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Mobile application to track people in covid19 monitoring and patients under covid19 supervision

IOP Conference Series: Earth and Environmental science 2021年第1期729卷

作者： A Chrysler H L H S Warnars W H Utomo Computer Science Department School of Computer Science Bina Nusantara University Jakarta Indonesia 11480 Computer Science Department BINUS Graduate Program – Doctor of Computer Science Bina Nusantara University Jakarta Indonesia 11480 Department of Magister Science of Information Technology Faculty of Computing President University Bekasi Indonesia 17550

It is crucial for the community including the government and health workers to collaborate to halt the spread of Covid-19. The idea of developing the mobile application surfaced from the previous findings. Previous researches have implemented and developed different features to better the application. The development of a mobile application to provide a platform that will assist people with information regarding patients that are around the perimeter of users to help notify them. With the help of the notification, users will be able to avoid the chances of them being in contact with the people (ODP), patients that are under surveillance (PDP) confirmed patients. All patients including ODP and PDP are required to have the application therefore, the Minister of Health will be able to track the geolocation of patients. Moreover, people will be able to be aware of patients that are around their perimeter. Therefore, with the help of the application, it will be able to help assist the community for them to be aware of and to be able to avoid being in contact with the infected patients.

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The Multi-modality Cell Segmentation Challenge: Towards Universal Solutions

arXiv

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arXiv 2023年

作者： Ma, Jun Xie, Ronald Ayyadhury, Shamini Ge, Cheng Gupta, Anubha Gupta, Ritu Gu, Song Zhang, Yao Lee, Gihun Kim, Joonkee Lou, Wei Li, Haofeng Upschulte, Eric Dickscheid, Timo de Almeida, José Guilherme Wang, Yixin Han, Lin Yang, Xin Labagnara, Marco Gligorovski, Vojislav Scheder, Maxime Rahi, Sahand Jamal Kempster, Carly Pollitt, Alice Espinosa, Leon Mignot, Tâm Middeke, Jan Moritz Eckardt, Jan-Niklas Li, Wangkai Li, Zhaoyang Cai, Xiaochen Bai, Bizhe Greenwald, Noah F. Van Valen, David Weisbart, Erin Cimini, Beth A. Cheung, Trevor Brück, Oscar Bader, Gary D. Wang, Bo Peter Munk Cardiac Centre University Health Network TorontoON Canada Department of Laboratory Medicine and Pathobiology University of Toronto TorontoON Canada Vector Institute TorontoON Canada Department of Molecular Genetics University of Toronto TorontoON Canada Donnelly Centre University of Toronto TorontoON Canada Princess Margaret Cancer Centre University Health Network TorontoON Canada School of Medicine and Pharmacy Ocean University of China Qingdao China New Delhi India Laboratory Oncology Dr. BRA-IRCH All India Institute of Medical Sciences New Delhi India Department of Image Reconstruction Nanjing Anke Medical Technology Co. Ltd. Nanjing China Shanghai Artificial Intelligence Laboratory Shanghai China Graduate School of AI KAIST Seoul Korea Republic of Shenzhen Research Institute of Big Data Shenzhen China Shenzhen China Helmholtz AI Research Center Jülich Jülich Germany Faculty of Mathematics and Natural Sciences Institute of Computer Science Heinrich Heine University Düsseldorf Düsseldorf Germany Hinxton United Kingdom Champalimaud Foundation - Centre for the Unknown Lisbon Portugal Department of Bioengineering Stanford University Palo AltoCA United States Tandon School of Engineering New York University New YorkNY United States School of Biomedical Engineering Health Science Center Shenzhen University Shenzhen China Lausanne Switzerland School of Biological Sciences University of Reading Reading United Kingdom Laboratoire de Chimie Bactérienne CNRS Université Aix Marseille UMR Institut de Microbiologie de la Méditerranée Marseille France Department of Internal Medicine I University Hospital Dresden Technical University Dresden Dresden Germany Else Kroener Fresenius Center for Digital Health Technical University Dresden Dresden Germany Department of Automation University of Science and Technology of China Hefei China Institute of Advanced Technology University of Science and Technology of China Hefei Chi

