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Significant effects of transport on nanoparticles during new particle formation events in the atmosphere of Beijing

Particuology 2023年第9期80卷 1-10页

作者： Dongjie Shang Min Hu Lizi Tang Xin Fang Ying Liu Yusheng Wu Zhuofei Du Xuhui Cai Zhijun Wu Shengrong Lou Mattias Hallquist Song Guo Yuanhang Zhang State Key Joint Laboratory of Environmental Simulation and Pollution Control College of Environmental Sciences and EngineeringInternational JointLaboratory for Regional Pollution ControlMinistry of Education(IJRC)Peking UniversityBeijing100871China Collaborative Innovation Center of Atmospheric Environment and Equipment Technology Nanjing University of Information Science&TechnologyNanjing210044China Department of Chemistry and Molecular Biology University of GothenburgGothenburg41296Sweden Shanghai Academy of Environmental Sciences Shanghai200233China

The mechanisms of new particle formation(NPF)events that occurred under high aerosol loadings(“polluted”NPF)in the atmosphere have been unclear,which has inhibited the precision of particlepollution *** deepen the understanding of how the“polluted”NPF events occur,a one-monthcomprehensive measurement was conducted in the atmosphere of Beijing during the summer ***“clean”NPF events(frequency=22%)(condensation sink,CS<0.015 s^(-1))were found to becaused by local nucleation and ***“polluted”NPF events(frequency=28%)(CS>0.015 s^(-1))were influenced by both local nucleation-growth and regional transport,and the contributions from thetwo factors to 6e25 nm particle number concentration were 60%and 40%,*** studyemphasized the importance of the transport for nanoparticles in relatively polluted atmospheres,and forthat the regional joint particle pollution control would be an essential policy.

关键词： New particle formation Transport Nanoparticles Sulfuric acid

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Load balancing strategy for wireless multi-hotspot networks based on improved NSGA-II algorithm

Load balancing strategy for wireless multi-hotspot networks ...

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2022 International Conference on Networking and Network Applications, NaNA 2022

作者： Yu, Han Zhan, Jie Libin, Jiao Han, Jun-Mei School of Physics and Electronic Science Hunan University of Science and Technology Xiangtan412001 China Science and Technology on Communication Networks Laboratory Shijiazhuang050081 China National Key Laboratory for Complex Systems Simulation Department of Systems General Design Institute of Systems Engineering Beijing100101 China

ISBN: (数字)9781665461313

ISBN: (纸本)9781665461313

IEEE 802.11 Wireless Local Area Network (WLAN) is a popular way for mobile devices to access the Internet. Operators and service providers often increase the density of wireless access points in order to provide users with better connections and user experience. As a result, WLAN users find themselves covered by multiple access points. In traditional wireless multi-hotspot networks most user terminals choose the access point with the strongest signal without considering the existing load on that access point, leading to severe congestion and load imbalance problems. This paper proposes an improved NSGA-II-based load balancing strategy for wireless multi-hotspot networks, which determines which hotspot should be associated with each user terminal by taking into account the current access point load, the received signal strength and the throughput size of the user terminal. The simulation results show that compared with the traditional strongest signal First (SSF) strategy, the proposed load balancing strategy can improve the network throughput by more than 30%. © 2022 IEEE.

关键词： IEEE Standards

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MPS-AMS: Masked Patches Selection and Adaptive Masking Strategy Based Self-Supervised Medical Image Segmentation 48

MPS-AMS: Masked Patches Selection and Adaptive Masking Strat...

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48th IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP 2023

作者： Wang, Xiangtao Wang, Ruizhi Tian, Biao Zhang, Jiaojiao Zhang, Shuo Chen, Junyang Lukasiewicz, Thomas Xu, Zhenghua Hebei University of Technology State Key Laboratory of Reliability and Intelligence of Electrical Equipment School of Health Sciences and Biomedical Engineering Tianjin China Shenzhen China Institute of Logic and Computation Tu Wien Vienna Austria University of Oxford Department of Computer Science Oxford United Kingdom

ISBN: (纸本)9781728163277

Existing self-supervised learning methods based on contrastive learning and masked image modeling have demonstrated impressive performances. However, current masked image modeling methods are mainly utilized in natural images, and their applications in medical images are relatively lacking. Besides, their fixed high masking strategy limits the upper bound of conditional mutual information, and the gradient noise is considerable, making less the learned representation information. Motivated by these limitations, in this paper, we propose masked patches selection and adaptive masking strategy based self-supervised medical image segmentation method, named MPS-AMS. We leverage the masked patches selection strategy to choose masked patches with lesions to obtain more lesion representation information, and the adaptive masking strategy is utilized to help learn more mutual information and improve performance further. Extensive experiments on three public medical image segmentation datasets (BUSI, Hecktor, and Brats2018) show that our proposed method greatly outperforms the state-of-the-art self-supervised baselines. © 2023 IEEE.

