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18th AIAA Aviation Technology, Integration, and Operations Conference, 2018

作者： Hayward, Douglas M. Duff, Andrew K. Wagner, Charles Lockheed Martin Aeronautics F-35 Systems Engineering Mail Zone 6500 PO Box 748 Fort WorthTX76101 United States Lockheed Martin Aeronautics F-35 Armament and Stores Management Mail Zone 6421 PO Box 748 Fort WorthTX76101 United States GS-14 F-35 Weapons Integrated Product Team Lead F-35 Joint Program Office ArlingtonVA22202 United States

ISBN: (数字)9781624105562

ISBN: (纸本)9781624105562

Tactical aircraft operations in a high-threat, hostile environment require an internal weapon carriage capability that supports stealth operations while ensuring aircrew survivability and mission success. Once the threats have been reduced, a multirole, increased external carriage capability is then required to prosecute an expanded target set. The F-35 meets both roles with internal carriage of air-to-air and air-to-surface stores. It has a robust external carriage capability of multirole stores, an internal 25-millimeter Gatling gun for the F-35A, and a missionized 25-millimeter gun pod for the F-35B and F-35C. It also has a stores management system designed to control current and future store interfaces. The F-35 weapon carriage design is based on experience gained from developing our successful 4th Generation F-16 and 5th Generation F-22 fighter aircraft. The design is highly common across the three F-35 variants and provides interoperability and operational flexibility to the theater commanders to engage a wide array of targets. This paper describes the weapons requirements, design development, evolution, and trades performed to define and mature the weapon carriage layout. It also details the associated systems required to load, carry, release, and interface with F-35 weapons. © 2018, American Institute of Aeronautics and Astronautics Inc, AIAA. All rights reserved.

关键词： Fighter Aircraft Aircraft Operations Aircrew Advanced Short Range Air to Air Missile Landing Gear Flight Test programme Ground Support Equipment Wind Tunnel Tests Close Air Support Air Vehicle

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ANTARCTICA AND THE SOUTHERN OCEAN

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BULLETIN OF THE AMERICAN METEOROLOGICAL SOCIETY 2023年第9期104卷 S322-S365页

作者： Clem, Kyle R. Raphael, Marilyn N. School of Geography Environment and Earth Sciences Victoria University of Wellington Wellington New Zealand Scripps Institution of Oceanography University of California San Diego La Jolla California Department of Atmospheric and Oceanic Sciences University of Colorado Boulder Boulder Colorado Earth Science Observation Center Cooperative Institute for Research in Environmental Sciences (ESOC/CIRES) University of Colorado Boulder Boulder Colorado Argentine Naval Hydrographic Service Buenos Aires Argentina Department of Earth and Environmental Science Temple University Philadelphia Pennsylvania Department of Meteorology University of Valparaíso Valparaíso Chile Center for Climate and Resilience Research (CR)2 Santiago Chile British Antarctic Survey Cambridge United Kingdom Science Systems and Applications Inc. Lanham Maryland NASA Goddard Space Flight Center Greenbelt Maryland Royal Netherlands Meteorological Institute (KNMI) DeBilt The Netherlands Department of Marine Sciences University of Gothenburg Gothenburg Sweden Department of Geography Ohio University Athens Ohio NASA Jet Propulsion Laboratory Pasadena California NOAA/OAR Earth System Research Laboratory Global Monitoring Division Boulder Colorado University of Colorado Boulder Boulder Colorado National Oceanography Centre Southampton United Kingdom. Antarctic Meteorological Research and Data Center Space Science and Engineering Center University of Wisconsin-Madison Madison Wisconsin Department of Physical Sciences School of Arts and Sciences Madison Area Technical College Madison Wisconsin Australian Bureau of Meteorology and Institute for Marine and Antarctic Studies (IMAS) University of Tasmania Hobart Australia Earth Science and Observation Center CIRES University of Colorado Boulder Colorado University of St. Andrews St Andrews United Kingdom Princeton University Princeton New Jersey Australian Antarctic Division Australian Antarctic Program Partnership (AAPP) and Australian Centre fo

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Highly accurate model for prediction of lung nodule malignancy with ct scans

arXiv

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arXiv 2018年

作者： Causey, Jason Zhang, Junyu Ma, Shiqian Jiang, Bo Qualls, Jake Politte, David G. Prior, Fred Zhang, Shuzhong Huang, Xiuzhen Department of Computer Science Arkansas State University JonesboroAR72467 United States Department of Industrial and Systems Engineering University of Minnesota MinneapolisMN55455 United States Department of Systems Engineering and Engineering Management Chinese University of Hong Kong Shatin N.T. Hong Kong Research Center for Management Science and Data Analytics School of Information Management and Engineering Shanghai University of Finance and Economics Shanghai200433 China Mallinckrodt Institute of Radiology Washington University St. LouisMO63110 United States Department of Biomedical Informatics University of Arkansas for Medical Sciences Little RockAR72205 United States UALR/UAMS Joint Graduate Program in Bioinformatics Little RockAR72204 United States

