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IoT based mobile app for continuous health monitoring of the person

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AIP Conference Proceedings 2023年第1期2690卷

作者： Indira Priyadarsini I. S. Chakrapani S. Manochitra B. Tejaswini S. Ramesh Kamal Alaskar 1Department of Botany SKR Govt. Degree College Nagari Andhra Pradesh-517590 India 2Department of Zoology PRR & VS Govt College Vidavalluru Nellore Andhra Pradesh-524318 India 3Department of Computer science & Information Technology Kalasalingam Academy of Research & Education Anand Nagar Krishnankoil-626126Tamil Nadu India 4Department of Information Science and Engineering East point college of engineering and Technology Avalahalli Bengaluru Karnataka 560049 India 5Department of Electronics and Communication Engineering St. Mother Theresa Engineering College Vagaikulam Mudivaithanenthal Post Thoothukudi District–628102 Tamil Nadu India 6Department of Computer Application Bharati Vidyapeeth (Deemed to be University) Institute of Management Kadamwadi Rd Laxminarayan Nagar Tarabai Park Kolhapur Maharashtra 416003India

In the sphere of medicine, IOT is meant to keep people safe and healthy plays a crucial part in communicating with doctors and patients through the use of health monitoring equipment and lowering healthcare costs in the future years. The internet of things (IoT) is making the world a smarter and more efficient village by allowing a variety of sensors and smart gadgets to gather and analyse data for a variety of reasons. As a result of these smart things, the healthcare system is growing wiser. When basic health facilities lack comprehensive medical care infrastructure, emerging countries gain. However, there is currently no specialized architecture for smart health units that can allow for this gathering and transferring patient health information to headquarters hospitals where live patient assistance is offered. Here, a smart IoT-based healthcare system is proposed, which includes a smart medical kit linked to sensors and a server for frequent health tracking. This smart medical kit is associated with sensors to measure the health parameters like body temperature, blood pressure, and heart rate for the effective function of the body. The proposed idea can alert the patient and their relatives in case of any abnormalities in their health parameters and also get suggestions from the doctor without physical contact with the doctor.

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Convergence of the follow-the-leader scheme for scalar conservation laws with space dependent flux

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arXiv 2019年

作者： Di Francesco, M. Stivaletta, G. Department of Information Engineering Computer Science and Mathematics Via Vetoio 1 Coppito L'AquilaI-67100 Italy

This paper deals with the derivation of entropy solutions to Cauchy problems for a class of scalar conservation laws with space-density depending fluxes from systems of deterministic particles of follow-theleader type. We consider fluxes which are product of a function of the density v(ρ) and a function of the space variable φ(x). We cover four distinct cases in terms of the sign of φ, including cases in which the latter is not constant. The convergence result relies on a local maximum principle and on a uniform BV estimate for the approximating density. Copyright © 2019, The Authors. All rights reserved.

关键词： Entropy

Design and development of digital e-library

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AIP Conference Proceedings 2021年第1期2387卷

作者： Vani Rajasekar Premalatha J. Sathya K. Janani Varthini R. Ishwarya S. 1Department of Computer Science Engineering Kongu Engineering College Perundurai-638060 Tamil Nadu India 2Department of Information Technology Kongu Engineering College Perundurai-638060 Tamil Nadu India 3Department of Computer Technology (UG) Kongu Engineering College Perundurai-638060 Tamil Nadu India

Digital libraries are platforms that allow users to access structured information in a knowledge-based repository of data and access. In the end, the availability of good content and easy accessibility and use will drive the production and growth of digital libraries. Significant advancements in IT and the rapid development of online data have generated an intense interest in tools to help users find desired data. This paper describes how, particularly in college libraries, a digital library can be built and enforced in an academic library. The specifications for hardware, software, processing and recovery technologies are addressed. An elegant user interface, combined with better browsing, insertion and reporting capabilities, functionality that anyone can access from anywhere. The library’s automatic update facility helps to get a clear idea of which books are accessed by the members, allows users to create a ’hard copy’ report. The Digital library system stores information such as name, address, ID number, date of birth of library members. The information of books such as book name, book number, topic to which it refers, author, edition, edition, year of publication, total number of publications, total number of books in the library can also be stored and accessed digitally.

