\\n\\n
IntechOpen Book Series will also publish a program of research-driven Thematic Edited Volumes that focus on specific areas and allow for a more in-depth overview of a particular subject.
\\n\\nIntechOpen Book Series will be launching regularly to offer our authors and editors exciting opportunities to publish their research Open Access. We will begin by relaunching some of our existing Book Series in this innovative book format, and will expand in 2022 into rapidly growing research fields that are driving and advancing society.
\\n\\nLaunching 2021
\\n\\nArtificial Intelligence, ISSN 2633-1403
\\n\\nVeterinary Medicine and Science, ISSN 2632-0517
\\n\\nBiochemistry, ISSN 2632-0983
\\n\\nBiomedical Engineering, ISSN 2631-5343
\\n\\nInfectious Diseases, ISSN 2631-6188
\\n\\nPhysiology (Coming Soon)
\\n\\nDentistry (Coming Soon)
\\n\\nWe invite you to explore our IntechOpen Book Series, find the right publishing program for you and reach your desired audience in record time.
\\n\\nNote: Edited in October 2021
\\n"}]',published:!0,mainMedia:{caption:"",originalUrl:"/media/original/132"}},components:[{type:"htmlEditorComponent",content:'With the desire to make book publishing more relevant for the digital age and offer innovative Open Access publishing options, we are thrilled to announce the launch of our new publishing format: IntechOpen Book Series.
\n\nDesigned to cover fast-moving research fields in rapidly expanding areas, our Book Series feature a Topic structure allowing us to present the most relevant sub-disciplines. Book Series are headed by Series Editors, and a team of Topic Editors supported by international Editorial Board members. Topics are always open for submissions, with an Annual Volume published each calendar year.
\n\nAfter a robust peer-review process, accepted works are published quickly, thanks to Online First, ensuring research is made available to the scientific community without delay.
\n\nOur innovative Book Series format brings you:
\n\nIntechOpen Book Series will also publish a program of research-driven Thematic Edited Volumes that focus on specific areas and allow for a more in-depth overview of a particular subject.
\n\nIntechOpen Book Series will be launching regularly to offer our authors and editors exciting opportunities to publish their research Open Access. We will begin by relaunching some of our existing Book Series in this innovative book format, and will expand in 2022 into rapidly growing research fields that are driving and advancing society.
\n\nLaunching 2021
\n\nArtificial Intelligence, ISSN 2633-1403
\n\nVeterinary Medicine and Science, ISSN 2632-0517
\n\nBiochemistry, ISSN 2632-0983
\n\nBiomedical Engineering, ISSN 2631-5343
\n\nInfectious Diseases, ISSN 2631-6188
\n\nPhysiology (Coming Soon)
\n\nDentistry (Coming Soon)
\n\nWe invite you to explore our IntechOpen Book Series, find the right publishing program for you and reach your desired audience in record time.
\n\nNote: Edited in October 2021
\n'}],latestNews:[{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"},{slug:"introducing-intechopen-book-series-a-new-publishing-format-for-oa-books-20210915",title:"Introducing IntechOpen Book Series - A New Publishing Format for OA Books"}]},book:{item:{type:"book",id:"11371",leadTitle:null,fullTitle:"Cerebral Circulation - Updates on Models, Diagnostics and Treatments of Related Diseases",title:"Cerebral Circulation",subtitle:"Updates on Models, Diagnostics and Treatments of Related Diseases",reviewType:"peer-reviewed",abstract:"Diagnostics and diseases related to the cerebrovascular system are constantly evolving and updating. 3D augmented reality or quantification of cerebral perfusion are becoming important diagnostic tools in daily practice and the role of the cerebral venous system is being constantly revised considering new theories such as that of “the glymphatic system.” This book provides updates on models, diagnosis, and treatment of diseases of the cerebrovascular system.",isbn:"978-1-80355-361-0",printIsbn:"978-1-80355-360-3",pdfIsbn:"978-1-80355-362-7",doi:"10.5772/intechopen.98169",price:119,priceEur:129,priceUsd:155,slug:"cerebral-circulation-updates-on-models-diagnostics-and-treatments-of-related-diseases",numberOfPages:120,isOpenForSubmission:!1,isInWos:null,isInBkci:!1,hash:"e2d3335445d2852d0b906bb9750e939f",bookSignature:"Alba Scerrati, Luca Ricciardi and Flavia Dones",publishedDate:"June 23rd 