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Toward Throughput Optimization: A Congestion Control Scheme for CAM Delivery via NR Sidelink

IEEE Internet of Things Journal 2025年第9期12卷 12206-12218页

作者： Fu, Qiang Liu, Jiajia Wang, Jiadai Kong, Jun Northwestern Polytechnical University National Engineering Laboratory for Integrated Aero-Space-Ground-Ocean Big Data Application Technology The School of Cybersecurity Shaanxi Xi’an710072 China

In the new radio (NR) vehicle-to-everything (V2X),congestion control (CC) is adopted to reduce channel occupancy and improve delivery performance. However, most existing CC schemes decide to adjust the number of messages while ignoring the throughput requirements, which may lead to serious traffic accidents due to the loss of information. In light of this, we investigate the performance of cooperative awareness messages (CAMs) delivery via NR sidelink under different CC configurations, including the modulation and coding scheme, the semi-persistent scheduling-based resource allocation, as well as the CAM transmission period. Specifically, taking into account these configurations, we develop a theoretical framework to capture two metrics of CAM delivery, namely the effective throughput and the channel busy ratio, based on the stochastic geometry approach. With the help of this framework, we propose the CC-(m,n,τ ) scheme, which is able to optimize the two metrics simultaneously by properly tuning the parameters m, n, and τ . Extensive numerical results show that the proposed scheme is highly beneficial for efficient and reliable CAM delivery via NR sidelink, particularly in scenarios with high vehicle densities. © 2014 IEEE.

关键词： Congestion control (communication)

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Multi-Label MambaOut for Quality Assessment of Low-Field Pediatric Brain MR Images 1st

Multi-Label MambaOut for Quality Assessment of Low-Field P...

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1st MICCAI Challenge on Low Field Pediatric Brain Magnetic Resonance Image Segmentation and Quality Assurance, LISA 2024, held in Conjunction with medical Image Computing and Computer Assisted Intervention Conference, MICCAI 2024

作者： Zhu, Yueyue Jiang, Haotian Cai, Rongqing Chen, Geng National Engineering Laboratory for Integrated Aero-Space-Ground-Ocean Big Data Application Technology School of Computer Science and Engineering Northwestern Polytechnical University Xi’an China

ISBN: (纸本)9783031830105

Magnetic Resonance Imaging (MRI) can be utilized to study the structure of pediatric brains non-invasively. In practice, low-field MRI scanners are widely adopted for pediatric brain imaging. However, the corresponding acquired MRI data usually suffers from severe artifacts, such as noise and motion. Therefore, an effective Quality Assessment (QA) method is essential. To this end, we design a Multi-Label MambaOut (MLMambaOut) model for the low-field pediatric brain MRI QA challenge. Specifically, we view this challenge as a multi-label classification task, utilizing four stages of gated convolution neural network blocks and ML-Decoder to finish the classification with class balance loss. Furthermore, we explore the performance of Mamba and some advanced models for this challenge. We performed extensive experiments on the challenge data, which is low-field and corrupted with seven kinds of artifacts. The results show that our MLMambaOut achieves superior classification results compared with other methods. © The Author(s) 2025.

关键词： Magnetic resonance imaging

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Electrochemical dissolution, reduction, and nucleation mechanisms of molybdenum in NaCl-KCl molten salt systems

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Journal of Materials Science and technology 2025年 238卷 45-54页

作者： Lv, Hongzhan Zhang, Liwen Xi, Xiaoli Nie, Zuoren Collaborative Innovation Center of Capital Resource-Recycling Material Technology Beijing University of Technology Beijing100124 China Key Laboratory of Advanced Functional Materials Ministry of Education Faculty of Materials and Manufacturing Beijing University of Technology Beijing100124 China National Engineering Laboratory for Industrial Big-data Application Technology Beijing University of Technology Beijing100124 China

This study investigates the anodic dissolution and electrochemical behavior of molybdenum in a NaCl-KCl molten salt system at 1023 K. The anodic dissolution process was systematically analyzed, revealing a sequential oxidation pathway of molybdenum into high-valence ions (Mo6+, Mo5+, Mo4+) under varying electrolysis potentials. Electrochemical Impedance Spectroscopy (EIS) demonstrated that the dissolution is governed by both charge transfer and diffusion mechanisms, with reduced impedance at higher potentials facilitating molybdenum dissolution. The reduction behavior of dissolved molybdenum ions was further explored using cyclic voltammetry (CV) and square wave voltammetry (SWV), confirming a multi-step reduction process controlled by diffusion and high reversibility. Nucleation studies using chronoamperometry established that molybdenum deposition follows an instantaneous nucleation mechanism. Morphological analysis of cathodic deposits revealed that current density significantly influences particle size, transitioning from nano-sized spherical particles to larger equiaxed crystals with increasing current density. These findings provide a comprehensive understanding of molybdenum's electrochemical properties in molten salts, offering valuable insights for optimizing electrolysis processes and advancing molybdenum-based material production. © 2025

