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Progress in quantitative research on the relationship between atmospheric oxidation and air quality

Journal of Environmental Sciences 2023年第1期123卷 350-366页

作者： Yuesi Wang Xin Jin Zirui Liu Gehui Wang Guiqian Tang Keding Lu Bo Hu Shanshan Wang Guohui Li Xinqin An Chao Wang Qihou Hu Lingyan He Fenfen Zhang Yuanhang Zhang State Key Laboratory of Atmospheric Boundary Layer Physics and Atmospheric Chemistry(LAPC) Institute of Atmospheric PhysicsChinese Academy of SciencesBeijing 100029China College of Earth and Planetary Sciences University of Chinese Academy of SciencesBeijing 100049China 3 State Key Joint Laboratory or Environmental Simul ation and Pollution Control College of Environmental Sciences and EngineeringPeking UniversityBeijing 100871China State Key Joint Laboratory of Environmental Simulation and Pollution Control School of EnvironmentTsinghua UniversityBeijing 100084China Key Lab of Geophysical Information System of the Ministry of Education School of Geographic SciencesEast China Normal UniversityShanghai 200241China Shanghai Key Laboratory of Atmospheric Particle Pollution and Prevention(LAP3) Department of Environmental Science and EngineeringFudan UniversityShanghai 201203China Key Lab of Aerosol Chemistry and Physics State Key Laboratory of Loess and Quaternary GeologyInstitute of Earth EnvironmentChinese Academy of SciencesXi’an 710061China Institute of Atmospheric Composition and Environmental Meteorology Chinese Academy of Meteorological SciencesBeijing 100081China Key Lab of Environmental Optics and Technology Anhui Institute of Optics and Fine MechanicsHefei Institutes of Physical ScienceChinese Academy of SciencesHefei 230031China

Atmospheric oxidizing capacity(AOC)is an essential driving force of troposphere chemistry and self-cleaning,but the definition of AOC and its quantitative representation remain *** by national demand for air pollution control in recent years,Chinese scholars have carried out studies on theories of atmospheric chemistry and have made considerable progress in AOC *** paper will give a brief review of these ***,AOC indexes were established that represent apparent atmospheric oxidizing ability(AOIe)and potential atmospheric oxidizing ability(AOIp)based on aspects of macrothermodynamics and microdynamics,respectively.A closed study refined the quantitative contributions of heterogeneous chemistry to AOC in Beijing,and these AOC methods were further applied in Beijing-Tianjin-Hebei and key areas across the *** addition,the detection of ground or vertical profiles for atmospheric OH·,HO_(2)·,NO_(3)·radicals and reservoir molecules can now be obtained with domestic instruments in diverse ***,laboratory smoke chamber simulations revealed heterogeneous processes involving reactions of O_(3)and NO_(2),which are typical oxidants in the surface/interface atmosphere,and the evolutionary and budgetary implications of atmospheric oxidants reacting under multispecies,multiphase and multi-interface conditions were ***,based on the GRAPES-CUACE adjoint model improved by Chinese scholars,simulations of key substances affecting atmospheric oxidation and secondary organic and inorganic aerosol formation have been *** numerical simulations of AOIe and AOIp were performed,and regional coordination of AOC was *** optimized plan for controlling O_(3)and PM2.5was analyzed by scenario simulation.

关键词： Atmospheric oxidizing capacity(AOC) Quantitative index Free radicals Observation and modeling Air quality

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The Power of Graph Signal Processing for Chip Placement Acceleration 24

The Power of Graph Signal Processing for Chip Placement Acce...