Cell segmentation is a critical step for quantitative single-cell analysis in microscopy images. Existing cell segmentation methods are often tailored to specific modalities or require manual interventions to specify hyper-parameters in different experimental settings. Here, we present a multi-modality cell segmentation benchmark, comprising over 1500 labeled images derived from more than 50 diverse biological experiments. The top participants developed a Transformer-based deep-learning algorithm that not only exceeds existing methods but can also be applied to diverse microscopy images across imaging platforms and tissue types without manual parameter adjustments. This benchmark and the improved algorithm offer promising avenues for more accurate and versatile cell analysis in microscopy imaging. © 2023, CC BY-NC-ND.

关键词： Deep learning

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ASIC Solution for the Directional Intra Prediction of the AV1 Encoder Targeting UHD 4K Videos

ASIC Solution for the Directional Intra Prediction of the AV...

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IEEE International Symposium on Circuits and Systems (ISCAS)

作者： Marcel Corrěa Luiz Neto Daniel Palomino Guilherme Corrěa Luciano Agostini Video Technology Research Group (ViTech) Federal University of Pelotas (UFPel) Brazil Graduate Program in Computing (PPGC) Federal University of Pelotas (UFPel) Brazil Sul-rio-grandense Federal Institute of Education Science and Technology (IFSul) Brazil

ISBN: (数字)9781728133201

ISBN: (纸本)9781728133218

AOMedia Video 1 (AV1), developed by the Alliance for Open Media consortium and released in 2018, is an open-source and royalty-free video format. It was designed to deliver substantial compression gains over its predecessor VP9 whilst keeping hardware feasibility and a practical decoding complexity. When compared to state-of-the-art formats, AV1 has more complex encoder tools, including the intra prediction which is the focus of this work. This paper presents a highly parallelized ASIC solution for the directional intra prediction module. It supports all 56 directional modes defined in AV1 and is able to process all combinations of block partitions. When synthesized to the TSMC 40nm technology with a target frequency of 1,296MHz, the proposed design used an area of 455.8K gates and showed a power dissipation and energy consumption per predicted sample of 40.92mW and 0.055pJ/sample, respectively. The reached throughput supports the processing of 60 frames per second for UHD 4K videos (3840×2160 pixels). No other work was found in the literature with a hardware design supporting the AV1 intra prediction directional modes.

关键词： Videos Video coding Vegetation Hardware Decoding Standards Encoding

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Fluctuating risk of acute kidney injury-related mortality for four weeks after exposure to air pollution: A multi-country time-series study in 6 countries

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Environment International 2024年 183卷 108367页

