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Mutual-structure weighted guided image filtering for depth map restoration

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Optoelectronics Letters 2025年第1期21卷 51-56页

作者： LIU Zijian song jian CHEN Quanmin XU jiangtao Tianjin Key Laboratory of Imaging and Sensing Microelectronic Technology School of Microelectronics Tianjin University Spikesee Technology Co. Ltd.

Although guided image filtering(GIF) is known for preserving edges and fast computation, it may produce inaccurate outputs in depth map restoration. In this paper, a novel confidence-weighted GIF called mutual-structure weighted GIF(MSWGIF) is proposed, which replaces the mean filtering strategy in GIF during handling overlapping windows. The confidence value is composed of a depth term and a mutual-structure term, where the depth term is utilized to protect the edges of the output, and the mutual-structure term helps to select accurate windows during the structure characteristics of the guidance image are transferred to the output. Experimental results show that MSWGIF reduces the root mean square error(RMSE) by an average of 12.37%, and the average growth rate of correlation(CORR) is 0.07% on average. Additionally, the average growth rate of structure similarity index measure(SSIM) is 0.34%.

关键词： Wiener filtering

Research progress of catalysts for direct coal liquefaction

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Journal of Energy Chemistry 2025年第1期100卷 481-497页

作者： Wei song Penggao Liu Xinyue Chen Ting Wang Chunrong He rui Hao Kaiyu Liu State Key Laboratory of Chemistry and Utilization of Carbon Based Energy Resources College of Chemistry Xinjiang University College of Chemistry and Chemical Engineering Henan Polytechnic University Hunan Provincial Key Laboratory of Chemical Power Sources College of Chemistry and Chemical Engineering Central South University

Coal direct liquefaction technology is a crucial contemporary coal chemical technology for efficient and clean use of coal resources. The development of direct coal liquefaction technology and the promotion of alternative energy sources are important measures to guarantee energy security and economic security. However, several challenges need to be addressed, including low conversion rate, inadequate oil yield, significant coking, demanding reaction conditions, and high energy consumption. Extensive research has been conducted on these issues, but further exploration is required in certain aspects such as pyrolysis of macromolecules during the liquefaction process, hydrogen activation, catalysts' performance and stability, solvent hydrogenation, as well as interactions between free radicals to understand their mechanisms better. This paper presents a comprehensive analysis of the design strategy for efficient catalysts in coal liquefaction, encompassing the mechanism of coal liquefaction, catalyst construction,and enhancement of catalytic conversion efficiency. It serves as a comprehensive guide for further research endeavors. Firstly, it systematically summarizes the conversion mechanism of direct coal liquefaction, provides detailed descriptions of various catalyst design strategies, and especially outlines the catalytic mechanism. Furthermore, it addresses the challenges and prospects associated with constructing efficient catalysts for direct coal liquefaction based on an understanding of their action mechanisms.

关键词： Direct coal liquefaction Catalysts Mechanism of action Solvent hydrogenation

Satellite-assisted 6G wide-area edge intelligence:dynamics-aware task offloading and resource allocation for remote IoT services

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Science China(Information Sciences) 2025年

作者： Di ZHAO rui DING Bin song State Key Laboratory of Integrated Services Networks Xidian University Hangzhou Institute of Technology Xidian University China Satellite Network Group Co. Ltd.

Future 6G networks will integrate non-terrestrial communication with mobile edge computing to enable wide-area edge intelligence, providing ubiquitous communication and computation services for everyone and everything. In this paper, we introduce the intelligent cloud-edge-device architecture into low Earth orbit (LEO) satellite-supported remote Internet of Things(IoT) networks to facilitate latency-sensitive and compute-intensive IoT applications. However, the dynamic spatio-temporal characteristics inherent in LEO satellite networks, such as the high volatility of task traffic and the high mobility of space nodes, pose severe challenges. For efficient task execution, we investigate the joint optimization of cross-region task offloading and cross-domain resource allocation, and innovatively propose a spatio-temporal attention-based proximal policy optimization(STA-PPO) algorithm. Specifically, the temporal attention-based actor network analyzes the timing dependencies of task arrival and makes time-variant decisions. Simultaneously, the spatial attention-based critic network captures the spatial variations of satellite motion and evaluates the topology-related value. We verify the effectiveness of the cloud-edge-device collaboration through extensive simulations. Numerical results demonstrate that the STA-PPO algorithm outperforms benchmarks, showing the lowest system delay and the highest link throughput.