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43rd International Conference on Computer-Aided Design, ICCAD 2024

作者： Liu, Yiting Zhou, Hai Wang, Jia Yang, Fan Zeng, Xuan Shang, Li School of Computer Science Fudan University Shanghai China Department of ECE Northwestern University Evanston United States Department of ECE IIIinois Institute of Technology Chicago United States State Key Lab of ASIC & System Microelectronics Department Fudan University Shanghai China

ISBN: (纸本)9798400710773

Placement is a critical task with high computation complexity in VLSI physical design. Modern analytical placers formulate the placement objective as a nonlinear optimization task, which suffers a long iteration time. To accelerate and enhance the placement process, recent studies have turned to deep learning-based approaches, particularly leveraging graph convolution networks (GCNs). However, learning-based placers require time- and data-consuming model training due to the complexity of circuit placement that involves large-scale cells and design-specific graph statistics. This paper proposes GiFt, a parameter-free technique for accelerating placement, rooted in graph signal processing. GiFt excels at capturing multi-resolution smooth signals of circuit graphs to generate optimized placement solutions without the need for time-consuming model training, and meanwhile significantly reduces the number of iterations required by analytical placers. Experimental results show that GiFt significantly improving placement efficiency, while achieving competitive or superior performance compared to state-of-the-art placers. In particular, compared to DREAMPlace, the recently proposed GPU-accelerated analytical placer, GF-Placer improves total runtime over 45%. © 2024 Copyright is held by the owner/author(s).

关键词： Nonlinear programming

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Advancements in Intelligent Photonics: The Role of Silicon Photonics and Phase Change Materials in High-Efficiency Computing 15

Advancements in Intelligent Photonics: The Role of Silicon P...

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15th International Conference on Information Optics and Photonics, CIOP 2024

作者： Yun, Yiting Xu, Kai Wang, Weiquan Wei, Maoliang Li, Junying Chen, Zequn Li, Lan Lin, Hongtao The State Key Lab of Brain-Machine Intelligence Key Laboratory of Micro-Nano Electronics and Smart System of Zhejiang Province College of Information Science and Electronic Engineering Zhejiang University Zhejiang Hangzhou310027 China Hangzhou Institute for Advanced Study University of Chinese Academy of Sciences Zhejiang Hangzhou310024 China Key Laboratory of 3D Micro/Nano Fabrication and Characterization of Zhejiang Province School of Engineering Westlake University Zhejiang Hangzhou310030 China

ISBN: (数字)9781510686175

ISBN: (纸本)9781510686168

Intelligent photonics, driven by silicon photonics, is revolutionizing high-speed data processing, low-power computing, and precision sensing. Leveraging these advances, photonic chips are enabling the development of optical neural networks and nonlinear activation mapping, which are crucial for addressing the demands of large generative models. However, traditional on-chip control methods struggle with high power consumption and volatility. To overcome these challenges, phase-change materials(PCMs) offer high optical contrast and non-volatility, enhancing integration density and reducing power usage. This article discusses the performance and reversible control of PCMs and their integration with silicon photonics. By incorporating PCMs into in-memory optical computing chips, we achieved 4-bit storage and over 88% accuracy on the MNIST dataset, marking significant progress in next-generation high-performance computing. © 2024 SPIE.

关键词： Silicon photonics

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Animate3D: animating any 3D model with multi-view video diffusion 24

Animate3D: animating any 3D model with multi-view video diff...

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Proceedings of the 38th International Conference on Neural Information Processing systems

作者： Yanqin Jiang Chaohui Yu Chenjie Cao Fan Wang Weiming Hu Jin Gao State Key Laboratory of Multimodal Artificial Intelligence Systems (MAIS) CASIA and School of Artificial Intelligence University of Chinese Academy of Sciences DAMO Academy Alibaba Group and Hupan Lab State Key Laboratory of Multimodal Artificial Intelligence Systems (MAIS) CASIA and School of Artificial Intelligence University of Chinese Academy of Sciences and School of Information Science and Technology ShanghaiTech University