关键词： Conditional Entropy Medical Image Segmentation Mutual Information Self-supervised Learning

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Surface-enhanced Raman scattering for mixing state characterization of individual fine particles during a haze episode in Beijing,China

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Journal of Environmental sciences 2021年第6期33卷 216-224页

作者： Hui Chen Fengkui Duan Jingjing Du Ranhao Yin Lidan Zhu Jinlu Dong Kebin He Zhenli Sun Suhua Wang MOE Key Laboratory of Resources and Environmental System Optimization College of Environmental Science and EngineeringNorth China Electric Power UniversityBeijing 102206China State Key Joint Laboratory of Environment Simulation and Pollution Control School of EnvironmentTsinghua UniversityBeijing 100084China State Key Laboratory of Environmental Chemistry and Ecotoxicology Research Center for Eco-Environmental SciencesChinese Academy of SciencesBeijing 100085China Guangdong Provincial Key Laboratory of Petrochemcial Pollution Processes and Control School of Environmental Science and EngineeringGuangdong University of Petrochemical TechnologyMaoming 525000China

The nondestructive characterization of the mixing state of individual fine particles using the traditional single particle analysis technique remains a *** this study,fine particles were collected during haze events under different pollution levels from September 5 to 112017 in Beijing,China.A nondestructive surface-enhanced Raman scattering(SERS)technique was employed to investigate the morphology,chemical composition,and mixing state of the multiple components in the individual fine *** image and SERS spectral analysis results show that soot existing in the form of opaque material was predominant during clear periods(PM_(2.5)≤75μg/m^(3)).During polluted periods(PM_(2.5)>75μg/m^(3)),opaque particles mixed with transparent particles(nitrates and sulfates)were generally *** classical least squares analysis further identified the relative abundances of the three major components of the single particles:soot(69.18%),nitrates(28.71%),and sulfates(2.11%).A negative correlation was observed between the abundance of soot and the mass concentration of PM_(2.5).Furthermore,mapping analysis revealed that on hazy days,PM_(2.5)existed as a core-shell structure with soot surrounded by nitrates and *** mixing state analysis method for individual PM_(2.5)particles provides information regarding chemical composition and haze formation mechanisms,and has the potential to facilitate the formulation of haze prevention and control policies.

关键词： PM_(2.5) Surface-enhanced Raman scattering Individual fine particle Nitrate Sulfate Soot

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MvCo-DoT: Multi-View Contrastive Domain Transfer Network for Medical Report Generation 48

MvCo-DoT: Multi-View Contrastive Domain Transfer Network for...

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48th IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP 2023

作者： Wang, Ruizhi Wang, Xiangtao Xu, Zhenghua Xu, Wenting Chen, Junyang Lukasiewicz, Thomas Hebei University of Technology State Key Laboratory of Reliability and Intelligence of Electrical Equipment School of Health Sciences and Biomedical Engineering Tianjin China Shenzhen China Tu Wien Institute of Logic and Computation Vienna Austria University of Oxford Department of Computer Science Oxford United Kingdom

ISBN: (纸本)9781728163277

In clinical scenarios, multiple medical images with different views are usually generated at the same time, and they have high semantic consistency. However, the existing medical report generation methods cannot exploit the rich multi-view mutual information of medical images. Therefore, in this work, we propose the first multi-view medical report generation model, called MvCo-DoT. Specifically, MvCo-DoT first propose a multi-view contrastive learning (MvCo) strategy to help the deep reinforcement learning based model utilize the consistency of multi-view inputs for better model learning. Then, to close the performance gaps of using multi-view and single-view inputs, a domain transfer network is further proposed to ensure MvCo-DoT achieve almost the same performance as multi-view inputs using only single-view inputs. Extensive experiments on the IU X-Ray public dataset show that MvCo-DoT outperforms the SOTA medical report generation baselines in all metrics. © 2023 IEEE.

