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Modulation of inactive Li_(2)O via iodinated MOF nanocapsules interfacial transformation engineering for high-performance solid electrolyte interphase

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Journal of Energy Chemistry 2025年第5期104卷 482-493页

作者： xingxing Zhang Qingmei Su Gaohui Du Bingshe Xu Xuehan Hou xiaowei Yang Weihao Shi Zhuo Chen Yang Shi Yujie Lv Wenhuan Huang School of Materials Science&Engineering Shaanxi University of Science and TechnologyXi’an 710021ShaanxiChina Key Laboratory of Chemical Additives for China National Light Industry College of Chemistry and Chemical EngineeringShaanxi University of Science and TechnologyXi’an 710021ShaanxiChina Materials Institute of Atomic and Molecular Science School of Physics&Information ScienceShaanxi University of Science and TechnologyXi’an 710021ShaanxiChina School of Chemistry and Chemical Engineering Shanghai Jiaotong UniversityShanghai 200240China

Lithium(Li)deposition and nucleation at solid electrolyte interphase(SEI)is the main origin for the capacity decay in Li metal batteries(LMBs).SEI conversion with enhanced electrochemical and mechanical properties is an effective approach to achieve uniform nucleation of Li^(+)and stabilize the lithium metal ***,complex interfacial reaction mechanisms and interface compatibility issues hinder the development of SEI conversion strategies for stabilizing lithium metal ***,we presented the release of I_(3)^(-)in–NH_(2)-modified metal–organic frameworks for a Li metal surface SEI phase conversion ***–NH_(2)group in MOF pores induced the formation of I_(3)^(-)from I_(2),which was further spontaneously reacted with inactive Li_(2)O transforming into high-performance LiI and LiIO_(3)***,theoretical calculation provided deeply insight into the unique reconstructed interfacial formation and electrochemical mechanism of rich LiI and LiIO_(3)*** a result,the Li^(+)deposition and nucleation were improved,facilitating the transport kinetics of Li^(+)and inhibiting the growth of lithium *** assembled solid-state Li||LiFePO_(4)full cells exhibited superior long-term stability of 800 cycles and high Coulombic efficiency(>99%),Li||LiNi_(0.8)Co_(0.1)Mn_(0.1)O_(2)pouch cell also displayed superior practical performance over 200 cycles at 2 C,high loading of 5 mg cm^(-2)and safety *** innovative SEI design strategy promotes the development of high-performance solid-state Li metal batteries.

关键词： Solid electrolyte interphase(SEI) SEI phase conversion MOF Nano-capsule Solid-state electrolytes Li metal battery

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CMDCF: an effective cross-modal dense cooperative fusion network for RGB-D SOD

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Neural Computing and Applications 2024年第23期36卷 14361-14378页

作者： Jia, xingZhao Zhao, Wenxiu Wang, YuMei DongYe, ChangLei Peng, YanJun College of Computer Science and Engineering Shandong University of Science and Technology Qingdao266590 China

The success of vision transformer demonstrates that the transformer structure is also suitable for various vision tasks, including high-level classification tasks and low-level dense prediction tasks. Salient object detection (SOD) is a pixel-level dense prediction task that simulates the most salient objects in human visual recognition scenarios. In recent years, depth images have been widely used for salient object detection. Compared with RGB SOD, the key point of RGB-D SOD is the effective fusion of depth information. As RGB-D SOD requires extracting depth features and fusing cross-modal information, additional computation is involved. However, except for lightweight models, most RGB-D SOD methods tend to obtain better prediction maps by consuming more computational resources. We propose a cross-modal dense cooperative fusion net, which provides state-of-the-art performance with less computation and parameters. We take advantage of the ability of the transformer structure to model long sequence dependencies to extract saliency features from RGB images. Since there is less information in the depth image than in the RGB image, it is not necessary to use the same structure in the depth stream. For the sake of reducing parameters and computation, we consider the asymmetric architecture. It is enough to meet our needs that deep features extracted by lightweight MobileV2Net. Our decoder can perform dense cooperative fusion of cross-modal information while decoding features. It can both effectively fuse cross-modal information and save computation. Comprehensive experiments on multiple benchmark datasets for RGB-D SOD show that compared with SOTA methods, our method performs much better with less computation and parameters. © The Author(s), under exclusive licence to Springer-Verlag London Ltd., part of Springer Nature 2024.