2022",coverURL:"https://cdn.intechopen.com/books/images_new/11371.jpg",numberOfDownloads:345,numberOfWosCitations:0,numberOfCrossrefCitations:1,numberOfCrossrefCitationsByBook:0,numberOfDimensionsCitations:1,numberOfDimensionsCitationsByBook:0,hasAltmetrics:0,numberOfTotalCitations:2,isAvailableForWebshopOrdering:!0,dateEndFirstStepPublish:"September 3rd 2021",dateEndSecondStepPublish:"October 1st 2021",dateEndThirdStepPublish:"November 30th 2021",dateEndFourthStepPublish:"February 18th 2022",dateEndFifthStepPublish:"April 19th 2022",currentStepOfPublishingProcess:5,indexedIn:"1,2,3,4,5,6",editedByType:"Edited by",kuFlag:!1,featuredMarkup:null,editors:[{id:"182614",title:"Dr.",name:"Alba",middleName:null,surname:"Scerrati",slug:"alba-scerrati",fullName:"Alba Scerrati",profilePictureURL:"https://mts.intechopen.com/storage/users/182614/images/system/182614.jpeg",biography:"Dr. Alba Scerrati is an Assistant Professor of Neurosurgery, at the University of Ferrara, Italy, and a neurosurgeon at the University Hospital of Ferrara. She graduated from medical school in 2010 and completed her residency in neurosurgery at the Catholic University of Rome, Policlinico Gemelli. Her main scientific interests are skull base surgery and neurovascular surgery. She is working on the development of 3D printing techniques for neurovascular surgery training and simulation. She has participated in different clinical studies on cerebrovascular diseases and CSF dynamics. Dr. Scerrati is the author and co-author of more than eighty indexed publications.",institutionString:"University of Ferrara",position:null,outsideEditionCount:0,totalCites:0,totalAuthoredChapters:"3",totalChapterViews:"0",totalEditedBooks:"2",institution:{name:"University of Ferrara",institutionURL:null,country:{name:"Italy"}}}],equalEditorOne:null,equalEditorTwo:null,equalEditorThree:null,coeditorOne:{id:"421212",title:"Dr.",name:"Luca",middleName:null,surname:"Ricciardi",slug:"luca-ricciardi",fullName:"Luca Ricciardi",profilePictureURL:"https://mts.intechopen.com/storage/users/421212/images/system/421212.jpg",biography:"Dr. Ricciardi graduated with degrees in Medicine and Surgery in 2013 and completed his residency in neurosurgery in 2019. In 2017, he completed a fellowship in spinal deformities at the Catholic University of Rome, Italy, and in 2018 he completed a research fellowship at the Mayo Clinic, Jacksonville, Florida, USA. He also completed a four-year training course from the European Association of Neurosurgical Societies and is a fellow of the European. Board of Neurological Surgery (FEBNS). Dr. Ricciardi has authored more than sixty papers published in peer-reviewed international journals. He is a reviewer for more than fifteen scientific journals and has conducted more than eighty certified peer reviews to date. In 2021, Dr. Ricciardi was a guest editor for the Journal of Neurosurgical Sciences and an invited editor for Frontiers in Neurooncology, Life, and Cell. In 2021, Dr. Ricciardi was nominated as co-chairman and president of the Scientific Committee at SPINE20, the World Congress on Spine Disorders at the G20 conference in Rome, Italy.",institutionString:"Sapienza University of Rome",position:null,outsideEditionCount:0,totalCites:0,totalAuthoredChapters:"0",totalChapterViews:"0",totalEditedBooks:"0",institution:{name:"Sapienza University of Rome",institutionURL:null,country:{name:"Italy"}}},coeditorTwo:{id:"421215",title:"Dr.",name:"Flavia",middleName:null,surname:"Dones",slug:"flavia-dones",fullName:"Flavia Dones",profilePictureURL:"https://mts.intechopen.com/storage/users/421215/images/system/421215.png",biography:'Dr. Flavia Dones graduated from medical school in 2011 and completed her neurosurgical residency in 2017 at the University of Naples \\"Federico II,\\" Italy. She was previously a neurosurgeon at Niguarda Metropolitan Hospital, Milan, Italy, and in 2019 she moved to Sant\\\'Anna Hospital, Ferrara, Italy, where she is currently working. Dr. Dones’ main interests are neurovascular and neuro-oncology surgery. She is the author and co-author of more than twenty indexed publications.',institutionString:"Arcispedale Sant'Anna",position:null,outsideEditionCount:0,totalCites:0,totalAuthoredChapters:"0",totalChapterViews:"0",totalEditedBooks:"0",institution:{name:"Arcispedale Sant'Anna",institutionURL:null,country:{name:"Italy"}}},coeditorThree:null,coeditorFour:null,coeditorFive:null,topics:[{id:"1056",title:"Neurology",slug:"neurology"}],chapters:[{id:"81841",title:"Introductory Chapter: New Models of Cerebral Circulation",doi:"10.5772/intechopen.104963",slug:"introductory-chapter-new-models-of-cerebral-circulation",totalDownloads:1,totalCrossrefCites:0,totalDimensionsCites:0,hasAltmetrics:0,abstract:null,signatures:"Alba