作者： Min, Jieun Kang, Duk-Hee Kang, Cinoo Bell, Michelle L. Kim, Ho Yang, Juyeon Gasparrini, Antonio Lavigne, Eric Hashizume, Masahiro Kim, Yoonhee Fook Sheng Ng, Chris Honda, Yasushi das Neves Pereira da Silva, Susana Madureira, Joana Leon Guo, Yue Pan, Shih-Chun Armstrong, Ben Sera, Francesco Masselot, Pierre Schwartz, Joel Maria Vicedo-Cabrera, Ana Pyo Lee, Jung Al-Aly, Ziyad Won Lee, Jung Kwag, Youngrin Ha, Eunhee Lee, Whanhee Department of Environmental Medicine College of Medicine Ewha Womans University Seoul Korea Republic of Graduate Program in System Health Science and Engineering College of Medicine Ewha Womans University Seoul Korea Republic of Division of Nephrology Department of Internal Medicine Ewha Womans University School of Medicine Ewha Medical Research Center Seoul Korea Republic of Department of Public Health Sciences Graduate School of Public Health Seoul National University Seoul Korea Republic of Yale School of the Environment Yale University New HavenCT United States Biostatistics Collaboration Unit Yonsei University College of Medicine Seoul Korea Republic of Lab Department of Public Health Environments and Society London School of Hygiene & Tropical Medicine London United Kingdom School of Epidemiology & Public Health Faculty of Medicine University of Ottawa Ottawa Canada Department of Global Health Policy Graduate School of Medicine The University of Tokyo Tokyo Japan Department of Global Environmental Health Graduate School of Medicine University of Tokyo Tokyo Japan School of Tropical Medicine and Global Health Nagasaki University Nagasaki Japan Center for Climate Change Adaptation National Institute for Environmental Studies Tsukuba Japan Department of Epidemiology Instituto Nacional de Saúde Dr. Ricardo Jorge Lisbon Portugal EPIUnit-Institute of Public Health University of Porto Porto Portugal Porto Portugal College of Medicine and NTU Hospital Taipei Taiwan National Institute of Environmental Health Science National Health Research Institutes Zhunan Taiwan Department of Public Health Environments and Society London School of Hygiene & Tropical Medicine London United Kingdom Department of Statistics Computer Science and Applications "G. Parenti" University of Florence Florence Italy Department of Environmental Health Harvard T.H. Chan School of Public Health BostonMA United States Institute of Social and Preventive Medicine Universi

Background: Recent studies have reported that air pollution is related to kidney diseases. However, the global evidence on the risk of death from acute kidney injury (AKI) owing to air pollution is limited. Therefore, we investigated the association between short-term exposure to air pollution—particulate matter ≤ 2.5 μm (PM2.5), ozone (O3), and nitrogen dioxide (NO2)—and AKI-related mortality using a multi-country dataset. Methods: This study included 41,379 AKI-related deaths in 136 locations in six countries during 1987–2018. A novel case time-series design was applied to each air pollutant during 0–28 lag days to estimate the association between air pollution and AKI-related deaths. Moreover, we calculated AKI deaths attributable to non-compliance with the World Health Organization (WHO) air quality guidelines. Results: The relative risks (95% confidence interval) of AKI-related deaths are 1.052 (1.003, 1.103), 1.022 (0.994, 1.050), and 1.022 (0.982, 1.063) for 5, 10, and 10 µg/m3 increase in lag 0–28 days of PM2.5, warm-season O3, and NO2, respectively. The lag-distributed association showed that the risk appeared immediately on the day of exposure to air pollution, gradually decreased, and then increased again reaching the peak approximately 20 days after exposure to PM2.5 and O3. We also found that 1.9%, 6.3%, and 5.2% of AKI deaths were attributed to PM2.5, warm-season O3, and NO2 concentrations above the WHO guidelines. Conclusions: This study provides evidence that public health policies to reduce air pollution may alleviate the burden of death from AKI and suggests the need to investigate the several pathways between air pollution and AKI death. © 2023 The Author(s)

关键词： Air quality

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Skin cancer detection based on deep learning and entropy to detect outlier samples

arXiv

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arXiv 2019年

作者： Pacheco, Andre G. C. Ali, Abder-Rahman Trappenberg, Thomas Graduate Program in Computer Science Federal University of Espírito Santo Faculty of Computer Science Dalhousie University Faculty of Natural Sciences Computing Science and Mathematics University of Stirling

We describe our methods to address both tasks of the ISIC 2019 challenge. The goal of this challenge is to provide the diagnostic for skin cancer using images and meta-data. There are nine classes in the dataset, nonetheless, one of them is an outlier and is not present on it. To tackle the challenge, we apply an ensemble of classifiers, which has 13 convolutional neural networks (CNN), we develop two approaches to handle the outlier class and we propose a straightforward method to use the meta-data along with the images. Throughout this report, we detail each methodology and parameters to make it easy to replicate our work. The results obtained are in accordance with the previous challenges and the approaches to detect the outlier class and to address the meta-data seem to be work properly. Copyright © 2019, The Authors. All rights reserved.