ISBN: (纸本)9798331314385

Recent advances in 4D generation mainly focus on generating 4D content by distilling pre-trained text or single-view image-conditioned models. It is inconvenient for them to take advantage of various off-the-shelf 3D assets with multi-view attributes, and their results suffer from spatiotemporal inconsistency owing to the inherent ambiguity in the supervision signals. In this work, we present Animate3D, a novel framework for animating any static 3D model. The core idea is two-fold: 1) We propose a novel multi-view video diffusion model (MV-VDM) conditioned on multi-view renderings of the static 3D object, which is trained on our presented large-scale multi-view video dataset (MV-Video). 2) Based on MV-VDM, we introduce a framework combining reconstruction and 4D Score Distillation Sampling (4D-SDS) to leverage the multi-view video diffusion priors for animating 3D objects. Specifically, for MV-VDM, we design a new spatiotemporal attention module to enhance spatial and temporal consistency by integrating 3D and video diffusion models. Additionally, we leverage the static 3D model's multi-view renderings as conditions to preserve its identity. For animating 3D models, an effective two-stage pipeline is proposed: we first reconstruct motions directly from generated multi-view videos, followed by the introduced 4D-SDS to refine both appearance and motion. Benefiting from accurate motion learning, we could achieve straightforward mesh animation. Qualitative and quantitative experiments demonstrate that Animate3D significantly outperforms previous approaches. Data, code, and models are open-released.

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Mantle sources of Cenozoic volcanoes around the South China Sea revealed by geochemical and isotopic data using the principal component analysis

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Journal of Oceanology and Limnology 2023年第2期41卷 562-574页

作者： Shuangshuang CHEN Zewei WANG Rui GAO Yongzhang ZHOU School of Earth Sciences and Engineering Sun Yat-sen UniversityGuangzhou 510275China Southern Marine Science and Engineering Guangdong Laboratory(Zhuhai) Zhuhai 519080China Guangdong Provincial Key Lab of Geological Processes and Mineral Resources Guangzhou 510275China State Key Laboratory of Marine Environmental Science Xiamen UniversityXiamen 361102China Department of Earth and Space Sciences Southern University of Science and TechnologyShenzhen 518055China State Key Laboratory of Tibetan Plateau Earth System Environment and Resources(TPESER)Institute of Tibetan Plateau ResearchChinese Academy of SciencesBeijing 100101China

Principal component analysis(PCA)was employed to determine the implications of geochemical and isotopic data from Cenozoic volcanic activities in the Southeast Asian region,including China(South China Sea(SCS),Hainan Island,Fujian-Zhejiang coast,Taiwan Island),and parts of Vietnam and *** analyzed 15 trace element indicators and 5 isotopic indicators for 623 volcanic rock samples collected from the study *** principal components(PCs)were extracted by PCA based on the trace elements and Sr-Nd-Pb isotopic ratios,which probably indicate an enriched oceanic island basalt-type mantle plume and a depleted mid-ocean ridge basalt-type spreading *** results show that the influence of the Hainan mantle plume on younger volcanic activities(<13 Ma)is stronger than that on older ones(>13 Ma)at the same location in the Southeast Asian *** was employed to verify the mantle-plume-ridge interaction model of volcanic activities beneath the expansion center of SCS and refute the hypothesis that the tension of SCS is triggered by the Hainan *** study reveals the efficiency and applicability of PCA in discussing mantle sources of volcanic activities;thus,PCA is a suitable research method for analyzing geochemical data.

关键词： volcanic rocks geochemical indicators mantle source principal component analysis South China Sea

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Evaluation of Vibrotactile Glove and Handheld Controller in a Visuo-Haptic VR Space Station 2

Evaluation of Vibrotactile Glove and Handheld Controller in ...