Scerrati",downloadPdfUrl:"/chapter/pdf-download/81841",previewPdfUrl:"/chapter/pdf-preview/81841",authors:[{id:"182614",title:"Dr.",name:"Alba",surname:"Scerrati",slug:"alba-scerrati",fullName:"Alba Scerrati"}],corrections:null},{id:"80306",title:"Cerebral Arterial Circulation: 3D Augmented Reality Models and 3D Printed Puzzle Models",doi:"10.5772/intechopen.102510",slug:"cerebral-arterial-circulation-3d-augmented-reality-models-and-3d-printed-puzzle-models",totalDownloads:86,totalCrossrefCites:0,totalDimensionsCites:0,hasAltmetrics:0,abstract:"The field of augmented reality (AR) and three-dimensional (3D) printing are rapidly growing with many new potential applications in medical education and pedagogy. In this chapter, we have used 3D AR and 3D printed models of the cerebral arterial circulatory system, created by us to simplify concept learning. Various cerebral circulation diseases pertaining to ophthalmology can be explained in detail for immersive learning, with the help of various 3D models, for structures such as the circle of Willis, cavernous sinus, various cranial nerves, cerebrum, cerebellum and the eye. These models not only help in cognitive understanding of cerebral circulation diseases but also aid in diagnosing them with better conviction. Ophthalmologists, sometimes being the first responder, have a vigilant role to play with a heightened awareness of these cerebral arterial circulation diseases, which are not only vision-threatening but life-threatening too. This chapter summarizes the construction and holistic application of these 3D ophthalmology-related arterial cerebral circulation models in AR and 3D printing.",signatures:"Prasanna Venkatesh Ramesh, Prajnya Ray, Shruthy Vaishali Ramesh, Aji Kunnath Devadas, Tensingh Joshua, Anugraha Balamurugan, Meena Kumari Ramesh and Ramesh Rajasekaran",downloadPdfUrl:"/chapter/pdf-download/80306",previewPdfUrl:"/chapter/pdf-preview/80306",authors:[{id:"415606",title:"Dr.",name:"Prasanna Venkatesh",surname:"Ramesh",slug:"prasanna-venkatesh-ramesh",fullName:"Prasanna Venkatesh Ramesh"},{id:"428816",title:"Dr.",name:"Shruthy Vaishali",surname:"Ramesh",slug:"shruthy-vaishali-ramesh",fullName:"Shruthy Vaishali Ramesh"},{id:"428817",title:"Ms.",name:"Prajnya",surname:"Ray",slug:"prajnya-ray",fullName:"Prajnya Ray"},{id:"428818",title:"Mr.",name:"Aji",surname:"K",slug:"aji-k",fullName:"Aji K"},{id:"428819",title:"Mr.",name:"Tensingh",surname:"Joshua",slug:"tensingh-joshua",fullName:"Tensingh Joshua"},{id:"428820",title:"Dr.",name:"Anugraha",surname:"Balamurugan",slug:"anugraha-balamurugan",fullName:"Anugraha Balamurugan"},{id:"428821",title:"Dr.",name:"Meena Kumari",surname:"Ramesh",slug:"meena-kumari-ramesh",fullName:"Meena Kumari Ramesh"},{id:"428822",title:"Dr.",name:"Ramesh",surname:"Rajasekaran",slug:"ramesh-rajasekaran",fullName:"Ramesh Rajasekaran"}],corrections:null},{id:"80939",title:"Diagnosis and Treatment of Ophthalmology Related Cerebral Arterial Circulation Diseases: A 3D Animated Encyclopedia",doi:"10.5772/intechopen.102846",slug:"diagnosis-and-treatment-of-ophthalmology-related-cerebral-arterial-circulation-diseases-a-3d-animate",totalDownloads:31,totalCrossrefCites:0,totalDimensionsCites:0,hasAltmetrics:0,abstract:"Cerebral circulation is the flow of blood through a group of arteries and veins which supply the brain. There are various diseases related to ophthalmology, due to pathologies in the cerebral arterial system. Arteries inside the skull can be blocked by plaque or disease, which in turn triggers a series of events leading to various cranial nerve palsies, visual fields defects, retinal diseases, etc. The highlights of this chapter are the novel three-dimensional (3D) animative videos created by us, to simplify various cerebral arterial circulation diseases and their diagnostic concepts for neophytes. 3D animative videos can aid learning and help in the cognitive concept building of these complex pathologies.",signatures:"Prasanna Venkatesh Ramesh, Shruthy Vaishali Ramesh, Prajnya Ray, Aji Kunnath Devadas, Tensingh Joshua, Anugraha Balamurugan, Meena Kumari Ramesh and Ramesh Rajasekaran",downloadPdfUrl:"/chapter/pdf-download/80939",previewPdfUrl:"/chapter/pdf-preview/80939",authors:[{id:"415606",title:"Dr.",name:"Prasanna Venkatesh",surname:"Ramesh",slug:"prasanna-venkatesh-ramesh",fullName:"Prasanna Venkatesh Ramesh"},{id:"428816",title:"Dr.",name:"Shruthy Vaishali",surname:"Ramesh",slug:"shruthy-vaishali-ramesh",fullName:"Shruthy Vaishali Ramesh"},{id:"428817",title:"Ms.",name:"Prajnya",surname:"Ray",slug:"prajnya-ray",fullName:"Prajnya