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Structure deformation of Ni-Fe-Se enables efficient oxygen evolution via RE atoms doping

Rare Metals 2025年第1期44卷 336-348页

作者： Hong-Rui Zhao Cheng-Zong Yuan Cong-Hui Li Wen-Kai Zhao Fu-Ling Wu Lei Xin Hong Yin Shu-Feng Ye Xiao-Meng Zhang Yun-Fa Chen Jiangxi Province Research Institute of Rare Earths Ganjiang Innovation AcademyChinese Academy of SciencesGanzhou341119China School of Rare Earths University of Science and Technology of ChinaHefei230026China Key Laboratory of Hunan Province for Advanced Carbon-Based Functional Materials School of Chemistry and Chemical EngineeringHunan Institute of Science and TechnologyYueyang414006China State Key Laboratory of Multiphase Complex Systems Institute of Process EngineeringChinese Academy of SciencesBeijing100190China

The development of cost-effective and highly stable electrocatalysts for oxygen evolution reactions holds paramount importance in practical hydrogen ***,we present a novel self-supported electrode comprising Ce-doped Ni-Fe-Se nanosheets grown on carbon cloth(Ni-Fe-Ce-Se/CC).This electrode was synthesized through a selenylation process,utilizing Ni-Fe-Ce-layered double hydroxide/carbon cloth(Ni-Fe-Ce LDH/CC)as the ***,Ni-Fe-Ce-Se/CC electrode demonstrates remarkable performance,requiring a low overpotential of 300 mV to attain a current density of 100 mA·cm^(-2)under harsh alkaline ***,the electrode exhibits exceptional stability during continuous operation for 100 *** into the underlying mechanisms was gained through a combination of experimental results and density functional theory *** findings reveal that Ce doping induces crystal structure deformation in Ni-Fe-Se and enhances electron enrichment around Ni *** structural modification optimizes the adsorption energy of oxygen-based intermediates on the Ni-Fe-Se *** work offers a valuable strategy for regulating the electron transfer and adsorption capabilities of transition metal selenide electrocatalysts through RE atoms doping,opening new avenues for enhanced electrocatalytic performance.

关键词： Ce doping Structure deformation Ni-Fe-Se Electron transfer Oxygen evolution

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Boosting electrochemical reduction of CO_(2)to CO using molecule-regulated Ag nanoparticle in ionic liquids

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Green Energy & Environment 2025年第4期10卷 813-820页

作者： Fangfang Li Kuilin Peng Chongyang Jiang Shaojuan Zeng Xiangping Zhang Xiaoyan Ji Energy Engineering Division of Energy ScienceLuleåUniversity of TechnologyLuleå97187Sweden Beijing Key Laboratory of Ionic Liquids Clean Process State Key Laboratory of Multiphase Complex SystemsInstitute of Process EngineeringChinese Academy of SciencesBeijing100190China College of Chemical Engineering and Environment China University of PetroleumBeijing102249China

Electrochemical reduction of CO_(2)is a promising approach to convert CO_(2)to high-valued chemicals and ***,developing efficient electrocatalysts featuring desirable activity and selectivity is still a big *** this work,a strategy of introducing functionalized molecules with desirable CO_(2)affinity to regulate Ag catalyst for promoting electrochemical reduction of CO_(2)was ***,3-mercapto-1,2,4-triazole was introduced onto the Ag nanoparticle(Ag-m-Triz)for the first time to achieve selectively converting CO_(2)to carbon monoxide(CO).This Ag-m-Triz exhibits excellent performance for CO_(2)reduction with a high CO Faradaic efficiency(FECO)of 99.2%and CO partial current density of 85.0 mA cm^(-2)at-2.3 V ***/Agt in H-cell when combined with the ionic liquid-based electrolyte,30 wt%1-butyl-3-methylimidazolium hexafluorophosphate([Bmim][PF6])-65 wt%acetonitrile(AcN)-5 wt%H2O,which is 2.5-fold higher than the current density in Ag-powder under the same *** studies confirm that the significantly improved performance of Ag-m-Triz originates from(i)the stronger adsorption ability of CO_(2)molecule and(ii)the weaker binding energy to form the COOH*intermediate on the surface of Ag-m-Triz compared with the Ag-powder catalyst,which boosts the conversion of CO_(2)to *** research provides a facile way to regulate electrocatalysts for efficient CO_(2)reduction by introducing functionalized molecules.

