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Physics-Based Model for Nonuniform Thermionic Electron Emission from Polycrystalline Cathodes

Physical Review Applied 2022年第5期18卷 054010-054010页

作者： Dongzheng Chen Ryan Jacobs John Petillo Vasilios Vlahos Kevin L. Jensen Dane Morgan John Booske Department of Materials Science and Engineering University of Wisconsin-Madison 1509 University Ave Madison Wisconsin 53706 USA Leidos 700 Technology Park Dr. Billerica Massachusetts 01821 USA Viasat Space Systems 2040 E. Technology Circle Tempe Arizona 85284 USA Code 6362 MSTD Naval Research Laboratory Washington DC 20375 USA Department of Electrical and Computer Engineering University of Wisconsin-Madison 1415 Engineering Dr. Madison Wisconsin 53706 USA

A physics-based model that predicts the emitted current from thermionic cathodes is developed, which accurately spans from the temperature-limited (TL) to full-space-charge-limited (FSCL) regions. Experimental observations of thermionic electron emission demonstrate a smooth transition between TL and FSCL regions of the emitted-current-density-versus-temperature (J-T) (Miram) curve and the emitted-current-density-versus-voltage (J-V) curve. Knowledge of the temperature and shape of the TL-FSCL transition is important in evaluating the thermionic electron-emission performance of cathodes, including predicting the lifetime. However, there are no first-principles physics-based models that predict the smooth TL-FSCL transition region for real thermionic cathodes without applying a priori assumptions or empirical phenomenological equations that are physically difficult to justify. Previous work detailing the nonuniform thermionic emission found that the effects of three-dimensional space charge, patch fields (electrostatic potential nonuniformity on the cathode surface based on local work-function values), and Schottky barrier lowering can lead to a smooth TL-FSCL transition region from a model thermionic cathode surface with a checkerboard spatial distribution of work-function values. In this work, we construct a physics-based nonuniform emission model for commercial dispenser cathodes. This emission model is obtained by incorporating the cathode surface grain orientation via electron-backscatter diffraction and the facet-orientation-specific work-function values from density-functional-theory calculations. The model enables the construction of two-dimensional emitted-current-density maps of the cathode surface and corresponding J-T and J-V curves. The predicted emission curves show excellent agreement with experiment, not only in the TL and FSCL regions but, crucially, also in the TL-FSCL transition region. This model provides a method to predict the thermionic emissio

关键词： Surface & interfacial phenomena Thermal energy harvesting devices Thermionic emission Complex oxides Free-electron lasers Electron diffraction First-principles calculations Materials modeling

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Enhancing operational performance and productivity benefits in breweries through smart manufacturing technologies

Journal of Advanced Manufacturing and Processing

引用

Journal of Advanced Manufacturing and Processing 2020年第4期2卷 1-12页

作者： Nimbalkar, Sachin Supekar, Sarang D. Meadows, Will Wenning, Thomas Guo, Wei Cresko, Joseph Energy and Transportation Science Division Oak Ridge National Laboratory Oak RidgeTN United States Energy Systems Division Argonne National Laboratory LemontIL United States Department of Electrical and Computer Engineering Mississippi State University Mississippi StateMS United States Advanced Manufacturing Office U.S. Department of Energy WashingtonDC United States

This article uses case studies to demonstrate the potential of smart manufacturing (SM) and Internet of Things (IoT) technologies to enhance operational performance and productivity in industry. The analysis highlights benefits such as cost reduction, production flexibility, shorter product time-to-market, energy/water efficiency and environmental impact reduction, and increased productivity. To illustrate the effectiveness of SM and IoT approaches, the authors sought out manufacturers currently implementing or seeking to implement SM and IoT technologies. The authors identified beer brewing (NAICS Code 312120) as a rapidly expanding industry whose members appear eager to implement SM technologies to optimize production lines by revealing bottlenecks and identifying performance-reducing nodes. This article presents two case studies based on SM and IoT technologies in breweries. It briefly describes a systematic framework introduced elsewhere by the authors and uses it to assess the energy productivity and competitiveness of SM applications in breweries. This article addresses questions concerning the information and communications technology infrastructure needed to build smart breweries and how corporations simplify the installation and deployment of SM and IoT components. This article was originally published in the Proceedings of the 2019 ACEEE Summer Study on Energy Efficiency in Industry. © 2020 American Institute of Chemical Engineers

关键词： Productivity

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NTIRE 2023 Challenge on Efficient Super-Resolution: Methods and Results

NTIRE 2023 Challenge on Efficient Super-Resolution: Methods ...