关键词： Chest X-Ray Domain transfer Medical report generation Multi-view contrastive learning

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A BDDC method for three-dimensional advection-diffusion problems with an adaptive coarse space

arXiv

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arXiv 2025年

作者： Peng, Jie Shu, Shi Wang, Junxian Zhong, Liuqiang College of Mathematics and Statistics Hengyang Normal University Hengyang421010 China School of Mathematical Sciences South China Normal University Guangzhou510631 China School of Mathematics and Computational Science Xiangtan University Xiangtan411105 China Hunan Key Laboratory for Computation and Simulation in Science and Engineering Xiangtan University Xiangtan411105 China

The solution of nonsymmetric positive definite (NSPD) systems for advection-diffusion problems is an important research topic in science and engineering. The adaptive BDDC method is a significant class of non-overlapping domain decomposition methods, which is often used for solving symmetric positive definite problems. In this paper, we apply the adaptive BDDC method to solve the NSPD systems of te advection-diffusion problems. Moreover, by designing a class of edge generalized eigenvalue problems based on prior selected primal constraints, the number of primal unknowns is further reduced. Numerical experiments have verified the effectiveness of the proposed methods. Copyright © 2025, The Authors. All rights reserved.

关键词： Domain decomposition methods

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Independently keypoint Learning for Small Object Semantic Correspondence

SSRN

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SSRN 2024年

作者： Jin, Hailong Li, Huiying Jilin University College of Computer Science and Technology Jilin Province Changchun China Key Laboratory of Symbol Computation and Knowledge Engineering Jilin University Changchun130012 China

Semantic correspondence remains a challenging task for establishing correspondences between a pair of images with the same category or similar scenes due to the large intra-class appearance. In this paper, we introduce a novel problem called 'Small Object Semantic Correspondence (SOSC).' This problem is challenging due to the close proximity of keypoints associated with small objects, which results in the fusion of these respective features. It is difficult to identify the corresponding key points of the fused features, and it is also difficult to be recognized. To address this challenge, we propose the keypoint Bounding box-centered Cropping (KBC) method, which aims to increase the spatial separation between keypoints of small objects, thereby facilitating independent learning of these keypoints. The KBC method is seamlessly integrated into our proposed inference pipeline and can be easily incorporated into other methodologies, resulting in significant performance enhancements. Additionally, we introduce a novel framework, named KBCNet, which serves as our baseline model. KBCNet comprises a Cross-Scale Feature Alignment (CSFA) module and an efficient 4D convolutional decoder. The CSFA module is designed to align multi-scale features, enriching keypoint representations by integrating fine-grained features and deep semantic features. Meanwhile, the 4D convolutional decoder, based on efficient 4D convolution, ensures efficiency and rapid convergence. To empirically validate the effectiveness of our proposed methodology, extensive experiments are conducted on three widely used benchmarks: PF-PASCAL, PF-WILLOW, and SPair-71k. Our KBC method demonstrates a substantial performance improvement of 7.5\% on the SPair-71K dataset, providing compelling evidence of its efficacy. © 2024, The Authors. All rights reserved.

关键词： Convolution

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Engineered poly(A)-surrogates for translational regulation and therapeutic biocomputation in mammalian cells

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细胞研究（英文版） 2024年第1期34卷 31-46页

作者： Jiawei Shao Shichao Li Xinyuan Qiu Jian Jiang Lihang Zhang Pengli Wang Yaqing Si Yuhang Wu Minghui He Qiqi Xiong Liuqi Zhao Yilin Li Yuxuan Fan Mirta Viviani Yu Fu Chaohua Wu Ting Gao Lingyun Zhu Martin Fussenegger Hui Wang Mingqi Xie International Institutes of Medicine The Fourth Affiliated HospitalZhejiang University School of MedicineYiwuZhejiangChina Key Laboratory of Growth Regulation and Translational Research of Zhejiang Province School of Life SciencesWestlake UniversityHangzhouZhejiangChina Westlake Laboratory of Life Sciences and Biomedicine HangzhouZhejiangChina Institute of Basic Medical Sciences Westlake Institute for Advanced StudyHangzhouZhejiangChina College of Life Sciences Zhejiang UniversityHangzhouZhejiangChina Department of Biology and Chemistry College of ScienceNational University of Defense TechnologyChangshaHunanChina Key Laboratory of Growth Regulation and Translational Research of Zhejiang Province School of Life SciencesWestlake UniversityHangzhouZhejiangChina Westlake Laboratory of Life Sciences and Biomedicine HangzhouZhejiangChina Institute of Basic Medical Sciences Westlake Institute for Advanced StudyHangzhouZhejiangChina School of Life Sciences Fudan UniversityShanghaiChina Key Laboratory of Growth Regulation and Translational Research of Zhejiang Province School of Life SciencesWestlake UniversityHangzhouZhejiangChina Westlake Laboratory of Life Sciences and Biomedicine HangzhouZhejiangChina Institute of Basic Medical Sciences Westlake Institute for Advanced StudyHangzhouZhejiangChina Research Center of Biological Computation Zhejiang LaboratoryHangzhouZhejiangChina Key Laboratory of Growth Regulation and Translational Research of Zhejiang Province School of Life SciencesWestlake UniversityHangzhouZhejiangChina Westlake Laboratory of Life Sciences and Biomedicine HangzhouZhejiangChina Institute of Basic Medical Sciences Westlake Institute for Advanced StudyHangzhouZhejiangChina Key Laboratory of Growth Regulation and Translational Research of Zhejiang Province School of Life SciencesWestlake UniversityHangzhouZhejiangChina Westlake Laboratory of Life Sciences and Biomedicine HangzhouZhejiangChina Institute of Basic Medical Sciences Westlake Institute