关键词： CO_(2)reduction CO Electrochemical Molecule-regulated Silver Ionic liquid

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On Weighted Compactness of Commutators of Bilinear Vector-valued Singular Integral Operators and Applications

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Acta Mathematica Sinica,English Series 2025年第1期41卷 169-190页

作者： Zhengyang Li Liu Lu Fanghui Liao Qingying Xue School of Mathematics&Computational Science Hu’nan University of Science and TechnologyXiangtan 411201P.R.China School of Mathematics&Computational Science Xiangtan UniversityXiangtan 411105P.R.China School of Mathematical Sciences Laboratory of Mathematics and Complex Systems Ministry of EducationBeijing Normal UniversityBeijing 100875P.R.China

Let T be a bilinear vector-valued singular integral operator satisfies some mild regularity conditions,which may not fall under the scope of the theory of standard Calder¬on–Zygmund *** anyb^(→)=(b_(1),b_(2))∈(CMO(R^(n)))^(2),let[T,b_(j)]e_(j)(j=1,2),[T,→b]_(α)be the commutators in the j-th entry and the iterated commutators of T,*** this paper,for all p_(0)>1,p0/2

关键词： Weighted compactness commutators multilinear square functions Fourier multiplier operator

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A Service Mining Scheme Based on Semantic for Internet of Things

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Chinese Journal of Electronics 2025年第2期23卷 236-242页

作者： Xinming Li Yan Sun The Science and Technology on Complex Electronic System Simulation Laboratory Academy of Equipment Beijing China The School of Computer Science Beijing University of Posts and Telecommunication Beijing China

As the development of Internet of things (IOT), massive sensors have been deployed as the public infrastructure. With the development of in-depth applications in IOT, service discovery and composition are challenges to the end users. To handle this challenge, we develop a service mining scheme based on semantic for IOT to provide users with interesting composite services. In this scheme, services can be combined and recommended to users actively according to the calculation of service similarity and an updatable semantic database. By the results of service similarity, useless compositions can be filtered out so that energy consumption on service flooding will be reduced. The update strategy of semantic database is also given out, by which the composite services can keep up with time and be more applicative. The benefits of the proposed method are that all operations such as calculating, filtering, and updating are simple enough to be performed in sensor networks.

关键词： Smart buildings Databases Filtering Semantics Public infrastructure Ontologies Sensor systems Internet of Things Floods Intelligent sensors

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Synthesis ofδ-MnO_(2)via ozonation routine for low temperature formaldehyde removal

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Journal of Environmental sciences 2025年第1期147卷 642-651页

作者： Guijun Fan Yacong Guo Shaohua Chai Le Zhang Jian Guan Guojun Ma Ning Han Yunfa Chen State Key Laboratory of Multiphase Complex Systems Institute of Process EngineeringChinese Academy of SciencesBeijing 100190China College of Chemical Engineering University of Chinese Academy of SciencesBeijing 100049China Key Laboratory of Science and Technology on Particle Materials Institute of Process EngineeringChinese Academy of SciencesBeijing 361021China Key Laboratory for Mechanics in Fluid Solid Coupling Systems Institute of MechanicsChinese Academy of SciencesBeijing 100190China School of Petrochemical Engineering&Environment Zhejiang Ocean UniversityZhoushan 316022China

Nowadays,it is still a challenge to prepared high efficiency and low cost formaldehyde(HCHO)removal catalysts in order to tackle the long-living indoor air ***,δ-MnO_(2)is successfully synthesized by a facile ozonation strategy,where Mn^(2+)is oxidized by ozone(O_(3))bubble in an alkaline *** presents one of the best catalytic properties with a low 100%conversion temperature of 85℃for 50 ppm of HCHO under a GHSV of 48,000 mL/(g·hr).As a comparison,more than 6 times far longer oxidation time is needed if O3 is replaced by O_(2).Characterizations show that ozonation process generates a different intermediate of tetragonalβ-HMnO_(2),which would favor the quick transformation into the final productδ-MnO_(2),as compared with the relatively more thermodynamically stable monoclinicγ-HMnO_(2)in the O_(2)***,HCHO is found to be decomposed into CO_(2)via formate,dioxymethylene and carbonate species as identified by room temperature insitu diffuse reflectance infrared fourier transform *** these results show great potency of this facile ozonation routine for the highly activeδ-MnO_(2)synthesis in order to remove the HCHO contamination.

