Sensitivity and specificity of some methods used in diagnosis of invasive candidiasis as compared to conventional methods.
\\n\\n
Released this past November, the list is based on data collected from the Web of Science and highlights some of the world’s most influential scientific minds by naming the researchers whose publications over the previous decade have included a high number of Highly Cited Papers placing them among the top 1% most-cited.
\\n\\nWe wish to congratulate all of the researchers named and especially our authors on this amazing accomplishment! We are happy and proud to share in their success!
Note: Edited in March 2021
\\n"}]',published:!0,mainMedia:{caption:"Highly Cited",originalUrl:"/media/original/117"}},components:[{type:"htmlEditorComponent",content:'IntechOpen is proud to announce that 191 of our authors have made the Clarivate™ Highly Cited Researchers List for 2020, ranking them among the top 1% most-cited.
\n\nThroughout the years, the list has named a total of 261 IntechOpen authors as Highly Cited. Of those researchers, 69 have been featured on the list multiple times.
\n\n\n\nReleased this past November, the list is based on data collected from the Web of Science and highlights some of the world’s most influential scientific minds by naming the researchers whose publications over the previous decade have included a high number of Highly Cited Papers placing them among the top 1% most-cited.
\n\nWe wish to congratulate all of the researchers named and especially our authors on this amazing accomplishment! We are happy and proud to share in their success!
Note: Edited in March 2021
\n'}],latestNews:[{slug:"intechopen-supports-asapbio-s-new-initiative-publish-your-reviews-20220729",title:"IntechOpen Supports ASAPbio’s New Initiative Publish Your Reviews"},{slug:"webinar-introduction-to-open-science-wednesday-18-may-1-pm-cest-20220518",title:"Webinar: Introduction to Open Science | Wednesday 18 May, 1 PM CEST"},{slug:"step-in-the-right-direction-intechopen-launches-a-portfolio-of-open-science-journals-20220414",title:"Step in the Right Direction: IntechOpen Launches a Portfolio of Open Science Journals"},{slug:"let-s-meet-at-london-book-fair-5-7-april-2022-olympia-london-20220321",title:"Let’s meet at London Book Fair, 5-7 April 2022, Olympia London"},{slug:"50-books-published-as-part-of-intechopen-and-knowledge-unlatched-ku-collaboration-20220316",title:"50 Books published as part of IntechOpen and Knowledge Unlatched (KU) Collaboration"},{slug:"intechopen-joins-the-united-nations-sustainable-development-goals-publishers-compact-20221702",title:"IntechOpen joins the United Nations Sustainable Development Goals Publishers Compact"},{slug:"intechopen-signs-exclusive-representation-agreement-with-lsr-libros-servicios-y-representaciones-s-a-de-c-v-20211123",title:"IntechOpen Signs Exclusive Representation Agreement with LSR Libros Servicios y Representaciones S.A. de C.V"},{slug:"intechopen-expands-partnership-with-research4life-20211110",title:"IntechOpen Expands Partnership with Research4Life"}]},book:{item:{type:"book",id:"3339",leadTitle:null,fullTitle:"Radio Frequency Identification Fundamentals and Applications Design Methods and Solutions",title:"Radio Frequency Identification Fundamentals and Applications",subtitle:"Design Methods and Solutions",reviewType:"peer-reviewed",abstract:"This book, entitled Radio Frequency Identification Fundamentals and Applications, Bringing Research to Practice, bridges the gap between theory and practice and brings together a variety of research results and practical solutions in the field of RFID. 