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Evaporation dynamics and deposition patterns of ethanol-based Al2O3 nanofluid droplets: Effects of particle sizes and substrate temperatures

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Colloids and Surfaces A: Physicochemical and engineering Aspects 2025年 719卷

作者： Wei, Youqiang Tao, Yuequn Lin, Yukai Feng, Yanhui Chu, Fuqiang School of Energy and Environmental Engineering University of Science and Technology Beijing Beijing100083 China National Key Laboratory of Spacecraft Thermal Control Beijing Institute of Spacecraft System Engineering China Academy of Space Technology Beijing100094 China National Microgravity Laboratory Institute of Mechanics Chinese Academy of Sciences Beijing100190 China Department of Energy and Power Engineering Tsinghua University Beijing100084 China

The evaporation of nanofluid droplets holds significant potential for applications in thermal management. Nonetheless, the ways in which nanoparticles affect the evaporation dynamics and deposition properties of nanofluid droplets are still not well understood. Here, we investigate the effects of Al₂O₃ nanoparticle sizes and substrate temperatures on the wetting characteristics, evaporation rate, and particle deposition behavior of ethanol-Al₂O₃ nanofluid droplets. Additionally, the features and transitions of internal convective instabilities are observed and discussed. The results reveal that the addition of nanoparticles has a minor impact on the changes in wetting patterns during droplet evaporation, and all droplets evaporate in a mixed mode. Nanoparticle size plays a pivotal role in regulating deposition patterns and wetted area, which in turn indirectly affects the evaporation rate. Specifically, the heat flux at the solid-liquid interface and the evaporation rate are enhanced compared to the base fluid, with these differences becoming more pronounced at higher substrate temperatures and with larger nanoparticle sizes. The internal convection within the droplets is primarily driven by Marangoni flow, and the presence of nanoparticles has negligible influence on the flow behavior. Smaller nanoparticles tend to deposit near the center of the droplet, resulting in a reduced coffee-ring effect, whereas larger nanoparticles predominantly deposit at the contact line, forming a marked coffee ring. Therefore, by selecting nanoparticles of appropriate sizes, it is possible to enhance evaporation rates or mitigate the coffee-ring effect to meet the requirements of various industrial applications. © 2025 Elsevier B.V.

关键词： Nanoparticles

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Dissemination Characteristics and Exposure Risk Assessment of Antibiotic Resistance Genes via Aerosols from Wastewater Treatment Processes

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Water (Switzerland) 2025年第9期17卷 1305-1305页

作者： Ding, Diangang Sun, Jianbin Chi, Mingjia Liu, Lan Ren, Zening Liu, Jianwei Beijing Engineering Research Center of Sustainable Urban Sewage System Construction and Risk Control Beijing University of Civil Engineering and Architecture Beijing100044 China School of Environment and Energy Engineering Beijing University of Civil Engineering and Architecture Beijing100044 China State Key Laboratory of Soil and Sustainable Agriculture Institute of Soil Science Chinese Academy of Sciences Nanjing210008 China

Wastewater treatment plants (WWTPs) have been confirmed as reservoirs of antibiotic resistance genes (ARGs). This study systematically investigated the distribution patterns of ARGs across different treatment units in municipal WWTPs, along with the environmental drivers, dissemination characteristics, and exposure risks of aerosol-borne ARGs in aerated tank environments. The results revealed a high compositional similarity in aerosol-borne ARGs across the sampling sites, with multidrug ARGs predominating at an average relative abundance of 52%, followed sequentially by tetracycline (11%), MLS (10%), and glycopeptide resistance genes (7%). The diffusion of aerosol-borne ARGs is significantly influenced by environmental factors including temperature, relative humidity, wind speed, and total suspended particulate (TSP) concentration, with temperature being the most dominant factor affecting the dispersion of ARGs. The atmospheric dispersion model demonstrates that aerosol-borne ARGs decay with increasing downwind distance, showing potential for transport from aeration tanks to locations exceeding 1500 m along the prevailing wind direction. Both within wastewater treatment units and downwind areas, adult males had higher respiratory exposure doses but lower skin contact doses compared to females, with respiratory doses exceeding skin contact by 3–4 orders of magnitude. This study highlights the potential health risks posed by aerosol-borne ARG transmission from WWTP operations. © 2025 by the authors.

