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Hot spot temperature optimization of micro-channel heat sinks enabled by designing vortex generators and realizing optimal flow pattern

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International Journal of Heat and Mass Transfer 2025年 247卷

作者： Yu, Lingfeng Wu, Xiaoling Song, Mengxuan Chen, Kai Key Laboratory of Enhanced Heat Transfer and Energy Conservation of the Ministry of Education School of Chemistry and Chemical Engineering South China University of Technology Guangdong Guangzhou510640 China Lab of Applied Biocatalysis School of Food Science and Engineering South China University of Technology Guangdong Guangzhou510640 China School of Energy and Materials Shanghai Key Laboratory of Engineering Materials Application and Evaluation Shanghai Polytechnic University Shanghai 201209 China Shanghai Thermophysical Properties Big Data Professional Technical Service Platform Shanghai Engineering Research Center of Advanced Thermal Functional Materials Shanghai 201209 China

Reduction of hot spot temperature is critical for electronic devices under high heat flux conditions. Micro-channel heat sinks (MCHSs) are commonly used in electronic cooling, with vortex generators introduced to enhance the heat transfer. However, existing convective heat transfer optimization equations are not consistent with the aim of hot spot temperature minimization, which are not efficient for design of vortex generators in MCHSs. To address this issue, the optimization equations with minimizing the hot spot temperature of MCHSs are developed, and a novel method is proposed to efficiently design vortex generators in MCHSs. The heat convection optimization equations aiming at hot spot temperature minimization of MCHSs under fixed power consumption are derived using variational method. The equations enable us to achieve the optimal flow field that guarantees a lower hot spot temperature than those obtained based on equations that aim at entropy generation minimization or entransy dissipation extremum in previous studies. The results reveal that the mechanism of hot spot temperature minimization in the rectangular channel is to induce four longitudinal vortices at the cross-section with specific rotations that drive more fluid to the heating surface. Furthermore, vortex generators composed of the inclined triangular-prism ribs and plates are inserted into the channel, which successfully constructs the optimal flow patterns matching the derived optimization equations. The generated similar longitudinal vortices are evidenced by numerical results. With mass flow rate at 0.1 g/s, the hot spot temperature of the MCHSs with the designed vortex generators is reduced by 32.7 K, and the maximum temperature rising decreases by 48 %, and the performance evaluation criterion increases by 60 % when compared to the channel without vortex generators. Moreover, the designed vortex generator increases the performance evaluation criterion by more than 55 % compared to the one in

关键词： Electronic cooling

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WiViPose: A Video-aided Wi-Fi Framework for Environment-Independent 3D Human Pose Estimation

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IEEE Transactions on Multimedia 2025年

作者： Zhang, Lei Ning, Haoran Tang, Jiaxin Chen, Zhenxiang Zhong, Yaping Han, Yahong Tianjin University College of Intelligence and Computing the Tianjin Key Laboratory of Advanced Network Technology and Application Tianjin300050 China Key Laboratory of Computing Power Network and Information Security Ministry of Education China University of Jinan Shandong Provincial Key Laboratory of Ubiquitous Intelligent Computing the School of Information Science and Engineering Jinan250022 China Wuhan Sports University Sports Big-data Research Center Wuhan430079 China Tianjin University College of Intelligence and Computing the Tianjin Key Laboratory of Machine Learning Tianjin300350 China

The inherent complexity of Wi-Fi signals makes video-aided Wi-Fi 3D pose estimation difficult. The challenges include the limited generalizability of the task across diverse environments, its significant signal heterogeneity, and its inadequate ability to analyze local and geometric information. To overcome these challenges, we introduce WiViPose, a video-aided Wi-Fi framework for 3D pose estimation, which attains enhanced cross-environment generalization through cross-layer optimization. Bilinear temporal-spectral fusion (BTSF) is initially used to fuse the time-domain and frequency-domain features derived from Wi-Fi. Video features are derived from a multiresolution convolutional pose machine and enhanced by local self-attention. Cross-modality data fusion is facilitated through an attention-based transformer, with the process further refined under a supervisory mechanism. WiViPose demonstrates effectiveness by achieving an average percentage of correct keypoints (PCK)@50 of 91.01% across three typical indoor environments. © 2025 IEEE.