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I wish to extend my most sincere gratitude to InTech publishing house for continuing to publish new, interesting and valuable books for all of us.",isbn:null,printIsbn:"978-953-7619-72-5",pdfIsbn:"978-953-51-6409-8",doi:"10.5772/175",price:139,priceEur:155,priceUsd:179,slug:"radio-frequency-identification-fundamentals-and-applications-design-methods-and-solutions",numberOfPages:336,isOpenForSubmission:!1,isInWos:null,isInBkci:!1,hash:"7aca4c1d01b02aa7fb7c7db35c38e000",bookSignature:"Cristina Turcu",publishedDate:"February 1st 2010",coverURL:"https://cdn.intechopen.com/books/images_new/3339.jpg",numberOfDownloads:85804,numberOfWosCitations:48,numberOfCrossrefCitations:38,numberOfCrossrefCitationsByBook:3,numberOfDimensionsCitations:64,numberOfDimensionsCitationsByBook:3,hasAltmetrics:1,numberOfTotalCitations:150,isAvailableForWebshopOrdering:!0,dateEndFirstStepPublish:"April 24th 2012",dateEndSecondStepPublish:"May 15th 2012",dateEndThirdStepPublish:"August 19th 2012",dateEndFourthStepPublish:"November 17th 2012",dateEndFifthStepPublish:"December 17th 2012",currentStepOfPublishingProcess:5,indexedIn:"1,2,3,4,5,6,7",editedByType:"Edited by",kuFlag:!1,featuredMarkup:null,editors:[{id:"9302",title:"Dr.",name:"Cristina",middleName:null,surname:"Turcu",slug:"cristina-turcu",fullName:"Cristina Turcu",profilePictureURL:"https://mts.intechopen.com/storage/users/9302/images/system/9302.jpg",biography:"Cristina Turcu is an Associate Professor of Software Engineering and Artificial Intelligence at Stefan cel Mare University of Suceava, Romania. 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The phenotypic appearance of
The laboratory diagnosis of the Candidiasis involves the use of both Conventional (phenotypic) and molecular (genotypic) methods to detect visible and genetic characteristics of Candida respectively.
Conventional methods are still commonly used for diagnosis and identification of fungi. These techniques are based on microscopic examination and fungal culture. Oral swab is collected, followed by microscopy and culture on selective media [4]. Microscopy can be done directly either from fresh samples or from fungal cultures. However, microscopy is non-specific, as different species can show the same morphological patterns and it is not possible to identify the
Indirect nonculture-based methods are available such as
Test | Sensitivity (%) | Specificity (%) | Reference |
---|---|---|---|
Mannan and antimannan | 58 and 59 | 93 and 83 | [18] |
(1,3)-ß-D-glucan | 75–80 | 80 | [19] |
76.2 | 80.3 | [20] | |
T2Candida | 91.1 | 99.4 | [20] |
Polymerase chain reaction | 95 | 92 | [19] |
PNA-FISHa | 98–100 | 99–100 | [21] |
MALDI-TOF MSb | 91–100 | 100 | [11] |
Sensitivity and specificity of some methods used in diagnosis of invasive candidiasis as compared to conventional methods.
Peptide nucleic acid fluorescent in situ hybridization.
Matrix-assisted laser desorption/ionization time-of-flight mass spectrometry.
Enzyme-linked immunosorbent assay (ELISA) kits can be used to identify both mannan and anti-mannan antibodies however, this test is not recommended for identification of
Molecular methods are more accurate and rapid in detecting
Adopted from Chen et al., 2000, showing the non-coding internal transcribed spacer between the coding regions of 18S, 5.8S and 28S ribosomal RNA [
Molecular techniques are categorized into two methods, i.e., polymerase chain reaction-based methods and non-polymerase chain reaction (PCR) based methods.
Polymerase chain reaction (PCR) is one of the most important molecular techniques used to detect
PCR is based on the amplification of a small specific DNA target through multiple repeated cycles of temperature changes into multiple copies. The main PCR steps are denaturation of the template DNA into single strands (94–98°C), annealing of the primers to the target sequence (50–65°C), and elongation whereby DNA polymerase elongates a DNA complementary to each strand of the target (72°C) [27].
Various PCR techniques have been developed, such as real-time PCR, Restriction Fragment Length Polymorphism (RFLP) PCR technique, multiplex PCR, reverse transcriptase PCR and nested PCR [27, 28].
Real-time PCR can be used to quantify the PCR product during amplification. Moreover, it has advantages over the conventional PCR in that it does not require agarose gel electrophoresis to visualize the amplified products. In real-time PCR, the amplified product can be measured automatically after each cycle by a fluorometer [29].
Nested PCR is based on the amplification of DNA by using two sets of primers to improve its specificity and sensitivity.
