0.5 W light-emitting diodes(LEDs)are successfully illuminated by the *** can continuously power a temperature sensor by harvesting the actual compressor vibration *** brief,the HSR-TENG provides a promising way for constant frequency vibration energy harvesting,so as to achieve in-situ power supply for the WSNs in the vicinity.

关键词： vibration energy harvesting triboelectric nanogenerator flexible silicone rubber strip harmonic vibration broadband

Exploring multiple phases and first-order phase transitions in Kármán Vortex Street

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Science China(Physics,Mechanics & Astronomy) 2024年第11期Mechanics & Astronomy) .卷 51-58页

作者： Xu Li Xing Xiang Tingting Xue Limin Wang Xiaosong Chen School of systems Science and institute of Nonequilibrium systems Beijing Normal University State Key Laboratory of Multiphase Complex systems Institute of Process Engineering Chinese Academy of Sciences School of Chemical Engineering University of Chinese Academy of Sciences

Kármán Vortex Street, a fascinating phenomenon of fluid dynamics, has intrigued the scientific community for a long time. Many researchers have dedicated their efforts to unraveling the essence of this intriguing flow pattern. Here, we apply the lattice Boltzmann method with curved boundary conditions to simulate flows around a circular cylinder and study the emergence of Kármán Vortex Street using the eigen microstate approach, which can identify phase transition and its order-parameter. At low Reynolds number, there is only one dominant eigen microstate W1of laminar flow. At Rec1= 53.6, there is a phase transition with the emergence of an eigen microstate pair W2,3of pressure and velocity fields. Further at Rec2= 56, there is another phase transition with the emergence of two eigen microstate pairs W4,5and W6,7. Using the renormalization group theory of eigen microstate,both phase transitions are determined to be first-order. The two-dimensional energy spectrum of eigen microstate for W1, W2,3after Rec1, W4-7after Rec2exhibit-5/3 power-law behavior of Kolnogorov's K41 theory. These results reveal the complexity and provide an analysis of the Kármán Vortex Street from the perspective of phase transitions.

关键词： Kármán Vortex Street first-order phase transition eigen microstate approach renormalization group theory of eigen microstate

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Unveiling the early stage evolution of local atomic structures in the crystallization process of a metallic glass

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Chinese Physics B 2024年第3期33卷 58-64页

作者：马琳杨晓东杨锋周鑫嘉武振伟 institute of Nonequilibrium systems School of Systems ScienceBeijing Normal UniversityBeijing 100875China

The early stage evolution of local atomic structures in a multicomponent metallic glass during its crystallization process has been investigated via molecular dynamics *** is found that the initial thermal stability and earliest stage evolution of the local atomic clusters show no strong correlation with their initial short-range orders,and this leads to an observation of a novel symmetry convergence phenomenon,which can be understood as an atomic structure manifestation of the ***,in our system we have quantitatively proved that the crucial factor for the thermal stability against crystallization exhibited by the metallic glass is not the total amount of icosahedral clusters,but the degree of global connectivity among them.

关键词： metallic glass crystallization molecular dynamics simulation local atomic clusters

Facet effects on bimetallic ZnSn hydroxide microcrystals for selective electrochemical CO2 reduction

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Green Energy & Environment 2024年第8期9卷 1314-1320页

作者： Liu Han Cheng-wei Wang Shan-shan Luo Ying-tang Zhou Bing Li Ming Liu School of Chemistry and Chemical Engineering Harbin Institute of Technology National Engineering Research Center for marine Aquaculture Marine Science and Technology CollegeZhejiang Ocean University

Employing crystal facets to regulate the catalytic properties in electrocatalytic carbon dioxide reduction reaction（eCO2RR） has been well demonstrated on electrocatalysts containing single metals but rarely explored for bimetallic systems. Here, we synthesize Zn Sn（OH）6（ZSO）microcrystals（MCs） with distinct facets and investigate the facet effects in eCO2RR. Electrochemical studies and in situ Fourier Transform Infrared Spectroscopy（in situ-FTIR） reveal that ZSO MCs produce mainly C1 products of HCOOH and CO. The {111} facet of the ZSO MCS exhibits higher selectivity and faradaic efficiency（FE） than that of the {100} facet over a wide range of potentials（-0.9 V ～-1.3 V versus RHE）. Density Functional Theory（DFT） calculations elucidate that the {111} facet is favorable to the adsorption/activation of CO2molecules,the formation of intermediate in the rate-determining step, and the desorption of C1 products of CO and HCOOH molecules.