关键词： Frequency domain analysis

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Modified g-C3N4 photocatalysts for clean energy and environmental applications: a review

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Sustainable Energy and Fuels 2025年

作者： Tofil, Hafiz Muhammad Ghazi, Rizwana Ghaib, Fadhil A. Dara, Rebwar Nasir Kebaili, Imen Boukhris, Imed Ding, He Rehman, Ziaur Department of Chemistry Quaid-i-Azam University Islamabad45320 Pakistan Department of Petroleum and Mining Engineering Faculty of Engineering Tishk International University Kurdistan Region Erbil44001 Iraq Department of Earth Sciences and Petroleum College of Science Salahaddin University-Erbil Erbil44002 Iraq Department of Petroleum Engineering College of Engineering Knowledge University Erbil Iraq Department of Physics Faculty of Science King Khalid University 9004 Abha Saudi Arabia Key Laboratory of Superlight Materials and Surface Technology Ministry of Education College of Materials Science and Chemical Engineering Harbin Engineering University Harbin150001 China

The exponential growth in human population presents significant challenges to the long-term sustainability of civilization through escalating global energy crises and environmental issues. Governments and researchers are actively investigating green and clean technologies as potential solutions to these problems. Moreover, water pollution has become a critical concern, with industrial effluents and anthropogenic activities contaminating potable water sources, resulting in severe health risks. Simultaneously, CO2 emissions from fossil fuel combustion contribute to global warming, necessitating immediate intervention. In this context, semiconductor-based photocatalysis has emerged as a cost-effective, renewable, clean, and secure technology distinguished by its demonstrable advantages. Graphitic carbon nitride (g-C3N4) is noteworthy among the photocatalysts for its affordability, high thermal and chemical stability, suitable bandgap, and appropriate band positions. Nevertheless, the photocatalytic performance of g-C3N4 is affected by its weak light response and high rate of photoinduced charge recombination. This article outlines the synthesis methods and different approaches for improving g-C3N4-based photocatalysis to broaden its use in renewable energy generation and environmental cleanup. © 2025 The Royal Society of Chemistry.

关键词： River pollution

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Rapid Detection 2-Butanone Gas Sensors based on Biphase In2O3 Nanocubes Modified with Ag NPs and SnO2 QDs at Low Working Temperature

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IEEE Transactions on Instrumentation and Measurement 2025年 74卷

作者： Guo, Yinghao Yuan, Zhenyu Guo, Zhongming Ran, Mengran Meng, Fanli Northeastern University College of Information Science and Engineering Shenyang110819 China Northeastern University College of Information Science and Engineering State Key Laboratory of Synthetical Automation for Process industries Shenyang110819 China Northeastern University Key Laboratory of Data Analytics and Optimization for Smart Industry Ministry of Education Shenyang110819 China Hebei Key Laboratory of MicroNano Precision Optical Sensing and Measurement Technology Qinhuangdao066004 China

Increasing attention has been paid to environmental protection and human health. 2-Butanone is widely applied in industrial and pharmaceutical production causing small-area high-concentration harmful gas and large-area air pollution. The importance of quick and accurate detection is self-evident. In this work, the butanone-sensitive biphase In2O3 nanocubes co-decorated with SnO2 QDs and Ag NPs were prepared through a two-step hydrothermal strategy. Meanwhile, a fantastic detection speed and ultra-high selectivity at lower operating temperatures were experimentally determined. The test results show that the 1 mol% SnO2 QDs and 3 mol% Ag NPs co-decorated In2O3-based sensor have an ultra-fast response speed (4.6 s) and a better response value (119) at the low working temperature (160ºC) to 50 ppm 2-butanone gas. Compared to the previous work, it has significantly improved the cross-selectivity with acetone. With rh-In2O3 being highly defective crystal surfaces and abundant oxygen vacancies, the biphase homojunction plays a key role in decreasing working temperature, for electron flow between two crystalline phase interfaces. The electronic sensitization effect of the Ag element and the quantum effect of SnO2 quantum dots accelerate the detection speed. Moreover, the heterojunction between rh-In2O3 and SnO2 and the Schottky junction between Ag NPs and c-In2O3 largely improve the response capability. The significance of this study is not only to provide a sensor that can accurately detect butanone gas in industrial production and air pollution but also to provide new design ideas for preparing rapid detection semiconductor gas sensors at low working temperatures. The sensor performance in this study indicates that this sensor design scheme can enhance the accuracy and detection speed of butanone sensors used in exhaust gas detection. © 1963-2012 IEEE.