Restriction Fragment Length Polymorphism (RFLP) PCR is an important technique to detect and identify strains of
Multiplex PCR requires multiple different primers and specific probes labeled with different fluorophores in a single PCR tube to allow the identification of many different
Sanger sequencing is a first-generation sequencing technique developed by Sanger Frederick and it is based on chain-termination (Sanger
Next generation sequencing (NGS) is accurate and rapid high throughput sequencing technique and is very vital in genome sequencing, fungal research, diagnostic purposes, outbreak monitoring [36]. Most of NGS platforms including the Ion Torrent PGM (Life Technologies), HiSeq, MiSeq and NextSeq (Illumina), 454 GS (Roche) and SOLiD System (Applied Biosystems) are based on sequencing by synthesis and have three main steps: template preparation, sequencing and imaging and data analysis [37, 38]. In addition to
Pyrosequencing is another PCR based technique which depends on the release of pyrophosphate when nucleotides are incorporated into the nucleic acid chain by DNA polymerase and produced pyrophosphate is then subsequently converted to Adenosine-5’triphosphate (ATP) by ATP sulfurylase, and that provides energy for luciferin oxidation by luciferase, which produces light that can be detected as a peak on the pyrogram [37]. Any unincorporated nucleotides are degraded by apyrase to allow iterative nucleotide addition into the nucleic acid chain and peak heights are associated with the number of the same nucleotides added to the nascent strand [41].
Pyrosequencing is a rapid and accurate molecular method for the detection of point mutations in any selected gene within short DNA fragments. It has been used widely for the identification and detection of antifungal drug resistance [42].
These methods can facilitate rapid identification of
MALDI-TOF MS is a method that uses mass spectrometry to identify the protein fingerprints of microorganisms that are compared with databases of reference spectra [43]. MALDI-TOF MS is able to accurately detect and identify
The ITS region of ribosomal DNA (rDNA) is the most useful genetic marker for rapid and accurate molecular identification of
Emergence of non albicans
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As a case study, this paper presents how the tools can be utilized to develop a FPGA-based controller for a laboratory scale air levitation system.",book:{id:"3620",slug:"factory-automation",title:"Factory Automation",fullTitle:"Factory Automation"},signatures:"T. Barlas and M. Moallem",authors:null}],mostDownloadedChaptersLast30Days:[{id:"63005",title:"Industry 3.0 to Industry 4.0: Exploring the Transition",slug:"industry-3-0-to-industry-4-0-exploring-the-transition",totalDownloads:1803,totalCrossrefCites:0,totalDimensionsCites:0,abstract:"This work is a How-To-Guide for DigitALIZAtion of Industry 4.0 Manufacturing. It provides a novel ALIZA Canvas and ALIZA Process supported by a comprehensive ALIZA Toolset. This output is derived from observed, tangible deficiencies in contemporary functional communications in manufacturing. This study proposes an innovative approach with robust methodologies for strategic alignment of the technical and business components in manufacturing. The requirement for a supplementary educational infrastructure, to address the pronounced educational shortcomings and knowledge gaps in the transition to Industry 4.0 is outlined. An explanation is provided of how E-Cubers (our own educational organization) will design, develop, and deliver educational programmes on Topics relevant to achieving Industry 4.0 Equipment Engineering Excellence. It defines and tests the novel concept of the E-Cubers Eight Ps; encompassing prioritized problem solving, via portfolios and projects, through peer collaboration within a defined technology playground with emphasis on learning and playing with passion. The E-Cubers Eight Ps is combined with The E-Cubers Library to deliver a truly comprehensive specialist, national learning framework. 