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Acquisition of the enhanced Maritime Prepositioning Force, MPF(E), Ship

NAVAL ENGINEERS JOURNAL 1999年第1期111卷 15-26页

作者： Mazumdar, T Sandison, J DuFlocq, R Thpan Mazurndar:is a Deputy Ship Design Manager from Naval Surface Warfare Center Carderock Division. He was the Design Manager for the Engineering and Design Phase ofthe Enhanced Maritime Prepositioning Fme Ship (MPF(E)). Cuwently Mt: M2.zumdar is Deputy Ship Design Manager in NAVSEA 030 for the LHD and LSD classes of ships. Mr. Mazumdar was awarded a BSE in Naval Architecture and Marine Engineering from the University of Michigan in 1981 and an MS in Computer Science fiom Virginia Tech in 1988. He also possesses an International ChiejEngineer License (Motot unlimited). Mr. Mancmdar has been an Associate Member of WAME since 1981. James C. Sandison:is a Senior Ship Design Manager (SDM) for surface ships in the Nawl Sea Systems Command (NAVSEA03D3C). He has a long tem practical background in design construction and testing of surface ships. Starting in NAVSEC as a diving and salvage systems engineer for the Bathyscaph TRIESTE he has been involved with most ofthe Nays Mine Warfare and Auxiliary ships from naval architect to the present Senior Ship Design Manager for the Strategic Sealift Program. Mr: Sandison entered the U.S. Navy in 1956 in the (diesel) Submarine Service. Afterward he “went to sea in sailing ships and completed an apprenticeship as a wooden shipbuildex. In 1971 he graduated from the University of Michigan with a BSE in Naval Architecture and Marine Engineering and was employed by NAVSEC. His latest additional duties have been as engineering coordinator on board the USS CONSTITUTION for her 200th anniversary sail. Mr. Sandison is a member of SNAME ASNE and the U.S. Naval Institute. Rick DuFlocq has over 24 years of combined project management mechanical system and general awangmmt design and design documentation experience the last 14 years urith Advance Marine Enterprises (AME). He has fmjmned this wurk on a wide variety of ships and auxiliary crafl including submarines primarily for the U.S. Navy and the Military Sealift Command (MSC). He has worked for both shiprards and marine eng

The paper will describe the streamlined acquisition process involved in the procurement, and conversion, of the first two of three Enhanced Maritime Prepositioning Force (MPF(E)) ships. This program was one of the first programs undertaken within the Government's new policy of Acquisition Reform, which resulted in the development of "performance based" requirements for these ships. This program is notable in that one prime contractor is responsible for the accomplishment of all phases, and that the contractors participating were not shipyards as is usually the fashion for Government ship acquisition programs. Also of note, was that after the conversion contracts were awarded, responsibility for the conduct of detail design, conversion, and operation and maintenance of the ship was transferred from the NAVSEA Sealift program Office (PMS 385) to the Military Sealift Command (MSC). The first part of the paper will describe the basic mission of the MPF(E) ships, and a description of the origin of the program requirements. The second part of the paper will chronicle in detail the portions of the engineering design and specification development process, which will include descriptions of the unique digital data recording and tracking systems developed by the Government MPF(E) Design Support Team to support the acquisition phases of the procurement. The third and final part of the paper will elaborate on the conversion contract awards and the transition of the program from PMS 385 to MSC.

关键词： Naval vessels

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ROLE OF SIMULATION IN RAPID PROTOTYPING FOR CONCEPT DEVELOPMENT

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NAVAL ENGINEERS JOURNAL 1991年第3期103卷 204-211页

作者： KING, JF BARTON, DE J. Fred King:is the manager of the Advanced Technology Department for Unisys in Reston Virginia. He earned his Ph.D. in mathematics from the University of Houston in 1977. He has been principal investigator of research projects in knowledge engineering pattern recognition and heuristic problem-solving. Efforts include the development of a multi-temporal multispectral classifier for identifying graincrops using LANDSAT satellite imagery data for NASA. Also as a member of the research team for a NCI study with Baylor College of Medicine and NASA he helped develop techniques for detection of carcinoma using multispectral microphotometer scans of lung tissue. He established and became technical director of the AI Laboratory for Ford Aerospace where he developed expert scheduling modeling and knowledge acquisition systems for NASA. Since joining Unisys in 1985 he has led the development of object-oriented programming environments blackboard architectures data fusion techniques using neural networks and intelligent data base systems. Douglas E. Barton:is manager of Logistics Information Systems for Unisys in Reston Virginia. He earned his B.A. degree in computer science from the College of William and Mary in 1978 and did postgraduate work in London as a Drapers Company scholar. Since joining Unisys in 1981 his work has concentrated on program management and software engineering of large scale data base management systems and design and implementation of knowledge-based systems in planning and logistics. As chairman of the Logistics Data Subcommittee of the National Security Industrial Association (NSIA) he led an industry initiative which examined concepts in knowledge-based systems in military logistics. His responsibilities also include evaluation development and tailoring of software engineering standards and procedures for data base and knowledge-based systems. He is currently program manager of the Navigation Information Management System which provides support to the Fleet Ballistic Missile Progr