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Recent Advances in Fibrous Materials for Hydroelectricity Generation

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Nano-Micro Letters 2025年第2期17卷 109-133页

作者： Can Ge Duo Xu Xiao Feng Xing Yang Zheheng song Yuhang song Jingyu Chen Yingcun Liu Chong Gao Yong Du Zhe Sun Weilin Xu jian Fang College of Textile and Clothing Engineering Soochow UniversitySuzhou 215123People’s Republic of China National Engineering Laboratory for Modern Silk Soochow UniversitySuzhou 215123People’s Republic of China State Key Laboratory of New Textile Materials and Advanced Processing Technologies Wuhan Textile UniversityWuhan 430200People’s Republic of China Institute of Functional Nano&Soft Materials(FUNSOM) Soochow UniversitySuzhou 215123People’s Republic of China Department of Electrical and Computer Engineering University of MassachusettsAmherstMA 01003USA Department of Materials Imperial College LondonSouth Kensington CampusLondon SW72AZUK College of Textile Science and Engineering Zhejiang Sci-Tech UniversityHangzhou 310018People’s Republic of China School of Materials Science and Engineering Shanghai Institute of Technology100 Haiquan RoadShanghai 201418People’s Republic of China

Depleting fossil energy sources and conventional polluting power generation pose a threat to sustainable *** generation from ubiquitous and spontaneous phase transitions between liquid and gaseous water has been considered a promising strategy for mitigating the energy *** materials with unique flexibility,processability,multifunctionality,and practicability have been widely applied for fibrous materials-based hydroelectricity generation(FHG).In this review,the power generation mechanisms,design principles,and electricity enhancement factors of FHG are first ***,the fabrication strategies and characteristics of varied constructions including 1D fiber,1D yarn,2D fabric,2D membrane,3D fibrous framework,and 3D fibrous gel are ***,the advanced functions of FHG during water harvesting,proton dissociation,ion separation,and charge accumulation processes are analyzed in ***,the potential applications including power supply,energy storage,electrical sensor,and information expression are also ***,some existing challenges are considered and prospects for future development are sincerely proposed.

关键词： Hydroelectricity Fibrous material Streaming potential Ion diffusion

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Secure Channel Estimation Using Norm Estimation Model for 5G Next Generation Wireless Networks

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Computers, Materials & Continua 2025年第1期82卷 1151-1169页

作者： Khalil Ullah song jian Muhammad Naeem Ul Hassan Suliman Khan Mohammad Babar Arshad Ahmad Shafiq Ahmad Faculty of Information Engineering and Automation Kunming University of Science and TechnologyKunming650500China Department of Computer Science Abbottabad University of Science and TechnologyHavelianAbbottabad22500Pakistan Department of Computing and Electronics Engineering Middle East CollegeMuscat124Oman Department of CS&IT Pak-Austria Fachhochschule Institute of Applied Sciences and Technology MangHaripur22621Pakistan Industrial Engineering Department College of EngineeringKing Saud UniversityRiyadh11421Saudi Arabia

The emergence of next generation networks(NextG),including 5G and beyond,is reshaping the technological landscape of cellular and mobile *** networks are sufficiently scaled to interconnect billions of users and *** in academia and industry are focusing on technological advancements to achieve highspeed transmission,cell planning,and latency reduction to facilitate emerging applications such as virtual reality,the metaverse,smart cities,smart health,and autonomous *** continuously improves its network functionality to support these *** input multiple output(MIMO)technology offers spectral efficiency,dependability,and overall performance in *** article proposes a secure channel estimation technique in MIMO topology using a norm-estimation model to provide comprehensive insights into protecting NextG network components against adversarial *** technique aims to create long-lasting and secure NextG networks using this extended *** viability of MIMO applications and modern AI-driven methodologies to combat cybersecurity threats are explored in this ***,the proposed model demonstrates high performance in terms of reliability and accuracy,with a 20%reduction in the MalOut-RealOut-Diff metric compared to existing state-of-the-art techniques.

关键词： Next generation networks massive mimo communication network artificial intelligence 5G adversarial attacks channel estimation information security

Unlocking the future:Mitochondrial genes and neural networks in predicting ovarian cancer prognosis and immunotherapy response

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World Journal of Clinical Oncology 2025年第1期16卷 43-52页

作者： Zhi-jian Tang Yuan-Ming Pan Wei Li rui-Qiong Ma jian-Liu Wang Department of Obstetrics and Gynecology Peking University People’s HospitalBeijing 100044China Cancer Research Center Beijing Chest HospitalBeijing 101149China Department of Thoracic Surgery Sichuan Provincial People's HospitalChengdu 610072Sichuan ProvinceChina

BACKGROUND Mitochondrial genes are involved in tumor metabolism in ovarian cancer(OC)and affect immune cell infiltration and treatment *** To predict prognosis and immunotherapy response in patients diagnosed with OC using mitochondrial genes and neural *** Prognosis,immunotherapy efficacy,and next-generation sequencing data of patients with OC were downloaded from The Cancer Genome Atlas and Gene Expression *** genes were sourced from the MitoCarta3.0 *** discovery cohort for model construction was created from 70% of the patients,whereas the remaining 30% constituted the validation *** the expression of mitochondrial genes as the predictor variable and based on neural network algorithm,the overall survival time and immunotherapy efficacy(complete or partial response)of patients were *** In total,375 patients with OC were included to construct the prognostic model,and 26 patients were included to construct the immune efficacy *** average area under the receiver operating characteristic curve of the prognostic model was 0.7268[95% confidence interval(CI):0.7258-0.7278]in the discovery cohort and 0.6475(95%CI:0.6466-0.6484)in the validation *** average area under the receiver operating characteristic curve of the immunotherapy efficacy model was 0.9444(95%CI:0.8333-1.0000)in the discovery cohort and 0.9167(95%CI:0.6667-1.0000)in the validation *** The application of mitochondrial genes and neural networks has the potential to predict prognosis and immunotherapy response in patients with OC,providing valuable insights into personalized treatment strategies.