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Transitions to alternative transportation technologies such as electric vehicles (EVs) have gained increased attention from the automotive industries. A fuel cell electric vehicle (FCEV) occupying a hydrogen engine is one of the most stupendous technologies, since it is suitable for a large-scale transportation. However, its performance limitations are in question due to voltage degradation in long term operations through steady conditions under constant load and dynamic working conditions. Other drawbacks of using fuel cells in EVs are energy balances and management issues necessary for vehicle power and energy requirements. An efficient solution to accommodate driving behavior like dynamic loads comprises of hybridizing PEMFCs with energy storage devices like supercapacitors and batteries. This opening chapter reviews the projected gist of FCEV status; considers the factors that are going to affect how FCEVs could enter commercialization, including the importance of fuel cells for EV technologies; the degradation diagnoses using accelerated stress test (AST) procedures; FCEV hybridization; and the contribution of an energy storage device for charging EVs. The article also addresses case studies relating to material degradation occurring from driving behavior. Information about material degradation can be compiled into a database for the improvement of cell component performance and durability, leading to the creation of new materials and new fuel cell hybridization designs. To support the growth of EV technologies, an energy storage is required for the integrated alternative electricity generations. 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Existing LFC system parameters are usually tuned based on experiences, classical methods, and trial and error approaches, and they are incapable of providing good dynamic performance over a wide range of operating conditions and various load scenarios. Therefore, the novel modeling and control approaches are strongly required, to obtain a new trade-off between efficiency and robustness. Thus, the proposed techniques in this chapter are referred to be an adaptive control technique based on new optimization methods such as Jaya, Practical Swarm Optimization Algorithm, etc., which are used to make an on-line tuning of the LFC parameters in order to face the previous challenges in LFC. The system under study is a small microgrid with a renewable energy source and variable demand load. 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The whole process of submitting an article and editing of the submitted article goes extremely smooth and fast, the number of reads and downloads of chapters is high, and the contributions are also frequently cited.",author:{id:"55578",name:"Antonio",surname:"Jurado-Navas",institutionString:null,profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bRisIQAS/Profile_Picture_1626166543950",slug:"antonio-jurado-navas",institution:{id:"720",name:"University of Malaga",country:{id:null,name:"Spain"}}}},{id:"6",text:"It is great to work with the IntechOpen to produce a worthwhile collection of research that also becomes a great educational resource and guide for future research endeavors.",author:{id:"259298",name:"Edward",surname:"Narayan",institutionString:null,profilePictureURL:"https://mts.intechopen.com/storage/users/259298/images/system/259298.jpeg",slug:"edward-narayan",institution:{id:"3",name:"University of Queensland",country:{id:null,name:"Australia"}}}}]},series:{item:{id:"14",title:"Artificial Intelligence",doi:"10.5772/intechopen.79920",issn:"2633-1403",scope:"Artificial Intelligence (AI) is a rapidly developing multidisciplinary research area that aims to solve increasingly complex problems. 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He is currently appointed as the Voigt Chair in Data Science in the Department of Industrial Engineering, with a joint appointment as Professor in the Computer Science Division, Stellenbosch University. Prior to his appointment at Stellenbosch University, he has been at the University of Pretoria, Department of Computer Science (1998-2018), where he was appointed as South Africa Research Chair in Artifical Intelligence (2007-2018), the head of the Department of Computer Science (2008-2017), and Director of the Institute for Big Data and Data Science (2017-2018). 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He is a full professor of signal processing and pattern recognition and is head of the Signals and Communications Department at ULPGC, teaching from 2001 on subjects on signal processing and learning theory. His research lines are biometrics, biomedical signals and images, data mining, classification system, signal and image processing, machine learning, and environmental intelligence. He has researched in 52 international and Spanish research projects, some of them as head researcher. He is co-author of 4 books, co-editor of 27 proceedings books, guest editor for 8 JCR-ISI international journals, and up to 24 book chapters. He has over 450 papers published in international journals and conferences (81 of them indexed on JCR – ISI - Web of Science). He has published seven patents in the Spanish Patent and