引用

2023 IEEE/CVF Conference on computer Vision and Pattern Recognition Workshops, CVPRW 2023

作者： Li, Yawei Zhang, Yulun Timofte, Radu Van Gool, Luc Yu, Lei Li, Youwei Li, Xinpeng Jiang, Ting Wu, Qi Han, Mingyan Lin, Wenjie Jiang, Chengzhi Luo, Jinting Fan, Haoqiang Liu, Shuaicheng Wang, Yucong Cai, Minjie Li, Mingxi Zhang, Yuhang Fan, Xian-Jun Sheng, Yankai Mao, Yanyu Zhang, Nihao Wang, Qian Zheng, Mingjun Sun, Long Pan, Jinshan Dong, Jiangxin Tang, Jinhui Yang, Zhongbao Wang, Yan Pan, Erlin Cai, Qixuan Dai, Xinan Zhussip, Magauiya Kalyazin, Nikolay Vyal, Dmitry Zou, Xueyi Yan, Youliang Chung, Heaseo Zhang, Jin Yu, Gaocheng Zhang, Feng Wang, Hongbin Liao, Bohao Du, Zhibo Wu, Yu-Liang Shi, Gege Peng, Long Wang, Yang Cao, Yang Zha, Zhengjun Huang, Zhi-Kai Chen, Yi-Chung Chiang, Yuan-Chun Yang, Hao-Hsiang Chen, Wei-Ting Chang, Hua-En Chen, I-Hsiang Hsieh, Chia-Hsuan Kuo, Sy-Yen Liu, Xin Pan, Jiahao Yu, Hongyuan Yu, Weichen Ge, Lin Dong, Jiahua Zou, Yajun Wu, Zhuoyuan Han, Binnan Zhang, Xiaolin Zhang, Heng Yin, Xuanwu Zuo, Kunlong Deng, Weijian Yuan, Hongjie Lu, Zengtong Ouyang, Mingyu Ma, Wenzhuo Liu, Nian Zheng, Hanyou Zhang, Yuantong Zhang, Junxi Chen, Zhenzhong Gendy, Garas Sabor, Nabil Hou, Jingchao He, Guanghui Zhu, Yurui Wang, Xi Fu, Xueyang Zha, Zheng-Jun Yin, Daheng Liu, Mengyang Chen, Baijun Li, Ao Luo, Lei Jin, Kangjun Zhu, Ce Zhang, Xiaoming Xie, Chengxing Li, Linze Meng, Haiteng Zhang, Tianlin Li, Tianrui Zhao, Xiaole Zhang, Zhao Li, Baiang Zheng, Huan Zhao, Suiyi Gao, Yangcheng Ren, Jiahuan Hu, Kang Shi, Jingpeng Wu, Zhijian Huang, Dingjiang Zhu, Jinchen Li, Hui Xv, Qianru Liu, Tianle Weng, Shizhuang Wu, Gang Jiang, Junpeng Liu, Xianming Jiang, Junjun Zhang, Mingjian Hu, Jing Wu, Chengxu Fan, Qinrui Feng, Chengming Luo, Ziwei Hu, Shu Lyu, Siwei Wu, Xi Wang, Xin Computer Vision Lab ETH Zurich Switzerland Computer Vision Lab University of Würzburg Germany Megvii Technology China MicroBT China College of Computer Science and Electronic Engineering Hunan University China Attrsense Xian University of Posts and Telecommunications Xi'an China National Engineering Laboratory for Cyber Event Warning and Control Technologies China Nanjing University of Science and Technology China Nankai University China University of Electronic Science and Technology of China China Tianjin University China Noah's Ark Lab Huawei Technologies McMaster University Canada Espresomedia Korea Republic of AntGroup China University of Science and Technology of China China Department of Electrical Engineering National Taiwan University Taiwan Graduate Institute of Communication Engineering National Taiwan University Taiwan Graduate Institute of Electronics Engineering National Taiwan University Taiwan ServiceNow United States China Mobile Research Institute China Chongqing University of Technology China Multimedia Department Xiaomi Inc. China Institute of Automation Chinese Academy of Sciences China Shenyang Institute of Automation Chinese Academy of Sciences China School of Information and Communication Engineering Communication University of China China Smart Classroom Division Ruijie Networks Co. Ltd. China School of Remote Sensing and Information Engineering Wuhan University China Micro-Nano Electronics Department Shanghai Jiao Tong University Shanghai200240 China Electrical Engineering Department Faculty of Engineering Assiut University Assiut71516 Egypt Southeast University China University of Electronic Science and Technology of China Chengdu China Chongqing University of Posts and Telecommunications Chongqing China Information Technology Co. Ltd Hangzhou China Southwest Jiaotong University China National Space Science Center Chinese Academy of Science China Hefei University of Technology Hefei China Anhui University China Fried Ric