Ray"},{id:"428818",title:"Mr.",name:"Aji",surname:"K",slug:"aji-k",fullName:"Aji K"},{id:"428819",title:"Mr.",name:"Tensingh",surname:"Joshua",slug:"tensingh-joshua",fullName:"Tensingh Joshua"},{id:"428820",title:"Dr.",name:"Anugraha",surname:"Balamurugan",slug:"anugraha-balamurugan",fullName:"Anugraha Balamurugan"},{id:"428821",title:"Dr.",name:"Meena Kumari",surname:"Ramesh",slug:"meena-kumari-ramesh",fullName:"Meena Kumari Ramesh"},{id:"428822",title:"Dr.",name:"Ramesh",surname:"Rajasekaran",slug:"ramesh-rajasekaran",fullName:"Ramesh Rajasekaran"}],corrections:null},{id:"80543",title:"Measurement of Cerebral Circulation in Human",doi:"10.5772/intechopen.102383",slug:"measurement-of-cerebral-circulation-in-human",totalDownloads:64,totalCrossrefCites:1,totalDimensionsCites:1,hasAltmetrics:0,abstract:"In this chapter, we review state-of-the-art non-invasive techniques to monitor and study cerebral circulation in humans. The measurement methods can be divided into two categories: direct and indirect methods. Direct methods are mostly based on using contrast agents delivered to blood circulation. Clinically used direct methods include single-photon emission computed tomography (SPECT), positron emission tomography (PET), magnetic resonance imaging (MRI) with contrast agents, xenon computed tomography (CT), and arterial spin labeling (ASL) MRI. Indirect techniques are based on measuring physiological parameters reflecting cerebral perfusion. The most commonly used indirect methods are near-infrared spectroscopy (NIRS), transcranial Doppler ultrasound (TCD), and phase-contrast MRI. In recent years, few more techniques have been intensively developed, such as diffuse correlation spectroscopy (DCS) and microwave-based techniques, which are still emerging as methods for cerebral circulation monitoring. In addition, methods combining different modalities are discussed and, as a summary, the presented techniques and their benefits for cerebral circulation will be compared.",signatures:"Sadegh Moradi, Hany Ferdinando, Aleksandra Zienkiewicz, Mariella Särestöniemi and Teemu Myllylä",downloadPdfUrl:"/chapter/pdf-download/80543",previewPdfUrl:"/chapter/pdf-preview/80543",authors:[{id:"439902",title:"Associate Prof.",name:"Teemu",surname:"Myllylä",slug:"teemu-myllyla",fullName:"Teemu Myllylä"},{id:"450252",title:"MSc.",name:"Sadegh",surname:"Moradi",slug:"sadegh-moradi",fullName:"Sadegh Moradi"},{id:"450307",title:"Dr.",name:"Hany",surname:"Ferdinando",slug:"hany-ferdinando",fullName:"Hany Ferdinando"},{id:"450308",title:"MSc.",name:"Aleksandra",surname:"Zienkiewicz",slug:"aleksandra-zienkiewicz",fullName:"Aleksandra Zienkiewicz"},{id:"450309",title:"Dr.",name:"Mariella",surname:"Särestöniemi",slug:"mariella-sarestoniemi",fullName:"Mariella Särestöniemi"}],corrections:null},{id:"80949",title:"The Cerebral Venous System: New Pathophysiological Theories and Diseases Related to Veins Occlusion",doi:"10.5772/intechopen.102351",slug:"the-cerebral-venous-system-new-pathophysiological-theories-and-diseases-related-to-veins-occlusion",totalDownloads:47,totalCrossrefCites:0,totalDimensionsCites:0,hasAltmetrics:1,abstract:"Cerebral physiology and pathology are still frequently missing a comprehensive explanation and a complete description, but new data and hypothesis are emerging on a daily basis. Particularly, comprehension of the cerebral venous system’s functions and functioning has undergone through the last decades a deep and extended change. Depiction of the perivascular spaces and the mechanisms of glymphatic system has given light about venous system pivotal role in the genesis of different pathologies such as multiple sclerosis, hydrocephalus, cerebral hemorrhages, and strokes. After a key point discussion about embryology, physiology, and anatomy of the cerebral venous system, an overview is provided on the main pathologies, both well-known and newly described ones, in which cerebral veins act a major pathogenic role.",signatures:"Giorgio Mantovani and Alba Scerrati",downloadPdfUrl:"/chapter/pdf-download/80949",previewPdfUrl:"/chapter/pdf-preview/80949",authors:[{id:"182614",title:"Dr.",name:"Alba",surname:"Scerrati",slug:"alba-scerrati",fullName:"Alba Scerrati"},{id:"479187",title:"Dr.",name:"Giorgio",surname:"Mantovani",slug:"giorgio-mantovani",fullName:"Giorgio Mantovani"}],corrections:null},{id:"80456",title:"Cerebrospinal Venous Obstruction: Anatomy, Clinical Presentation, Diagnosis, and Treatment of Chronic Infective Cerebrospinal Venulitis",doi:"10.5772/intechopen.102685",slug:"cerebrospinal-venous-obstruction-anatomy-clinical-presentation-diagnosis-and-treatment-of-chronic-in",totalDownloads:116,totalCrossrefCites:0,totalDimensionsCites:0,hasAltmetrics:1,abstract:"This