关键词： Risk assessment

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Trajectory control and Fair Communications for Multi-UAV Networks: A Federated Multi-Agent Deep Reinforcement Learning Approach

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IEEE Transactions on Wireless Communications 2025年

作者： Tarekegn, Getaneh Berie Tesfaw, Belayneh Abebe Juang, Rong-Terng Saha, Dola Tarekegn, Robel Berie Lin, Hsin-Piao Tai, Li-Chia Nycu Department of Electrical and Computer Engineering 1001 University Road Hsinchu300 Taiwan Nycu Institute of Electrical and Control Engineering 1001 University Road Hsinchu300 Taiwan National Taipei University of Technology Department of Electrical Engineering and Computer Science Taipei10608 Taiwan National Taipei University of Technology Institute of Aerospace and System Engineering Taipei10608 Taiwan University at Albany Suny Department of Electrical and Computer Engineering AlbanyNY12222 United States

Due to their highly flexible deployment and agility features, unmanned aerial vehicles (UAVs) serving as aerial base stations are increasingly being used in challenging environments, including emergency communication, traffic offloading, and failures of existing communications infrastructure. A reliable and effective communication service requires 3D deployment and autonomous UAV trajectory optimization in each time slot. While most prior approaches focus on trajectory design that maximizes communication coverage or network throughput without considering fairness as well as computation time. This paper presents a multi-UAV trajectory control and fair communication (TCFC) scheme that maximizes ground user data rate and communication coverage while ensuring service fairness in a UAV-aided wireless communications system. The proposed TCFC scheme employs a two-stage learning approach. Firstly, it develops a gated recurrent unit-based link quality estimation model to assess each user's link quality over time. Then, a federated multi-agent deep reinforcement learning (FedMADRL) algorithm is utilized to continuously adjust the trajectory of the UAVs, optimizing communication performance. We evaluated our proposed system using real channel measurement data, i.e., amplitude and phase signal information. The results show that the proposed TCFC scheme reduces computation time by 26.91% and provides comparable network performance with the baseline methods while improving DRL agents' privacy. © 2025 IEEE.

关键词： Deep reinforcement learning

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Efficient Trajectory Generation Based on Traversable Planes in 3D Complex Architectural Spaces

arXiv

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arXiv 2025年

作者： Zhang, Mengke Tian, Zhihao Xia, Yaoguang Xu, Chao Gao, Fei Cao, Yanjun The State Key Laboratory of Industrial Control Technology College of Control Science and Engineering Zhejiang University Hangzhou310027 China Huzhou Institute Zhejiang University Huzhou Key Laboratory of Autonomous System Huzhou313000 China China Tobacco Zhejiang Industrial Co. Ltd. Hangzhou310024 China

With the increasing integration of robots into human life, their role in architectural spaces where people spend most of their time has become more prominent. While motion capabilities and accurate localization for automated robots have rapidly developed, the challenge remains to generate efficient, smooth, comprehensive, and high-quality trajectories in these areas. In this paper, we propose a novel efficient planner for ground robots to autonomously navigate in large complex multi-layered architectural spaces. Considering that traversable regions typically include ground, slopes, and stairs, which are planar or nearly planar structures, we simplify the problem to navigation within and between complex intersecting planes. We first extract traversable planes from 3D point clouds through segmenting, merging, classifying, and connecting to build a plane-graph, which is lightweight but fully represents the traversable regions. We then build a trajectory optimization based on motion state trajectory and fully consider special constraints when crossing multi-layer planes to maximize the robot’s maneuverability. We conduct experiments in simulated environments and test on a CubeTrack robot in real-world scenarios, validating the method’s effectiveness and practicality. Copyright © 2025, The Authors. All rights reserved.

关键词： Flight paths

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Pathological axonal enlargement in connection with amyloidosis,lysosome destabilization,and bleeding is a major defect in Alzheimer’s disease

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Neural Regeneration Research 2026年第2期21卷 790-799页

作者： Hualin Fu Jilong Li Chunlei Zhang Guo Gao Qiqi Ge Xinping Guan Daxiang Cui Institute of Nano Biomedicine and Engineering School of Sensing Science and EngineeringSchool of Electronic Information and Electrical EngineeringShanghai Jiao Tong UniversityShanghaiChina Institute of Marine Equipment Shanghai Jiao Tong UniversityShanghaiChina National Center for Translational Medicine Shanghai Jiao Tong UniversityShanghaiChina Department of Automation Shanghai Jiao Tong UniversityShanghaiChina The Key Laboratory of System Control and Information Processing Ministry of EducationShanghaiChina