关键词： Cyclic voltammetry

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Spatiotemporal deformation analysis of glaciers and surrounding landscapes in the Shishapangma region using InSAR techniques

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Journal of Mountain Science 2025年第1期22卷 210-229页

作者： LIANG Wenli LIU Rui JI Qin KOU Pinglang Chongqing Key Laboratory of GIS Application School of Geography and TourismChongqing Normal UniversityChongqing 401331China National Earth System Science Data Center Beijing 100000China Chongqing Engineering Research Center of Spatial Big Data Intelligent Technology Chongqing University of Posts and TelecommunicationsChongqing 400065China Key Laboratory of Tourism Multisource Data Perception and Decision Ministry of Culture and Tourism(TMDPDMCT)Chongqing University of Posts and TelecommunicationsChongqing 400065China

Glacier dynamics in the Himalayan midlatitudes,particularly in regions like the Shishapangma,are not yet fully understood,especially the localized topographic and climatic impacts on glacier *** study analyzes the spatiotemporal characteristics of glacier surface deformation in the Shishapangma region using the Small Baseline Subset(SBAS)Interferometric Synthetic Aperture Radar(In SAR)*** analysis reveals an average deformation rate of-4.02±17.65 mm/yr across the entire study area,with glacier regions exhibiting significantly higher rates of uplift(16.87±13.20 mm/yr)and subsidence(20.11±14.55 mm/yr)compared to non-glacier *** identifies significant surface lowering on the mountain flanks and localized uplift in certain catchments,emphasizing the higher deformation rates in glacial areas compared to non-glacial *** found a strong positive correlation between temperature and cumulative deformation(correlation coefficient of 0.63),particularly in glacier areas(0.82).The research highlights the role of temperature as the primary driver of glacier wastage,particularly at lower elevations,with strong correlations found between temperature and cumulative *** also indicates the complex interactions between topographic features,notably,slope gradient,which shows a positive correlation with subsidence rates,especially for slopes below 35°.South-,southwest-,and west-facing slopes exhibit significant uplift,while north-,northeast-,and east-facing slopes predominantly ***,we identified transition zones between debris-covered glaciers and clean ice as areas of most intense deformation,with average rates exceeding 30 mm/yr,highlighting these as potential high-risk zones for *** study comprehensively analyzes the deformation characteristics in both glacier and non-glacier areas in the Shishapangma region,revealing the complex interplay of topographic,climatic,and hydrological factors influencing glacier dynamic

关键词： Glacier melting SBAS-InSAR Topographic factors Temperature change Middle Himalayas

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A Revisit of Landsat-Observed Macroalgal Blooms in the Yellow Sea and East China Sea Before 2008

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Journal of Ocean University of China 2025年第2期24卷 525-531页

作者： YUAN Chao HUANG Juan WU Lingjuan XIAO Jie ZHANG Xuelei GAO Song LI Yifei XU Jiangling WANG Zongling Shandong Key Laboratory of Marine Ecological Environment and Disaster Prevention and Mitigation North China Sea Marine Forecasting and Hazard Mitigation CenterMinistry of Natural ResourcesQingdao 266061China Laboratory for Marine Ecology and Environmental Science Qingdao Marine Science and Technology CenterQingdao 266061China First Institute of Oceanography Ministry of Natural ResourcesQingdao 266061China National Engineering Laboratory for Integrated Aero-Space-Ground-Ocean Big Data Application Technology Xi’an 710129China

Harmful macroalgal blooms caused by Ulva prolifera and Sargassum horneri are increasing in the Yellow Sea and East China ***,our understanding of macroalgal blooms before 2008 is fragmented and *** time-series Landsat imagery from 1984 to 2008,we examined macroalgal bloom events and their evolutionary *** results suggest that no macroalgal blooms were observed before *** blooms could be traced back to 1999 and occurred on a small scale in 2000,2004 and 2005,before escalating into large green tides in 2007 and ***,these Ulva blooms were confined to the southern Yellow Sea from May to *** comparison,Sargassum blooms were first detected in the East China Sea in March 2000 and occurred almost every year thereafter,although the size of the blooms showed significant interannual *** distribution areas generally moved northwards from March until the bloom dissipated in May or June,suggesting the influence of the monsoon and *** investigation provided some insight into the bloom history of these two harmful macroalgal blooms in the Yellow Sea and East China Sea.

关键词： macroalgal bloom green tide golden tide remote sensing Landsat Yellow Sea East China Sea

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Research of photon counting imaging detector based on delay line anode 10

Research of photon counting imaging detector based on delay ...

