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2024 International Conference on Photonics Solutions, ICPS 2024

作者： Awatsuji, Yasuhiro Kumon, Yuki Inoue, Tomoyoshi Rajput, Sudheesh K. Nishio, Kenzo Hou, Natsu Kumar, Manoj Matoba, Osamu Faculty of Electrical Engineering and Electronics Kyoto Institute of Technology Matsugasaki Sakyo-ku Kyoto606-8585 Japan Graduate School of Science and Technology Kyoto Institute of Technology Matsugasaki Sakyo-ku Kyoto606-8585 Japan Advanced Technology Center Kyoto Institute of Technology Matsugasaki Sakyo-ku Kyoto606-8585 Japan Central 2 1-1-1 Umezono Tsukuba305-8568 Japan Amity School of Physical Sciences Amity University Punjab Mohali140306 India Center of Optical Scattering Image Science Kobe University Rokkodai 1-1 Nada Kobe657-850 Japan Department of Systems Science Graduate School of System Informatics Kobe University Rokkodai 1-1 Nada-ku Kobe657-8501 Japan

ISBN: (数字)9781510688308

ISBN: (纸本)9781510688292

Parallel phase-shifting digital holography is a technique capable of single-shot recording of complex amplitude distribution of light wave from an object. This technique records a single hologram of the object with an image sensor and reconstructs the instantaneous 3D image of the object with a computer. We constructed a high-speed parallel phase-shifting digital holography system using a high-speed polarization camera that can record a video of holograms at a rate of up to 1, 550, 000 fps. We recorded a video of the holograms of the heated air using the constructed system at the rate of 7, 000 fps. The phase video of the object wave passing through the heated air was reconstructed from the movie of the hologram. The Abel inversion was applied to the phase video and then the 3D video of air temperature distribution was obtained. © 2025 SPIE.

关键词： Holograms

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Was Wuhan the early epicenter of the COVID-19 pandemic?——a critique

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National science Review 2023年第4期10卷 19-21页

作者： Yanan Cao Lingling Chen Hua Chen Yupeng Cun Xiaofeng Dai Hongli Du Feng Gao Fengbiao Guo Yalong Guo Pei Hao Shunmin He Shunping He XiongLei He Zheng Hu Boon-Peng Hoh Xin Jin Qian Jiang Qinghua Jiang Asifullah Khan Hong-Zhi Kong Jinchen Li Shuai Cheng Li Ying Li Qiang Lin Jianquan Liu Qi Liu Jian Lu Xuemei Lu Shujin Luo Qinghua Nie Zilong Qiu Tieliu Shi Xiaofeng Song Jianzhong Su Sheng-ce Tao Chaolong Wang Chuan-Chao Wang Guo-Dong Wang Jiguang Wang Qi Wu Shaoyuan Wu Shuhua Xu Yu Xue Wenjun Yang Zhaohui Yang Kai Ye Yuan-Nong Ye Li Yu Fangqing Zhao Yiqiang Zhao Weiwei Zhai Dandan Zhang Liye Zhang Houfeng Zheng Qi Zhou Tianqi Zhu Ya-ping Zhang Ruijin Hospital Shanghai Jiao Tong University College of Life Science and Technology Guangxi University Beijing Institute of Genomics Chinese Academy of Sciences Children's Hospital of Chongqing Medical University Wuxi School of Medicine Jiangnan University School of Biology and Biological Engineering South China University of Technology Department of Physics School of ScienceTianjin University School of Pharmaceutical Sciences Wuhan University Institute of Botany Chinese Academy of Sciences Institut Pasteur of Shanghai Chinese Academy of Sciences Institute of Biophysics Chinese Academy of Sciences Institute of Hydrobiology Chinese Academy of Sciences School of Life Sciences Sun Yat-sen University Institute of Synthetic Biology Shenzhen Institute of Advanced TechnologyChinese Academy of Sciences Faculty of Medicine and Health Sciences University College Sedaya International School of Medicine South China University of Technology Department of Medical Genetics Capital Institute of Pediatrics School of Life Science and Technology Harbin Institute of Technology Department of Biochemistry Abdul Wali Khan University Xiangya Hospital Central South University Department of Computer Science City University of Hong Kong College of Life Science and Technology Foshan University South China Sea Institute of Oceanology Chinese Academy of Sciences College of Ecology Lanzhou University School of Life Sciences and Technology Tongji University School of Life Sciences Peking University Kunming Institute of Zoology Chinese Academy of Sciences College of Animal Science South China Agricultural University Institute of Neuroscience Chinese Academy of Sciences School of Life Sciences East China Normal University Nanjing University of Aeronautics and Astronautics Wenzhou Institute University of Chinese Academy of Sciences Institute of Systems Biomedicine Shanghai Jiao Tong University Tongji Medical College Huazhong University of Science and Technology School of Life Sciences Xiamen University Division of Life Science and Department of