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2nd International Conference on Automation, Robotics and Computer Engineering, ICARCE 2023

作者： Luo, Hu Zhou, Zejian Cao, Tianyang Na, Yufeng Nie, Jingwen Bai, Ruixue Wang, Dangxiao Beihang University State Key Lab of Virtual Reality Technology and System Beijing China School of General Engineering Beihang University Beijing China Application and Science Education Co. Ltd. Beijing SpaceD Aerospace Beijing China

ISBN: (纸本)9798350308341

Using virtual reality technology, we can simulate the microgravity environment of the outer space for popularizing the space science. Compared with handheld controllers, we expect using a glove with localized vibrotactile feedback might be more efficient and natural for simulating grasping gestures for space roaming and 3D-objects manipulating, however, quantitative and qualitative effects remain unknown. Thus, this study developed a science popularization orientated visuo-haptic VR space station for elucidating the difference between the two interaction devices. We used the number of times of trying to grasp, success grasping rate, and total time of completing the roaming task to objectively describe the interacting efficiency. The results of subjective rating showed better motion intuitiveness and vibrotactile fidelity using the vibrotactile glove, however, quantitative results showed using the glove was less efficient as compared to using the handheld controller. So, analyses of the underlying reasons were performed in aspects of both hardware and software. The findings may provide suggestions for designing VR interacting devices for space science popularization. © 2023 IEEE.

关键词： Virtual reality

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CAT:a coarse-to-fine attention tree for semantic change detection

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Visual intelligence 2023年第1期1卷 385-396页

作者： Xiu-Shen Wei Yu-Yan Xu Chen-Lin Zhang Gui-Song Xia Yu-Xin Peng School of Computer Science and Engineering Nanjing University of Science and TechnologyNanjingChina State Key Laboratory of Integrated Services Networks Xidian UniversityXi’anChina Key Lab of Intelligent Perception and Systems for High-Dimensional Information of Ministry of Education and Jiangsu Key Lab of Image and Video Understanding for Social SecurityNanjingChina Paradigm Inc BeijingChina School of Computer Science and Institute of Artificial Intelligence Wuhan UniversityWuhanChina Wangxuan Institute of Computer Technology Peking UniversityBeijingChina

Semantic change detection(SCD)and land cover mapping(LCM)are always treated as a dual task in thefield of remote ***,due to diverse real-world scenarios,many SCD categories are not easy to be clearly recognized,such as“water-vegetation”and“water-tree”,which can be regarded asfine-grained *** addition,even a single LCM category is usually difficult to *** instance,some“vegetation”categories with litter vegetation coverage are easily confused with the general“ground”***/LCM becomes challenging under both challenges of itsfine-grained nature and label *** this paper,we tackle the SCD and LCM tasks simultaneously by proposing a coarse-to-fine attention tree(CAT)***,it consists of an encoder,a decoder and a coarse-to-fine attention tree *** encoder-decoder structure extracts the high-level features from input multi-temporal imagesfirst and then reconstructs them to return SCD and LCM *** coarse-to-fine attention tree,on the one hand,utilizes the tree structure to better model a hierarchy of categories by predicting the coarse-grained labelsfirst and then predicting thefine-grained labels *** the other hand,it applies the attention mechanism to capture discriminative pixel ***,to address label ambiguity in SCD/LCM,we also equip a label distribution learning loss upon our *** on the large-scale SECOND dataset justify that the proposed CAT model outperforms state-of-the-art ***,various ablation studies have demonstrated the effectiveness of tailored designs in the CAT model for solving semantic change detection problems.

关键词： Semantic change detection Fine-grained recognition Coarse-to-fine Attention tree label ambiguity

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A Real-time Framework for UAV Indoor Self-Positioning and 3D Mapping Base on 2D Lidar, Stereo Camera and IMU

A Real-time Framework for UAV Indoor Self-Positioning and 3D...

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2023 IEEE International Conference on Real-Time Computing and Robotics, RCAR 2023

作者： Liang, Lebin Rao, Haotian Shen, Guohao Wang, Can Wu, Xinyu Chinese Academy of Sciences Guangdong Provincial Key Lab of Robotics and Intelligent System Shenzhen Institute of Advanced Technology Shenzhen518055 China University of Chinese Academy of Sciences Beijing100049 China South China Agricultural University College of Electronic Engineering College of Artificial Intelligence Guangzhou510642 China