review chapter describes the normal anatomy and function of the cerebrospinal venous system, ultrasound diagnosis of obstructions in the system, and the clinical implications and treatment of chronic cerebrospinal venous obstruction (CCSVO) associated with chronic persistent Chlamydophila pneumoniae (Cpn) infection. The normal patterns of flow in the cerebrospinal venous system are described and guidelines for the interpretation of the extracranial duplex ultrasound (ECDU) examination of the neck veins are presented. An infective cause of CCSVO is proposed and relevant pathology tests necessary for a diagnosis of chronic persistent Cpn venulitis are discussed. A treatment protocol for Cpn chronic venulitis is described and recommended. The progress of the patient with CCSVO can then be followed and monitored by using the ECDU and relevant pathology tests after 3 and 6 months. CCSVO is a relatively common condition encountered in chronic diseases of unknown etiology and is often neglected by medical practitioners when managing patients with symptoms of brain fog, chronic headaches, and fatigue. Objective diagnostic and treatment protocols are required to make further progress with these conditions.",signatures:"Paul K. 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The Roll of the Entrepreneur in the Establishment of Economic Equilibria",doi:null,correctionPDFUrl:"https://cdn.intechopen.com/pdfs/65667.pdf",downloadPdfUrl:"/chapter/pdf-download/65667",previewPdfUrl:"/chapter/pdf-preview/65667",totalDownloads:null,totalCrossrefCites:null,bibtexUrl:"/chapter/bibtex/65667",risUrl:"/chapter/ris/65667",chapter:{id:"57461",slug:"the-roll-of-the-entrepreneur-in-the-establishment-of-economic-equilibria",signatures:"Er’el Granot",dateSubmitted:"April 7th 2017",dateReviewed:"August 22nd 2017",datePrePublished:"December 20th 2017",datePublished:"January 24th 2018",book:{id:"6165",title:"Entrepreneurship",subtitle:"Development Tendencies and Empirical Approach",fullTitle:"Entrepreneurship - Development Tendencies and Empirical Approach",slug:"entrepreneurship-development-tendencies-and-empirical-approach",publishedDate:"January 24th 2018",bookSignature:"Ladislav Mura",coverURL:"https://cdn.intechopen.com/books/images_new/6165.jpg",licenceType:"CC BY 3.0",editedByType:"Edited by",editors:[{id:"85474",title:"Associate Prof.",name:"Ladislav",middleName:null,surname:"Mura",slug:"ladislav-mura",fullName:"Ladislav Mura"}],productType:{id:"1",title:"Edited Volume",chapterContentType:"chapter",authoredCaption:"Edited by"}},authors:[{id:"181601",title:"Prof.",name:"Er'El",middleName:null,surname:"Granot",fullName:"Er'El Granot",slug:"er'el-granot",email:"erelgranot@gmail.com",position:null,institution:{name:"Ariel University",institutionURL:null,country:{name:"Israel"}}}]}},chapter:{id:"57461",slug:"the-roll-of-the-entrepreneur-in-the-establishment-of-economic-equilibria",signatures:"Er’el Granot",dateSubmitted:"April 7th 2017",dateReviewed:"August 22nd 2017",datePrePublished:"December 20th 2017",datePublished:"January 24th 2018",book:{id:"6165",title:"Entrepreneurship",subtitle:"Development Tendencies and Empirical Approach",fullTitle:"Entrepreneurship - Development Tendencies and Empirical Approach",slug:"entrepreneurship-development-tendencies-and-empirical-approach",publishedDate:"January 24th 2018",bookSignature:"Ladislav Mura",coverURL:"https://cdn.intechopen.com/books/images_new/6165.jpg",licenceType:"CC BY 3.0",editedByType:"Edited by",editors:[{id:"85474",title:"Associate Prof.",name:"Ladislav",middleName:null,surname:"Mura",slug:"ladislav-mura",fullName:"Ladislav Mura"}],productType:{id:"1",title:"Edited Volume",chapterContentType:"chapter",authoredCaption:"Edited by"}},authors:[{id:"181601",title:"Prof.",name:"Er'El",middleName:null,surname:"Granot",fullName:"Er'El Granot",slug:"er'el-granot",email:"erelgranot@gmail.com",position:null,institution:{name:"Ariel University",institutionURL:null,country:{name:"Israel"}}}]},book:{id:"6165",title:"Entrepreneurship",subtitle:"Development Tendencies and Empirical Approach",fullTitle:"Entrepreneurship - Development Tendencies and Empirical Approach",slug:"entrepreneurship-development-tendencies-and-empirical-approach",publishedDate:"January 24th 2018",bookSignature:"Ladislav Mura",coverURL:"https://cdn.intechopen.com/books/images_new/6165.jpg",licenceType:"CC BY 3.0",editedByType:"Edited by",editors:[{id:"85474",title:"Associate Prof.",name:"Ladislav",middleName:null,surname:"Mura",slug:"ladislav-mura",fullName:"Ladislav Mura"}],productType:{id:"1",title:"Edited Volume",chapterContentType:"chapter",authoredCaption:"Edited by"}}},ofsBook:{item:{type:"book",id:"11579",leadTitle:null,title:"Animal Welfare - New Insights",subtitle:null,reviewType:"peer-reviewed",abstract:"\r\n\tAt present, especially in the last years, the achievements made by scientists have been exceptional, leading to major advancements in the fast-growing field of animal science. Therefore, experimental animals play a very important role in scientific research.