Here,we present a gene regulation strategy enabling programmable control over eukaryotic translational *** excising the natural poly-adenylation(poly-A)signal of target genes and replacing it with a synthetic control region harboring RNA-binding protein(RBP)-specific aptamers,cap-dependent translation is rendered exclusively dependent on synthetic translation initiation factors(STIFs)containing different RBPs engineered to conditionally associate with different elF4F-binding proteins(eIFBPs).This modular design framework facilitates the engineering of various gene switches and intracellular sensors responding to many user-defined trigger signals of interest,demonstrating tightly controlled,rapid and reversible regulation of transgene expression in mammalian cells as well as compatibility with various clinically applicable delivery routes of in vivo gene *** efficacy was demonstrated in two animal *** exemplify disease treatments that require on-demand drug secretion,we show that a custom-designed gene switch triggered by the FDA-approved drug grazoprevir can effectively control insulin expression and restore glucose homeostasis in diabetic *** diseases that require instantaneous sense-and-response treatment programs,we create highly specific sensors for various subcellularly(mis)localized protein markers(such as cancer-related fusion proteins)and show that translation-based protein sensors can be used either alone or in combination with other cell-state classification strategies to create therapeutic biocomputers driving self-sufficient elimination of tumor cells in *** design strategy demonstrates unprecedented flexibility for translational regulation and could form the basis for a novel class of programmable gene therapies in vivo.

关键词： Riboswitches Targeted therapies

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Shortcut Learning in In-Context Learning: A Survey

arXiv

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arXiv 2024年

作者： Song, Rui Li, Yingji Shi, Lida Giunchiglia, Fausto Xu, Hao College of Computer Science and Technology Jilin University Changchun China Key Laboratory of Symbol Computation and Knowledge Engineering of Ministry of Education Jilin University China Department of Information Engineering and Computer Science University of Trento Italy

Shortcut learning refers to the phenomenon where models employ simple, non-robust decision rules in practical tasks, which hinders their generalization and robustness. With the rapid development of Large Language Models (LLMs) in recent years, an increasing number of studies have shown the impact of shortcut learning on LLMs. This paper provides a novel perspective to review relevant research on shortcut learning in In-Context Learning (ICL). It conducts a detailed exploration of the types of shortcuts in ICL tasks, their causes, available benchmarks, and strategies for mitigating shortcuts. Based on the corresponding observations, we summarize the unresolved issues in existing research and attempts to outline the future research landscape of shortcut learning. © 2024, CC BY.

关键词： Contrastive Learning

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Interpreting Multi-objective Evolutionary Algorithms via Sokoban Level Generation

Interpreting Multi-objective Evolutionary Algorithms via Sok...

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IEEE Symposium on computational Intelligence and Games, CIG

作者： Qingquan Zhang Yuchen Li Yuhang Lin Handing Wang Jialin Liu Department of Computer Science and Engineering Guangdong Key Laboratory of Brain-inspired Intelligent Computation Southern University of Science and Technology Shenzhen China School of Artificial Intelligence Xidian University Xi’an China

ISBN: (数字)9798350350678

ISBN: (纸本)9798350350685

This paper presents an interactive platform to interpret multi-objective evolutionary algorithms. Sokoban level generation is selected as a showcase for its widespread use in procedural content generation. By balancing the emptiness and spatial diversity of Sokoban levels, we illustrate the improved two-archive algorithm, Two_Arch2, a well-known multi-objective evolutionary algorithm. Our web-based platform integrates Two_Arch2 into an interface that visually and interactively demonstrates the evolutionary process in real-time. Designed to bridge theoretical optimisation strategies with practical game generation applications, the interface is also accessible to both researchers and beginners to multi-objective evolutionary algorithms or procedural content generation on a website. Through dynamic visualisations and interactive gameplay demonstrations, this web-based platform also has potential as an educational tool.

关键词： Bridges Visualization Procedural generation Spatial diversity Evolutionary computation Real-time systems Optimization

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