关键词： Dermatology

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Electrostatic Properties and Ions Elimination Effect of Polyvinyl Chloride (PVC) Adhesive Tape Manufacturing

Electrostatic Properties and Ions Elimination Effect of Poly...

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International Electrical Engineering Congress (iEECON)

作者： Tatsanee Jenbanphue Komsan Hongesombut Kulsawasd Jitkajornwanich Siwapon Srisonphan Graduate program in safety engineering Kasetsart University Bangkok Thailand Department of Electrical Engineering Kasetsart University Bangkok Thailand Department of Computer Science King Mongkut’s Institute of Technology Ladkrabang Bangkok Thailand

ISBN: (数字)9781728130767

ISBN: (纸本)9781728130774

Electrostatic discharges (ESD) can release large amounts of energy to products and humans, causing product failure and pain, respectively. In this research, we elucidate the electrostatic charge generation, and discharge phenomena in real polyvinyl chloride (PVC) based electrical tape factory, which is primarily operated by the roll to roll manufacturing process. We perform the electrostatic potential measurement to identify the critical process of charge generation and to eliminate static charge at the source in order to prevent incidents caused by electrostatic discharge to operators or staff in the winding process. We also perform a numerical simulation-based finite element method (FEM) that provides modeling of an induced electric field, allowing the electrostatic discharge. The maximum potential is ~20 kV measured at 25 mm, indicating that the meter was induced by the electric field approximately ~0.8 MV/m, corresponding to surface charges density is ~ 10 μC/m 2 . Therefore, we introduced the ionization emitter bar in this case because it is feasible to install to the current infrastructure of the tested factory. The ionization emitter appears to reduce the electrostatic charge deposited on the PVC surface ~ 30% of the original charges. Therefore, installing a charge-dissipation technology at a proper location or combining with other methods, the electrostatic charge generation can be minimized even in roll to roll process.

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Research Opportunities for E-health Applications with DNA Sequence Data using Blockchain Technology

Research Opportunities for E-health Applications with DNA Se...

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IEEE International Conference on Software Architecture Workshops (ICSAW)

作者： Maurício Moreira Neto Carlos Sérgio da S.Marinho Emanuel F. Coutinho Leonardo O. Moreira Javam de C. Machado José Neuman de Souza Master and Doctorate in Computer Science (MDCC) Federal University of Ceará (UFC) Fortaleza Ceará Brazil Graduate Program in Computer Science (PCOMP) Federal University of Ceará (UFC) Quixadá Ceará Brazil Virtual University Institute (UFC VIRTUAL) Federal University of Ceará (UFC) Fortaleza Ceará Brazil

ISBN: (数字)9781728174150

ISBN: (纸本)9781728174167

E-health applications are health-related computing solutions that use the internet to provide services to users. One of the main challenges of E-health applications is the data privacy and security of patients. E-health application need should provide security and privacy mechanisms due to sensitive user data such as medical exams, DNA sequences, and others. Blockchain technology has become a research focus on several sectors that require their inherent characteristics, especially, about the security and privacy of data. This paper aims to present research opportunities with the use of Blockchain technology in applications that manipulate DNA sequence data. For this purpose, we propose an architecture for general E-health applications with Blockchain and implement a Proof of Concept (POC) to analyze the use of Blockchain technology in E-health applications using DNA sequence data. We also listed a set of research opportunities that permeate this topic.

