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Experimental demonstration of D-band signals wireless transmission over 30 km

science China(Technological sciences) 2025年第2期68卷 318-320页

作者： Yi WEI Xiongwei YANG Jianjun YU Xianming ZHAO Mingxu WANG Jingwen TAN Weiping LI Feng ZHAO Chengzhen BIAN Hansong MA Qinyi ZHANG Qiutong ZHANG Bing Zhang Wen ZHOU Kaihui WANG Sicong XU Jianguo YU State Key Laboratory of ASIC and System Key Laboratory for Information Science of Electromagnetic Waves(MoE)and School of Information Science and TechnologyFudan UniversityShanghai 200433China Harbin Institute of Technology Harbin 150001China School of Automation Xi’an University of Posts and TelecommunicationsXi’an 710121China School of Electronic Engineering Beijing University of Posts and TelecommunicationsBeijing 100876China

Due to the rise of innovative technologies like artificial intelligence(AI),the Internet of Things(IoT),and telemedicine,the demand for internet traffic is rapidly *** order to achieve ultra-high-speed wireless communication,many researchers are directing their efforts towards the *** D-band,spanning the frequency band 110-170 GHz,has abundant spectrum resources and license-free characteristics[1,2].

关键词： IoT wireless band

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Hypoxia-triggered photothermal/drug combination therapy of tumors using a perylene diimide molecular capsule

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science China Chemistry 2025年第3期68卷 1009-1017页

作者： Fei Yang Guo Wang Kecheng Huang Yanqing Xu Xiao Feng Weizhi Wang Wei Wei Key Laboratory of Medical Molecule Science and Pharmaceutics Engineering Ministry of Industry and Information TechnologySchool of Chemistry and Chemical EngineeringBeijing Institute of TechnologyBeijing 100081China Beijing Key Laboratory for Optical Materials and Photonic Devices Department of ChemistryCapital Normal UniversityBeijing 100048China

Hypoxia is a common characteristic of tumors and associated with poor outcome in most cancer types,thus hypoxia-triggered combined therapeutic systems with well-defined structure hold significant promise for achieving specific and effective tumor ***,a water-soluble perylene diimide(PDI)cyclophane“Gemini Box”(GBox-1^(4+))is demonstrated as both a hypoxia-responsive photothermal agent and a drug capsule for tumor-specific combination ***,owing to the covalent enclosure of PDI chromophore by double-sided molecular straps,GBox-1^(4+)can significantly stabilize labile PDI radical anions generated through bioreduction at the lesion site of hypoxic tumors,leading to high-efficiency near-infrared photothermal ablation of ***,GBox-1^(4+)can act as a molecular capsule to bind water-insoluble antitumor drugs camptothecin and hydroxycamptothecin in 1:1 host-guest stoichiometry with high affinities,greatly enhancing the water solubility of ***,such drug-loading cyclophane system as a hypoxia-activated photothermal/drug combined therapeutic platform exhibits more effective inhibition of tumor growth than the single treatment under identical *** study significantly extends the application range of host-guest cyclophane systems and opens a promising avenue to structurally uniform combined therapeutic agents against hypoxic tumors with improved specificity.

关键词： hypoxia-responsive photothermal agent cyclophanes host-guest system near-infrared combination therapy

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Handwritten W-Net for High-Frequency Guided Single-Image Super-Resolution

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IEEE Access 2025年 13卷 73124-73134页

作者： Yang, Xiang Fang, Chen Xie, Xiaolan Dong, Minggang Guilin University of Technology College of Computer Science and Engineering Guangxi Guilin China Guilin University of Technology Guangxi Key Laboratory of Embedded Technology and Intelligent System Guangxi Guilin China Guilin University of Technology College of Physics and Electronic Information Engineering Guangxi Guilin China

Super-resolution (SR) imaging involves converting low-resolution images into corresponding high-resolution data in specific scenarios. Recent advances in intelligent image reconstruction algorithms have been accompanied by impressive visual outcomes in SR generative adversarial networks (GANs). However, existing research has methodological limitations owing to the constraints posed by the model architecture and loss guidance used for optimization. Consequently, unnatural artifacts often appear in the complex backgrounds of images, leading to unappealing visual results. To address these problems, we propose an enhanced U-Net, known as the handwritten W-Net (HW-Net) architecture, as well as a loss function that uses high-frequency components for guidance. The former improves the best approximate representation of image regions, whereas the latter guides the generation of SR images with more detailed features. We experimentally implemented a biased strategy called parameter transfer, which is suitable for hybrid parameter models. This approach facilitates the blending of weight parameters between similar but different models, significantly improving the peak signal-to-noise ratio and structural similarity index measure metrics without sacrificing the learned perceptual image patch similarity. Across nine SR benchmark datasets, the proposed combinations, with and without parameter transfer, demonstrated excellent performance across multiple evaluation metrics, surpassing the state-of-the-art SRGAN. The code is available at https://***/DaHuaSen/H2SR. © 2013 IEEE.