关键词： Air quality

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Dream to Drive with Predictive Individual World Model

arXiv

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arXiv 2025年

作者： Gao, Yinfeng Zhang, Qichao Ding, Da-Wei Zhao, Dongbin School of Automation and Electrical Engineering University of Science and Technology Beijing Beijing100083 China Key Laboratory of Knowledge Automation for Industrial Processes Ministry of Education Beijing100083 China The State Key Laboratory of Multimodal Artificial Intelligence Systems Institute of Automation Chinese Academy of Sciences Beijing100190 China School of Artificial Intelligence University of Chinese Academy of Sciences Beijing100049 China

It is still a challenging topic to make reactive driving behaviors in complex urban environments as road users’ intentions are unknown. Model-based reinforcement learning (MBRL) offers great potential to learn a reactive policy by constructing a world model that can provide informative states and imagination training. However, a critical limitation in relevant research lies in the scene-level reconstruction representation learning, which may overlook key interactive vehicles and hardly model the interactive features among vehicles and their long-term intentions. Therefore, this paper presents a novel MBRL method with a predictive individual world model (PIWM) for autonomous driving. PIWM describes the driving environment from an individual-level perspective and captures vehicles’ interactive relations and their intentions via trajectory prediction task. Meanwhile, a behavior policy is learned jointly with PIWM. It is trained in PIWM’s imagination and effectively navigates in the urban driving scenes leveraging intention-aware latent states. The proposed method is trained and evaluated on simulation environments built upon real-world challenging interactive scenarios. Compared with popular model-free and state-of-the-art model-based reinforcement learning methods, experimental results show that the proposed method achieves the best performance in terms of safety and efficiency. Copyright © 2025, The Authors. All rights reserved.

关键词： Prediction models

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A 3D Memristive Cubic Map with Dual Discrete Memristors: Design, Implementation, and Application in Image Encryption

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IEEE Transactions on Circuits and Systems for Video Technology 2025年

作者： Gao, Suo Iu, Herbert Ho-Ching Erkan, Ugur Simsek, Cemaleddin Toktas, Abdurrahim Cao, Yinghong Wu, Rui Mou, Jun Li, Qi Wang, Chunpeng Dalian Polytechnic University School of Information Science and Engineering Dalian116034 China The University of Western Australia School of Electrical Electronic and Computer Engineering Perth6009 Australia Faculty of Engineering Electrical and Electronics Engineering Respectively Karamanoglu Mehmetbey University Karaman70200 Turkey Ankara University Engineering Faculty Department of Artificial Intelligence and Data Engineering Ankara06830 Turkey Harbin Institute of Technology School of Computer Science and Technology Harbin150001 China Key Laboratory of Computing Power Network and Information Security Ministry of Education Shandong Computer Science Center National Supercomputer Center in Jinan Shandong Provincial Key Laboratory of Computer Networks Shandong Fundamental Research Center for Computer Science Jinan250000 China

Discrete chaotic systems based on memristors exhibit excellent dynamical properties and are more straightforward to implement in hardware, making them highly suitable for generating cryptographic keystreams. However, most existing memristor-based chaotic systems rely on a single memristor. This paper introduces a novel discrete chaotic system employing dual memristors, named the 3D memristive cubic map with dual discrete memristors (3D-MCM). The 3D-MCM system demonstrates richer and more intricate dynamical behaviors compared to its single-memristor counterparts, as verified through bifurcation diagrams, Lyapunov exponent spectra, and complexity analyses. Notably, the system exhibits coexisting attractors, substantially enhancing its dynamical complexity. Hardware implementation of the 3D-MCM attractors confirms its feasibility for industrial applications. To illustrate the system's potential in encryption tasks, this study integrates the quaternary-based permutation and dynamic emanating diffusion (QPDED-IE) scheme for image encryption with the *** results demonstrate that the QPDED-IE scheme based on the 3D-MCM exhibits strong diffusion and confusion properties, effectively resisting cryptanalytic attacks. © 1991-2012 IEEE.

关键词： Bifurcation (mathematics)

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Beam Tracking for High-Speed UAV Via Generative Diffusion Model-Enabled Joint Optimization Approach

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IEEE Transactions on Vehicular Technology 2025年

作者： Zhang, Jing Zhang, Chaofeng Feng, Xin Yang, Hongwei Liang, Shuang Sun, Geng Wang, Jiacheng Niyato, Dusit Changchun University of Science and Technology College of Computer Science and Technology Changchun130022 China Jilin University College of Communication Engineering Changchun130012 China Northeast Normal University School of Information Science and Technology Changchun130117 China Jilin University Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education Changchun130012 China Jilin University College of Computer Science and Technology Changchun130012 China Nanyang Technological University College of Computing and Data Science 639798 Singapore Nanyang Technological University 639798 Singapore