关键词： δ-MnO_(2) Ozone oxidation HCHO oxidation In-situ DRIFTS

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Stochastic Block Models for complex Network Analysis: A Survey

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ACM Transactions on Knowledge Discovery from Data 2025年第3期19卷 1-35页

作者： Liu, Xueyan Song, Wenzhuo Musial, Katarzyna Li, Yang Zhao, Xuehua Yang, Bo College of Computer Science and Technology Jilin University Changchun China School of Information Science and Technology Northeast Normal University Changchun China Complex Adaptive Systems Lab Data Science Institute University of Technology Sydney Sydney Australia Aviation University of the Air Force Changchun China School of Digital Media Shenzhen Institute of Information Technology Shenzhen China Key Laboratory of Symbolic Computation and Knowledge Engineer Jilin University Ministry of Education Changchun China

complex networks enable to represent and characterize the interactions between entities in various complex systems which widely exist in the real world and usually generate vast amounts of data about all the elements, their behaviors and interactions over time. The studies concentrating on new network analysis approaches and methodologies are vital because of the diversity and ubiquity of complex networks. The stochastic block model (SBM), based on Bayesian theory, is a statistical network model. SBMs are essential tools for analyzing complex networks since SBMs have the advantages of interpretability, expressiveness, flexibility and generalization. Thus, designing diverse SBMs and their learning algorithms for various networks has become an intensively researched topic in network analysis and data mining. In this article, we review, in a comprehensive and in-depth manner, SBMs for different types of networks (i.e., model extensions), existing methods (including parameter estimation and model selection) for learning optimal SBMs for given networks and SBMs combined with deep learning. Finally, we provide an outlook on the future research directions of SBMs. © 2025 Copyright held by the owner/author(s). Publication rights licensed to ACM.

关键词： complex Networks Structural Pattern Discovery Stochastic Block models Learning Methods of SBMs

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Maximization of k-Submodular Function with d-Knapsack Constraints Over Sliding Window

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Tsinghua science and technology 2025年第2期30卷 488-498页

作者： Wenqi Wang Yuefang Sun Zhiren Sun Donglei Du Xiaoyan Zhang School of Mathematical Science&Institute of Mathematics Nanjing Normal UniversityNanjing 210023China Key Laboratory of Ministry of Education Numerical Simulation of Large Scale Complex Systems Nanjing 210023China School of Mathematics and Statistics Ningbo UniversityNingbo 315211China Faculty of Management University of New BrunswickFredericton E3B9Y2Canada

Submodular function maximization problem has been extensively studied recently.A natural variant of submodular function is k-submodular function,which has many applications in real life,such as influence maximization and sensor placement *** domain of a k-submodular function has k disjoint subsets,and hence includes submodular function as a special case when k=*** work investigates the k-submodular function maximization problem with d-knapsack constraints over the sliding *** on the smooth histogram technique,we design a deterministic approximation ***,we propose a randomized algorithm to improve the approximation ratio.

关键词： k-submodular function d-knapsack constraints sliding window streaming algorithm approximation algorithm

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Enhancing realism in LiDAR scene generation with CSPA-DFN and linear cross-attention via Diffusion Transformer model

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Neural Networks 2025年 189卷 107503页

作者： Ye, Shaoxun Di, Xiaoguang Liao, Ming Li, Ximing Control and Simulation Center Harbin Institute of Technology Harbin150080 China National Key Laboratory of Modeling and Simulation for Complex Systems Harbin150080 China