关键词： ZnSn(OH) 6 Crystal facets Electrochemical carbon dioxide reduction C1 product Density functional theory

Combined Effect of Temperature and Cadmium on Molecular Responses of Hsp70 and P-gp Genes in Crassostrea gigas

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Journal of Ocean University of China 2024年第4期23卷 1115-1120页

作者： HU Fanguang SUN Ming LIU Guangbin JING Yuanyuan CHEN Qun ZHANG Tianwen marine Science Research institute of Shandong Province Qingdao 266104China

To evaluate the combined effect of temperature and cadmium on the molecular responses of heat shock protein 70(hsp70)and P-glycoprotein(P-gp)in mantle,digestive gland and gills of Crassostrea gigas,oysters were exposed to combinations of five temperature levels(10,15,20,25,and 30℃)and 10μg L^(-1)cadmium for 21 *** were sampled for mRNA quantification by qPCR,and the results showed that the P-gp gene expression changed significantly after treatment at different temperatures and different treatment *** P-gp gene expression was the highest in the digestive *** with the control group,the P-gp gene expression in cadmium treatment groups at all the different temperatures were significantly higher than the control *** control oysters(kept at 10℃during the whole experiment without cadmium)expressed low levels of hsp70,but the groups treated with cadmium displayed somewhat higher *** present study demonstrated hsp70 and P-gp played an important role in the detoxification of Cd in ***,and confirmed temperature should be considered for the assessment of Cd-induced toxicity in oysters.

关键词： temperature cadmium P-gp hsp70 Crassostrea gigas

A novel non-intrusive load monitoring technique using semi-supervised deep learning framework for smart grid

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Building Simulation 2024年第3期17卷 441-457页

作者： Mohammad Kaosain Akbar Manar Amayri Nizar Bouguila Concordia institute for Information systems Engineering Concordia UniversityMontrealCanada

Non-intrusive load monitoring(NILM)is a technique which extracts individual appliance consumption and operation state change information from the aggregate power consumption made by a single residential or commercial *** plays a pivotal role in modernizing building energy management by disaggregating total energy consumption into individual appliance-level *** enables informed decision-making,energy optimization,and cost ***,NILM encounters substantial challenges like signal noise,data availability,and data privacy concerns,necessitating advanced algorithms and robust methodologies to ensure accurate and secure energy disaggregation in real-world *** learning techniques have recently shown some promising results in NILM research,but training these neural networks requires significant labeled *** initial sets of labeled data for the research by installing smart meters at the end of consumers’appliances is laborious and expensive and exposes users to severe privacy *** is also important to mention that most NILM research uses empirical observations instead of proper mathematical approaches to obtain the threshold value for determining appliance operation states(On/Off)from their respective energy consumption *** paper proposes a novel semi-supervised multilabel deep learning technique based on temporal convolutional network(TCN)and long short-term memory(LSTM)for classifying appliance operation states from labeled and unlabeled *** two thresholding techniques,namely Middle-Point Thresholding and Variance-Sensitive Thresholding,which are needed to derive the threshold values for determining appliance operation states,are also compared *** superiority of the proposed model,along with finding the appliance states through the Middle-Point Thresholding method,is demonstrated through 15%improved overall improved F1micro score and almost 26%improved Hamming loss,F1 and Specificity score for the p

关键词： semi-supervised learning non-intrusive load monitoring middle-point thresholding deep learning TCN LSTM