关键词： Object detection

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Research on Feature Dimension Reduction Method of Serum Mass Spectrometry Data Based on Machine Learning 9

Research on Feature Dimension Reduction Method of Serum Mass...

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9th International Conference on Intelligent Computing and Signal Processing, ICSP 2024

作者： Han, Jiaxin Yan, Yaxuan Jia, Pengtao School of Computer Science Xi'an Shiyou University Shaanxi Xi'an China College of Computer Science and Technology Xi'an University of Science and Technology Shaanxi Xi'an China

ISBN: (纸本)9798350376548

Mass spectrometry data is a kind of data describing the mass-to-charge ratio and relative intensity of compounds, which has the characteristics of high dimensionality, high noise, and large arithmetic capacity in processing, etc. Among them, serum mass spectrometry data can provide key information in the diagnosis and treatment of colon cancer, so it is of great significance to carry out a reasonable dimensionality reduction on mass spectrometry data. Currently, feature dimensionality reduction is mainly divided into two categories: Feature Extraction and Feature Selection, and each of the two methods has its own advantages and disadvantages. In this paper, we will use PCA - SVM, PCA - RF, RFE - SVM and RFE - RF methods to carry out dimensionality approximation and classification of preprocessed serum mass spectrometry data. And the classification accuracy is obtained by optimising the parameters. The classification results of the data are outputted in the confusion matrix, and the classification of different categories can be seen. The results show that the model based on Recursive Feature Elimination is better than the model based on Principal Component Analysis for classification, which is beneficial for medical practitioners to diagnose patients more efficiently. © 2024 IEEE.

关键词： Dimensionality reduction

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Monocular 3D object detection with Pseudo-LiDAR confidence sampling and hierarchical geometric feature extraction in 6G network

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Digital Communications and Networks 2023年第4期9卷 827-835页

作者： Jianlong Zhang Guangzu Fang Bin Wang xiaobo Zhou Qingqi Pei Chen Chen School of Electronic Engineering Xidian UniversityXi'an710071China School of Computer Science and Technology College of Intelligence and ComputingTianjin UniversityTianjin300000China School of Telecommunications Engineering Xidian UniversityXi'an710071China

The high bandwidth and low latency of 6G network technology enable the successful application of monocular 3D object detection on vehicle *** 3D-object-detection-based Pseudo-LiDAR is a low-cost,lowpower solution compared to LiDAR solutions in the field of autonomous ***,this technique has some problems,i.e.,(1)the poor quality of generated Pseudo-LiDAR point clouds resulting from the nonlinear error distribution of monocular depth estimation and(2)the weak representation capability of point cloud features due to the neglected global geometric structure features of point clouds existing in LiDAR-based 3D detection ***,we proposed a Pseudo-LiDAR confidence sampling strategy and a hierarchical geometric feature extraction module for monocular 3D object *** first designed a point cloud confidence sampling strategy based on a 3D Gaussian distribution to assign small confidence to the points with great error in depth estimation and filter them out according to the ***,we present a hierarchical geometric feature extraction module by aggregating the local neighborhood features and a dual transformer to capture the global geometric features in the point ***,our detection framework is based on Point-Voxel-RCNN(PV-RCNN)with high-quality Pseudo-LiDAR and enriched geometric features as *** the experimental results,our method achieves satisfactory results in monocular 3D object detection.