Point cloud diffusion models have found extensive applications in autonomous driving and robotics. However, there is still a big gap between their generated LiDAR scene samples and real-world data in terms of visual quality. This discrepancy primarily arises from the loss of detailed information during the decoding process from latent space and the lack of guidance from global 3D structural information in the point cloud generation process, leading to distortions and artifacts in LiDAR scene samples. In this paper, we propose a novel LiDAR Diffusion Transformer Model that integrates Channel-Spatial Parallel Attention and Dilation Fusion Network (CSPA-DFN) with a linear cross-attention post-processing module to refine the generated LiDAR scene samples. Specifically, CSPA-DFN is designed to simultaneously emphasize detailed features across different channels and spatial locations in parallel, leveraging multi-scale dilated convolutions and channel grouping to preserve and enhance these detailed features. In order to provide global 3D structural information and balance performance and efficiency, we design a post-processing module that fuses voxelized features and range images using a linear ReLU cross-attention mechanism. Our approach is evaluated on the unconditional generation task using the KITTI-360 and nuScenes datasets, achieving the state-of-the-art results in LiDAR scene's generation quality. Furthermore, by incorporating semantic labels and camera views into the latent space, in addition to enhancing the model's semantic understanding capability for LiDAR scenes, our method also demonstrates additional performance improvements compared to previous works in terms of LiDAR scene's visual quality. The code implementation has been released on https://***/HITysx/LiDAR-Scene-Generation. © 2025 Elsevier Ltd

关键词： Photointerpretation

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HRSTORY: Historical News Review Based Online Story Discovery 25

HRSTORY: Historical News Review Based Online Story Discovery

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Proceedings of the 31st ACM SIGKDD Conference on Knowledge Discovery and Data Mining V.1

作者： Renjie Zhou Haoran Ye Jian Wan Yong Liao Key Laboratory of Complex Systems Modeling and Simulation of the Ministry of Education Hangzhou Dianzi University Hangzhou Zhejiang China Zhejiang University of Science and Technology Hangzhou Zhejiang China University of Science and Technology of China Hefei Anhui China

ISBN: (纸本)9798400712456

Story discovery on news streams can help people quickly find story from vast amounts of news, improving the efficiency of information acquisition. Recent online story discovery methods encode text topics and then cluster articles into stories based on similarity. However, the results obtained by these methods are one-time, and clustered news cannot adaptively update in a continuous news stream. Additionally, the inadequate quality of article encoding and the presence of noise data deteriorate the performance of story discovery. To this end, we propose HRSTORY for online story discovery on news streams, which employs a historical news review method to enable news to continuously adapt to the latest environment in the stream data and make corrections and updates. Furthermore, HRSTORY captures better article embeddings through modeling multi-layer relational dependencies within the text. By using sentence-level noise masking, HRSTORY improves the relevance of news article representation to core topics and reduces the interference of noise data. Experiments on real news datasets show that HRSTORY outperforms the state-of-the-art algorithms in unsupervised online story discovery performance.

关键词： historical news

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Imp: Highly Capable Large Multimodal Models for Mobile Devices

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IEEE Transactions on Multimedia 2025年 27卷 2961-2974页

作者： Shao, Zhenwei Yu, Zhou Yu, Jun Ouyang, Xuecheng Zheng, Lihao Gai, Zhenbiao Wang, Mingyang Kuang, Zhenzhong Ding, Jiajun Hangzhou Dianzi University Key Laboratory of Complex Systems Modeling and Simulation School of Computer Science Hangzhou310005 China Harbin Institute of Technology Shenzhen Department of Computer Science and Technology Shenzhen China Hangzhou Dianzi University HDU-ITMO Joint Institute Hangzhou310005 China

By harnessing the capabilities of large language models (LLMs), recent large multimodal models (LMMs) have shown remarkable versatility in open-world multimodal understanding. Nevertheless, they are usually parameter-heavy and computation-intensive, thus hindering their applicability in resource-constrained scenarios. To this end, several lightweight LMMs have been proposed successively to maximize the capabilities under constrained scale (e.g., 3B). Despite the encouraging results achieved by these methods, most of them only focus on one or two aspects of the design space, and the key design choices that influence model capability have not yet been thoroughly investigated. In this paper, we conduct a systematic study for lightweight LMMs from the aspects of model architecture, training strategy, and training data. Based on our findings, we obtain Imp - a family of highly capable LMMs at the 2B$\sim$4B scales. Notably, our Imp-3B model steadily outperforms all the existing lightweight LMMs of similar size, and even surpasses the state-of-the-art LMMs at the 13B scale. With low-bit quantization and resolution reduction techniques, our Imp model can be deployed on a Qualcomm Snapdragon 8Gen3 mobile chip with a high inference speed of about 13 tokens/s. © 2025 IEEE.

关键词： Visual languages

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