A valuable technique during concept development is rapid prototyping of software for key design components. This approach is particularly useful when the optimum design approach is not readily apparent or several known alternatives need to be rapidly evaluated. A problem inherent in rapid prototyping is the lack of a "target system" with which to interface. Some alternatives are to develop test driver libraries, integrate the prototype with an existing working simulator, or build one for the specific problem. This paper presents a unique approach to concept development using rapid prototyping for concept development and scenario-based simulation for concept verification. The rapid prototyping environment, derived from artificial intelligence technology, is based on a blackboard architecture. The rapid prototype simulation capability is provided through an object-oriented modeling environment. It is shown how both simulation and blackboard technologies are used collectively to rapidly gain insight into a tenacious problem. A specific example will be discussed where this approach was used to evolve the logic of a mission controller for an autonomous underwater vehicle.

关键词： Military engineering

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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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Market Basket Analysis Using Apriori and FP-Growth for Analysis Consumer Expenditure Patterns at Berkah Mart in Pekanbaru Riau

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Journal of Physics: Conference Series 2018年第1期1114卷

作者： Mustakim Della Maulina Herianda Ahmad Ilham Achmad Daeng GS Folkes E. Laumal Nuning Kurniasih Akbar Iskandar Gloria Manulangga Ida Bagus Ary Indra Iswara Robbi Rahim Puzzle Research Data Technology UIN Sultan Syarif Kasim Riau Indonesia Department of Information System UIN Sultan Syarif Kasim Riau indonesia Informatics Department Universitas Muhammadiyah Semarang Semarang Indonesia Department of Management University of 45 Surabaya Surabaya Indonesia Department of Electrical Engineering Politeknik Negeri Kupang Kupang Indonesia Faculty of Communication Sciences Library and Information Science Program UniversitasPadjadjaran Bandung Indonesia Informatics Engineering STMIK AKBA Makassar Indonesia Informatics Department STMIK STIKOM Indonesia Denpasar Indonesia School of Computer and Communication Engineering Universiti Malaysia Perlis Kubang Gajah Malaysia

Berkah Mart is one of the new minimarkets in Pekanbaru city which began to develop as a retail business to meet the needs of the community. In his operation, Berkah Mart still uses the traditional store management perception that the placement of product layout on sale shelves has not been through sales analysis. Existing products have not been reviewed from the consumer's point of view, whereas the marketing economics concept provides a variety of product and consumer management methods for business management in Berkah Mart, including market bucket analysis techniques and various itemset search algorithms. In this research, Market Basket Basket Analysis with FP-Growth algorithm is proposed to determine the layout and planning of goods availability. The application of FP-Growth algorithm proved to be useful in generating many and informative association rules to find out the consumer spending pattern at Berkah Mart in Pekanbaru. Moreover, from the rules of the customer association can be segmented separately to meet the specific needs of customers with cost-effective by using some special promotions for the general group. The experimental results show that FP-Growth algorithm can analyze quickly and efficiently informing consumer shopping pattern at Berkah Mart and can increase Berkah Mart revenue.

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Retraction: LUC Algorithm in Visual Cryptography (J. Phys.: Conf. Ser. 1114 012090)

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Journal of Physics: Conference Series 2018年第1期1114卷

作者： Ratnadewi Christian Dio Alpha G Darmawan Napitupulu Heri Nurdiyanto Nuning Kurniasih Abdurrozaq Hasibuan GS Achmad Daengs Rosida Tiurma Manurung Indrya Mulyaningsih Robbi Rahim Castaka Agus Sugianto Dahlan Abdullah Department of Electrical Engineering Universitas Kristen Maranatha Bandung Indonesia Research Center for Quality System and Testing Technology Indonesian Institute of Sciences Banten Indonesia STMIK Dharma Wacana Indonesia Faculty of Communication Sciences Library and Information Science Program Universitas Padjadjaran Bandung Indonesia Universitas Islam Sumatera Utara Indonesia University of 45 Surabaya Indonesia Graduate Program in Scientific Psychology Universitas Kristen Maranatha Bandung Indonesia Department of Education Institut Agama Islam Negeri Syekh Nurjati Cirebon Indonesia School of Computer and Communication Engineering Universiti Malaysia Perlis Kubang Gajah Malaysia Politeknik TEDC Bandung Indonesia Department of Informatics Universitas Malikussaleh Aceh Utara Indonesia