\r\n\r\n\tPigs, rodents, and aquaculture animals are important experimental animals. To obtain the accuracy of the experimental data and meet the basic quality requirements of biological experiment materials, the quality of the experimental animals for the biological experiments should reach the level of specific pathogen-free (SPF). These SPF animals are applied not only to meet the demand for biomedical research but can also be used for the research and the development of drugs and vaccines. Furthermore, as animal welfare has gradually attracted attention in recent years, the reduction of animal pain and quantity and the increase of the experimental refinement are important issues in the 3R (replacement, reduction, and refinement) of animal welfare.
\r\n\r\n\tAnimal testing is an important verification stage before the listing of biomedical products. This book will focus on new insights, novel developments, current challenges, latest discoveries, recent advances, and future perspectives in the field of animal welfare.
",isbn:"978-1-83768-202-7",printIsbn:"978-1-83769-983-4",pdfIsbn:"978-1-83768-203-4",doi:null,price:0,priceEur:0,priceUsd:0,slug:null,numberOfPages:0,isOpenForSubmission:!0,isSalesforceBook:!1,isNomenclature:!1,hash:"12e4f41264cbe99028655e5463fa941a",bookSignature:"Dr. Shao-Wen Hung, Dr. Chia-Chi Chen, Dr. Chung-Lun Lu and Dr. Tseng-Ting Kao",publishedDate:null,coverURL:"https://cdn.intechopen.com/books/images_new/11579.jpg",keywords:"Animal Welfare, New Insights, Experiment, Rodents, Larger Animals, Aquaculture Animals, Replacement, Reduction, Refinement, Alternative Methods, Animal Studies, Biological Experiments",numberOfDownloads:null,numberOfWosCitations:0,numberOfCrossrefCitations:null,numberOfDimensionsCitations:null,numberOfTotalCitations:null,isAvailableForWebshopOrdering:!0,dateEndFirstStepPublish:"May 4th 2022",dateEndSecondStepPublish:"July 8th 2022",dateEndThirdStepPublish:"September 6th 2022",dateEndFourthStepPublish:"November 25th 2022",dateEndFifthStepPublish:"January 24th 2023",dateConfirmationOfParticipation:null,remainingDaysToSecondStep:"7 days",secondStepPassed:!1,areRegistrationsClosed:!1,currentStepOfPublishingProcess:2,editedByType:null,kuFlag:!1,biosketch:"Dr. Hung is a pioneering researcher in animal and cell sciences. He focuses his research interests on Experimental Animals, Animal Welfare, and Epilepsy. He has authored 112 journal papers, and 12 book chapters, edited 7 books and authored 160 other publications including conference proceedings and abstracts. He is also the holder of 12 registered patents and is a member of the Chinese Society of Veterinary Sciences.",coeditorOneBiosketch:"Associate Researcher Chia-Chi Chen works in the Animal Technology Research Center, Agricultural Technology Research Institute. She is a pioneering researcher in animal science and has published many articles and books related to life science.",coeditorTwoBiosketch:"Dr. Chung-Lun Lu is a researcher at Aquaculture Technology Research Center, Agricultural Technology Research Institute. Dr. Chung-Lun Lu is a pioneering researcher in aquaculture sciences. 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Cases no regulation or homeostasis disorders, thrombosis (intravascular coagulation) or bleeding occur. In normal conditions, the secretion of vascular endothelial heparin-like and trmbomodulin molecules prevent blood coagulation and secretion of nitric oxide and prostacyclin prevent platelet aggregation and blood brings the liquid keeps. Homeostasis has three stages: vasoconstriction, platelet plug formation and blood coagulation, blood coagulation are reactions in which plasma zymogens become active enzymes that create the clotting reaction. Coagulation reactions will be set with inhibitory and stimulatory mechanisms. Coagulation is a regulatory process that keeps the blood flowing. Blood coagulation has two external and internal pathways (Figure 1), tissue factor and FVII form the external pathway, internal pathway is formed of FVIII, FIX and FXI (Ramanarayana et al., 2011; Ellison, 1977).