Recently, Worobey et al.(2022) published a report entitled ‘The Huanan Seafood Wholesale Market in Wuhan was the early epicenter of the COVID-19 pandemic' that succinctly summarizes their study [1]. A pre-print version of this study had earlier elicited a series of highprofile media coverages [2,3]. All these reports deliver a social-political message that the Huanan market is the epicenter of COVID-19.

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Exploring Nanoscale Perovskite Materials for Next‑Generation Photodetectors:A Comprehensive Review and Future Directions

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Nano-Micro Letters 2025年第2期17卷 46-108页

作者： Xin Li Sikandar Aftab Maria Mukhtar Fahmid Kabir Muhammad Farooq Khan Hosameldin Helmy Hegazy Erdi Akman State Key Laboratory of Pulsed Power Laser Technology National University of Defense TechnologyHefei 230037AnhuiPeople’s Republic of China Anhui Laboratory of Advanced Laser Technology Hefei 230037AnhuiPeople’s Republic of China Nanhu Laser Laboratory Changsha 410015HunanPeople’s Republic of China Department of Semiconductor Systems Engineering and Clean Energy Sejong UniversitySeoul 05006Republic of Korea Department of Artificial Intelligence and Robotics Sejong UniversitySeoul 05006Republic of Korea School of Engineering Science Simon Fraser UniversityBurnabyBC V5A 1S6Canada Department of Electrical Engineering Sejong UniversitySeoul 05006South Korea Department of Physics Faculty of ScienceKing Khalid UniversityP.O.Box 9004AbhaSaudi Arabia Central Labs King Khalid UniversityAlQura’aP.O.Box 96061413 AbhaSaudi Arabia Scientific and Technological Research and Application Center Karamanoglu Mehmetbey University70100 KaramanTurkey

The rapid advancement of nanotechnology has sparked much interest in applying nanoscale perovskite materials for photodetection *** materials are promising candidates for next-generation photodetectors(PDs)due to their unique optoelectronic properties and flexible synthesis *** review explores the approaches used in the development and use of optoelectronic devices made of different nanoscale perovskite architectures,including quantum dots,nanosheets,nanorods,nanowires,and *** a thorough analysis of recent literature,the review also addresses common issues like the mechanisms underlying the degradation of perovskite PDs and offers perspectives on potential solutions to improve stability and scalability that impede widespread *** addition,it highlights that photodetection encompasses the detection of light fields in dimensions other than light intensity and suggests potential avenues for future research to overcome these obstacles and fully realize the potential of nanoscale perovskite materials in state-of-the-art photodetection *** review provides a comprehensive overview of nanoscale perovskite PDs and guides future research efforts towards improved performance and wider applicability,making it a valuable resource for researchers.

关键词： Nanoscale perovskites Photodetectors Nanosheets Nanorods Nanowires Quantum dots Nanocrystals

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Transfer-Learning-Aided Defect Prediction in Simply Shaped Cfrp Specimens Based on Stress Distribution Obtained from Finite Element Analysis and Infrared Stress Measurement

SSRN

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SSRN 2024年

作者： Kojima, Yuta Hirayama, Kenta Endo, Katsuhiro Harada, Yoshihisa Muramatsu, Mayu Department of Science for Open and Environmental Systems Graduate School of Keio University 3-14-1 Hiyoshi Kohoku-ku Yokohama223-8522 Japan National Institute of Advanced Industrial Science and Technology 1-1-1 Umezono Ibaraki Tsukuba305-8568 Japan National Institute of Advanced Industrial Science and Technology 1-2-1 Namiki Ibaraki Tsukuba305-8564 Japan Department of Mechanical Engineering Faculty of Science and Technology Keio University 3-14-1 Hiyoshi Kohoku-ku Kanagawa223-8522 Japan