This paper was retracted by IOP Publishing on 12 December 2018. This paper was published due to a technical error and was not intended to be included in this journal. Retraction published: 8 February 2019

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computer-system ARCHITECTURE CONCEPTS FOR FUTURE COMBAT systemS

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NAVAL ENGINEERS JOURNAL 1990年第3期102卷 43-62页

作者： ZITZMAN, LH FALATKO, SM PAPACH, JL Dr. Lewis H. Zitzman:is the group supervisor of the Advanced Systems Design Group Fleet Systems Department The Johns Hopkins University Applied Physics Laboratory (JHU/APL). He has been employed at JHU/APL since 1972 performing applied research in computer science and in investigating and applying advanced computer technologies to Navy shipboard systems. He is currently chairman of Aegis Computer Architecture Data Bus and Fiber Optics Working Group from which many concepts for this paper were generated. Dr. Zitzman received his B.S. degree in physics from Brigham Young University in 1963 and his M.S. and Ph.D. degrees in physics from the University of Illinois in 1967 and 1972 respectively. Stephen M. Falatko:was a senior engineering analyst in the Combat Systems Engineering Department Comptek Research Incorporated for the majority of this effort. He is currently employed at ManTech Services Corporation. During his eight-year career first at The Johns Hopkins University Applied Physics Laboratory and currently with ManTech Mr. Falatko's work has centered around the development of requirements and specifications for future Navy systems and the application of advanced technology to Navy command and control systems. He is a member of both the Computer Architecture Fiber Optics and Data Bus Working Group and the Aegis Fiber Optics Working Group. Mr. Falatko received his B.S. degree in aerospace engineering with high distinction from the University of Virginia in 1982 and his M.S. degree in applied physics from The Johns Hopkins University in 1985. Mr. Falatko is a member of Tau Beta Pi Sigma Gamma Tau the American Society of Naval Engineers and the U.S. Naval Institute. Janet L. Papach:is a section leader and senior engineering analyst in the Combat Systems Engineering Department Comptek Research Incorporated. She has ten years' experience as an analyst supporting NavSea Spa War and the U.S. Department of State. She currently participates in working group efforts under Aegis Combat System Doctrin

This paper sets forth computer systems architecture concepts for the combat system of the 2010–2030 timeframe that satisfy the needs of the next generation of surface combatants. It builds upon the current Aegis computer systems architecture, expanding that architecture while preserving, and adhering to, the Aegis fundamental principle of thorough systems engineering, dedicated to maintaining a well integrated, highly reliable, and easily operable combat system. The implementation of these proposed computer systems concepts in a coherent architecture would support the future battle force capable combat system and allow the expansion necessary to accommodate evolutionary changes in both the threat environment and the technology then available to effectively counter that threat. Changes to the current Aegis computer architecture must be carefully and effectively managed such that the fleet will retain its combat readiness capability at all times. This paper describes a possible transition approach for evolving the current Aegis computer architecture to a general architecture for the future. The proposed computer systems architecture concepts encompass the use of combinations of physically distributed, microprocessor-based computers, collocated with the equipment they support or embedded within the equipment itself. They draw heavily on widely used and available industry standards, including instruction set architectures (ISAs), backplane busses, microprocessors, computer programming languages and development environments, and local area networks (LANs). In this proposal, LANs, based on fiber optics, will provide the interconnection to support system expandability, redundancy, and higher data throughput rates. A system of cross connected LANs will support a high level of combat system integration, spanning the major warfare areas, and will facilitate the coordination and development of a coherent multi-warfare tactical picture supporting the future combatant command st

关键词： computer Architecture

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LUC Algorithm in Visual Cryptography

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Journal of Physics: Conference Series 2018年第1期1114卷

Nowadays, messaging technology in digital data form more often used and not less messages that confidentially wanted. Then it should be modified so that can be understood only by the sender and the intended recipients. All of this system can be realization by using cryptography. LUC algorithms are introduced by Smith and Lennon in 1993. LUC algorithm is an algorithm that based on the use of Lucas sequence (specific arithmetic operations derived from Lucas row) that rarely used to enhance the security of the messages. In this research, LUC algorithm is combined with visual cryptography to process the encryption and the description of a colored image. Four different images were used in the trial here. The performance of the system is assessed using Structural similarity (SSIM) which has an assessment similar to human eye. If the image quality is the same as the original image, then the SSIM value is one. Whereas if the quality of decryption image is very different from the original image then the value of SSIM is zero.