关键词： Monocular 3D object detection Pseudo-LiDAR Confidence sampling Hierarchical geometric feature extraction

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Model for atomization droplet size and energy distribution ratio at the distal end of an electrostatic nozzle

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Frontiers of Mechanical engineering 2024年第5期19卷 33-58页

作者： Dongzhou JIA Keke JIANG Yanbin ZHANG Zhenlin LV Changhe LI College of Mechanical Engineering and Automation Liaoning University of TechnologyJinzhou 121001China School of Materials Science and Engineering Xi’an University of TechnologyXi’an 710048China School of Mechanical and Automotive Engineering Qingdao University of TechnologyQingdao 266520China

Electrostatic atomization minimum quantity lubrication(EMQL)employs the synergistic effect of multiple physical fields to atomize minute quantities of *** innovative methodology is distinguished by its capacity to ameliorate the atomization attributes of the lubricant substantially,which subsequently augments the migratory and infiltration proficiency of the droplets within the complex and demanding milieu of the cutting *** with the traditional minimum quantity lubrication(MQL),the EMQL process is further complicated by the multiphysical field *** presence of multiple physical fields not only increases the complexity of the forces acting on the liquid film but also induces changes in the physical properties of the lubricant itself,thus making the analysis of atomization characteristics and energy distribution particularly *** address this objective reality,the current study has conducted a meticulous measurement of the volume average diameter,size distribution span,and the percentage concentration of inhalable particles of the charged droplets at various intercept positions of the EMQL nozzle.A predictive model for the volume-averaged droplet size at the far end of the EMQL nozzle was established with the observed statistical value F of 825.2125,which indicates a high regression accuracy of the ***,based on the changes in the potential energy of surface tension,the loss of kinetic energy of gas,and the electric field work at different nozzle orifice positions in the EMQL system,an energy distribution ratio model for EMQL was *** energy distribution ratio coefficients under operating conditions of 0.1 MPa air pressure and 0 to 40 kV voltage on the 20 mm cross-section ranged from 3.094‰to 3.458‰,while all other operating conditions and cross-sections had energy distribution ratios below 2.06‰.This research is expected to act as a catalyst for the progression of EMQL by stimulating innovation in the sp

关键词： atomization performance EMQL energy distribution PIV observation sustainable manufacturing

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Towards characterizing bug fixes through dependency-level changes in Apache Java open source projects

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science China(Information sciences) 2022年第7期65卷 102-120页

作者： Di CUI Lingling FAN Sen CHEN Yuanfang CAI Qinghua ZHENG Yang LIU Ting LIU School of Computer Science and Technology Xi'an Jiaotong University College of Cyber Science Nankai University College of Intelligence and Computing Tianjin University Department of Computer Science Drexel University School of Computer Science and Engineering Nanyang Technological University School of Cyber Science and Engineering Xi'an Jiaotong University

The complexity and diversity of bug fixes require developers to understand bug fixes from multiple perspectives in addition to fine-grained code changes. The dependencies among files in a software system are an important dimension to inform software quality. Recent studies have revealed that most bug-prone files are always architecturally connected with dependencies, and as one of the best practices in the industry,changes in dependencies should be avoided or carefully made during bug fixing. Hence, in this paper, we take the first attempt to understand bug fixes from the dependencies perspective, which can complement existing code change perspectives. Based on this new perspective, we conducted a systematic and comprehensive study on bug fixes collected from 157 Apache open source projects, involving 140456 bug reports and182621 bug fixes in total. Our study results show that a relatively high proportion of bug fixes(30%) introduce dependency-level changes when fixing the corresponding 33% bugs. The bugs, whose fixes introduce dependency-level changes, have a strong correlation with high priority, large fixing churn, long fixing time,frequent bug reopening, and bug inducing. More importantly, patched files with dependency-level changes in their fixes, consume much more maintenance costs compared with those without these changes. We further summarized three representative patch patterns to explain the reasons for the increasing costs. Our study unveils useful findings based on qualitative and quantitative analysis and also provides new insights that might benefit existing bug prediction techniques. We release a large set of benchmarks and also implement a prototype tool to automatically detect dependency-level changes from bug fixes, which can warn developers and remind them to design a better fix.