Alzheimer’s disease is a multi-amyloidosis disease characterized by amyloid-βdeposits in brain blood vessels,microaneurysms,and senile *** amyloid-βdeposition affects axon pathology has not been examined *** used immunohistochemistry and immunofluorescence staining to analyze the forebrain tissue slices of Alzheimer’s disease *** axonal amyloidosis with distinctive axonal enlargement was observed in patients with Alzheimer’s *** average,amyloid-β-positive axon diameters in Alzheimer’s disease brains were 1.72 times those of control brain ***,axonal amyloidosis was associated with microtubule-associated protein 2 reduction,tau phosphorylation,lysosome destabilization,and several blood-related markers,such as apolipoprotein E,alpha-hemoglobin,glycosylated hemoglobin type A1C,and *** destabilization in Alzheimer’s disease was also clearly identified in the neuronal soma,where it was associated with the co-expression of amyloid-β,Cathepsin D,alpha-hemoglobin,actin alpha 2,and collagen type *** suggests that exogenous hemorrhagic protein intake influences neural lysosome ***,the data showed that amyloid-β-containing lysosomes were 2.23 times larger than control ***,under rare conditions,axonal breakages were observed,which likely resulted in Wallerian *** summary,axonal enlargement associated with amyloidosis,micro-bleeding,and lysosome destabilization is a major defect in patients with Alzheimer’s *** finding suggests that,in addition to the well-documented neural soma and synaptic damage,axonal damage is a key component of neuronal defects in Alzheimer’s disease.

关键词： Alzheimer’s disease amyloid-β amyloidosis axonal enlargement hemoglobin hemorrhage lysosome destabilization neuropil thread tau Wallerian degeneration

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Secure-by-Construction Synthesis for control systems

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IEEE Transactions on Automatic control 2025年第6期70卷 4170-4177页

作者： Zhong, Bingzhuo Liu, Siyuan Caccamo, Marco Zamani, Majid Thrust of Artificial Intelligence Information Hub The Thrust of Intelligent Transportation System Hub China KTH Royal Institute of Technology Division of Decision and Control Systems Stockholm Sweden Technical University of Munich TUM School of Engineering and Design Germany University of Colorado Boulder Department of Computer Science United States Ludwig Maximilian University Department of Computer Science Munich Germany

In this note, we present the synthesis of secure-by-construction controllers that address safety and security properties simultaneously in cyber-physical systems. Our focus is on studying a specific security property called opacity, which characterizes the system's ability to maintain plausible deniability of its secret behavior in the presence of an intruder. These controllers are synthesized based on a concept of so-called (augmented) control barrier functions. We propose conditions that facilitate the construction of the desired (augmented) control barrier functions and their corresponding secure-by-construction controllers. To compute these functions, we propose an iterative scheme that leverages iterative sum-of-square programming techniques. This approach enables efficient computation of these functions, particularly for polynomial systems. Finally, we validate the effectiveness of our results through a case study of a vehicle. © 1963-2012 IEEE.

关键词： Iterative methods

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TRNet: Two-Tier Recursion Network for Co-Salient Object Detection

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IEEE Transactions on Circuits and systems for Video Technology 2025年

作者： Cong, Runmin Yang, Ning Liu, Hongyu Zhang, Dingwen Huang, Qingming Kwong, Sam Zhang, Wei Shandong University School of Control Science and Engineering Jinan250061 China Ministry of Education Key Laboratory of Machine Intelligence and System Control Jinan250061 China Beijing Jiaotong University Institute of Information Science Beijing100044 China Beijing Key Laboratory of Advanced Information Science and Network Technology Beijing100044 China Northwestern Polytechnical University Brain and Artificial Intelligence Laboratory School of Automation Xi'an710129 China University of Chinese Academy of Sciences School of Computer Science and Technology Beijing101408 China Lingnan University Hong Kong

Co-salient object detection (CoSOD) is to find the salient and recurring objects from a series of relevant images, where modeling inter-image relationships plays a crucial role. Different from the commonly used direct learning structure that inputs all the intra-image features into some well-designed modules to represent the inter-image relationship, we resort to adopting a recursive structure for inter-image modeling, and propose a two-tier recursion network (TRNet) to achieve CoSOD in this paper. The two-tier recursive structure of the proposed TRNet is embodied in two stages of inter-image extraction and distribution. On the one hand, considering the task adaptability and inter-image correlation, we design an inter-image exploration with recursive reinforcement module to learn the local and global inter-image correspondences, guaranteeing the validity and discriminativeness of the information in the step-by-step propagation. On the other hand, we design a dynamic recursion distribution module to fully exploit the role of inter-image correspondences in a recursive structure, adaptively assigning common attributes to each individual image through an improved semi-dynamic convolution. Experimental results on five prevailing CoSOD benchmarks demonstrate that our TRNet outperforms other competitors in terms of various evaluation metrics. The code and results of our method are available at https://***/rmcong/TRNetTCSVT2025. © 1991-2012 IEEE.