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A computer-MODEL FOR SHIPBOARD ENERGY ANALYSIS

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NAVAL ENGINEERS JOURNAL 1984年第5期96卷 33-45页

作者： DETOLLA, JP FLEMING, JR Joseph DeTolla:is a ship systems engineer in the Ship Systems Engineering Division SEA 56D5 at the Naval Sea Systems Command. His career with the Navy started in 1965 at the Philadelphia Naval Shipyard Design Division. In 1971 he transferred to the Naval Ship Engineering Center. He has held positions as a fluid systems design engineer and auxiliary systems design integration engineer. Mr. DeTolla has worked extensively in the synthesis and analysis of total energy systems notably the design development of the FFG-7 class waste heat recovery system. He is NA VSEA's machinery group computer supported design project coordinator and is managing the development of a machinery systems data base load forecasting algorithms and design analysis computer programs. Mr. DeTolla has a bachelor of science degree in mechanical engineering from Drexel University and a master of engineering administration degree from George Washington University. He is a registered professional engineer in the District of Columbia and has written several technical papers on waste heat recovery and energy conservation. Jeffrey Fleming:is a senior project engineer in the Energy R&D Office at the David Taylor Naval Ship R&D Center. In his current position as group leader for the future fleet energy conservation portion of the Navy's energy R&D program he is responsible for the identification and development of advanced components and subsystems which will lead to reductions in the fossil fuel consumption of future ships. Over the past several years he has also directed the development and application of total energy computer analysis techniques for the assessment of conventional and advanced shipboard machinery concepts. Mr. Fleming is a 1971 graduate electrical engineer of Virginia Polytechnic Institute and received his MS in electrical engineering from Johns Hopkins University in 1975. Mr. Fleming has authored various technical publications and was the recipient of the Severn Technical Society's “Best Technical Paper of the Year” award in 1

In support of the Navy's efforts to improve the energy usage of future ships and thereby to reduce fleet operating costs, a large scale computer model has been developed by the David Taylor Naval Ship Research and Development Center (DTNSRDC) to analyze the performance of shipboard energy systems for applications other than nuclear or oil-fired steam propulsion plants. This paper discusses the applications and utility of this computer program as a performance analysis tool for design of ship machinery systems. The program is a simulation model that performs a complete thermodynamic analysis of a user-specified energy system. It offers considerable flexibility in analyzing a variety of propulsion, electrical, and auxiliary plant configurations through a component building block structure. Component subroutines that model the performance of shipboard equipment such as engines, boilers, generators, and compressors are available from the program library. Component subroutines are selected and linked in the program to model the desired machinery plant functional configurations. The operation of the defined shipboard energy system may then be simulated over a user-specified scenario of temperature, time, and load profiles. The program output furnishes information on component operating characteristics and fuel demands, which allows evaluation of the total system performance.

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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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26th Annual Computational Neuroscience Meeting (CNS*2017): Part 3 Antwerp, Belgium. 15-20 July 2017 Abstracts

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BMC NEUROscience 2017年第SUPPL 1期18卷 95-176页

作者： [Anonymous] Department of Neuroscience Yale University New Haven CT 06520 USA Department Physiology & Pharmacology SUNY Downstate Brooklyn NY 11203 USA NYU School of Engineering 6 MetroTech Center Brooklyn NY 11201 USA Departament de Matemàtica Aplicada Universitat Politècnica de Catalunya Barcelona 08028 Spain Institut de Neurobiologie de la Méditerrannée (INMED) INSERM UMR901 Aix-Marseille Univ Marseille France Center of Neural Science New York University New York NY USA Aix-Marseille Univ INSERM INS Inst Neurosci Syst Marseille France Laboratoire de Physique Théorique et Modélisation CNRS UMR 8089 Université de Cergy-Pontoise 95300 Cergy-Pontoise Cedex France Department of Mathematics and Computer Science ENSAT Abdelmalek Essaadi’s University Tangier Morocco Laboratory of Natural Computation Department of Information and Electrical Engineering and Applied Mathematics University of Salerno 84084 Fisciano SA Italy Department of Medicine University of Salerno 84083 Lancusi SA Italy Dipartimento di Fisica Università degli Studi Aldo Moro Bari and INFN Sezione Di Bari Italy Data Analysis Department Ghent University Ghent Belgium Coma Science Group University of Liège Liège Belgium Cruces Hospital and Ikerbasque Research Center Bilbao Spain BIOtech Department of Industrial Engineering University of Trento and IRCS-PAT FBK 38010 Trento Italy Department of Data Analysis Ghent University Ghent 9000 Belgium The Wellcome Trust Centre for Neuroimaging University College London London WC1N 3BG UK Department of Electronic Engineering NED University of Engineering and Technology Karachi Pakistan Blue Brain Project École Polytechnique Fédérale de Lausanne Lausanne Switzerland Departement of Mathematics Swansea University Swansea Wales UK Laboratory for Topology and Neuroscience at the Brain Mind Institute École polytechnique fédérale de Lausanne Lausanne Switzerland Institute of Mathematics University of Aberdeen Aberdeen Scotland UK Department of Integrativ

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