Computed tomography (CT) examinations are commonly used to predict lung nodule malignancy in patients, which are shown to improve noninvasive early diagnosis of lung cancer. It remains challenging for computational approaches to achieve performance comparable to experienced radiologists. Here we present NoduleX, a systematic approach to predict lung nodule malignancy from CT data, based on deep learning convolutional neural networks (CNN). For training and validation, we analyze >1000 lung nodules in images from the LIDC/IDRI cohort. All nodules were identified and classified by four experienced thoracic radiologists who participated in the LIDC project. NoduleX achieves high accuracy for nodule malignancy classification, with an AUC of ~0.99. This is commensurate with the analysis of the dataset by experienced radiologists. Our approach, NoduleX, provides an effective framework for highly accurate nodule malignancy prediction with the model trained on a large patient population. Our results are replicable with software available at http://***/NoduleX. Copyright © 2018, The Authors. All rights reserved.

关键词： Forecasting

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Electromagnetic Optimization Based on Gaussian Crow Search Approach

Electromagnetic Optimization Based on Gaussian Crow Search A...

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2018 International Symposium on Power Electronics, Electrical Drives, Automation and Motion, SPEEDAM 2018

作者： Dos Santos Coelho, Leandro Klein, Carlos Eduardo Mariani, Viviana Cocco Do Nascimento, Carlos Augusto Richter Askarzadeh, Alireza PUCPR Industrial and Systems Eng. Graduate Program PPGEPS Federal University of Parana UFPR Department of Electrical Engineering DEE/PPGEE Pontifical Catholic University of Parana Curitiba PR Brazil PUCPR Mechanical Engineering Graduate Program PPGEM Curitiba Pontifical Catholic University of Parana PR Brazil Department of Energy Management and Optimization Institute of Science and High Technology and Environmental Sciences Graduate University of Advanced Technology Kerman Iran

ISBN: (纸本)9781538649411

Metaheuristic algorithms have provided efficient tools to designers by which it became possible to determine the optimum solutions of optimization problems encountered in several fields such as engineering, finance and computation. Generally metaheuristics are based on metaphors that are taken from nature or some other processes. Recently, an optimization metaheuristic paradigm based on the social behavior of the crows, called crow search algorithm (CSA), has been proposed. The idea of CSA is motivated from the storing process of the excess food in hiding places then restoring it in the necessary time. The CSA has many favorable characteristics, such as ease of implementation, the need to adjust only a few parameters, a favorable balance between search diversification and intensification, and fast convergence and high sensitivity. However, to enhance the performance of the standard CSA approach, this paper proposes to tune the control parameters using population diversity information and normal (Gaussian) probability distribution function. Loney's solenoid benchmark and circular antenna array design problems are used to evaluate the effectiveness of the conventional CSA and the proposed variant. Simulation results and comparisons with the CSA demonstrated that the performance of the proposed MCSA approach is promising in electromagnetics optimization. © 2018 IEEE.

关键词： Optimization

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4. Alcohol use disorder and inflammation among those seeking care in the emergency department for acute mild traumatic brain injury

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Alcohol 2023年 113卷 58-58页

作者： Brenner, Lisa A. Hoisington, Andrew Penzenik, Molly Stearns-Yoder, Kelly Lowry, Chris Postolache, Teodor Hoffmire, Claire Betz, Marian Stamper, Christopher Forster, Jeri Department of Psychiatry University of Colorado Anschutz Medical Campus Aurora CO Department of Physical Medicine & Rehabilitation University of Colorado Anschutz Medical Campus Aurora CO VA Rocky Mountain Mental Illness Research Education and Clinical Center (MIRECC) Rocky Mountain Regional VA Medical Center Aurora CO Military and Veteran Microbiome Consortium for Research and Education Aurora CO Department of Neurology University of Colorado Anschutz Medical Campus Aurora CO Department of Systems Engineering & Management Air Force Institute of Technology Wright-Patterson AFB OH Department of Integrative Physiology University of Colorado Boulder Boulder CO Center for Neuroscience and Center for Microbial Exploration University of Colorado Boulder Boulder CO Center for Neuroscience University of Colorado Anschutz Medical Campus Aurora CO Mood and Anxiety Program Department of Psychiatry University of Maryland School of Medicine Baltimore MD Veterans Integrated Service Networks 5 MIRECC Department of Veterans Affairs Baltimore MD Department of Emergency Medicine University of Colorado Anschutz Medical Campus Aurora CO VA Eastern Colorado Geriatric Research Education and Clinical Center Aurora CO