ISBN: (纸本)9798350302493

This paper reviews the NTIRE 2023 challenge on efficient single-image super-resolution with a focus on the proposed solutions and results. The aim of this challenge is to devise a network that reduces one or several aspects such as runtime, parameters, FLOPs, activations, memory footprint, and depth of RFDN while at least maintaining the PSNR of 29.00dB on DIV2K validation datasets. The challenge had 272 registered participants, and 35 teams made valid submissions. They gauge the state-of-the-art for efficient single-image super-resolution. © 2023 IEEE.

关键词： Optical resolving power

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Minimum Energy Problem in the Sense of Caputo for Fractional Neutral Evolution systems in Banach Spaces

arXiv

引用

arXiv 2022年

作者： Ech-Chaffani, Zoubida Aberqi, Ahmed Karite, Touria Torres, Delfim F.M. LAMA Laboratory Faculty of Sciences Dhar El Mahraz Sidi Mohamed Ben Abdellah University Fez–Atlas BP 1796 Morocco LAMA Laboratory Department of Electrical Engineering & Computer Science National School of Applied Sciences Sidi Mohamed Ben Abdellah University Avenue My Abdallah Km 5 Route d’Imouzzer Fez BP 72 Morocco Laboratory of Engineering Systems and Applications Department of Electrical Engineering & Computer Science National School of Applied Sciences Sidi Mohamed Ben Abdellah University Avenue My Abdallah Km 5 Route d’Imouzzer Fes BP 72 Morocco Department of Mathematics University of Aveiro Aveiro3810-193 Portugal

We investigate a class of fractional neutral evolution equations on Banach spaces involving Caputo derivatives. Main results establish conditions for the controllability of the fractional-order system and conditions for existence of a solution to an optimal control problem of minimum energy. The results are proved with the help of fixed-point and semigroup *** Codes 26A33, 34K40, 49J30, 93B05 Copyright © 2022, The Authors. All rights reserved.

关键词： Banach spaces

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Generative AI for Space-Air-Ground Integrated Networks

arXiv

引用

arXiv 2023年

作者： Zhang, Ruichen Du, Hongyang Niyato, Dusit Kang, Jiawen Xiong, Zehui Jamalipour, Abbas Zhang, Ping Kim, Dong In The College of Computing and Data Science Nanyang Technological University Singapore The Department of Electrical and Electronic Engineering University of Hong Kong Pok Fu Lam Hong Kong The School of Automation Guangdong University of Technology China The Pillar of Information Systems Technology and Design Singapore University of Technology and Design Singapore The University of Sydney SydneyNSW2006 Australia The State Key Laboratory of Networking and Switching Technology Beijing University of Posts and Telecommunications Beijing100876 China The Department of Electrical and Computer Engineering Sungkyunkwan University Suwon16419 Korea Republic of