关键词： Image enhancement

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Machine learning-assisted fluorescence visualization for sequential quantitative detection of aluminum and fluoride ions

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Journal of Environmental sciences 2025年第3期149卷 68-78页

作者： Qiang Zhang Xin Li Long Yu Lingxiao Wang Zhiqing Wen Pengchen Su Zhenli Sun Suhua Wang School of Environmental Science and Engineering Guangdong University of Petrochemical TechnologyMaoming 525000China MOE Key Laboratory of Resources and Environmental System Optimization College of Environmental Science and EngineeringNorth China Electric Power UniversityBeijing 102206China

The presence of aluminum(Al^(3+))and fluoride(F^(−))ions in the environment can be harmful to ecosystems and human health,highlighting the need for accurate and efficient *** this paper,an innovative approach is presented that leverages the power of machine learning to enhance the accuracy and efficiency of fluorescence-based detection for sequential quantitative analysis of aluminum(Al^(3+))and fluoride(F^(−))ions in aqueous *** proposed method involves the synthesis of sulfur-functionalized carbon dots(C-dots)as fluorescence probes,with fluorescence enhancement upon interaction with Al^(3+)ions,achieving a detection limit of 4.2 nmol/***,in the presence of F^(−)ions,fluorescence is quenched,with a detection limit of 47.6 nmol/*** fingerprints of fluorescence images are extracted using a cross-platform computer vision library in Python,followed by data ***,the fingerprint data is subjected to cluster analysis using the K-means model from machine learning,and the average Silhouette Coefficient indicates excellent model ***,a regression analysis based on the principal component analysis method is employed to achieve more precise quantitative analysis of aluminum and fluoride *** results demonstrate that the developed model excels in terms of accuracy and *** groundbreaking model not only showcases exceptional performance but also addresses the urgent need for effective environmental monitoring and risk assessment,making it a valuable tool for safeguarding our ecosystems and public health.

关键词： Machine learning Aluminum ion detection Fluorine ion detection Fluorescence probe K-means model

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Multi-parameter ultrasound imaging for musculoskeletal tissues based on a physics informed generative adversarial network

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Chinese Physics B 2025年第4期34卷 442-455页

作者： Pengxin Wang Heyu Ma Tianyu Liu Chengcheng Liu Dan Li Dean Ta Institute of Biomedical Engineering&Technology Academy for Engineering and TechnologyFudan UniversityShanghai 200433China State Key Laboratory of Integrated Chips and Systems Fudan UniversityShanghai 201203China Department of Electronic Engineering School of Information Science and TechnologyFudan UniversityShanghai 200438China Department of Biomedical Engineering School of Information Science and TechnologyFudan UniversityShanghai 200438China

Full waveform inversion(FWI)has showed great potential in the detection of musculoskeletal ***,FWI is an ill-posed inverse problem and has a high requirement on the initial model during the imaging *** inaccurate initial model may lead to local minima in the inversion and unexpected imaging results caused by cycle-skipping *** learning methods have been applied in musculoskeletal imaging,but need a large amount of data for *** by work related to generative adversarial networks with physical informed constrain,we proposed a method named as bone ultrasound imaging with physics informed generative adversarial network(BUIPIGAN)to achieve unsupervised multi-parameter imaging for musculoskeletal tissues,focusing on speed of sound(SOS)and *** the in-silico experiments using a ring array transducer,conventional FWI methods and BUIPIGAN were employed for multiparameter imaging of two musculoskeletal tissue *** results were evaluated based on visual appearance,structural similarity index measure(SSIM),signal-to-noise ratio(SNR),and relative error(RE).For SOS imaging of the tibia–fibula model,the proposed BUIPIGAN achieved accurate SOS imaging with best *** specific quantitative metrics for SOS imaging were SSIM 0.9573,SNR 28.70 dB,and RE 5.78%.For the multi-parameter imaging of the tibia–fibula and human forearm,the BUIPIGAN successfully reconstructed SOS and density distributions with SSIM above 94%,SNR above 21 dB,and RE below 10%.The BUIPIGAN also showed robustness across various noise levels(i.e.,30 dB,10 dB).The results demonstrated that the proposed BUIPIGAN can achieve high-accuracy SOS and density imaging,proving its potential for applications in musculoskeletal ultrasound imaging.

