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Generation of global 1-km daily top-of-atmosphere outgoing longwave radiation product from 2000 to 2021 using machine learning

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International Journal of Digital Earth 2023年第1期16卷 2002-2012页

作者： chuan zhan Shunlin Liang School of Resources and Environmental Engineering Wuhan University of Science and TechnologyWuhanPeople's Republic of China department of Geography The University of Hong KongPokfulamPeople's Republic of China

Top-of-atmosphere(TOA)outgoing longwave radiation(OLR),a key component of the Earth’s energy budget,serves as a diagnostic of the Earth’s climate system response to incoming solar ***,existing products are typically estimated using broadband sensors with coarse spatial *** paper presents a machine learning method to estimate TOA OLR by directly linking Moderate Resolution Imaging Spectroradiometer(MODIS)TOA radiances with TOA OLR determined by Clouds and the Earth’s Radiant Energy System(CERES)and other information,such as the viewing geometry,land surface temperature and cloud top temperature determined by Modern-Era Retrospective analysis for Research and Applications,Version 2(MERRA-2).Models are built separately under clear-and cloudy-sky conditions using a gradient boosting regression *** test results show that the root mean square errors(RMSEs)of the clear-sky and cloudy-sky models for estimating instantaneous values are 4.1 and 7.8 W/m^(2),***-time conversion ratios derived from CERES daily and hourly OLR data are used to convert the instantaneous MODIS OLR to daily ***-comparisons of the daily results show that the RMSE of the estimated MODIS OLR is 8.9 W/m^(2) in East *** developed high resolution dataset will be beneficial in analyzing the regional energy budget.

关键词： TOA outgoing longwave radiation MODIS CERES machine learning Earth’s energy budget

Controllable chaos in the coupled waveguide-optomechanical system with phase shifter

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Science China(Physics,Mechanics & Astronomy) 2025年第04期Mechanics & Astronomy) .卷 30-38页

作者： deng-Wei zhang Pei-Qi Qin Li-Li Zheng Zhi-Ming zhan Xin-You Lü department of Mathematics and Physics Luoyang Institute of Science and Technology School of Computer and Information Engineering School of Software Luoyang Institute of Science and Technology School of Artificial Intelligence Jianghan University School of Physics Huazhong University of Science and Technology

We theoretically investigate chaotic dynamics in an optomechanical system composed of a whispering-gallery-mode(WGM) microresonator and a sensor. We find that tuning the optical phase using a phase shifter and modifying the coupling strength via a unidirectional waveguide(IWG) can induce chaotic motion. The underlying reason for this phenomenon is that adjusting the phase and coupling strength via the phase shifter and IWG bring the system close to an exceptional point(EP), where field localization dynamically enhances the optomechanical nonlinearity, leading to the generation of chaotic motion. In addition, due to the sensitivity of chaos to phase in the vicinity of the EP, we propose a theoretical scheme to measure the optical phase perturbations using chaos. Our work may offer an alternative approach to chaos generation with current experimental technology and provide theoretical guidance for optical signal processing and chaotic secure communication.

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Research on SAR Image Lightweight detection Based on Improved YOLOV8

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印刷与数字媒体技术研究 2025年第1期 93-100页

作者： WANG Qing SI zhan-jun School of Institute of Artificial Intelligence Tianjin University of Science and TechnologyTianjin 300457China

In recent years,with the development of synthetic aperture radar(SAR)technology and the widespread application of deep learning,lightweight detection of SAR images has emerged as a research *** ultimate goal is to reduce computational and storage requirements while ensuring detection accuracy and reliability,making it an ideal choice for achieving rapid response and efficient *** this regard,a lightweight SAR ship target detection algorithm based on YOLOv8 was proposed in this ***,the C2f-Sc module was designed by fusing the C2f in the backbone network with the ScConv to reduce spatial redundancy and channel redundancy between features in convolutional neural *** the same time,the Ghost module was introduced into the neck network to effectively reduce model parameters and computational complexity.A relatively lightweight EMA attention mechanism was added to the neck network to promote the effective fusion of features at different *** results showed that the Parameters and GFLOPs of the improved model are reduced by 8.5%and 7.0%when mAP@0.5 and mAP@0.5:0.95 are increased by 0.7%and 1.8%,*** makes the model lightweight and improves the detection accuracy,which has certain application value.