Recently, generative AI technologies have emerged as a significant advancement in artificial intelligence field, renowned for their language and image generation capabilities. Meantime, space-air-ground integrated network (SAGIN) is an integral part of future B5G/6G for achieving ubiquitous connectivity. Inspired by this, this article explores an integration of generative AI in SAGIN, focusing on potential applications and case study. We first provide a comprehensive review of SAGIN and generative AI models, highlighting their capabilities and opportunities of their integration. Benefiting from generative AI’s ability to generate useful data and facilitate advanced decision-making processes, it can be applied to various scenarios of SAGIN. Accordingly, we present a brief survey on their integration, including channel modeling and channel state information (CSI) estimation, joint air-space-ground resource allocation, intelligent network deployment, semantic communications, image extraction and processing, security and privacy enhancement. Next, we propose a framework that utilizes a generative diffusion model (GDM) to construct channel information map to enhance quality of service for SAGIN. Simulation results demonstrate the effectiveness of the proposed framework. Finally, we discuss potential research directions for generative AI-enabled SAGIN. © 2023, CC BY.

关键词： Generative adversarial networks

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Meta-Learning Based Early Fault Detection for Rolling Bearings via Few-Shot Anomaly Detection

arXiv

引用

arXiv 2022年

作者： Song, Wenbin Wu, Di Shen, Weiming Boulet, Benoit School of Mechanical Science and Engineering Huazhong University of Science and Technology Wuhan430074 China Department of Electrical and Computer Engineering McGill University MontrealQCH3A 2A7 Canada Department of Industrial and Manufacturing Systems Engineering State Key Laboratory of Digital Manufacturing Equipment and Technology School of Mechanical Science and Engineering Huazhong University of Science and Technology Wuhan430074 China

Early fault detection (EFD) of rolling bearings can recognize slight deviation of the health states and contribute to the stability of mechanical systems. In practice, very limited target bearing data are available to conduct EFD, which makes it hard to adapt to the EFD task of new bearings. To address this problem, many transfer learning based EFD methods utilize historical data to learn transferable domain knowledge and conduct early fault detection on new target bearings. However, most existing methods only consider the distribution drift across different working conditions but ignore the difference between bearings under the same working condition, which is called Unit-to-Unit Variability (UtUV). The setting of EFD with limited target data considering UtUV can be formulated as a Few-shot Anomaly Detection task. Therefore, this paper proposes a novel EFD method based on meta-learning considering UtUV. The proposed method can learn a generic metric based on Relation Network (RN) to measure the similarity between normal data and the new arrival target bearing data. Besides, the proposed method utilizes a health state embedding strategy to decrease false alarms. The performance of proposed method is tested on two bearing datasets. The results show that the proposed method can detect incipient faults earlier than the baselines with lower false alarms. Copyright © 2022, The Authors. All rights reserved.

关键词： Fault detection

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Global Stability and Optimal Control of Epidemics in Heterogeneously Structured Populations Exhibiting Adaptive Behaviour

SSRN

引用

SSRN 2023年

作者： Liu, Lixiang Chen, Shanshan Small, Michael Moore, Jack Murdoch Shang, Keke Department of Computer Science School of Electronic and Electrical Engineering Shanghai University of Engineering Science Shanghai201620 China Complex Systems Group Department of Mathematics and Statistics The University of Western Australia Perth6009 Australia Mineral Resources Commonwealth Scientific and Industrial Research Organisation Kensington6151 Australia MOE Key Laboratory of Advanced Micro-Structured Materials School of Physics Science and Engineering Tongji University Shanghai200092 China Computational Communication Collaboratory Nanjing University Nanjing210093 China

During the outbreak of infectious diseases, individual always make some adaptive response to avoid infected the diseases. In this paper, we introduce SIRS model on scale-free networks that take into account behavioral memory and time delay to depict individuals’ adaptive feedback, which is better characterize the actual spread of epidemics. We address uniform persistence and find that the model has the sharp threshold property, that is, for the basic reproduction number less than one, the disease-free equilibrium is globally asymptotically stable, while for the basic reproduction number is above one, the endemic equilibrium is globally stable. We further analyze the effects of two control strategies (the vaccination of susceptible people and treatment of infected people) on epidemic dynamics by optimal control strategy. The existence and uniqueness of the optimal control strategy are obtained. Finally, we perform some stochastic network simulations that yield quantitative agreement with the deterministic mean-field approach. The final results show that the effect of time delay does not change the basic reproduction number, but it plays an important role in the process of disease transmission. The behavioral memory is able to affect the basic reproduction number, and it has important and positive implications for disease transmission and control. The work of this paper can provide a theoretical basis and reference for the prediction and prevention of infectious diseases. © 2023, The Authors. All rights reserved.