In this paper, we propose a framework of nondestructive testing for predicting the 3D structure of internal defects in carbon-fiber-reinforced plastic (CFRP) from the distribution of the sum of principal stresses on surfaces (DSPSS) through transfer learning. DSPSS is obtained from both the finite element method and infrared stress measurement results. Infrared stress measurements are based on Kelvin's theory to convert surface temperature changes to DSPSS changes. The machine learning model used in this framework is a 3D convolutional neural network (CNN). The transfer learning method employed in this framework is as follows. First, a 3D CNN that predicts the 3D structure of defects is trained using the DSPSS dataset by the finite element method and the 3D structure of internal defects. DSPSS is used with noise that imitates the noise generated by experimental factors such as temperature fluctuations in infrared stress measurements and differences in physical properties between the polymer resin and the carbon fiber bundle of CFRP. Next, the 3D CNN is trained using the DSPSS dataset obtained by infrared stress measurement and the 3D structure of defects. The accuracy of the trained 3D CNN is evaluated using DSPSS infrared stress measurements. We discuss the factors that enable us to predict the 3D defect data from the two-dimensional DSPSS using a variational autoencoder. The proposed method makes it possible to estimate internal defect information. © 2024, The Authors. All rights reserved.

关键词： Finite element method

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Additive Manufacturing of Ti6Al4V Alloy Through Laser Metal Deposition (LMD): An Elebotative Approach of Process Modelling Via Computational Fluid Dynamics

SSRN

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SSRN 2023年

作者： Rehman, Asif Ur Azher, Kashif Rehman, Aqsa Shah, Mussadiq Mahmood, Muhammed Arif Tüfekci, Celal Sami Salamci, Metin U. ERMAKSAN Bursa Turkey Department of Mechanical Engineering Faculty of Engineering Gazi University Ankara Turkey Additive Manufacturing Technologies Application and Research Center-EKTAM Ankara Turkey Department of Computer Science NFC-IET Punjab Multan60000 Pakistan Advanced Manufacturing Technologies Center of Excellence-URTEMM Ankara Turkey Intelligent Systems Center Missouri University of Science and Technology RollaMO65409 United States

Additive manufacturing (AM) has revolutionized many industries. Laser Melting Deposition (LMD) offers remarkable utility in size and is an effective method in terms of energy efficiency. The interaction of powder with laser before coming in contact with the substrate helps to attain fair melting and deposition. However, there is a problem associated with non-uniformity and accumulation of metallic melt on the edges of the manufactured parts which needs to be understood. Herein, LMD process of Ti6Al4V alloy is presented. The forces defining the melt pool flow have been elaborated. The phenomenon of recoil pressure and Marangoni actions along the single tracks of the melt pool is defined via the computational fluid dynamics (CFD) analysis. The behaviour of the melt pool in conduction mode and to check whether it will form a keyhole region or not. The main factor which influences the melt pool dynamics are found to be surface tension and density differences. Two modes of heat transfer conduction and depression are discussed with the Marangoni actions. Conduction mode is mainly governed by Marangoni actions while the depression mode is by recoil pressure. The stream traces and velocity vectors are observed for single tracks LMD process. A similar Marangoni actions experimental investigation is compared with the phenomenon observed under CFD analysis. The Discrete Element Modelling (DEM) adds value to the study as variable particle diameters are considered which are near to the actual powder size distribution. Moreover, considering the conduction mode flow dynamics to avoid the depression mode and generation of keyhole region in the melt pool will lead to porosity. © 2023, The Authors. All rights reserved.

关键词： Computational fluid dynamics

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Managed Pressure Drilling System State Estimation Using The Multiple Model Adaptive Estimation Approach 18

Managed Pressure Drilling System State Estimation Using The ...

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18th European control Conference, ECC 2020

作者： Molaei, Amir Masoud Hossein Nikoofard, Amir Khaki-Sedigh, Ali Imsland, Lars K.N. Toosi University of Technology Department of Systems and Control Faculty of Electrical Engineering Tehran Iran Norwegian University of Science and Technology Department of Engineering Cybernetics Trondheim Norway

ISBN: (纸本)9783907144015

This paper studies state estimation in the presence of parametric uncertainties, with flow estimation in Managed Pressure Drilling as a case study. Downhole measurements in most MPD systems have low frequency due to communication with mud-pulse telemetry. Also, the drilling process has parametric uncertainties due to unknown friction and fluid density and unmodeled actuator dynamics and noise add to the system complexity. This paper proposes a bank of estimators for simultaneous estimation of the model states. A Multiple-Model Adaptive Estimation (MMAE) algorithm is presented that encompasses a bank of Kalman Filters (KFs). Each KF is designed to handle a specific segment of the parametric uncertainty. In this algorithm, a probabilistically weighted combination of the local state estimations is used. Simulation results reveal that the proposed method can satisfactory estimate the unmeasured states in the presence of a wide range of uncertainties. Finally, the MMAE method is compared with a supervisory estimation algorithm to further clarify technical issues in the MPD system state estimation problem. © 2020 EUCA.