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Structural Effects and Aggregation in a Social-Network Model of Natural Resource Consumption

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IFAC-PapersOnLine 2017年第1期50卷 7675-7680页

作者： Manzoor T. Rovenskaya E. Muhammad A. Department of Electrical Engineering Lahore University of Management Sciences (LUMS) Lahore Pakistan Center for Water Informatics & Technology (WIT) Lahore University of Management Sciences (LUMS) Pakistan Advanced Systems Analysis Program International Institute for Applied Systems Analysis (IIASA) Laxenburg Austria Faculty of Computational Mathematics and Cybernetics Lomonosov Moscow State University Moscow Russian Federation

In this paper we consider a networked system of natural-resource consumption, where the agents are governed by a recently reported model of consumer psychology Dynamics of the consumption for each agent are influenced by the state of the resource and consumption of her neighbors. The process is parameterized by the psychological characteristics of each agent. This study extends the original model to incorporate the underlying network topology and explores the effects of aggregation via densely-connected communities present in the network. The exercise yields new interpretations of the predictions made by the original model in context of the influence network. We present aggregation mechanisms first for certain canonical structures of the consuming population and later on for a class of non-canonically structured populations. In the end we present an approximate aggregation scheme for populations where only some inaccurate information of the consumer characteristics is available. © 2017

关键词： Control in economics identification of environmental systems Modeling Multi-agent systems Natural resources management Social Networks

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Fungal diversity notes 1387-1511:taxonomic and phylogenetic contributions on genera and species of fungal taxa

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Fungal Diversity 2021年第6期111卷 1-335页

作者： Saranyaphat Boonmee Dhanushka N.Wanasinghe Mark S.Calabon Naruemon Huanraluek Sajini K.U.Chandrasiri Gareth E.B.Jones Walter Rossi Marco Leonardi Sanjay K.Singh Shiwali Rana Paras N.Singh Deepak K.Maurya Ajay C.Lagashetti Deepika Choudhary Yu-Cheng Dai Chang-Lin Zhao Yan-Hong Mu Hai-Sheng Yuan Shuang-Hui He Rungtiwa Phookamsak Hong-Bo Jiang María P.Martín Margarita Dueñas MTeresa Telleria Izabela L.Kałucka Andrzej M.Jagodziński Kare Liimatainen Diana S.Pereira Alan J.L.Phillips Nakarin Suwannarach Jaturong Kumla Surapong Khuna Saisamorn Lumyong Tarynn B.Potter Roger G.Shivas Adam H.Sparks Niloofar Vaghefi Mohamed A.Abdel-Wahab Faten A.Abdel-Aziz Guo-Jie Li Wen-Fei Lin Upendra Singh Rajendra P.Bhatt Hyang Burm Lee Thuong T.T.Nguyen Paul M.Kirk Arun Kumar Dutta Krishnendu Acharya VVenkateswara Sarma M.Niranjan Kunhiraman C.Rajeshkumar Nikhil Ashtekar Sneha Lad Nalin N.Wijayawardene Darbe J.Bhat Rong-Ju Xu Subodini N.Wijesinghe Hong-Wei Shen Zong-Long Luo Jing-Yi Zhang Phongeun Sysouphanthong Naritsada Thongklang Dan-Feng Bao Janith V.S.Aluthmuhandiram Jafar Abdollahzadeh Alireza Javadi Francesco Dovana Muhammad Usman Abdul Nasir Khalid Asha J.Dissanayake Anusha Telagathoti Maraike Probst Ursula Peintner Isaac Garrido-Benavent Lilla Bóna Zsolt Merényi Lajos Boros Bratek Zoltán JBenjamin Stielow Ning Jiang Cheng-Ming Tian Esmaeil Shams Farzaneh Dehghanizadeh Adel Pordel Mohammad Javan-Nikkhah Teodor T.Denchev Cvetomir M.Denchev Martin Kemler Dominik Begerow Chun-Ying Deng Emma Harrower Tohir Bozorov Tutigul Kholmuradova Yusufjon Gafforov Aziz Abdurazakov Jian-Chu Xu Peter E.Mortimer Guang-Cong Ren Rajesh Jeewon Sajeewa S.N.Maharachchikumbura Chayanard Phukhamsakda Ausana Mapook Kevin D.Hyde Center of Excellence in Fungal Research Mae Fah Luang UniversityChiang Rai 57100Thailand School of Science Mae Fah Luang UniversityChiang Rai 57100Thailand CAS Key Laboratory for Plant Biodiversity and Biogeography of East Asia(KLPB) Kunming Institute of BotanyChinese Academy of ScienceKunming 650201YunnanPeople’s Republic of China CIFOR-ICRAF China Program World Agroforestry(ICRAF)Kunming 650201YunnanPeople’s Republic of China Honghe Center for Mountain Futures Kunming Institute of BotanyHonghe CountyKunming 654400YunnanPeople’s Republic of China Department of Botany and Microbiology College of ScienceKing Saud UniversityP.O.Box 2455Riyadh 11451Saudi Arabia Section Environmental Sciences Department MeSVAUniversity of L’Aquila67100 CoppitoAQItaly National Fungal Culture Collection of India(NFCCI) Biodiversity and Palaeobiology GroupMACS Agharkar Research InstituteG.G.Agarkar RoadPune 411004India Institute of Microbiology School of Ecology and Nature ConservationBeijing Forestry UniversityBeijing 100083People’s Republic of China College of Biodiversity Conservation Southwest Forestry UniversityKunming 650224People’s Republic of China CAS Key Laboratory of Forest Ecology and Management Institute of Applied EcologyChinese Academy of SciencesShenyang 110164People’s Republic of China University of the Chinese Academy of Sciences Beijing 100049People’s Republic of China Centre for Mountain Futures(CMF) Kunming Institute of BotanyKunming 650201YunnanPeople’s Republic of China Department of Mycology Real Jardín Botánico-CSICPlaza de Murillo 228014 MadridSpain Department of Algology and Mycology Faculty of Biology and Environmental ProtectionUniversity of LodzBanacha 12/1690-237ŁódźPoland Institute of Dendrology Polish Academy of SciencesParkowa 562-035 KórnikPoland Jodrell Laboratory Royal Botanic GardensKewRichmond TW93DSSurreyUK Faculdade de Ciências Biosystems and Integrative Sciences Institute(BioISI)Universidade de LisboaCampo Grande1749-016 LisbonPortugal Dep