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Fetal Brain Tissue Annotation and Segmentation Challenge Results

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arXiv 2022年

作者： Payette, Kelly Li, Hongwei De Dumast, Priscille Licandro, Roxane Ji, Hui Siddiquee, Md Mahfuzur Rahman Xu, Daguang Myronenko, Andriy Liu, Hao Pei, Yuchen Wang, Lisheng Peng, Ying Xie, Juanying Zhang, Huiquan Dong, Guiming Fu, Hao Wang, Guotai Rieu, ZunHyan Kim, Donghyeon Kim, Hyun Gi Karimi, Davood Gholipour, Ali Torres, Helena R. Oliveira, Bruno Vilaça, João L. Lin, Yang Avisdris, Netanell Ben-Zvi, Ori Bashat, Dafna Ben Fidon, Lucas Aertsen, Michael Vercauteren, Tom Sobotka, Daniel Langs, Georg Alenyà, Mireia Villanueva, Maria Inmaculada Camara, Oscar Fadida, Bella Specktor Joskowicz, Leo Weibin, Liao Yi, Lv Xuesong, Li Mazher, Moona Qayyum, Abdul Puig, Domenec Kebiri, Hamza Zhang, Zelin Xu, Xinyi Wu, Dan Liao, KuanLun Wu, YiXuan Chen, JinTai Xu, Yunzhi Zhao, Li Vasung, Lana Menze, Bjoern Cuadra, Meritxell Bach Jakab, Andras Center for MR Research University Children's Hospital Zurich University of Zurich Zurich Switzerland Neuroscience Center Zurich University of Zurich Zurich Switzerland Department of Quantitative Biomedicine University of Zurich Zurich Switzerland Department of Informatics Technical University of Munich Munich Germany Medical Image Analysis Laboratory Department of Diagnostic and Interventional Radiology Lausanne University Hospital University of Lausanne Lausanne Switzerland CIBM Center for Biomedical Imaging Lausanne Switzerland Laboratory for Computational Neuroimaging Athinoula A. Martinos Center for Biomedical Imaging Massachusetts General Hospital Harvard Medical School CharlestownMA United States Medical University of Vienna Vienna Austria Arizona State University United States NVIDIA United States Shanghai Jiaotong University China School of Computer Science Shaanxi Normal University Xi'An710119 China Research Institute NEUROPHET Inc. Seoul06247 Korea Republic of Department of Radiology The Catholic University of Korea Eunpyeong St. Mary's Hospital Seoul06247 Korea Republic of Boston Children's Hospital Harvard Medical School BostonMA United States 2Ai - School of Technology IPCA Barcelos Portugal Algoritmi Center School of Engineering University of Minho Guimarães Portugal School of Medicine University of Minho Braga Portugal ICVS 3B's - PT Government Associate Laboratory Guimarães Braga Portugal School of Computer Science and Engineering The Hebrew University of Jerusalem Israel Sagol Brain Institute Tel Aviv Sourasky Medical Center Israel Sagol School of Neuroscience Tel Aviv University Israel Sackler Faculty of Medicine Tel Aviv University Israel School of Biomedical Engineering & Imaging Sciences King's College London LondonSE1 7EU United Kingdom Department of Radiology University Hospitals Leuven Leuven3000 Belgium Computational Imaging Research Lab Department of Biomedical Imaging and Image-guided Therapy Medical