Classification of knowledge graph completeness measurement techniques

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Journal of systems Engineering and Electronics 2024年第1期35卷 154-162页

作者： ZHANG Ying XIAO Gang institute of systems Engineering Academy of Military SciencesBeijing 100107China

At present,although knowledge graphs have been widely used in various fields such as recommendation systems,question and answer systems,and intelligent search,there are always quality problems such as knowledge omissions and *** assessment and control,as an important means to ensure the quality of knowledge,can make the applications based on knowledge graphs more complete and more accurate by reasonably assessing the knowledge graphs and fixing and improving the quality problems at the same ***,as an indispensable part of the knowledge graph construction process,the results of quality assessment and control determine the usefulness of the knowledge *** them,the assessment and enhancement of completeness,as an important part of the assessment and control phase,determine whether the knowledge graph can fully reflect objective phenomena and reveal potential connections among *** this paper,we review specific techniques of completeness assessment and classify completeness assessment techniques in terms of closed world assumptions,open world assumptions,and partial completeness *** purpose of this paper is to further promote the development of knowledge graph quality control and to lay the foundation for subsequent research on the completeness assessment of knowledge graphs by reviewing and classifying completeness assessment techniques.

关键词： quality assessment completeness assessment closed world assumptions open world assumption partial completeness assumption

Deep learning CNN-APSO-LSSVM hybrid fusion model for feature optimization and gas-bearing prediction

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Petroleum Science 2024年第4期21卷 2329-2344页

作者： Jiu-Qiang Yang Nian-Tian Lin Kai Zhang Yan Cui Chao Fu Dong Zhang College of Earth Sciences and Engineering Shandong University of Science and Technology Laboratory for marine Mineral Resources Qingdao National Laboratory for Marine Science and Technology Transportation institute of Inner Mongolia University Key Laboratory of Gas Hydrate Qingdao Institute of Marine Geology Ministry of Natural Resources

Conventional machine learning(CML) methods have been successfully applied for gas reservoir prediction. Their prediction accuracy largely depends on the quality of the sample data; therefore, feature optimization of the input samples is particularly important. Commonly used feature optimization methods increase the interpretability of gas reservoirs; however, their steps are cumbersome, and the selected features cannot sufficiently guide CML models to mine the intrinsic features of sample data efficiently. In contrast to CML methods, deep learning(DL) methods can directly extract the important features of targets from raw data. Therefore, this study proposes a feature optimization and gas-bearing prediction method based on a hybrid fusion model that combines a convolutional neural network(CNN)and an adaptive particle swarm optimization-least squares support vector machine(APSO-LSSVM). This model adopts an end-to-end algorithm structure to directly extract features from sensitive multicomponent seismic attributes, considerably simplifying the feature optimization. A CNN was used for feature optimization to highlight sensitive gas reservoir information. APSO-LSSVM was used to fully learn the relationship between the features extracted by the CNN to obtain the prediction results. The constructed hybrid fusion model improves gas-bearing prediction accuracy through two processes of feature optimization and intelligent prediction, giving full play to the advantages of DL and CML methods. The prediction results obtained are better than those of a single CNN model or APSO-LSSVM model. In the feature optimization process of multicomponent seismic attribute data, CNN has demonstrated better gas reservoir feature extraction capabilities than commonly used attribute optimization methods. In the prediction process, the APSO-LSSVM model can learn the gas reservoir characteristics better than the LSSVM model and has a higher prediction accuracy. The constructed CNN-APSO-LSSVM mode

关键词： Multicomponent seismic data Deep learning Adaptive particle swarm optimization Convolutional neural network Least squares support vector machine Feature optimization Gas-bearing distribution prediction

Current observation and analysis based on mooring systems in the Andaman Sea

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Journal of Oceanology and Limnology 2024年第2期42卷 484-491页