\n\t\tHemophilia had recognized in the fifth century BC, first the Jews law passed that when a woman has two dead boys doing the circumcision her third son should not be circumcised, they showed the mother will transmit the disease to her sons (History of hemophilia, 2011). Genetic and hereditary pattern of hemophilia was carefully described in 1803 by the American physician John Conrad Otto. He supposed that the bleeding was occurring due to lack of blood anti hemophilic factor (Cahill & Colvin, 1997). Glossary of hemophilia was developed for this disease in 1828 at the University of Zurich. Anti-hemophilia globin was discovered in 1937 by Patek and Tylor at Harvard University (History of Hemophilia Disease, 2011). The two forms of hemophilia A and B were distinguished in 1952 by Pavlosky, the Brazilian physician. Both diseases are sex-dependent and occur in males (Cahill & Colvin, 1977).
\n\t\tHemophilia is a genetic disorder happens in coagulation FVIII (hemophilia A) or FIX (hemophilia B) and are related to the X chromosome. Hemophilia A is a disease due to genetic defects in coagulation FVIII (Furie et al., 1994; White & Shoemaker, 1989) It is identified by Hoyer and Breckenridge (Hoyer & Breckenridge, 1968) and then by Denson for the first time (Denson et al., 1969). They showed that there was not FVIIIa in the plasma of the most people with hemophilia. Hemophilia B caused by genetic defects occur in the coagulation FIX; the FIX deficiency will inhibit the activation of FX by FVIIa through external coagulation pathway (Furie et al., 1994; Thompson, 1986). About half The patients who suffer from severe hemophilia A there is a large inversion in intron 22 of their FVIII mRNA (Figure 2) which it is repeated (Arruda et al., 1995; Deutz-Terlouw et al., 1995; Okamoto et al., 1995; Pieneman et al., 1995; Van de Water et al., 1995; Goodeve et al., Jenkins et al., 1994; 1994; Naylor et al., 1993; Naylor et al., 1992). Different alleles of the VNTR (di nucleotides) have observed in intron 13 of FVIII in people with hemophilia A (Kochhan et al., 1994).
\n\t\t\tExternal and internal pathways of blood coagulation process. (Reference
Hemophilia A is occurring one for 5000-10000 birthday boys and hemophilia B one for 20,000 to 34,000 birthday boys (Dimitrios et al., 2009). The bleeding in joints of hemophilia patients the wound bleeding is longer continued (Petkova et al., 2004). The position of FVIII gene is Xq28 and of FIX is Xq27.1 location on distal long arm of chromosome X (Figure 3). The FVIII gene has 186 kb organized in 26 exons (about 9 kb) (Figure 4). There are detected some gene mutations on FVIII as insertion, deletions or point mutations which involved in the reduced or cut up in FVIII activation (Ramanarayana et al., 2011; Salviato et al., 2002; Cahill & Colvin, 1997; Arruda et al., 1995; Naylor et al., 1991; Higuchi et al., 1989; Youssoufian et al., 1987; Gitschier et al., 1985;). The FVIII organized in A, B and C domains (Figure 5), which B domain is highly glycosylated and do not involve in FVIII activities (Eaton et al., 1986).