In-utero fetal MRI is emerging as an important tool in the diagnosis and analysis of the developing human brain. Automatic segmentation of the developing fetal brain is a vital step in the quantitative analysis of prenatal neurodevelopment both in the research and clinical context. However, manual segmentation of cerebral structures is time-consuming and prone to error and inter-observer variability. Therefore, we organized the Fetal Tissue Annotation (FeTA) Challenge in 2021 in order to encourage the development of automatic segmentation algorithms on an international level. The challenge utilized FeTA Dataset, an open dataset of fetal brain MRI reconstructions segmented into seven different tissues (external cerebrospinal fluid, grey matter, white matter, ventricles, cerebellum, brainstem, deep grey matter). 20 international teams participated in this challenge, submitting a total of 21 algorithms for evaluation. In this paper, we provide a detailed analysis of the results from both a technical and clinical perspective. All participants relied on deep learning methods, mainly U-Nets, with some variability present in the network architecture, optimization, and image pre- and post-processing. The majority of teams used existing medical imaging deep learning frameworks. The main differences between the submissions were the fine tuning done during training, and the specific pre- and post-processing steps performed. The challenge results showed that almost all submissions performed similarly. Four of the top five teams used ensemble learning methods. However, one team's algorithm performed significantly superior to the other submissions, and consisted of an asymmetrical U-Net network architecture. This paper provides a first of its kind benchmark for future automatic multi-tissue segmentation algorithms for the developing human brain in utero. © 2022, CC BY.

关键词： Magnetic resonance imaging

Roadmap on Nonlocality in Photonic Materials and Metamaterials

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arXiv 2025年

作者： Monticone, Francesco Mortensen, N. Asger Fernández-Domínguez, Antonio I. Luo, Yu Tserkezis, Christos Khurgin, Jacob B. Shahbazyan, Tigran V. Chaves, André J. Peres, Nuno M.R. Wegner, Gino Busch, Kurt Hu, Huatian della Sala, Fabio Zhang, Pu Ciracì, Cristian Aizpurua, Javier Babaze, Antton Borisov, Andrei G. Chen, Xue-Wen Christensen, Thomas Yan, Wei Yang, Yi Hohenester, Ulrich Huber, Lorenz Wubs, Martijn de Liberato, Simone Gonçalves, P.A.D. de Abajo, F. Javier García Hess, Ortwin Tarasenko, Illya Cox, Joel D. Jelver, Line Dias, Eduardo J.C. Sánchez, Miguel Sánchez Margetis, Dionisios Gómez-Santos, Guillermo Stauber, Tobias Tretyakov, Sergei Simovski, Constantin Pakniyat, Samaneh Gómez-Díaz, J. Sebastián Bondarev, Igor V. Biehs, Svend-Age Boltasseva, Alexandra Shalaev, Vladimir M. Krasavin, Alexey V. Zayats, Anatoly V. Alù, Andrea Song, Jung-Hwan Brongersma, Mark L. Levy, Uriel Long, Olivia Y. Guo, Cheng Fan, Shanhui Bozhevolnyi, Sergey I. Overvig, Adam Prudêncio, Filipa R. Silveirinha, Mário G. Gangaraj, S. Ali Hassani Argyropoulos, Christos Huidobro, Paloma A. Galiffi, Emanuele Yang, Fan Pendry, John B. Miller, David A.B. School of Electrical and Computer Engineering Cornell University IthacaNY14853 United States POLIMA Center for Polariton-driven Light–Matter Interactions University of Southern Denmark Campusvej 55 Odense MDK-5230 Denmark D-IAS—Danish Institute for Advanced Study University of Southern Denmark Campusvej 55 Odense MDK-5230 Denmark Departamento de Física Teórica de la Materia Condensada Universidad Autónoma de Madrid MadridE-28049 Spain Universidad Autónoma de Madrid MadridE-28049 Spain School of Electrical and Electronic Engineering Nanyang Technological University Singapore639798 Singapore Key Laboratory of Radar Imaging and Microwave Photonics Ministry of Education College of Electronic and Information Engineering Nanjing University of Aeronautics and Astronautics Nanjing211106 China Department of Electrical and Computer Engineering Johns Hopkins University BaltimoreMD21218 United States Department of Physics Jackson State University JacksonMS39217 United States Department of Physics Aeronautics Institute of Technology SP So Jos dos Campos12228-900 Brazil Departamento de Física Universidade do Minho BragaP-4710-057 Portugal Av Mestre José Veiga Braga4715-330 Portugal Max-Born-Institut Berlin12489 Germany Humboldt-Universität zu Berlin Institut für Physik AG Theoretische Optik and Photonik Berlin12489 Germany Center for Biomolecular Nanotechnologies Istituto Italiano di Tecnologia Via Barsanti 14 Arnesano73010 Italy Via Monteroni Campus Unisalento Lecce73100 Italy School of physics Huazhong University of Science and Technology Luoyu Road 1037 Wuhan430074 China Donostia International Physics Center DIPC Donostia-San Sebastián20018 Spain Ikerbasque Basque Foundation for Science Bilbao48009 Spain Department of Electricity and Electronics University of the Basque Country Leioa48940 Spain Department of Applied Physics University of the Basque Country Donostia20018 Spain Université Paris-Saclay CNRS Institut des Scienc