关键词： State estimation

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GETAE: Graph Information Enhanced Deep Neural Network Ensemble ArchitecturE for Fake News Detection

arXiv

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arXiv 2024年

作者： Truica, Ciprian-Octavian Apostol, Elena-Simona Marogel, Marius Paschke, Adrian Computer Science and Engineering Department Faculty of Automatic Control and Computers National University of Science and Technology Politehnica Bucharest Splaiul Independentei 313 Bucharest060042 Romania Academy of Romanian Scientists Ilfov 3 Bucharest050044 Romania Department of Mathematics and Computer Science Freie Universität Berlin Arnimallee 14 Berlin14195 Germany Fraunhofer Institute for Open Communication Systems Kaiserin-Augusta-Allee 31 Berlin10589 Germany

In today’s digital age, fake news has become a major problem that has serious consequences, ranging from social unrest to political upheaval. To address this issue, new methods for detecting and mitigating fake news are required. In this work, we propose to incorporate contextual and network-aware features into the detection process. This involves analyzing not only the content of a news article but also the context in which it was shared and the network of users who shared it, i.e., the information diffusion. Thus, we propose GETAE, Graph Information Enhanced Deep Neural Network Ensemble ArchitecturE for Fake News Detection, a novel ensemble architecture that uses textual content together with the social interactions to improve fake news detection. GETAE contains two Branches: the Text Branch and the Propagation Branch. The Text Branch uses Word and Transformer Embeddings and a Deep Neural Network based on feed-forward and bidirectional Recurrent Neural Networks ([Bi]RNN) for learning novel contextual features and creating a novel Text Content Embedding. The Propagation Branch considers the information propagation within the graph network and proposes a Deep Learning architecture that employs Node Embeddings to create novel Propagation Embedding. GETAE Ensemble combines the two novel embeddings, i.e., Text Content Embedding and Propagation Embedding, to create a novel Propagation-Enhanced Content Embedding which is afterward used for classification. The experimental results obtained on two real-world publicly available datasets, i.e., Twitter15 and Twitter16, prove that using this approach improves fake news detection and outperforms state-of-the-art models. © 2024, CC BY-NC-ND.

关键词： Graph embeddings

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Fault Detection in Inertial Measurement Unit and Global Navigation Satellite System of an Unmanned surface vehicle

Fault Detection in Inertial Measurement Unit and Global Navi...

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International Conference on control, Automation and systems ( ICCAS)

作者： Gyeongsub Song Nak Yong Ko Hyun Taek Choi Joono Sur Department of Control and Instrumentation Engineering Interdisciplinary Program in IT-Bio Convergence Systems Chosun University Gwangju Korea Department of Electronic Engineering Interdisciplinary Program in IT-Bio Convergence Systems Chosun University Gwangju Korea Autonomous & Intelligent Maritime Systems Research Division Korea Research Institute of Ships and Ocean Engineering Daejeon Korea Agency for Defense Development PM Research Institute for Advanced Defense Science and Technologies Daejeon Korea

This paper presents a method which detects faults in the measurement required for navigation of an unmanned surface vehicle. The measurement includes acceleration and angular rate by an inertial measurement unit (IMU), and the location by global navigation satellite system (GNSS). The method uses Kalman filter to estimate the state variables which represent the amount of faulty measurements. The method is tested by the experiment in which a boat equipped by commercial IMU and GNSS navigates in a sea trial. The result verifies that faults in acceleration and angular rate measurements are detected robustly and the GNSS position fault is detected when there is considerable location error.

关键词： Accelerometers Global navigation satellite system Sea surface Measurement units Sea measurements Inertial navigation Sensors

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Evaluation of Hydrogen Ions Flowing through Protonic Ceramic Fuel Cell Using Ytterbium-Doped Barium Zirconate as electrolyte

Evaluation of Hydrogen Ions Flowing through Protonic Ceramic...