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10th Symposium on Novel Optoelectronic Detection technology and applications

作者： Liu, Yong'an Zhang, Yalong Yang, Xianghui Zhang, Ruili Liu, Zhe Sheng, Lizhi State Key Laboratory of Transient Optics and Photonics Xi'an Institute of Optics and Precision Mechanics Chinese Academy of Sciences Xi'an China National Engineering Laboratory for Integrated Aero-Space-Ground-Ocean Big Data Application Technology China University of Chinese Academy of Sciences Beijing China

ISBN: (数字)9781510688155

ISBN: (纸本)9781510688148

Photon counting imaging detector based on microchannel plate (MCP) and position-sensitive anode readout has the ability to detect single photon, and has been widely used in space detection, high-energy physics and bioluminescence imaging. Traditionally, the detector consists of photocathode, electron multiplication part and position decoding part, in which position decoding is accomplished by position sensitive anode. The delay line anode not only has high spatial resolution and large detection area, but also has high count rate. Based on the principle of delay line decoding, an induction readout cross delay line anode (XDL) is designed and fabricated. And the performance of the detector is tested by using the experimental system. The results show that the width of XDL anode output pulse (FWHM) is about 4ns, the spatial resolution of the detector is better than 100μm, and the dark count rate is 2s). © 2025 SPIE.

关键词： Photocathodes

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Fundamental Diagram Modeling of Mixed Traffic Flow Considering Dedicated Lanes for Human-Driven Vehicles

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IEEE Transactions on Vehicular technology 2025年

作者： Wang, Yi Xu, Zeqi Wu, Yunxia Jiang, Yangsheng Yao, Zhihong Southwest Jiaotong University School of Transportation and Logistics National Engineering Laboratory of Integrated Transportation Big Data Application Technology National United Engineering Laboratory of Integrated and Intelligent Transportation Sichuan610031 China

To mitigate the impact of human-driven vehicles (HDVs) on connected and automated vehicles (CAVs) in mixed traffic environments, the implementation of dedicated lanes has been proposed to achieve partial separation between CAVs and HDVs, thereby improving the operational efficiency of both CAVs and the road segment. The lane management policy, where dedicated lanes for HDV (HDLs) and general lanes (GLs) coexist on a road segment, is referred to as the (G, H) policy. This paper proposes a multi-lane fundamental diagram model for mixed traffic flow and aims to investigate the effects of HDL configuration on the efficiency of road segments under the (G, H) policy. Firstly, different car-following modes in mixed traffic flow are analyzed, and various car-following models are employed to characterize the mixed traffic flow. Secondly, two lane selection principles are introduced to describe the lane choice behavior of HDVs under the (G, H) policy. Based on these principles, five equilibrium states that may exist on the road segment under the (G, H) policy are analyzed. Subsequently, a multi-lane fundamental diagram model incorporating HDL is derived based on the lane selection principles of HDV. Finally, numerical analysis is conducted to investigate the influence of lane configuration schemes under the (G, H) policy on the distribution of equilibrium states, fundamental diagram, and capacity. The results indicate that: (1) Based on the lane choice behavior of vehicles, the equilibrium states of road segment can be classified into five types. The distribution of each equilibrium state under different traffic conditions only depends on the proportion of HDL to the total number of lanes on road segment. A higher number of HDL leads to a reduced applicability of the (G, H) policy under different traffic conditions. (2) Under different penetration rates, as density increases, the overall traffic volume of road segment initially increases and then decreases until reaching the

关键词： Highway administration

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LightST: A Simplifying Spatio-Temporal Graph Neural Network for Traffic Flow Forecasting

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IEEE Transactions on big data 2025年

作者： Hu, Jie Zheng, Taichuan Peng, Lilan Teng, Fei Du, Shengdong Li, Tianrui Southwest Jiaotong University School of Computing and Artificial Intelligence Chengdu611756 China National Engineering Laboratory of Integrated Transportation Big Data Application Technology China

Traffic flow forecasting task plays an essential role in intelligent transportation systems. Accurately capturing the intricate spatio-temporal dependencies in traffic network signals is the core of precise prediction. Recently, a paradigm that models spatio-temporal dependencies through graph neural networks and time series models has become one of the most promising methods to solve this problem. However, existing methods still have limitations due to ineffectively modeling dynamic spatial dependencies and high time and space complexity. To address these issues, we propose a simplifying and powerful general spatio-temporal traffic flow forecasting model called LightST. Specifically, LightST first embeds temporal covariates and spatial position information to enhance the spatio-temporal modeling capabilities. Then, stacked temporal linear layers are introduced to capture temporal dependencies efficiently. Finally,we propose a concise adaptive spatio-temporal embedding graph convolution method to extract implicit spatial dependencies over time via dynamic graph convolution with adaptive spatio-temporal embedding graph generation. Extensive experiment results on four public traffic flow datasets demonstrate the superiority of our LightST concerning computational efficiency and prediction performance. © 2025 IEEE. All rights reserved,

关键词： Graph embeddings

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Super-Resolution of Diffusion-Weighted Images via TDI-Conditioned Diffusion Model 15th

Super-Resolution of Diffusion-Weighted Images via TDI-Cond...