关键词： empirical software engineering software maintenance software evolution software architecture software design

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Flame-assisted ultrafast synthesis of functionalized carbon nanosheets for high-performance sodium storage

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Carbon Energy 2024年第7期6卷 123-133页

作者： Chen Chen Dong Yan Yew Von Lim Lei Liu Xue Liang Li Junjie Chen Tian Chen Li Youyu Zhu Jiangtao Cai Ying Huang Yating Zhang Hui Ying Yang School of Chemistry and Chemical Engineering Northwestern Polytechnical UniversityXi'anChina Pillar of Engineering Product Development Singapore University of Technology and DesignSingaporeSingapore School of Electrical Engineering Xi'an University of TechnologyXi'anChina International Joint Laboratory of New Energy Materials and Devices of Henan Province School of Physics and ElectronicsHenan UniversityKaifengChina College of Chemistry and Chemical Engineering Xi'an University of Science and TechnologyXi'anChina

The unique structural features of hard carbon(HC)make it a promising anode candidate for sodium-ion batteries(SIB).However,traditional methods of preparing HC require special equipment,long reaction times,and large energy consumption,resulting in low throughputs and *** our contribution,a novel synthesis method is proposed,involving the formation of HC nanosheets(NS-CNs)within minutes by creating an anoxic environment through flame combustion and further introducing sulfur and nitrogen sources to achieve heteroatom *** effect of heterogeneous element doping on the microstructure of HC is quantitatively analyzed by high-resolution transmission electron microscopy and image processing *** with density functional theory calculation,it is verified that the functionalized HC exhibits stronger Na^(+)adsorption ability,electron gain ability,and Na^(+) migration *** a result,NS-CNs as SIB anodes provide an ultrahigh reversible capacity of 542.7mAh g^(-1) at 0.1Ag^(-1),and excellent rate performance with a reversible capacity of 236.4mAh g^(-1) at 2Ag^(-1) after 1200 ***,full cell assembled with NS-CNs as the can present 230mAh g^(-1) at 0.5Ag^(-1) after 150 ***,in/ex situ techniques confirm that the excellent sodium storage properties of NS-CNs are due to the construction of abundant active sites based on the novel synthesis method for realizing the reversible adsorption of Na^(+).This work provides a novel strategy to develop novel carbons and gives deep insights for the further investigation of facile preparation methods to develop high-performance carbon anodes for alkali-ion batteries.

关键词： carbon nanosheets heteroatom doping sodium-ion battery sustainable materials

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Electrostatic Encapsulation of Cobalt Ions into Crystalline Framework Derived Polymer Aerogel:Ultra-light,Pressure Resistant,Hydrophobic,Photothermal Conversion,Heat Insulation and Infrared Stealth

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Chinese Journal of Polymer science 2024年第7期42卷 946-957,I0007页

作者： Yi-Fan Kang Jin-Lu Tang Ming Song Wei Wang Jia-Cheng Ma Zhan-You Ji Tong Liu Wen-Huan Huang China Key Laboratory of Chemical Additives for China National Light Industry College of Chemistry and Chemical EngineeringShaanxi University of Science and TechnologyXi’an710021China College of New Energy Xi’an Shiyou UniversityXi’an710065China Xi’an Key Laboratory of Functional Supramolecular Structure and Materials College of Chemistry and Materials ScienceNorthwest UniversityXi’an710127China

A variety of electromagnetic wave absorption materials(EMWAs)have been reported,but the integration of powder materials and multifunctional devices should be investigated in-depth to adapt to practical ***,carbon-coated cobalt composites were prepared by adsorbing magnetic metal cations into an anionic crystalline framework through an electrostatic encapsulate *** reflection loss(RL_(min))of-40.49 d B and effective absorption bandwidth(EAB)of 5.36 GHz(RL<-10 d B,10.4-15.76 GHz)was achieved with an optimal radar cross section(RCS)reduction of 34.9 dB·m^(2) for the sample *** commercial applications,Co@CN-4 was integrated into sodium carboxymethyl cellulose(CMC)aerogel to create an ultra-lightweight composite aerogel that is compressive resistant and heat-holding while also having photothermal conversion *** hydrophobic modification makes it more widely *** study provides a new strategy for EWAMs to integrate versatility and improve their application prospects.