Photonic technologies continue to drive the quest for new optical materials with unprecedented responses. A major frontier in this field is the exploration of nonlocal (spatially dispersive) materials, going beyond the local, wavevector-independent assumption traditionally made in optical material modeling. On one end, the growing interest in plasmonic, polaritonic and quantum materials has revealed naturally occurring nonlocalities, emphasizing the need for more accurate models to predict and design their optical responses. This has major implications also for topological, nonreciprocal, and time-varying systems based on these material platforms. Beyond natural materials, artificially structured materials—metamaterials and metasurfaces–can provide even stronger and engineered nonlocal effects, emerging from long-range interactions or multipolar effects. This is a rapidly expanding area in the field of photonic metamaterials, with open frontiers yet to be explored. In the case of metasurfaces, in particular, nonlocality engineering has become a powerful tool for designing strongly wavevector-dependent responses, enabling enhanced wavefront control, spatial compression, multifunctional devices, and wave-based computing. Furthermore, nonlocality and related concepts play a critical role in defining the ultimate limits of what is possible in optics, photonics, and wave physics. This Roadmap aims to survey the most exciting developments in nonlocal photonic materials, highlight new opportunities and open challenges, and chart new pathways that will drive this emerging field forward–toward new scientific discoveries and technological advancements. Copyright © 2025, The Authors. All rights reserved.

关键词： Nanocrystals

Assessing Trustworthy AI in Times of COVID-19: Deep Learning for Predicting a Multiregional Score Conveying the Degree of Lung Compromise in COVID-19 Patients

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IEEE Transactions on Technology and Society

IEEE Transactions on Technology and Society 2022年第4期3卷 272-289页

作者： Allahabadi, Himanshi Amann, Julia Balot, Isabelle Beretta, Andrea Binkley, Charles Bozenhard, Jonas Bruneault, Frederick Brusseau, James Candemir, Sema Cappellini, Luca Alessandro Chakraborty, Subrata Cherciu, Nicoleta Cociancig, Christina Coffee, Megan Ek, Irene Espinosa-Leal, Leonardo Farina, Davide Fieux-Castagnet, Genevieve Frauenfelder, Thomas Gallucci, Alessio Giuliani, Guya Golda, Adam Van Halem, Irmhild Hildt, Elisabeth Holm, Sune Kararigas, Georgios Krier, Sebastien A. Kuhne, Ulrich Lizzi, Francesca Madai, Vince I. Markus, Aniek F. Masis, Serg Mathez, Emilie Wiinblad Mureddu, Francesco Neri, Emanuele Osika, Walter Ozols, Matiss Panigutti, Cecilia Parent, Brendan Pratesi, Francesca Moreno-Sanchez, Pedro A. Sartor, Giovanni Savardi, Mattia Signoroni, Alberto Sormunen, Hanna-Maria Spezzatti, Andy Srivastava, Adarsh Stephansen, Annette F. Theng, Lau Bee Tithi, Jesmin Jahan Tuominen, Jarno Umbrello, Steven Vaccher, Filippo Vetter, Dennis Westerlund, Magnus Wurth, Renee Zicari, Roberto V. Ey Netherlands Enterprise Intelligence Department Amsterdam1083 HP Netherlands Eth Zurich Health Ethics and Policy Lab Department of Health Sciences and Technology Zürich8092 Switzerland Center for Diplomatic and Strategic Studies Postgraduate Studies in Diplomacy and International Relations Paris75015 France Pisa56124 Italy Hackensack Meridian Health Bioethics Center EdisonNJ08820 United States University of Oxford Faculty of Philosophy OxfordOX2 6GG United Kingdom Collège André- Laurendeau Philosophie Department MontrealQCH8N 2J4 Canada Université du Québec À Montréal École des Médias MontrealQCH2L 2C4 Canada Pace University Philosophy Department New YorkNY10038 United States The Ohio State University Wexner Medical Center Department of Radiology ColumbusOH43210 United States Humanitas Research Hospital Department of Radiology Milan20089 Italy Humanitas University Department of Biomedical Sciences Milan20089 Italy University of New England Faculty of Science Agriculture Business and Law ArmidaleNSW2351 Australia University of Technology Sydney Faculty of Engineering and Information Technology SydneyNSW2007 Australia Scuola Superiore Sant'Anna European Centre of Excellence on the Regulation of Robotics and Ai Pisa56127 Italy University of Bremen Group of Computer Architecture Bremen28359 Germany New York University Grossman School of Medicine Division of Infectious Diseases and Immunology Department of Medicine New YorkNY10016 United States Digital Institute Ai Research Section Stockholm16731 Sweden Arcada University of Applied Sciences Department of Business Management and Analytics Helsinki00550 Finland University of Brescia Radiological Sciences and Public Health Department of Medical and Surgical Specialties Brescia25121 Italy Sncf Reseau Sa Ethique Groupe La Plaine93418 France Institute of Diagnostic and Interventional Radiology University Hospital Zurich Zürich8091 Switzerland Eindhoven University of Tech

