The impregnation method in the preparation of metal cluster catalysts typically inadvertently introduces single atoms(SAs) into the substrate. However, the question of whether the introduction of SAs will further impr...
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The impregnation method in the preparation of metal cluster catalysts typically inadvertently introduces single atoms(SAs) into the substrate. However, the question of whether the introduction of SAs will further improve the catalytic activity of cluster systems for specific reactions such as the hydrogen oxidation reaction(HOR) remains unraveled. Herein, we demonstrate Ru clusters anchored on WN nanowires(RuC/WN) show a higher alkaline HOR catalytic activity in comparison with Ru SAs and nanoclusters(NCs)-coupled catalyst anchored on WN nanowires system(RuC,S/WN). Notably, the RuC/WN exhibits superb intrinsic catalytic activity with a mass-normalized exchange current density of 890 m A mg^(-1)PGM, which is among the top level of well developed Ru-based HOR catalysts. Both theoretical simulation and experimental investigation suggest that RuC/WN owns an optimized H^(*)and OH^(*) reaction intermediates for the alkaline HOR, therefore resulting in the excellent intrinsic HOR catalytic performance.
High-dimensional data poses a great challenge to clustering, and subspace clustering algorithms have unique advantages when working with high-dimensional data. However, there are still some difficulties in adapting th...
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Influence maximization,whose aim is to maximise the expected number of influenced nodes by selecting a seed set of k influential nodes from a social network,has many applications such as goods advertising and rumour *...
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Influence maximization,whose aim is to maximise the expected number of influenced nodes by selecting a seed set of k influential nodes from a social network,has many applications such as goods advertising and rumour *** the existing influence maximization methods,the community‐based ones can achieve a good balance between effectiveness and ***,this kind of algorithm usually utilise the network community structures by viewing each node as a non‐overlapping *** fact,many nodes in social networks are overlapping ones,which play more important role in influence *** this end,an overlapping community‐based particle swarm opti-mization algorithm named OCPSO for influence maximization in social networks,which can make full use of overlapping nodes,non‐overlapping nodes,and their interactive information is ***,an overlapping community detection algorithm is used to obtain the information of overlapping community structures,based on which three novel evolutionary strategies,such as initialisation,mutation,and local search are designed in OCPSO for better finding influential *** results in terms of influence spread and running time on nine real‐world social networks demonstrate that the proposed OCPSO is competitive and promising comparing to several state‐of‐the‐arts(***,CMA‐IM,CIM,CDH‐SHRINK,CNCG,and CFIN).
Phytoplankton serve as vital indicators of eutrophication ***,relying solely on phytoplankton parameters,such as chlorophyll-a,limits our comprehensive understanding of the intricate eutrophication conditions in natur...
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Phytoplankton serve as vital indicators of eutrophication ***,relying solely on phytoplankton parameters,such as chlorophyll-a,limits our comprehensive understanding of the intricate eutrophication conditions in natural lakes,particularly in terms of timely analysis of changes in limiting nutrients and their *** study presents machine learning(ML)models for predicting and identifying lake *** tree-based ML models were developed using the latest data on hydrological,water quality,and meteorological parameters obtained from 34 sites in the Huating Lake basin over 5 *** extreme gradient boosting model exhibited high accuracy in predicting the total nitrogen/total phosphorus ratio(TN/TP)(R^(2)=0.88;RMSE=24.60;MAPE=26.14%).Analysis of the TN/TP ratio and output eigenvalue weight revealed that phosphorus plays a crucial role in eutrophication,probably because of the low-flow and deep-water characteristics of the ***,the light gradient boosting machine model exhibited outstanding performance and high accuracy in predicting phytoplankton parameters,especially the Shannon index(H′)(R^(2)=0.92;RMSE=0.11;MAPE=4.95%).The mesotrophic classification of the Huating Lake determined using the H′threshold,coincided with the findings from the H′*** research should cover a wider range of pollution sources and spatiotemporal dimensions to further validate our ***,this study highlights the potential of incorporating the TN/TP ratio and phytoplankton parameters into ML techniques for effective monitoring and management of environmental conditions.
Existing portrait segmentation methods are easily affected by the background. To address this challenge, we propose a simple convolution-based portrait segmentation algorithm to solve the problems of complex backgroun...
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Text-to-image person retrieval, a fine-grained cross-modal retrieval problem, aims to search for person images from an image library that match a given textual caption. Existing text-to-image person retrieval methods ...
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With the development of semiconductor technology,the size of transistors continues to *** complex radiation environments in aerospace and other fields,small-sized circuits are more prone to soft error(SE).Currently,si...
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With the development of semiconductor technology,the size of transistors continues to *** complex radiation environments in aerospace and other fields,small-sized circuits are more prone to soft error(SE).Currently,single-node upset(SNU),double-node upset(DNU)and triple-node upset(TNU)caused by SE are relatively ***’s solution is not yet fully mature.A novel and low-cost TNU self-recoverable latch(named NLCTNURL)was designed which is resistant to harsh radiation *** analyzing circuit resiliency,a double-exponential current source is used to simulate the flipping behavior of a node’s stored value when an error *** results show that the latch has full TNU self-recovery.A comparative analysis was conducted on seven latches related to ***,a comprehensive index combining delay,power,area and self-recovery—DPAN index was proposed,and all eight types of latches from the perspectives of delay,power,area,and DPAN index were analyzed and *** simulation results show that compared with the latches LCTNURL and TNURL which can also achieve TNU self-recoverable,NLCTNURL is reduced by 68.23%and 57.46%respectively from the perspective of *** the perspective of power,NLCTNURL is reduced by 72.84%and 74.19%,*** the area perspective,NLCTNURL is reduced by about 28.57%and 53.13%,*** the DPAN index perspective,NLCTNURL is reduced by about 93.12%and 97.31%.The simulation results show that the delay and power stability of the circuit are very high no matter in different temperatures or operating voltages.
Aiming at the limitations of traditional fire detection algorithms in terms of accuracy and real-time detection, a lightweight fire detection algorithm based on improved YOLOv8 is proposed. The Slim-neck is used to im...
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In this article, an optimal adaptive Kalman filter algorithm is proposed to mitigate the impact of measurement outliers on human motion tracking. The algorithm utilizes an inertial measurement unit (IMU) equipped with...
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Emotion recognition at sentence level is one of the fundamental problems of textual emotion understanding. Based on the observation that sentence emotional focus can be expressed by some clauses in this sentence, this...
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Emotion recognition at sentence level is one of the fundamental problems of textual emotion understanding. Based on the observation that sentence emotional focus can be expressed by some clauses in this sentence, this paper proposes to find the emotional focus for sentence emotion recognition. For the sake of breaking through the problems brought about by depending on emotion lexicons, we first recognize word emotions in a sentence based on Maximum entropy model. And then homogeneous Markov model is built for clause emotion recognition; After that, a strategy based on emotion selection is proposed for a sentence with multiple clauses, and genetic algorithm is used for clause selection by textual feature weighting. The experimental results show that, comparing with the baseline, there are 9.1% and 3.6% improvement respectively for two different evaluations. It is demonstrated that finding emotional focus by clause selection is able to improve the performance of sentence emotion recognition significantly.
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