关键词： YOLOv8 Synthetic aperture radar image Lightweight Target detection

论《红楼梦》改编的关键问题——以电影《红楼梦之金玉良缘》为讨论对象

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红楼梦学刊 2025年第1期 229-243页

作者：詹丹上海师范大学光启语文研究院 200234

《红楼梦》因为作品本身的内容庞杂、人物独特、情节淡化、结局缺失等原因而给影视剧改编带来了难题,有人认为,是否忠实于原著是判断改编成功与否的关键。其实,改编既可以力求忠实于原著,也可以站位时代而跟原著形成对话,但无论取何种方... 详细信息

《红楼梦》因为作品本身的内容庞杂、人物独特、情节淡化、结局缺失等原因而给影视剧改编带来了难题,有人认为,是否忠实于原著是判断改编成功与否的关键。其实,改编既可以力求忠实于原著,也可以站位时代而跟原著形成对话,但无论取何种方式,关键在于能否做到逻辑自洽,而胡玫执导的《红楼梦之金玉良缘》恰恰在这关键问题上留下颇多遗憾。

关键词：红楼梦影视剧改编胡玫导演逻辑自洽

甲骨文献材料立体化应用——以殷商射官事件重构为例

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文献 2025年第1期 33-47页

作者：展翔南开大学汉语言文化学院 “古文字与中华文明传承发展工程”协同攻关创新平台

甲骨文献材料零散的客观情况,需要不断探索新的研究方法提高其利用价值,树立立体化思维是一个可能路径。以殷商射官为例,以材料所涉时间、类组、内容、人物相同或相近为原则,进行事件重构,对相关人物、事件等展开考察,梳理出射官主要参... 详细信息

甲骨文献材料零散的客观情况,需要不断探索新的研究方法提高其利用价值,树立立体化思维是一个可能路径。以殷商射官为例,以材料所涉时间、类组、内容、人物相同或相近为原则,进行事件重构,对相关人物、事件等展开考察,梳理出射官主要参与过的七个事件:“射■以羌”和“射■获羌”事件、“射于■”事件、“射何遊卒”事件、“射倗防某地”事件、“射■即■”事件、军事资源输入输出事件以及“多射先陟”事件。以此为基础,总结出殷商王朝军事活动的五个特点:第一,对作战经验的重要性有足够认识,并对技术兵种进行训练;第二,利用军事资源进行交流;第三,具有根据作战目的进行兵种配置的思想;第四,军事建制较为完备;第五,战略、战术较为成熟,并能根据实际情况进行调整。

关键词：甲骨文献材料立体化思维射职官

Insight into the particle shape on the impact of dry granular flow against a rigid barrier: A deM study

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Journal of Earth Science 2025年

作者： Rui-Xiao zhan Dong Su Xiang-Sheng Chen Yuan-Jun Jiang Guo-Ping Lei Jing-Jing Yu Key Laboratory for Resilient Infrastructures of Coastal Cities (MOE)， Shenzhen University College of Civil and Transportation Engineering， Shenzhen University School of Architecture and Urban Planning， Shenzhen University Shenzhen Key Laboratory of Green， Efficient and Intelligent Construction of Underground Metro Station， Shenzhen University Institute of Mountain Hazards and Environment， Chinese Academy of Sciences School of Transportation， Civil Engineering & Architecture， Foshan University

The effect of particle shape on the impact of dry granular flow remains an open area for further investigation. Five distinct particle shapes were examined in this study using discrete element simulations after calibrating the numerical model using a published work. The findings indicated that the particle shape had a significant influence on granular mobility. With negligible variations in normalized kinetic energy between particles of different shapes， the effect of particle shape on the increasing rate of kinetic energy became more obvious. All irregular particle scenarios had longer accumulated particle lengths down the channel than spherical particles. Variations in particle shape led to adjustments in the distribution of impact forces on the barrier. These findings substantially enhance our understanding of the distinctive effects of particle shapes on the impact mechanism of dry granular flow.