关键词： Electrostatic incorporation Magnetic nanoparticle Co@CN composites Electromagnetic wave absorbing Metal-organic framework

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ASL-OOD:Hierarchical Contextual Feature Fusion with Angle-Sensitive Loss for Oriented Object Detection

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computers, Materials & Continua 2025年第2期82卷 1879-1899页

作者： Kexin Wang Jiancheng Liu Yuqing Lin Tuo Wang Zhipeng Zhang Wanlong Qi xingye Han Runyuan Wen Northwest Institute of Mechanical and Electrical Engineering Xianyang712099China School of Information Engineering Chang’an UniversityXi’an710064China School of Computer Science and Technology Xidian UniversityXi’an710071China

Detecting oriented targets in remote sensing images amidst complex and heterogeneous backgrounds remains a formidable challenge in the field of object *** frameworks for oriented detection modules are constrained by intrinsic limitations,including excessive computational and memory overheads,discrepancies between predefined anchors and ground truth bounding boxes,intricate training processes,and feature alignment *** overcome these challenges,we present ASL-OOD(Angle-based SIOU Loss for Oriented Object Detection),a novel,efficient,and robust one-stage framework tailored for oriented object *** ASL-OOD framework comprises three core components:the Transformer-based Backbone(TB),the Transformer-based Neck(TN),and the Angle-SIOU(Scylla Intersection over Union)based Decoupled Head(ASDH).By leveraging the Swin Transformer,the TB and TN modules offer several key advantages,such as the capacity to model long-range dependencies,preserve high-resolution feature representations,seamlessly integrate multi-scale features,and enhance parameter *** improvements empower the model to accurately detect objects across varying *** ASDH module further enhances detection performance by incorporating angle-aware optimization based on SIOU,ensuring precise angular consistency and bounding box *** approach effectively harmonizes shape loss and distance loss during the optimization process,thereby significantly boosting detection *** evaluations and ablation studies on standard benchmark datasets such as DOTA with an mAP(mean Average Precision)of 80.16 percent,HRSC2016 with an mAP of 91.07 percent,MAR20 with an mAP of 85.45 percent,and UAVDT with an mAP of 39.7 percent demonstrate the clear superiority of ASL-OOD over state-of-the-art oriented object detection *** findings underscore the model’s efficacy as an advanced solution for challenging remote sensing object detection tasks.

关键词： Oriented object detection transformer deep learning

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Performance issue monitoring, identification and diagnosis of SaaS software:a survey

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Frontiers of computer science 2025年第1期19卷 71-95页

作者： Rui WANG xiangbo TIAN Shi YING College of Mining and Safety Engineering Shandong University of Science and TechnologyQingdao 266590China School of Computer Science Wuhan UniversityWuhan 430072China

SaaS (Software-as-a-Service) is a service model provided by cloud computing. It has a high requirement for QoS (Quality of Software) due to its method of providing software service. However, manual identification and diagnosis for performance issues is typically expensive and laborious because of the complexity of the application software and the dynamic nature of the deployment environment. Recently, substantial research efforts have been devoted to automatically identifying and diagnosing performance issues of SaaS software. In this survey, we comprehensively review the different methods about automatically identifying and diagnosing performance issues of SaaS software. We divide them into three steps according to their function: performance log generation, performance issue identification and performance issue diagnosis. We then comprehensively review these methods by their development history. Meanwhile, we give our proposed solution for each step. Finally, the effectiveness of our proposed methods is shown by experiments.

关键词： SaaS software performance log generation performance issue identification performance issue diagnosis

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