Trademark Office. He has been a supervisor on 8 Ph.D. theses (11 more are under supervision), and 130 master theses. He is the founder of The IEEE IWOBI conference series and the president of its Steering Committee, as well as the founder of both the InnoEducaTIC and APPIS conference series. He is an evaluator of project proposals for the European Union (H2020), Medical Research Council (MRC, UK), Spanish Government (ANECA, Spain), Research National Agency (ANR, France), DAAD (Germany), Argentinian Government, and the Colombian Institutions. He has been a reviewer in different indexed international journals (<70) and conferences (<250) since 2001. He has been a member of the IASTED Technical Committee on Image Processing from 2007 and a member of the IASTED Technical Committee on Artificial Intelligence and Expert Systems from 2011. \n\nHe has held the general chair position for the following: ACM-APPIS (2020, 2021), IEEE-IWOBI (2019, 2020 and 2020), A PPIS (2018, 2019), IEEE-IWOBI (2014, 2015, 2017, 2018), InnoEducaTIC (2014, 2017), IEEE-INES (2013), NoLISP (2011), JRBP (2012), and IEEE-ICCST (2005)\n\nHe is an associate editor of the Computational Intelligence and Neuroscience Journal (Hindawi – Q2 JCR-ISI). He was vice dean from 2004 to 2010 in the Higher Technical School of Telecommunication Engineers at ULPGC and the vice dean of Graduate and Postgraduate Studies from March 2013 to November 2017. He won the “Catedra Telefonica” Awards in Modality of Knowledge Transfer, 2017, 2018, and 2019 editions, and awards in Modality of COVID Research in 2020.\n\nPublic References:\nResearcher ID http://www.researcherid.com/rid/N-5967-2014\nORCID https://orcid.org/0000-0002-4621-2768 \nScopus Author ID https://www.scopus.com/authid/detail.uri?authorId=6602376272\nScholar Google https://scholar.google.es/citations?user=G1ks9nIAAAAJ&hl=en \nResearchGate https://www.researchgate.net/profile/Carlos_Travieso",institutionString:null,institution:{name:"University of Las Palmas de Gran Canaria",institutionURL:null,country:{name:"Spain"}}},editorTwo:null,editorThree:null},{id:"23",title:"Computational Neuroscience",coverUrl:"https://cdn.intechopen.com/series_topics/covers/23.jpg",isOpenForSubmission:!0,editor:{id:"14004",title:"Dr.",name:"Magnus",middleName:null,surname:"Johnsson",slug:"magnus-johnsson",fullName:"Magnus Johnsson",profilePictureURL:"https://mts.intechopen.com/storage/users/14004/images/system/14004.png",biography:"Dr Magnus Johnsson is a cross-disciplinary scientist, lecturer, scientific editor and AI/machine learning consultant from Sweden. \n\nHe is currently at Malmö University in Sweden, but also held positions at Lund University in Sweden and at Moscow Engineering Physics Institute. \nHe holds editorial positions at several international scientific journals and has served as a scientific editor for books and special journal issues. \nHis research interests are wide and include, but are not limited to, autonomous systems, computer modeling, artificial neural networks, artificial intelligence, cognitive neuroscience, cognitive robotics, cognitive architectures, cognitive aids and the philosophy of mind. \n\nDr. Johnsson has experience from working in the industry and he has a keen interest in the application of neural networks and artificial intelligence to fields like industry, finance, and medicine. \n\nWeb page: www.magnusjohnsson.se",institutionString:null,institution:{name:"Malmö University",institutionURL:null,country:{name:"Sweden"}}},editorTwo:null,editorThree:null},{id:"24",title:"Computer Vision",coverUrl:"https://cdn.intechopen.com/series_topics/covers/24.jpg",isOpenForSubmission:!0,editor:{id:"294154",title:"Prof.",name:"George",middleName:null,surname:"Papakostas",slug:"george-papakostas",fullName:"George Papakostas",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002hYaGbQAK/Profile_Picture_1624519712088",biography:"George A. Papakostas has received a diploma in Electrical and Computer Engineering in 1999 and the M.Sc. and Ph.D. degrees in Electrical and Computer Engineering in 2002 and 2007, respectively, from the Democritus University of Thrace (DUTH), Greece. Dr. Papakostas serves as a Tenured Full Professor at the Department of Computer Science, International Hellenic University, Greece. Dr. Papakostas has 10 years of experience in large-scale systems design as a senior software engineer and technical manager, and 20 years of research experience in the field of Artificial Intelligence. Currently, he is the Head of the “Visual Computing” division of HUman-MAchines INteraction Laboratory (HUMAIN-Lab) and the Director of the MPhil program “Advanced Technologies in Informatics and