关键词： Diseases

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NTIRE 2023 Quality Assessment of Video Enhancement Challenge

NTIRE 2023 Quality Assessment of Video Enhancement Challenge

引用

2023 IEEE/CVF Conference on computer Vision and Pattern Recognition Workshops, CVPRW 2023

作者： Liu, Xiaohong Min, Xiongkuo Sun, Wei Zhang, Yulun Zhang, Kai Timofte, Radu Zhai, Guangtao Gao, Yixuan Cao, Yuqin Kou, Tengchuan Dong, Yunlong Jia, Ziheng Li, Yilin Wu, Wei Hu, Shuming Deng, Sibin Xiao, Pengxiang Chen, Ying Li, Kai Zhao, Kai Yuan, Kun Sun, Ming Cong, Heng Wang, Hao Fu, Lingzhi Zhang, Yusheng Zhang, Rongyu Shi, Hang Xu, Qihang Xiao, Longan Ma, Zhiliang Agarla, Mirko Celona, Luigi Rota, Claudio Schettini, Raimondo Huang, Zhiwei Li, Ya'nan Wang, Xiaotao Lei, Lei Liu, Hongye Hong, Wei Chuang, Ironhead Lin, Allen Guan, Drake Chen, Iris Lou, Kae Huang, Willy Tasi, Yachun Kao, Yvonne Fan, Haotian Kong, Fangyuan Zhou, Shiqi Liu, Hao Lai, Yu Chen, Shanshan Wang, Wenqi Wu, Haoning Chen, Chaofeng Zhu, Chunzheng Guo, Zekun Zhao, Shiling Yin, Haibing Wang, Hongkui Meftah, Hanene Brachemi Fezza, Sid Ahmed Hamidouche, Wassim Déforges, Olivier Shi, Tengfei Mansouri, Azadeh Motamednia, Hossein Bakhtiari, Amir Hossein Aznaveh, Ahmad Mahmoudi Shanghai Jiao Tong University China Eth Zürich Switzerland University of Würzburg Germany Department of Tao Technology Alibaba Group China Kuaishou Technology China Interactive Entertainment Group of Netease Inc Guangzhou China Transsion China Hefei University of Technology China Department of Informatics Systems and Communication University of Milano - Bicocca Italy Xiaomi Inc. China China Ji Liang University China FreeTech Advanced Research Center KKCompany Taiwan ByteDance China Mgtv China Fuzhou University China Shopee Information Technology Co. Ltd. S-Lab Nanyang Technological University Singapore Hunan University China Hangzhou Dianzi University China Insa Rennes Cnrs Ietr - Umr 6164 Rennes France National Higher School of Telecommunications and Ict Oran Algeria Buaa Department of Electrical and Computer Engineering Faculty of Engineering Kharazmi University Tehran Iran High Performance Computing Laboratory School of Computer Science Institute for Research in Fundamental Sciences Tehran Iran Cyberspace Research Institute Shahid Beheshti University Tehran Iran

ISBN: (纸本)9798350302493

This paper reports on the NTIRE 2023 Quality Assessment of Video Enhancement Challenge, which will be held in conjunction with the New Trends in Image Restoration and Enhancement Workshop (NTIRE) at CVPR 2023. This challenge is to address a major challenge in the field of video processing, namely, video quality assessment (VQA) for enhanced videos. The challenge uses the VQA Dataset for Perceptual Video Enhancement (VDPVE), which has a total of 1211 enhanced videos, including 600 videos with color, brightness, and contrast enhancements, 310 videos with deblurring, and 301 deshaked videos. The challenge has a total of 167 registered participants. 61 participating teams submitted their prediction results during the development phase, with a total of 3168 submissions. A total of 176 submissions were submitted by 37 participating teams during the final testing phase. Finally, 19 participating teams submitted their models and fact sheets, and detailed the methods they used. Some methods have achieved better results than baseline methods, and the winning methods have demonstrated superior prediction performance. © 2023 IEEE.