关键词： HTTP

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A Switched Neural Process for Long-Term Postprandial Glucose Trajectory Prediction Based on Insulin Sensitivity Estimation

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IEEE Transactions on Instrumentation and Measurement 2025年 74卷

作者： Chen, Jing Shi, Dawei Cai, Deheng Liu, Wei Ji, Linong Shi, Ling Beijing Institute of Technology MIIT Key Laboratory of Servo Motion System Drive and Control School of Automation Beijing100081 China Peking University People’s Hospital Department of Endocrine and Metabolism Beijing100044 China Hong Kong University of Science and Technology Department of Electronic and Computer Engineering Kowloon Hong Kong

Advanced sensing technology has enabled the real-time monitoring of blood glucose (BG), making it possible to explore the BG prediction problem based on continuous observations. In this work, we propose a novel switched neural process (SNP) approach for long-term postprandial BG prediction, which has the probabilistic inference ability conditioned on preprandial BG measurements. Distinct representative neural process (NP) models are constructed to capture the nonlinear BG dynamics based on a designed indicator. This indicator is developed to estimate insulin sensitivity (IS) at meal time by using physiological models, in which the effect of preprandial BG variation on IS estimation is evaluated. Besides, a robust model switching mechanism is designed to determine the appropriate NP model for prediction. The effectiveness of the proposed method is illustrated through the comparative results by using both the in silico data from the U.S. Food and Drug Administration (FDA)-accepted UVA/Padova type 1 diabetes mellitus (T1DM) simulator and the clinical data from 47 T1DM subjects. The obtained results indicate that the proposed method outperforms existing methods, especially for 3- and 4-h prediction, which shows promising potential in predicting postprandial BG levels. © 1963-2012 IEEE.

关键词： Glucose

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Data-Driven Learning and control with Event-Triggered Measurements

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IEEE Transactions on Automatic control 2025年

作者： Feng, Shilun Shi, Dawei Chen, Tongwen Shi, Ling Beijing Institute of Technology State Key Laboratory of Intelligent Control and Decision of Complex Systems MIIT Key Laboratory of Servo Motion System Drive and Control School of Automation Beijing100081 China University of Alberta Department of Electrical and Computer Engineering EdmontonABT6G 1H9 Canada Hong Kong University of Science and Technology Department of Electronic and Computer Engineering Clear Water Bay Kowloon Hong Kong

Event-triggered control has attracted considerable attention for its effectiveness in resource-restricted applications. To make event-triggered control as an end-to-end solution, a key issue is how to effectively learn unknown system dynamics from event-triggered measurements and consequently, develop a learning-based event-triggered controller. Existing works learn system dynamics based on periodic time-triggered measurements, and it is yet to know how to learn a controller with performance guarantee based on event-triggered measurements. To address this issue, we consider the problem of learning an event-triggered state feedback controller for an unknown linear system based on event-triggered state measurements in this work. In particular, we first analyze the event-triggered measurements within a set-membership framework. We prove that the estimation error belongs to a bounded ellipsoid determined by the historical measurements and the event-triggering condition. Subsequently, we demonstrate that all admissible systems compatible with the collected data samples can be explicitly represented in the form of quadratic matrix inequalities using the state estimates. With the acquired set of admissible systems, a co-design problem for the data-driven controller and event-triggering condition is solved using the linear matrix inequality technique, with guaranteed closed-loop stability and L2-gain performance. Finally, numerical examples and comparisons are provided to illustrate the effectiveness of the proposed event-triggered learning and control approach. © 1963-2012 IEEE.

关键词： Networked control systems

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Multiplexed model predictive attitude control for nadir-pointing satellite using only magnetorquers

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control engineering Practice 2025年 162卷

作者： Yang, Sen Ling, Keck Voon Wang, Zhenhua Li, Huiping School of Astronautic Harbin Institute of Technology Harbin150001 China School of Electrical and Electronic Engineering Nanyang Technological University Singapore639798 Singapore National Key Laboratory of Complex System Control and Intelligent Agent Cooperation Harbin150001 China School of Marine Science and Technology Northwestern Polytechnical University Xi'an710072 China

Due to the low failure risk of magnetorquers, the control strategy based on magnetic actuators can significantly enhance the reliability of the satellite attitude control system. In light of this advantage, this paper conducts research on model predictive control (MPC) algorithm for nadir-pointing satellites equipped only with magnetorquers. Firstly, to facilitate controller design, the linear time-varying (LTV) model for nadir-pointing satellites is derived by linearizing the nonlinear equations around the operating point. Then, leveraging this linearized representation, an LTV multiplexed MPC (MMPC) method with exponential weighting is proposed. The MMPC scheme allows for faster sampling rates and quicker responses to disturbances, thereby enhancing the overall performance of the satellite attitude control system while retaining the benefits of MPC. Finally, compared with a state-of-the-art SMPC method, the proposed method is particularly advantageous in situations where computational resources are limited, specifically for satellites that rely only on onboard computing capabilities. © 2025

关键词： Nonlinear equations

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