This article is the 13th contribution in the Fungal Diversity Notes series,wherein 125 taxa from four phyla,ten classes,31 orders,69 families,92 genera and three genera incertae sedis are treated,demonstrating worldwide and geographic *** taxa described and illustrated in the present study include three new genera,69 new species,one new com-bination,one reference specimen and 51 new records on new hosts and new geographical *** new genera,Cylindrotorula(Torulaceae),Scolecoleotia(Leotiales genus incertae sedis)and Xenovaginatispora(Lindomycetaceae)are introduced based on distinct phylogenetic lineages and unique *** described species are Aspergillus lan-naensis,Cercophora dulciaquae,Cladophialophora aquatica,Coprinellus punjabensis,Cortinarius alutarius,***-latus,***,Coryneum fagi,Cruentomycena uttarakhandina,Cryptocoryneum rosae,Cyathus uniperidiolus,Cylindrotorula indica,Diaporthe chamaeropicola,Didymella azollae,Diplodia alanphillipsii,Dothiora coronicola,Efibula rodriguezarmasiae,Erysiphe salicicola,Fusarium queenslandicum,Geastrum gorgonicum,***,Helicosporium sexualis,Helminthosporium chiangraiensis,Hongkongmyces kokensis,Hydrophilomyces hydraenae,Hygrocybe boertmannii,Hyphoderma australosetigerum,Hyphodontia yunnanensis,Khaleijomyces umikazeana,Laboulbenia divisa,Laboulbenia triarthronis,Laccaria populina,Lactarius pallidozonarius,Lepidosphaeria strobelii,Longipedicellata megafusiformis,Lophiotrema lincangensis,Marasmius benghalensis,***,***,Mariannaea camelliae,Mel-anographium smilaxii,Microbotryum polycnemoides,Mimeomyces digitatus,Minutisphaera thailandensis,Mortierella solitaria,Mucor harpali,Nigrograna jinghongensis,Odontia huanrenensis,***,Paraconiothyrium ajrekarii,Par-afuscosporella niloticus,Phaeocytostroma yomensis,Phaeoisaria synnematicus,Phanerochaete hainanensis,Pleopunctum thailandicum,Pleurotheciella dimorphospora,Pseudochaetosphaeronema

关键词： 72 new taxa One new combination One reference specimen 51 new records Agaricomycetes Ascomycota Bartheletiomycetes Basidiomycota Dothideomycetes Eurotiomycetes Exobasidiomycetes Laboulbeniomycetes Leotiomycetes Mortierellomycetes Mortierellomycota Mucoromycetes Mucoromycota Phylogeny Sordariomycetes Taxonomy