Beam tracking is crucial for maintaining stable data transmission in unmanned aerial vehicle (UAV) communications. However, a communication link can be disrupted by frequent switching of narrow beams between a base station and a UAV at certain moments. In this study, we propose a position prediction-based beam tracking algorithm with adaptive beam reconstruction (PPBT-AR) for high-speed UAV. Specifically, long short-term memory (LSTM) recurrent neural networks are utilized to predict the nonlinear flight trajectory during high-speed flight. Moreover, we employ the generative diffusion model (GDM) to jointly optimize the beam width and signal strength, thereby reducing the number of beam switches. In addition, we design an adaptive beam reconstruction (ABR) mechanism to mitigate communication interruptions caused by prediction errors. Simulation results demonstrate that the proposed PPBT-AR reduces the number of beam switches by 66.6% and 76.9% in low-speed and high-speed scenarios compared to the traditional phased array beam tracking algorithm, respectively. © 1967-2012 IEEE.

关键词： Long short-term memory

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Patient-Level Anatomy Meets Scanning-Level Physics: Personalized Federated Low-Dose CT Denoising Empowered by Large Language Model

arXiv

引用

arXiv 2025年

作者： Yang, Ziyuan Chen, Yingyu Wang, Zhiwen Shan, Hongming Chen, Yang Zhang, Yi College of Computer Science Sichuan University China Key Laboratory of Data Protection and Intelligent Management Ministry of Education Sichuan University China School of Cyber Science and Engineering Sichuan University China School of Computer Science and Software Engineering Southwest Petroleum University China Institute of Science and Technology for Brain-inspired Intelligence Fudan University China School of Computer Science and Engineering Southeast University China

Reducing radiation doses benefits patients, however, the resultant low-dose computed tomography (LDCT) images often suffer from clinically unacceptable noise and artifacts. While deep learning (DL) shows promise in LDCT reconstruction, it requires large-scale data collection from multiple clients, raising privacy concerns. Federated learning (FL) has been introduced to address these privacy concerns;however, current methods are typically tailored to specific scanning protocols, which limits their generalizability and makes them less effective for unseen protocols. To address these issues, we propose SCAN-PhysFed, a novel SCanning- and ANatomy-level personalized Physics-Driven Federated learning paradigm for LDCT reconstruction. Since the noise distribution in LDCT data is closely tied to scanning protocols and anatomical structures being scanned, we design a dual-level physics-informed way to address these challenges. Specifically, we incorporate physical and anatomical prompts into our physics-informed hypernetworks to capture scanning- and anatomy-specific information, enabling dual-level physics-driven personalization of imaging features. These prompts are derived from the scanning protocol and the radiology report generated by a medical large language model (MLLM), respectively. Subsequently, client-specific decoders project these dual-level personalized imaging features back into the image domain. Besides, to tackle the challenge of unseen data, we introduce a novel protocol vector-quantization strategy Copyright © 2025, The Authors. All rights reserved.

关键词： Computerized tomography

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The Equivalent Representation of the Breadth-One D-Invariant Polynomial Subspace and Its Discretization

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Journal of Systems Science & Complexity 2016年第5期29卷 1436-1445页

作者： JIANG Xue ZHANG Shugong Institute of Mathematics Key Laboratory of Symbolic Computation and Knowledge Engineering (Ministry of Education) Jilin University

This paper demonstrates the equivalence of two classes of D-invariant polynomial subspaces, i.e., these two classes of subspaces are different representations of the breadth-one D-invariant subspace. Moreover, the authors solve the discrete approximation problem in ideal interpolation for the breadth-one D-invariant subspace. Namely, the authors find the points, such that the limiting space of the evaluation functionals at these points is the functional space induced by the given D-invariant subspace, as the evaluation points all coalesce at one point.

关键词： Breadth-one D-invariant polynomial subspace discrete approximation problem idealinterpolation.

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A Two-Dimensional Improvement for Farr-Gao Algorithm

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Journal of Systems Science & Complexity 2016年第5期29卷 1382-1399页

作者： DONG Tian School of Mathematics Key Laboratory of Symbolic Computation and Knowledge Engineering (Ministry of Education) Jilin University

Farr-Gao algorithm is a state-of-the-art algorithm for reduced Gr?bner bases of vanishing ideals of finite points, which has been implemented in Maple as a build-in command. This paper presents a two-dimensional improvement for it that employs a preprocessing strategy for computing reduced Gr?bner bases associated with tower subsets of given point sets. Experimental results show that the preprocessed Farr-Gao algorithm is more efficient than the classical one.

关键词： Grobner basis GrSbner escalier Newton interpolation basis tower set vanishing ideal.

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