关键词： Image enhancement

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Reconstructing Noisy Gene Regulation Dynamics Using Extrinsic-Noise-Driven Neural Stochastic Differential Equations

arXiv

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arXiv 2025年

作者： Zhang, Jiancheng Li, Xiangting Guo, Xiaolu You, Zhaoyi Böttcher, Lucas Mogilner, Alex Hoffmann, Alexander Chou, Tom Xia, Mingtao Department of Electrical and Computer Engineering University of California RiversideCA United States Department of Computational Medicine University of California Los AngelesCA United States Institute for Quantitative and Computational Biosciences University of California Los Angeles Los AngelesCA United States Ray and Stephanie Lane Computational Biology Department School of Computer Science Carnegie Mellon University PittsburghPA United States Department of Computational Science and Philosophy Frankfurt School of Finance and Management Frankfurt am Main Germany Laboratory for Systems Medicine Department of Medicine University of Florida FL32610 United States Courant Institute of Mathematical Sciences New York University NY10012 United States Department of Mathematics University of California Los AngelesCA90095 United States Department of Mathematics University of Houston HoustonTX77004 United States

Proper regulation of cell signaling and gene expression is crucial for maintaining cellular function, development, and adaptation to environmental changes. Reaction dynamics in cell populations is often noisy because of (i) inherent stochasticity of intracellular biochemical reactions ("intrinsic noise") and (ii) heterogeneity of cellular states across different cells that are influenced by external factors ("extrinsic noise"). In this work, we introduce an extrinsic-noise-driven neural stochastic differential equation (END-nSDE) framework that utilizes the Wasserstein distance to accurately reconstruct SDEs from trajectory data from a heterogeneous population of cells (extrinsic noise). We demonstrate the effectiveness of our approach using both simulated and experimental data from three different systems in cell biology: (i) circadian rhythms, (ii) RPA-DNA binding dynamics, and (iii) NFκB signaling process. Our END-nSDE reconstruction method can model how cellular heterogeneity (extrinsic noise) modulates reaction dynamics in the presence of intrinsic noise. It also outperforms existing time-series analysis methods such as recurrent neural networks (RNNs) and long short-term memory networks (LSTMs). By inferring cellular heterogeneities from data, our END-nSDE reconstruction method can reproduce noisy dynamics observed in experiments. In summary, the reconstruction method we propose offers a useful surrogate modeling approach for complex biophysical processes, where high-fidelity mechanistic models may be impractical. © 2025, CC BY.

关键词： Stochastic systems

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A data-driven probabilistic-based flexibility region estimation method for aggregated distributed energy resources

arXiv

引用

arXiv 2021年

作者： Zhang, Mingzhi Zhu, Xiangqi Lu, Ning The Department of Electrical and Computer Engineering North Carolina State University RaleighNC27606 United States The Power Systems Engineering Center National Renewable Energy Laboratory Colorado Golden80401 United States

This paper presents a data-driven, distributionally robust chance-constrained optimization method for estimating the real and reactive power controllability of aggregated distributed energy resources (DER). At the DER-level, a two-dimensional flexibility region can be formed based on the real and reactive power regulating limits of each DER considering forecast uncertainty. At the feeder-level, an aggregated flexibility region is computed via a multi-directional search method. In each search direction, extend the real and reactive power of each controllable DER towards its operational limits until: i) all DERs' maximum operational limits are reached or, ii) one or more of the distribution network operational limits are violated. The method enables three key features for operating aggregated DER resources: controllability estimation, visualization, and risk quantification. Simulation results demonstrated the effectiveness of the algorithm and quantified the impact of different parameter settings on the flexibility region boundary changes. The proposed algorithm is robust and computationally efficient and can meet real-time computing needs. Copyright © 2021, The Authors. All rights reserved.

关键词： Energy resources

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