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15th International Workshop on Computational Diffusion MRI, CDMRI 2024, held in conjunction with 27th International Conference on medical Image Computing and Computer-Assisted Intervention, MICCAI 2024

作者： Ma, Jiquan Teng, Yujun Chen, Geng Jiang, Haotian Zhang, Kai Liu, Feihong Rekik, Islem Shen, Dinggang School of Computer Science and Technology Heilongjiang University Harbin China National Engineering Laboratory for Integrated Aero-Space-Ground-Ocean Big Data Application Technology School of Computer Science and Engineering Northwestern Polytechnical University Xi’an China School of Biomedical Engineering and State Key Laboratory of Advanced Medical Materials and Devices ShanghaiTech University Shanghai China School of Information Science and Technology Northwest University Xi’an China BASIRA Lab Imperial-X and Department of Computing Imperial College London London United Kingdom

ISBN: (纸本)9783031869198

Diffusion-Weighted Imaging (DWI) is a significant technique for studying white matter. However, it suffers from low-resolution obstacles in clinical settings. Post-acquisition Super-Resolution (SR) can enhance the resolution of DWIs and has gained increasing research interest in recent years. An advanced generative model, the Diffusion Model (DM), exhibits particularly promising performance in image SR. However, effective conditions are required to bootstrap the DM for DWI SR. To this end, we proposed the first DM-based DWI SR model with two effective conditions based on low-solution DWIs and Track Density Imaging (TDI) maps, which possess rich high-resolution prior knowledge Additionally, we consider another condition based on features from low-resolution DWIs. These two conditions are integrated into our model, which comprises three components: DWI Resolution Enhancer (DRE), DWI Feature Extractor (DFE), and TDI Feature Extractor (TFE). DRE combines low-resolution DWI features from DFE with TDI features from TFE to progressively generate high-resolution DWIs. We performed extensive experiments on DWIs of normal subjects from human connectome projects and patients with Parkinson’s disease. The results demonstrate that our model outperforms existing DWI SR models, both qualitatively and quantitatively. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Neurodegenerative diseases

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Five-user quantum virtual local area network with an AlGaAs entangled photon source

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Science China(Physics,Mechanics & Astronomy) 2025年第3期68卷 61-73页

作者： Cheng Qian Hongkai Tian Xu Jing Yichen Liu Zhe Chen Huiran Luo Yuan Du Xiaodong Zheng Tangsheng Chen Yuechan Kong Hua-Lei Yin Dong Jiang Bin Niu Liangliang Lu Key Laboratory of State Manipulation and Advanced Materials in Provincial Universities School of Physical Science and TechnologyNanjing Normal UniversityNanjing210023China School of Internet Anhui UniversityHefei230039China National Key Laboratory of Solid-State Microwave Devices and Circuits Nanjing Chip Valley Industrial Technology InstituteNanjing Electronic Devices InstituteNanjing210016China Research Center for Quantum Optics and Quantum Communication School of ScienceQingdao University of TechnologyQingdao266520China Department of Physics and Beijing Key Laboratory of Opto-electronic Functional Materials and Micro-nano Devices Key Laboratory of Quantum State Construction and Manipulation(Ministry of Education)Renmin University of ChinaBeijing100872China Beijing Academy of Quantum Information Sciences Beijing100193China National Engineering Research Center of Agro-Ecological Big Data Analysis and Application Anhui UniversityHefei230601China National Laboratory of Solid-State Microstructures and School of Physics Nanjing UniversityNanjing210093China Hefei National Laboratory Hefei230088China

The promotion of quantum network applications demands the scalable connection of quantum *** is preferable to set up multiple logical networks coexisting on a single physical network infrastructure to accommodate a larger number of *** we present a quantum virtual network architecture that offers this level of scalability,without being constrained to a fixed physical-layer network relying solely on passive multiplexing *** architecture can be understood as arising from the superposition of a fully connected entanglement distribution network and port-based virtual local area network,which group multiusers by access *** terms of hardware,we leverage a semiconductor chip with a high figure-of-merit modal overlap to directly generate high-quality polarization entanglement,and a streamlined polarization analysis module,which requires only one single-photon detector for each end *** experimentally perform the BBM92 QKD protocol on the five-user quantum virtual network and demonstrate voice and image encryption on a campus area *** results may provide insights into the realization of large-scale quantum networks with integrated and cost-efficient photonic architecture.

关键词： quantum network quantum entanglement distribution integrated photonics image and voice encryption

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