Computers” hosted by the Department of Computer Science, International Hellenic University. He has (co)authored more than 150 publications in indexed journals, international conferences and book chapters, 1 book (in Greek), 3 edited books, and 5 journal special issues. His publications have more than 2100 citations with h-index 27 (GoogleScholar). His research interests include computer/machine vision, machine learning, pattern recognition, computational intelligence. \nDr. Papakostas served as a reviewer in numerous journals, as a program\ncommittee member in international conferences and he is a member of the IAENG, MIR Labs, EUCogIII, INSTICC and the Technical Chamber of Greece (TEE).",institutionString:null,institution:{name:"International Hellenic University",institutionURL:null,country:{name:"Greece"}}},editorTwo:null,editorThree:null},{id:"25",title:"Evolutionary Computation",coverUrl:"https://cdn.intechopen.com/series_topics/covers/25.jpg",isOpenForSubmission:!0,editor:{id:"136112",title:"Dr.",name:"Sebastian",middleName:null,surname:"Ventura Soto",slug:"sebastian-ventura-soto",fullName:"Sebastian Ventura Soto",profilePictureURL:"https://mts.intechopen.com/storage/users/136112/images/system/136112.png",biography:"Sebastian Ventura is a Spanish researcher, a full professor with the Department of Computer Science and Numerical Analysis, University of Córdoba. Dr Ventura also holds the positions of Affiliated Professor at Virginia Commonwealth University (Richmond, USA) and Distinguished Adjunct Professor at King Abdulaziz University (Jeddah, Saudi Arabia). Additionally, he is deputy director of the Andalusian Research Institute in Data Science and Computational Intelligence (DaSCI) and heads the Knowledge Discovery and Intelligent Systems Research Laboratory. He has published more than ten books and over 300 articles in journals and scientific conferences. Currently, his work has received over 18,000 citations according to Google Scholar, including more than 2200 citations in 2020. In the last five years, he has published more than 60 papers in international journals indexed in the JCR (around 70% of them belonging to first quartile journals) and he has edited some Springer books “Supervised Descriptive Pattern Mining” (2018), “Multiple Instance Learning - Foundations and Algorithms” (2016), and “Pattern Mining with Evolutionary Algorithms” (2016). He has also been involved in more than 20 research projects supported by the Spanish and Andalusian governments and the European Union. He currently belongs to the editorial board of PeerJ Computer Science, Information Fusion and Engineering Applications of Artificial Intelligence journals, being also associate editor of Applied Computational Intelligence and Soft Computing and IEEE Transactions on Cybernetics. Finally, he is editor-in-chief of Progress in Artificial Intelligence. He is a Senior Member of the IEEE Computer, the IEEE Computational Intelligence, and the IEEE Systems, Man, and Cybernetics Societies, and the Association of Computing Machinery (ACM). Finally, his main research interests include data science, computational intelligence, and their applications.",institutionString:null,institution:{name:"University of Córdoba",institutionURL:null,country:{name:"Spain"}}},editorTwo:null,editorThree:null},{id:"26",title:"Machine Learning and Data Mining",coverUrl:"https://cdn.intechopen.com/series_topics/covers/26.jpg",isOpenForSubmission:!0,editor:{id:"24555",title:"Dr.",name:"Marco Antonio",middleName:null,surname:"Aceves Fernandez",slug:"marco-antonio-aceves-fernandez",fullName:"Marco Antonio Aceves Fernandez",profilePictureURL:"https://mts.intechopen.com/storage/users/24555/images/system/24555.jpg",biography:"Dr. Marco Antonio Aceves Fernandez obtained his B.Sc. (Eng.) in Telematics from the Universidad de Colima, Mexico. He obtained both his M.Sc. and Ph.D. from the University of Liverpool, England, in the field of Intelligent Systems. He is a full professor at the Universidad Autonoma de Queretaro, Mexico, and a member of the National System of Researchers (SNI) since 2009. Dr. Aceves Fernandez has published more than 80 research papers as well as a number of book chapters and congress papers. He has contributed in more than 20 funded research projects, both academic and industrial, in the area of artificial intelligence, ranging from environmental, biomedical, automotive, aviation, consumer, and robotics to other applications. He is also a honorary president at the National Association of Embedded Systems (AMESE), a senior member of the IEEE, and a board member of many institutions. 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