关键词： DNA Genomics Bioinformatics Peer-to-peer computing Data privacy

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The Quantum Internet (Technical Version)

arXiv

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arXiv 2025年

作者： Rohde, Peter P. Huang, Zixin Ouyang, Yingkai Huang, He-Liang Su, Zu-En Devitt, Simon Ramakrishnan, Rohit Mantri, Atul Tan, Si-Hui Liu, Nana Harrison, Scott Radhakrishnan, Chandrashekar Brennen, Gavin K. Baragiola, Ben Q. Dowling, Jonathan P. Byrnes, Tim Munro, William J. Centre for Quantum Software and Information Faculty of Engineering and Information Technology University of Technology Sydney SydneyNSW Australia Hearne Institute for Theoretical Physics Louisiana State University Baton Rouge United States School of Mathematical and Physical Sciences Macquarie University NSW2109 Australia School of Mathematical and Physical Sciences University of Sheffield SheffieldS3 7RH United Kingdom Henan Key Laboratory of Quantum Information and Cryptography Henan Zhengzhou450000 China Hefei National Laboratory for Physical Sciences at Microscale Department of Modern Physics University of Science & Technology of China Hefei China CAS Centre for Excellence and Synergetic Innovation Centre in Quantum Information & Quantum Physics University of Science & Technology of China Hefei China CAS-Alibaba Quantum Computing Laboratory Shanghai China InstituteQ Aalto University Espoo02150 Finland Indian Institute of Science Bangalore India Singapore University of Technology & Design Singapore Centre for Quantum Technologies National University of Singapore Singapore Horizon Quantum Ireland 24 Fitzwilliam Place Dublin 2 D02 T296 Ireland Institute of Natural Sciences Shanghai Jiao Tong University Shanghai200240 China School of Mathematical Sciences Shanghai Jiao Tong University Shanghai200240 China Ministry of Education Key Laboratory in Scientific and Engineering Computing Shanghai Jiao Tong University Shanghai200240 China Shanghai Artificial Intelligence Laboratory Shanghai China University of Michigan Shanghai Jiao Tong University Joint Institute Shanghai200240 China Leibniz Institute for Research & Information in Education Frankfurt am Main Germany Department of Computer Science and Engineering NYU Shanghai 567 West Yangsi Road Shanghai200124 China Centre of Excellence in Engineered Quantum Systems Macquarie University NSW Australia Centre for Quantum Computation and Communication Technology School of Science RMIT University VIC

The desire to share and unite remote digital assets motivated the development of the classical internet, the enabler of the entire 21st century economy and our modern way of life. As we enter the quantum era, it is to be expected there will be a similar demand for networking quantum assets, motivating a global quantum internet for bringing together the world's quantum resources, leveraging off their exponential trajectory in capability. We present models for quantum networking, how they might be applied in the future, and the implications they will have. Socially, economically, politically and geostrategically, the upcoming era of quantum supremacy will be as significant for the 21st century as the transistor was for the 20th. The inherently different scaling in the computational power of quantum computers fundamentally changes the dynamics of how they will operate in the future. Given their high expected initial cost, a client/server model for outsourcing computation will be essential for enabling the accessibility and proliferation of this technology, and ensuring its economic viability. We therefore anticipate the emergence of cloud quantum computing, a model for outsourcing quantum computations to the network. We argue that economic efficiency will mandate that all future quantum computers be united into a single global virtual quantum computer, offering exponentially more power to all network participants than if they were to keep their resources to themselves. This model for the allocation of computational resources is uniquely quantum, with no classical analogue, completely altering the economic landscape for the future of computation. Given the sensitivity of much of the data to which future quantum computers are going to foreseeably be applied, protocols for encrypted quantum computation will be essential - the outsourcing of computations that neither an eavesdropper nor even the server performing the computation can spy upon. This will enable new models fo

关键词： Outsourcing

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Homoharringtonine as a PHGDH inhibitor: Unraveling metabolic dependencies and developing a potent therapeutic strategy for high-risk neuroblastoma

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Biomedicine and Pharmacotherapy 2023年第1期166卷 115429-115429页