作者： Yimeng WANG Jingsong GUO Dapeng QU Zhixin ZHANG Chalermrat SANGMANEE Varintha VASINAMEKHIN Binghuo GUO First institute of Oceanography and Key Laboratory of Marine Science and Numerical ModelingMinistry of Natural ResourcesQingdao 266061China Laboratory for Regional Oceanography and Numerical Modeling Pilot National Laboratory for Marine Science and Technology(Qingdao)Qingdao 266237China Shandong Key Laboratory of marine Science and Numerical Modeling Qingdao 266061China Phuket marine Biological Center Department of Marine and Coastal ResourcesPhuket 83000Thailand marine and Coastal Resources Research&Development institute Department of Marine and Coastal ResourcesBangkok 10210Thailand

The basic structure and intraseasonal evolution of currents in the southeastern Andaman Sea was analyzed based on data collected in 2017 from two subsurface moorings(C1 and C5).Periodic variation in the upper ocean currents of the Andaman Sea was investigated by combining observational and satellite *** observations show that rapid changes of current speed and direction occurred in May and June,with a significant increase in current velocity at the C1 *** the second half of the year,southward flow dominated at the C1 mooring,and alternating northward and southward flows were evident at the C5 mooring during the same period but the northward flow prevailed in boreal *** addition,analysis of the power spectra of the upper currents revealed that the tidal period at both moorings is primarily semidiurnal with weaker energy than that of the low-frequency *** upper ocean currents at the C1 and C5 moorings exhibited intraseasonal variation of 30-60 d and 120 d,while the zonal current at the C1 mooring exhibited a notable period of approximately 180 *** analysis indicated that the variability of currents in the Andaman Sea is influenced primarily by equatorial Kelvin waves and Rossby wave ***,our results suggest that equatorial Kelvin waves from the eastern Indian Ocean entered the Andaman Sea in the form of Wyrtki Jets and propagated primarily along two distinct pathways during the observation *** addition to coastal boundary Kelvin waves,it was found that a branch of the Wyrtki Jet that directly enters the Andaman Sea and flows northward along the slope of the continental shelf,and reflected Rossby wave packets by topography.

关键词： mooring observation Wyrtki Jet Rossby waves intraseasonal variation

LPCS Ni-Zn-Al_(2)O_(3) Intermediate Layer Enhanced SPS NiCr-Cr_(3)C_(2) Coating with Higher Corrosion and Wear Resistances

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Journal of Wuhan University of Technology(Materials Science) 2024年第1期39卷 188-195页

作者：白杨 LI Yan XING Lukuo LI Xiangbo WANG Zhenhua State Key Laboratory of marine Coatings Marine Chemical Research Institute Co.Ltd.Qingdao 266071China College of Mechanical and Electrical Engineering University of China Petroleum(East China)Qingdao 266580China Science and Technology on marine Corrosion and Protection Laboratory Luoyang Ship Materials Research InstituteQingdao 266101China

The double-layer NiCr-Cr_(3)C_(2)/Ni-Zn-Al_(2)O_(3) coatings with sufficient corrosion and wear resistance were prepared on low carbon steel *** intermediate layers Ni-Zn-Al_(2)O_(3) were fabricated by using low-pressure cold spray (LPCS) method to improve the salt fog corrosion resistance properties of the supersonic plasma spray (SPS) NiCr-Cr_(3)C_(2) *** friction and wear performance for the double-layer and single-layer NiCr-Cr_(3)C_(2) coatings were carried out by line-contact reciprocating sliding,*** with the coating surface analysis techniques,the effect of the salt fog corrosion on the tribological properties of the double-layer coatings was *** results showed that the double-layer coatings exhibited better wear resistance than that of the single-layer coatings,due to the better corrosion resistance of the intermediate layer;the wear mass losses of the double-layer coatings was reduced by 70%than that of the single layer coatings and the wear mechanism of coatings after salt fog corrosion conditions is mainly corrosion wear.

关键词： low-pressure cold spray NiCr-Cr_(3)C_(2)coating wear behavior salt fog corrosion