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Author Correction: Discrepancy in scientific authority and media visibility of climate change scientists and contrarians

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Nature communications 2019年第1期10卷 3966页

作者： Alexander Michael Petersen Emmanuel M Vincent Anthony LeRoy Westerling Management of Complex Systems Department Ernest and Julio Gallo Management Program School of Engineering University of California Merced CA 95343 USA. apetersen3@ucmerced.edu. Medialab Sciences Po Paris 75007 France. mel.manux@***. Center for Climate Communication University of California Merced CA 95343 USA. mel.manux@***. Management of Complex Systems Department Ernest and Julio Gallo Management Program School of Engineering University of California Merced CA 95343 USA. awesterling@ucmerced.edu. Center for Climate Communication University of California Merced CA 95343 USA. awesterling@ucmerced.edu. Sierra Nevada Research Institute University of California Merced CA 95343 USA. awesterling@ucmerced.edu.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

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Author Correction: Towards symbiotic approaches between universities, sustainable development, and cities

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Scientific reports 2023年第1期13卷 552页

作者： Walter Leal Filho Liliana Caughman Maria Alzira Pimenta Dinis Fernanda Frankenberger Anabela Marisa Azul Amanda Lange Salvia Department of Natural Sciences Manchester Metropolitan University Chester Street Manchester M115GD UK. Research and Transfer Centre "Sustainable Development and Climate Change Management" Hamburg University of Applied Sciences Ulmenliet 20 21033 Hamburg Germany. Postdoctoral Research Scholar Earth Systems Science for the Anthropocene Arizona State University Tempe USA. UFP Energy Environment and Health Research Unit (FP-ENAS) University Fernando Pessoa (UFP) Praça 9 de Abril 349 4249-004 Porto Portugal. Business School PUCPR Pontifical Catholic University of Paraná Rua Imaculada Conceição Curitiba 1155 Brazil. Brazil Business School Universidade Positivo Rua Pedro Viriato Parigot de Souza Curitiba 5300 Brazil. CNC-Center for Neuroscience and Cell Biology University of Coimbra 3004-504 Coimbra Portugal. CIBB-Center for Innovative Biomedicine and Biotechnology University of Coimbra Coimbra Portugal. IIIUC-Institute for Interdisciplinary Research University of Coimbra 3030-789 Coimbra Portugal. Graduate Program in Civil and Environmental Engineering University of Passo Fundo Campus I - BR285 São José Passo Fundo RS 99052-900 Brazil. amandasalvia@***. European School of Sustainability Science and Research Hamburg University of Applied Sciences Ulmenliet 20 21033 Hamburg Germany. amandasalvia@***.

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Entrepreneurial Mindfulness Based on Artificial Intelligence

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Journal of Physics: Conference Series 2020年第1期1641卷

作者： Yasinta Indrianti Sasmoko Nor Fadila Mohd Amin Sucianna Ghadati Rabiha Nugroho Juli Setiadi Agustinus Dedy Handrimurtjahjo Muktiono Waspodo Entrepreneurship Department Podomoro University Jakarta Indonesia 11470 Primary Teacher Education Department Faculty of Humanities Bina Nusantara University Jakarta Indonesia 11480 Department of Technical and Engineering Education School of Education Faculty of Social Sciences and Humanities Universiti Teknologi Malaysia Malaysia Information Systems Department Binus Online Learning Bina Nusantara University Jakarta Indonesia 11480 Management Department BINUS Business School Undergraduate Program Bina Nusantara University Jakarta Indonesia 11480 Center for Research on Education and Culture Policy Ministry of Education and Culture of the Republic of Indonesia Jakarta Indonesia

The ability to self-diagnose to build capacity as an entrepreneur is something that is important in order to bridge the development of self-competence needed in the industrial era 4.0. This ability is expected to bring up a condition in which a person has full active awareness of the awakening of the entrepreneurial spirit within himself to then produce a productive person called Entrepreneurial Mindfulness. This study aims to develop self-detection tools about Entrepreneurial Mindfulness through an artificial intelligence-based website for students and alumni who are entrepreneurs. The research method used is the Neuroresearch method for developing Entrepreneurial Mindfulness measurement tools and the waterfall method for developing Artificial Intelligence-based websites. The results of research in the form of an Artificial Intelligence-based website about Entrepreneurial Mindfulness where the website will be able to provide profiling based on diagnoses made related to the level of Entrepreneurial Mindfulness owned by students and alumni in implementing entrepreneurial practices.

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