This article's main contributions are twofold: 1) to demonstrate how to apply the general European Union's High-Level Expert Group's (EU HLEG) guidelines for trustworthy AI in practice for the domain of healthcare and 2) to investigate the research question of what does 'trustworthy AI' mean at the time of the COVID-19 pandemic. To this end, we present the results of a post-hoc self-assessment to evaluate the trustworthiness of an AI system for predicting a multiregional score conveying the degree of lung compromise in COVID-19 patients, developed and verified by an interdisciplinary team with members from academia, public hospitals, and industry in time of pandemic. The AI system aims to help radiologists to estimate and communicate the severity of damage in a patient's lung from Chest X-rays. It has been experimentally deployed in the radiology department of the ASST Spedali Civili clinic in Brescia, Italy, since December 2020 during pandemic time. The methodology we have applied for our post-hoc assessment, called Z-Inspection®, uses sociotechnical scenarios to identify ethical, technical, and domain-specific issues in the use of the AI system in the context of the pandemic. © 2020 IEEE.

关键词： COVID-19

Existence and uniqueness for a viscoelastic Kelvin-Voigt model with nonconvex stored energy

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arXiv 2020年

作者： Koumatos, Konstantinos Lattanzio, Corrado Spirito, Stefano Tzavaras, Athanasios E. Department of Mathematics University of Sussex Pevensey 2 Building Falmer BrightonBN1 9QH United Kingdom AQ I-67010 Italy Department of Information Engineering Computer Science and Mathematics University of L’Aquila Via Vetoio CoppitoL’AquilaI-67100 Italy Thuwal23955-6900 Saudi Arabia

We consider nonlinear viscoelastic materials of Kelvin-Voigt type with stored energies satisfying an Andrews-Ball condition, allowing for non convexity in a compact set. Existence of weak solutions with deformation gradients in H1 is established for energies of any superquadratic growth. In two space dimensions, weak solutions notably turn out to be unique in this class. Conservation of energy for weak solutions in two and three dimensions, as well as global regularity for smooth initial data in two dimensions are established under additional mild restrictions on the growth of the stored energy. © 2020, CC BY.