ISBN: (纸本)9798350327182

This paper proposed a real-time Unmanned Aerial Vehicle (UAV) autonomous localization framework based on onboard sensors, including 2D Lidar, Stereo Camera and Inertial Measurement Unit (IMU), built on the open-source VINS-Fusion software to achieve real-time and drift-free UAV pose estimation. The proposed framework eliminates the motion distortion of Lidar during UAV motion by combining Visual-Inertial Odometry (VIO). It obtains global localization information of Lidar by PL-ICP algorithm based on a global point cloud map. Graph optimization method is used to fuse the local positional estimation and the global information from the Lidar, which eliminate the cumulative error caused by VIO. The feasibility of the method is verified by experiments and compared with the method of only running Visual-Inertial Navigation systems (VINS), the framework improves the accuracy of localization. In addition, we have implemented the construction of octree maps of 3D environments through the framework of this system. © 2023 IEEE.

关键词： Optical radar

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A canonicalization perspective on invariant and equivariant learning 24

A canonicalization perspective on invariant and equivariant ...

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Proceedings of the 38th International Conference on Neural Information Processing systems

作者： George Ma Yifei Wang Derek Lim Stefanie Jegelka Yisen Wang School of EECS Peking University MIT CSAIL TUM CIT/MCML/MDSI & MIT EECS/CSAIL State Key Lab of General Artificial Intelligence School of Intelligence Science and Technology Peking University and Institute for Artificial Intelligence Peking University

ISBN: (纸本)9798331314385

In many applications, we desire neural networks to exhibit invariance or equivariance to certain groups due to symmetries inherent in the data. Recently, frame-averaging methods emerged to be a unified framework for attaining symmetries efficiently by averaging over input-dependent subsets of the group, i.e., frames. What we currently lack is a principled understanding of the design of frames. In this work, we introduce a canonicalization perspective that provides an essential and complete view of the design of frames. Canonicalization is a classic approach for attaining invariance by mapping inputs to their canonical forms. We show that there exists an inherent connection between frames and canonical forms. Leveraging this connection, we can efficiently compare the complexity of frames as well as determine the optimality of certain frames. Guided by this principle, we design novel frames for eigenvectors that are strictly superior to existing methods—some are even optimal—both theoretically and empirically. The reduction to the canonicalization perspective further uncovers equivalences between previous methods. These observations suggest that canonicalization provides a fundamental understanding of existing frame-averaging methods and unifies existing equivariant and invariant learning methods. Code is available at https://***/PKU-ML/canonicalization.

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UTD-Yolov5: A Real-time Underwater Targets Detection Method based on Attention Improved YOLOv5

arXiv

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arXiv 2022年

作者： Wang, Jingyao Yu, Naigong The Beijing Key Lab of the Computational Intelligence and Intelligent System Beijing University of Technology Beijing China

As the treasure house of nature, the ocean contains abundant resources. But the coral reefs, which are crucial to the sustainable development of marine life, are facing a huge crisis because of the existence of COTS and other organisms. The protection of society through manual labor is limited and inefficient. The unpredictable nature of the marine environment also makes manual operations risky. The use of robots for underwater operations has become a trend. However, the underwater image acquisition has defects such as weak light, low resolution, and many interferences, while the existing target detection algorithms are not effective. Based on this, we propose an underwater target detection algorithm based on Attention Improved YOLOv5, called UTD-Yolov5. It can quickly and efficiently detect COTS, which in turn provides a prerequisite for complex underwater operations. We adjusted the original network architecture of YOLOv5 in multiple stages, including: replacing the original Backbone with a two-stage cascaded CSP (CSP2);introducing the visual channel attention mechanism module SE;designing random anchor box similarity calculation method etc. These operations enable UTD-Yolov5 to detect more flexibly and capture features more accurately. In order to make the network more efficient, we also propose optimization methods such as WBF and iterative refinement mechanism. This paper conducts a lot of experiments based on the CSIRO dataset [1]. The results show that the average accuracy of our UTD-Yolov5 reaches 78.54%, which is a great improvement compared to the baseline. Copyright © 2022, The Authors. All rights reserved.

关键词： Network architecture

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