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243rd ECS Meeting

作者： Okuyama, Yuji Harada, Yoshiaki Mikami, Yuichi Yamauchi, Kosuke Kuroha, Tomohiro Shimada, Hiroyuki Yamaguchi, Yuki Mizutani, Yasunobu Research Center for Sustainable Energy & Environmental Engineering Faculty of Engineering University of Miyazaki 1-1 Gakuenkibanadai-nishi Miyazaki889-2192 Japan Department of Environmental Robotics Mechanical Systems and Informatics Course Graduate School of Engineering University of Miyazaki 1-1 Gakuenkibanadai-nishi Miyazaki889-2192 Japan Interdisciplinary Graduate School of Agriculture and Engineering University of Miyazaki 1-1 Gakuenkibanadai-nishi Miyazaki889-2192 Japan Technology Division Panasonic Holdings Corporation 3-1-1 Yagumo-naka-machi Osaka Moriguchi City570-8501 Japan Innovative Functional Materials Research Institute National Institute of Advanced Industrial Science and Technology 4-205 Sakurazaka Moriyama-ku Aichi Nagoya463-8560 Japan

ISBN: (纸本)9781607685395

To measure the proton current in a PCFC (protonic ceramic fuel cell), the proton current detector was developed using a proton conducting oxide. The amount of proton current that flowed in the PCFC can be measured by an apparatus developed based on the electromotive force of an electrochemical cell using 10 mol% In-doped CaZrO3 (hydrogen sensor) and Y-stabilized zirconia (oxygen sensor). The water vapor pressure on the cathode changed when hydrogen ions pass through the PCFC. The hydrogen ion current can be determined by monitoring the water vapor pressure. The electronic leakage was then estimated from the hydrogen ion current and external current. We measured the current of hydrogen flowing through protonic ceramic fuel cell using ytterbium-doped barium zirconate as the electrolyte. Hydrogen ions and holes were found to leak under the OCV at 700°C. The electronic leakage was found to be suppressed with the increasing electrolyte film thickness. On the other hand, no leakage of hydrogen and holes was observed at 500°C. © The Electrochemical Society.

关键词： Ions

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Cu_(2)Sb decorated Cu nanowire arrays for selective electrocatalytic CO_(2)to CO conversion

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Nano Research 2021年第8期14卷 2831-2836页

作者： Shiyong Mou Yonghao Li Luchao Yue Jie Liang Yonglan Luo Qian Liu Tingshuai Li Siyu Lu Abdullah M.Asiri Xiaoli Xiong Dongwei Ma Xuping Sun College of Chemistry and Materials Science Sichuan Normal UniversityChengdu 610068China Chemical Synthesis and Pollution Control Key Laboratory of Sichuan Province School of Chemistry and Chemical engineeringChina West Normal UniversityNanchong 637002China Institute of Fundamental and Frontier Sciences University of Electronic Science and Technology of ChinaChengdu 610054China Green Catalysis Center and College of ChemistryZhengzhou UniversityZhengzhou 450001China Chemistry Department Faculty of Science&Center of Excellence for Advanced Materials ResearchKing Abdulaziz UniversityP.O.Box 80203Jeddah 21589Saudi Arabia Key Laboratory for Special Functional Materials of Ministry of Education and School of Materials Science and Engineering Henan UniversityKaifeng 475004China

The advancement of cost-effective and selective electrocatalyst towards CO_(2) to CO conversion is crucial for renewable energy conversion and storage,thus to achieve carbon-neutral cycle in a sustainable *** this communication,we report that CujSb decorated Cu nanowire arrays on Cu foil act as a highly active and selective electrocatalyst for CO_(2) to CO *** CO_(2)-saturated 0.1 M KHCO_(3),it achieves a high Faraday efficiency(FE)of 86.5%for CO,at-0.90 V *** hydrogen electrode(RHE).The H_(2)/CO ratio is tunable from 0.08:1 to 5.9:1 by adjusting the *** is worth noting that HCOO-product was totally suppressed on such catalyst,compared with Sb *** improving selectivity for CO could be attributed to the bimetallic effect and nanowire arrays structure.

关键词： Cu_(2)Sb nanowire arrays electrochemical CO_(2)reduction CO_(2)to CO conversion

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