关键词： Ovarian cancer Mitochondria Prognosis Immunotherapy Neural network

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生成式人工智能对高校学术研究的影响与应对

黑龙江高教研究 2025年第1期43卷 9-14页

作者：姜岩宋瑞梅曲阜师范大学山东曲阜273165 山东工商学院山东烟台264005 滨州医学院山东烟台264003

以ChatGPT为代表的生成式人工智能正催生出一种全新的知识生产模式,并颠覆了人类通过学术研究进行知识生产这唯一方式的系统性和平衡性。生成式人工智能凭借其强大的文本生成功能、知识发现功能和审查评议功能不断挤占人类学术研究的主... 详细信息

以ChatGPT为代表的生成式人工智能正催生出一种全新的知识生产模式,并颠覆了人类通过学术研究进行知识生产这唯一方式的系统性和平衡性。生成式人工智能凭借其强大的文本生成功能、知识发现功能和审查评议功能不断挤占人类学术研究的主体角色空间,并以特有的知识生成创新特征对原有学科体系下的知识形态、规训制度和组织建制等三个方面产生显著影响,传统学术研究的原有规范已不再完全适用当前的知识创造环境。基于机器对人类学术研究影响的多角度深入分析,提出通过完善学术研究规范体系、提升学术失范审查技术、构建人机共研学术生态、加快人工智能素养培育等四个步骤,顺应智能技术的快速发展趋势,合理且有效发挥生成式人工智能对人类学术研究正面赋能作用的建议。

关键词： ChatCPT 学术研究知识生产学科模式

考虑场地效应的多点地震动作用下边坡永久位移分析

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岩土工程学报 2025年第1期47卷 65-75页

作者：宋健潘驭航陆朱汐姬建张飞高玉峰河海大学岩土力学与堤坝工程教育部重点实验室江苏南京210024 河海大学土木与交通学院江苏南京210024

地震动引起的边坡土层非线性动力响应可能导致坡体不同位置的地震动加速度时程不一致,从而对整个滑动体的极限平衡状态及之后的地震累积永久位移产生影响。为了研究场地效应对边坡地震永久位移的影响,基于极限平衡条分法,通过对不同土... 详细信息

地震动引起的边坡土层非线性动力响应可能导致坡体不同位置的地震动加速度时程不一致,从而对整个滑动体的极限平衡状态及之后的地震累积永久位移产生影响。为了研究场地效应对边坡地震永久位移的影响,基于极限平衡条分法,通过对不同土条赋予不同的水平和竖向地震动时程,推导出一种考虑场地效应的圆弧和任意形状滑面的多点地震作用下边坡永久位移分析方法。通过与有限差分软件FLAC的数值模拟结果进行对比,验证了该方法能够合理考虑地震动的场地效应。通过研究不同分布形式的多点地震动及竖向地震动对边坡永久位移的影响,结果表明:场地效应引起的水平地震动放大以及多点地震动不同分布模式会导致整个滑体平均地震惯性力作用位置发生改变,从而影响地震作用下滑动体沿滑面的永久变形量,竖向地震动对边坡地震位移影响较小。将方法应用于Lexington土石坝震后变形案例分析,计算得到的坝坡地震永久位移与实际震后观测值相吻合,证明了考虑场地效应的重要性及本文方法的合理性。

关键词：地震边坡稳定性场地效应永久位移极限平衡条分法多点地震动

Effect of Co-solvent on the Palladium Catalyzed Alkoxycarbonylation of Allyl Bromide in Supercritical CO_2

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Chinese Chemical Letters 2002年第10期13卷 933-934页

作者： rui Qi song jian Qing ZENG Bing ZHONG Guangzhou Institute of Chemistry Chinese Academy of SciencesGuangzhou 510650 State Key Laboratory of Coal Chemistry Institute of Coal ChemistryChinese Academy of SciencesTaiyuan 030001 School of Chemistry and ChemicalEngineering Zhongshan University Guangzhou 510275

The effect of cosolvent on the palladium catalyst which catalyze alkoxycarbonylation of allyl bromide in supercritical CO2 has been investigated. It was found that a small amount of cosolvent such as ethanol, CH2Cl2 and cyclohexane can affect both reaction yields and selectivities largely. Ethanol was the most favorable cosolvent for increasing the total yield of unsaturated esters and the selectivity of 3-butenoic acid ester. Using cosolvent ethanol and cocatalyst FeCl2 Simultaneously can lead to better reaction results.

关键词： Supercritical CO2 cosolvent alkoxycarbonylation palladium cocatalyst FeCl2.

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