关键词： Viscoelasticity

Improving the performance of AgCdF 3 -based perovskite solar cells using machine learning-driven adjustment of active layer and charge transport materials with SCAPS-1D

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Inorganic Chemistry Communications 2025年 179卷

作者： Avijit Ghosh Al Shahriar Zishan Mahbuba Moumita Yedluri Anil Kumar Anup Kumar Roy Siful Islam Shahan Ahmed Hasanur Zaman Anonto Asma Tabassum Happy Md Shameem Ahsan H.A. Alrafai Abeer A. Hassan Department of Electrical and Electronic Engineering Begum Rokeya University Rangpur 5400 Bangladesh Department of Electrical and Electronics Engineering American International University – Bangladesh 408/1 Kuratoli Road Kuril Dhaka 1229 Bangladesh Department of Mathematics Lamar University Beaumont TX 77705 USA Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences Saveetha University Chennai 602105 Tamil Nadu India Phillip M. Drayer Department of Electrical and Computer Engineering Lamar University TX USA Master of Science in Management Information Systems College of Business Lamar University TX USA Master of Arts in Social Research & Data Analysis Montclair State University NJ USA Department of Industrial and Systems Engineering Lamar University Beaumont TX 77710 USA Department of Chemistry Faculty of Science King Khalid University PO Box 9004 Abha 61413 Saudi Arabia

This study investigates the possibility of combining inorganic substances—which act as absorbers, HTLs) in order to produce stable, effective PSCs. A ZnSe ETL, HTLs (MoS 2 , MoTe 2 , and CuI), and an AgCdF 3 perovskite absorber, comprise the suggested architecture for this study. This study examines the impact of metal contacts, doping density, interface defect densities, absorber thickness, HTL and ETL layers, and defect density on the output of a solar device using the SCAPS-1D model. The investigation of how temperature impacts the performance of the proposed PSC is another important aspect of the study. By integrating the MoS 2 /MoTe 2 /CuI layers as an HTL with the studied structure of Al/FTO/ZnSe/AgCdF 3 /HTL/Ni, the V OC climbed to 0.834/0.910/0.969 V, the J SC to 42.122/42.862/42.885 mA cm −2 , the PCE to 30.31/34.05/36.06 %, and the FF to 86.21/87.23/86.69 %. A machine learning model was created to forecast the solar cells’ performance metrics. The model precisely evaluates the importance of each parameter by utilizing SHAP values, providing important insights into their contributions. With an accuracy rate of around 83.75 %, machine learning predicted the performance matrix of the optimal solar cell under investigation. An affordable AgCdF 3 solar cell may be developed as a result of this study’s significant findings and practical design.

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An application of the frequency-based matrix converter used in a wind energy conversion system using a synchronous generator with synchronous variable-speed, pulse width modulation technique

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AIP Conference Proceedings 2022年第1期2519卷

作者： V. Senthil Nayagam E. Fantin Irudaya Raj A. Sasireka M. Kumarasamy S. K. Dinesh Kumar Ram Subbiah G. Pavithra 1Department of Electrical and Electronics Engineering College Sathyabama Institute of Science and Technology Tamilnadu India 2Department of Electrical and Electronics Engineering Dr. Sivanthi Aditanar College of Engineering Tamilnadu India 3Department of Mathematics PSNA College of Engineering and Technology Dindigul Tamilnadu India 4Department of Computer Science College of Engineering and Technology Wollega University Nekemte Ethopia 5Department of Mechanical Engineering Sri Sairam Engineering Chennai Tamilnadu India 6Department of Mechanical Engineering Gokaraju Rangaraju Institute of Engineering and Technology Hyderabad India 7Department of Electronics & Communication Engineering Dayananda Sagar College of Engineering (DSCE) Bangalore India

An alternative source is growing in popularity with increasing global energy use and perceivable environmental degradation everywhere in the universe. The growth of wind farms necessitates system stability analysis, which incorporates dynamical distributed generation models. Doubly fed induction machines are widely used in the context of turbines of power higher than 1MW. However, direct-drive wind turbines that use synchronous generator principles have gained significant market penetration. This investigation implements a synchronous generator model using a frequency-based matrix converter with the assistance of an SVPWM method, which measures stator as grid voltage/current and analyses total THD. Converting the fluctuating voltages to something like a stable value using a frequency-based method is done with a matrix converter.

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