关键词： ultrasound image physics informed generative adversarial network musculoskeletal imaging

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Element relational graph-augmented multi-granularity contextualized encoding for document-level event role filler extraction

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Frontiers of Computer science 2025年第2期19卷 137-138页

作者： Enchang ZHU Zhengtao YU Yuxin HUANG Shengxiang GAO Yantuan XIAN Faculty of Information Engineering and Automation Kunming University of Science and TechnologyKunming 650500China Yunnan Key Laboratory of Artificial Intelligence Kunming University of Science and TechnologyKunming 650500China

1 Introduction Document-level Role Filler Extraction aims to identify those spans of text that denote the role fillers for each event described in the document[1].Despite achieving certain accomplishments,existing methods are still not effective due to the following two issues:(1)there are difficulties in contextual modeling of long text,which requires modeling and understanding coherence and connections across sentences and paragraphs;(2)there usually ignore the explicit dependency relationships between event elements displayed in long *** this end,we propose a novel graph-augmented approach for document-level event role filler extraction,named element relational graph-augmented multi-granularity contextualized encoder(ERGM),whose main idea is to effectively enhance the model's capabilities in capturing deep semantic information of events in long texts and modeling dependency relationships among event elements by incorporating the Event elements relational ***,this method first constructs the structural graph by extracting elements from the source document.

关键词： contextual spite semantic

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Improving Sensing Performance of Plate-Type Fiber-Optic Accelerometers Using Noncircular Fiber-Optic Coils

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IEEE Sensors Journal 2025年第9期25卷 15080-15091页

作者： Lu, Tan Wang, Shun Wen, Kunhua Yang, Jun Mo, Haohao Jiang, Ruiyao Ping, Xinyang An, Ran Wang, Yuncai Qin, Yuwen Guangdong University of Technology School of Physics and Optoelectronic Engineering Key Laboratory of Photonic Technology for Integrated Sensing and Communication Ministry of Education of China Guangdong Provincial Key Laboratory of Information Photonics Technology Guangdong Provincial Key Laboratory of Sensing Physics and System Integration Applications Guangzhou510006 China Guangdong University of Technology Institute of Advanced Photonic Technology School of Information Engineering Key Laboratory of Photonic Technology for Integrated Sensing and Communication Ministry of Education of China Guangdong Provincial Key Laboratory of Information Photonics Technology Guangzhou510006 China Harbin Engineering University Key Laboratory of In-Fiber Integrated Optics Ministry of Education of China College of Physics and Optoelectronic Engineering Harbin150001 China

The commonly used mandrel-type or disk-type fiber-optic accelerometers (DT-FOAs) are inherently limited in their capacity to detect low-frequency signals due to their structural characteristics. The fiber-optic coil (FOC), as the core sensing component of an interferometric FOA, plays a crucial role in determining the sensor’s sensitivity through its strain distribution characteristics on the transducer plate. This article presents, for the first time, the novel introduction of noncircular FOCs (NC-FOCs), which are employed in the design of a rectangular thin-plate FOA and plate-tpye FOA (PT-FOA) to improve low-frequency detection performance. In this study, the finite element method (FEM) and tensor analysis theory are employed to establish a universal model for PT-FOA constructed with NC-FOCs. Sensors with FOCs of various shapes were designed, fabricated, and tested. Both theoretical and experimental results demonstrate that different shapes of FOCs can improve sensitivity by approximately 14.62%. The underlying mechanisms of these improvements are analyzed by studying the strain tensor distribution on the transducer plate. The proposed PT-FOA addresses the limitations of existing FOAs in low-frequency detection. The sensitivity enhancement method maintains the same resonant frequency and thermal noise levels while significantly improving the signal-to-noise ratio (SNR) and sensitivity of the sensor. This work provides a general modeling approach and valuable practical guidance for the design and optimization of high-sensitivity FOAs, with important implications for both research and application. © 2001-2012 IEEE.

关键词： Signal to noise ratio

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Interdecadal Change of Relationship between North Atlantic Oscillation and Tropical Cyclone Genesis Frequency over the Western North Pacific

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Journal of Climate 2025年第8期38卷 1855-1870页

作者： Wang, Zhen Zhou, Botao Zhao, Jiuwei State Key Laboratory of Climate System Prediction and Risk Management Key Laboratory of Meteorological Disaster Ministry of Education Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters Nanjing University of Information Science and Technology Nanjing China School of Atmospheric Sciences Nanjing University of Information Science and Technology Nanjing China