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中山大学科技期刊出版史略(1866—2024)

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中山大学学报（自然科学版）（中英文） 2025年第1期64卷 1-27页

作者：张冰詹拔群中山大学学报编辑部广东广州510275 中山大学期刊管理中心广东广州510275

本文力图较为完整地展现中山大学100多年的科技期刊出版历史全貌,在明晰中山大学办学源流的基础上将其前身各校的科技期刊出版情况纳入梳理,整理统计出中山大学及其前身各校在正式建校前(1866—1923年)出版科技期刊25种、建校后的民国时... 详细信息

本文力图较为完整地展现中山大学100多年的科技期刊出版历史全貌,在明晰中山大学办学源流的基础上将其前身各校的科技期刊出版情况纳入梳理,整理统计出中山大学及其前身各校在正式建校前(1866—1923年)出版科技期刊25种、建校后的民国时期(1924—1948年)出版科技期刊87种,共和国时期(1949—2024年)出版科技期刊60种,共计172种,并对代表性刊物进行简要介绍。中山大学的科技期刊出版以医学类期刊的贡献最为突出,其影响一直延续至今。这些科技期刊从科研学术角度记录了中山大学的学科发展历史,同时为中国近代科学技术的传播和发展作出了重要的贡献。

关键词：中山大学科技期刊出版史校史

Thickness-dependent magnetic property of FeNi thin film grown on flexible graphene substrate

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Chinese Physics B 2025年第2期34卷 448-452页

作者： Suixin zhan Shaokang Yuan Yuming Bai Fu Liu Bohan zhang Weijia Han Tao Wang Shengxiang Wang Cai Zhou State Key Laboratory of New Textile Materials and Advanced Processing Technologies Wuhan Textile UniversityWuhan 430200China School of Mathematical and Physical Sciences Wuhan Textile UniversityWuhan 430200China School of Integrated Circuits Huazhong University of Science and TechnologyWuhan 430074China Key Laboratory for Magnetism and Magnetic Materials Ministry of EducationLanzhou UniversityLanzhou 730000China

Electronics over flexible substrates offer advantages of flexibility, portability and low cost, and promising applications in the areas of energy, information, defense science and medical service. In recent years, tremendous progress has been witnessed in the development of flexible wearable devices that can be potentially massively deployed. Of particular interest are intelligent wearable devices, such as sensors and storage cells, which can be integrated by flexible magnetoelectronic devices based on magnetic thin films. To examine this further, the magnetic properties of FeNi thin films with different thicknesses grown on flexible graphene substrate are investigated at room temperature. The coercivity increases with increasing thicknesses of FeNi thin film, which can be attributed to the increase of grain size and decrease of surface roughness. Moreover, the thickness modulated magnetic property shows a magnetic anisotropy shift increase with varying thicknesses of FeNi thin film by using measurements based on ferromagnetic resonance, which further enhances the resonance frequency. In addition, the resonance peak is quite stable after bending it for ten cycles. The result is promising for the future design of flexible magnetoelectronic devices.

关键词： resonance frequency FeNi thin film flexible graphene substrate magnetic property

MDCFS: few-shot object detection with multilevel decoupled classifiers

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Optoelectronics Letters 2025年

作者： LI chuanhui ZHOU Mian FENG Zhikun SUI Zezhou GAO zhan School of Computer Science and Engineering， Tianjin University of Technology

Few-shot object detection poses unique challenges as it requires effectively learning novel classes with limited labeled data. Current approaches often suffer from biases towards base classes during fine-tuning， leading to suboptimal performance on detecting novel classes. Additionally， in complex scenes， the confusion between foreground and background objects further affects the accuracy and robustness of the model. To address these issues， we propose the Multilevel decoupling Classification Few-Shot Algorithm (MDCFS). we decouple the standard classifier into a parallel foreground classifier and a background classifier in the Few-Shot Object detection (FSOD) setting. This decoupling enables the independent separation of positive samples from noisy negative samples， alleviating the foreground-background confusion problem commonly encountered in few-shot detectors. For Generalized Few-Shot Object detection (G-FSOD)， where the few-shot dataset contains base classes， we further decouple the foreground classification head into a base class classification head and a novel class classification head. To ensure balance， we assign more weight to the novel class classification head， effectively addressing the bias towards base classes. Furthermore， we optimize the initial weights of the few-shot fine-tuning stage， significantly reducing training time and mitigating catastrophic forgetting in G-FSOD. Additionally， we incorporate metric learning into our model with minimal cost. Experimental results demonstrate the effectiveness of our approach. Compared to state-of-the-art few-shot object detection methods based on fine-tuning， MDCFS achieves performance improvements of up to 6.3% on the PASCAL VOC dataset and 1.5% on the COCO dataset.

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