作者： Hsieh, Chiao-Hui Huang, Chen-Tsung Cheng, Yi-Sheng Hsu, Chun-Hua Hsu, Wen-Ming Chung, Yun-Hsien Liu, Yen-Lin Yang, Tsai-Shan Chien, Chia-Yu Lee, Yu-Hsuan Huang, Hsuan-Cheng Juan, Hsueh-Fen Department of Life Science National Taiwan University Taipei Taiwan Center for Computational and Systems Biology National Taiwan University Taipei Taiwan Graduate Institute of Biomedical Electronics and Bioinformatics National Taiwan University Taipei Taiwan Institute of Plant Biology National Taiwan University Taipei Taiwan Genome and Systems Biology Degree Program National Taiwan University and Academia Sinica Taipei Taiwan Department of Agricultural Chemistry National Taiwan University Taipei Taiwan Department of Surgery National Taiwan University Hospital and National Taiwan University College of Medicine Taipei Taiwan Department of Pediatrics School of Medicine College of Medicine Taipei Medical University Taipei Taiwan Institute of Biomedical Informatics National Yang Ming Chiao Tung University Taipei Taiwan Center for Advanced Computing and Imaging in Biomedicine Taipei Taiwan

Neuroblastoma, a childhood cancer affecting the sympathetic nervous system, continues to challenge the development of potent treatments due to the limited availability of druggable targets for this aggressive illness. Recent investigations have uncovered that phosphoglycerate dehydrogenase (PHGDH), an essential enzyme for de novo serine synthesis, serves as a non-oncogene dependency in high-risk neuroblastoma. In this study, we show that homoharringtonine (HHT) acts as a PHGDH inhibitor, inducing intricate alterations in cellular metabolism, and thus providing an efficient treatment for neuroblastoma. We have experimentally verified the reliance of neuroblastoma on PHGDH and employed molecular docking, thermodynamic evaluations, and X-ray crystallography techniques to determine the bond interactions between HHT and PHGDH. Administering HHT to treat neuroblastoma resulted in effective cell elimination in vitro and tumor reduction in vivo. Metabolite and functional assessments additionally disclosed that HHT treatment suppressed de novo serine synthesis, initiating intricate metabolic reconfiguration and oxidative stress in neuroblastoma. Collectively, these discoveries highlight the potential of targeting PHGDH using HHT as a potent approach for managing high-risk neuroblastoma. © 2023 The Authors

关键词： Computational molecular docking Drug discovery High-risk neuroblastoma Metabolic reprogramming Molecular target therapy Phosphoglycerate dehydrogenase

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An Evolutionary Algorithm for Quadcopter Trajectory Optimization in Aerial Challenges

An Evolutionary Algorithm for Quadcopter Trajectory Optimiza...

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IEEE Latin American Robotics Symposium, LARS

作者： Adson Nogueira Alves Murillo Augusto S. Ferreira Esther Luna Colombini Alexandre da Silva Simões Graduate program in Electrical Engineering (PGEE) at the Sao Paulo State University (Unesp) Sorocaba SP Brazil Institute of Computing (IC) of the University of Campinas (Unicamp) Sorocaba SP Brazil Institute of Science and Technology (ICT) of the Sao Paulo State University (Unesp) Sorocaba SP Brazil

ISBN: (数字)9780738111537

ISBN: (纸本)9781665419857

Machine learning methods have been widely employed in robotics over the years, and recent developments in machine learning have completely re-shaped problem-solving in the area. Indeed, if we consider multi-objective planning, these models' optimization and learning capabilities can derive more robust strategies. Inspired by the species natural selection mechanism, Evolutionary Algorithms (EA) are among the best known computational approaches available for this purpose. In this scenario, this work proposed an EA model developed to find the best travel trajectory for a quadcopter in the “Desafio Petrobras” challenge. In the challenge, a set of landing platforms that the robot has to visit are displaced in the 3D-space. To find the best trajectory possible, we optimize an EA over a low-level control that can take the quadcopter from point A to B. We vary our fitness function to support more complex decisions. The software-in-the-loop technique was applied for a simulated quadrotor in the Coppelia simulated environment. The proposed approach has shown the capability to generate short trajectories while considering variables like UAV dynamics and energy consumption.

关键词： Trajectory Statistics Sociology Genetics Genetic algorithms Vehicle dynamics Unmanned aerial vehicles

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