This article investigates the relationship between spring (March–May) North Atlantic Oscillation (NAO) and the tropical cyclone genesis frequency (TCGF) over the western North Pacific (WNP) from June to November. It is found that their relationship appears insignificant from 1950 to 1971, intensifies significantly from 1972 to 2010, and then weakens again since 2011. The interdecadal change of this relationship is strongly influenced by the meridional displacement of the North Atlantic jet stream (NAJS). During 1972–2010, the NAJS is located southward, facilitating the spread of Rossby wave energy to the equatorial region and enhancing the NAO impact on sea surface temperatures (SSTs) over the tropical North Atlantic (TNA). Generally, positive (negative) phases of the NAO relate to negative (positive) TNA SST anomalies in spring, subsequently triggering positive (negative) SST anomalies in the central Pacific through the wind–evaporation–SST feedback. The central Pacific SST anomalies, intensifying from summer to autumn, lead to a basin-uniform circulation anomaly over the WNP and ultimately control the WNP TCGF. Conversely, in the other two periods, owing to the northward shift of the NAJS, the influence of the NAO is constrained to the extratropics, thereby disrupting the linkage between the NAO and TNA SST anomalies. As a result, the interannual relationship of spring NAO with the WNP TCGF weakens. The decadal meridional shift of the NAJS is supposed to be associated with the phase transition of the Pacific decadal oscillation. © 2025 American Meteorological Society.

关键词： Tropical cyclone

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Cat Swarm Algorithm Generated Based on Genetic Programming Framework Applied in Digital Watermarking

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Computers, Materials & Continua 2025年第5期83卷 3135-3163页

作者： Shu-Chuan Chu Libin Fu Jeng-Shyang Pan Xingsi Xue Min Liu School of Artificial Intelligence Nanjing University of Information Science and TechnologyNanjing210000China College of Computer Science and Engineering Shandong University of Science and TechnologyQingdao266000China Department of Information Management Chaoyang University of TechnologyTaichung40601TaiwanChina School of Information Science and Engineering Fujian University of TechnologyFuzhou350000China Key Laboratory of Hydrometeorological Disaster Mechanism and Warning of Ministry of Water Resource Nanjing University of Information Science and TechnologyNanjing210000China

Evolutionary algorithms have been extensively utilized in practical ***,manually designed population updating formulas are inherently prone to the subjective influence of the *** programming(GP),characterized by its tree-based solution structure,is a widely adopted technique for optimizing the structure of mathematical models tailored to real-world *** paper introduces a GP-based framework(GPEAs)for the autonomous generation of update formulas,aiming to reduce human *** modifications to tree-based GP have been instigated,encompassing adjustments to its initialization process and fundamental update operations such as crossover and mutation within the *** designing suitable function sets and terminal sets tailored to the selected evolutionary algorithm,and ultimately derive an improved update *** Cat Swarm Optimization Algorithm(CSO)is chosen as a case study,and the GP-EAs is employed to regenerate the speed update formulas of the *** validate the feasibility of the GP-EAs,the comprehensive performance of the enhanced algorithm(GP-CSO)was evaluated on the CEC2017 benchmark ***,GP-CSO is applied to deduce suitable embedding factors,thereby improving the robustness of the digital watermarking *** experimental results indicate that the update formulas generated through training with GP-EAs possess excellent performance scalability and practical application proficiency.

关键词： Cat swarm algorithm genetic programming digital watermarking update mode mode generation framework

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An Uncertainty Quantization-Based Method for Anti-UAV Detection in Infrared Images

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Computers, Materials & Continua 2025年第4期83卷 1439-1458页

作者： Can Wu Wenyi Tang Yunbo Rao Yinjie Chen Hui Ding Shuzhen Zhu Yuanyuan Wang School of Information and Software Engineering University of Electronic Science and Technology of ChinaChengdu610054China State Key Laboratory of Air Traffic Management System Nanjing210000China National Airspace Management Center Beijing100094China

Infrared unmanned aerial vehicle(UAV)target detection presents significant challenges due to the inter-play between small targets and complex *** methods,while effective in controlled environments,often fail in scenarios involving long-range targets,high noise levels,or intricate backgrounds,highlighting the need for more robust *** address these challenges,we propose a novel three-stage UAV segmentation framework that leverages uncertainty quantification to enhance target *** framework incorporates a Bayesian convolutional neural network capable of generating both segmentation maps and probabilistic uncertainty *** utilizing uncer-tainty predictions,our method refines segmentation outcomes,achieving superior detection ***,this marks the first application of uncertainty modeling within the context of infrared UAV target *** evaluations on three publicly available infrared UAV datasets demonstrate the effectiveness of the proposed *** results reveal significant improvements in both detection precision and robustness when compared to state-of-the-art deep learning *** approach also extends the capabilities of encoder-decoder convolutional neural networks by introducing uncertainty modeling,enabling the network to better handle the challenges posed by small targets and complex environmental *** bridging the gap between theoretical uncertainty modeling and practical detection tasks,our work offers a new perspective on enhancing model interpretability and *** codes of this work are available openly at https://***/general-learner/UQ_Anti_UAV(acceessed on 11 November 2024).

关键词： Object segmentation uncertainty quantification bayesian convolutional neural network

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