\n\t\t\tGenetic mutation in intron 22 of FVIII (
The Map of FVIII on the long arm of chromosome X (
Genetic map of FVIII (
The domains organization of FVIII (
Laboratory diagnosis of hemophilia is done based on activated partial thromboplastin time (aPTT), prothrombin time (PT), platelet count and bleeding time. There is an abnormally in the initial section of internal coagulation pathway at the prolonged aPTT and normal PT. The normal aPTT should not be reject the FVIII deficiencies (hemophilia A), the aPTT is not enough sensitive too reduced amount of FVIII C. Prolonged PT alone, or PT and aPTT do not specify of hemophilia A, the liver diseases, overdose of warfarin or heparin and the distribution intravascular coagulation (DIC) can cause this coagulophaty. Thrombocytopenia alone cannot cause of hemophilia A. The nature and severity of bleeding is performed with cell blood counts (CBC) and differentiation also check for blood in the stool and urine (Schwartz et al., 2011). Knights and Ingram in 1967 were used thromboplastin time assay for hemophilia A and B differentiation. Based on their test when alumina is added to normal plasma do not see the harm of FVIII, but FIX is deleted, remove the alumina from plasma FIX will re- back up. If thromboplastin time is increased in males with a history of prolonged bleeding, test is repeated after adding or removing alumina from the plasma. If thromboplastin time is shorter than the control, the patient is suffering from hemophilia A, but if thromboplastin time is shortened after the removal of the alumina, patient is suffering from hemophilia B (Knights & Ingram, 1967). Stites et al (1971) and Essien and Ingram (1967) were distinguished hemophilia A and B by FVIII inhibitory antibodies.
\n\t\t\tThe test results in children and adults are different. Clotting Index and coagulability in hemophilia patients significantly lower than non-hemophilia one. In this test, coagulability of FVIII treated blood varies by the replaced FVIII type. rFVIII clotting index is lower than of derived plasma one (Goldenberg et al., 2006). Firshein and colleagues were diagnosed prenatal hemophilia A using radioimmunometric by fetal plasma and fetoscope by amniotic fluid at second trimester in pregnancy women (Firshein et al., 1979), other researchers were developed radoimmunometric method for measurements of FVIII antibody (Hoyer et al., 1985; Hellings et al., 1982; Ljung R, Holmberg, 1982). Antonarakis et al were analyzed FVIII gene for possibility detection of prenatal and hemophilia carrier through gene cloning method (Antonarakis et al., 1985), the problems and limitations of these methods were evaluated by other researchers (Graham et al., 1985). The PCR RFLP method was used for prenatal diagnosis and hemophilia A carrier for the first time in 1990s (Rudzki et al., 1996; Herrmann et al., 1988; Kogan et al., 1987;). Missense and nonsense point mutations in FVIII gene of hemophilia A patient, prenatal and carrier hemophilia A were detected using DGGE method (Gitschier, 1989). Ball and colleagues were used oral cells, urine and hair follicles samples to identify prenatal and carrier hemophilia A (Ball et al., 1990). Various polymorphism and mutations have been detected in FVIII gene of hemophilia A patients (Wacey et al., 1996’ Antonarakis et al, 1995; Naylor et al., 1991; Baranov et al., 1990; Gécz et al., 1990; Jedlicka et al., 1990; Sadler et al., 1990; Surin et al., 1990; Wehnert et al., 1990a; Wehnert et al., 1990b). Establishment the PCR technique in diagnostic laboratories was a large change in DNA analysis of FVIII gene for detecting carriers and individuals with hemophilia A (Song et al., 1993; Feng, 1991; Wadelius et al., 1991; Wu, 1991). Detection of unknown mutations is performed by universal mutation detection system methods such as SSCP (Arruda et al., 1995; Pieneman et al., 1995; David et al., 1994). Hemophilia diagnosis with PGD method was used by Michaelides (2006) and colleagues For the first time in 2006; they were diagnosed two point mutations in FVIII gene of donor (IVF) blastomere. Acquired hemophilia due to FVIII autoantibody is a rare disease and occurs one in a million, yearly; its mortality is 20 percent (Shetty et al., 2010).
\n\t\t\tHemophilia treatment doing by replacing the natural (Brackmann & Gormsen, 1977) or recombinant FVIII (Kaufman, 1991) via intravenous injection. The half life of transfused FVIII in normal individuals or patients with hemophilia is 8 to 12 hours (White & Shoemaker, 1989). Using recombinant serum proteins in the treatment of hemophilia began in 1990 (Liras, 2008), but Homate P / humate-P is a derived pasteurized human plasma which was approved in Germany in 1981 and used administered intravenous injection for 25 years to control bleeding in patients with hemophilia A and von Willebrand disease (Berntorp, 2009; Carter & Scott, 2007; Czapek et al, 1988). The main presentation following hemophilia treatment is creating inhibitory antibodies against the FVIII which observed 5% in patients with hemophilia B and 40 -20 percent in patients with severe hemophilia A (Hong & Stachnik, 2010; Kempton et al., 2010; Eckhardt et al., 2009; Ghosh & Shetty, 2009; von Auer et al., 2005; Sharathkumar wt al., 2003; Scharrer, 1999; de Biasi et al., 1994). Complication inhibitory antibodies seem to produce with plasma-derived FVII severe than with recombinant one (Lusher, 2002; Lusher, 2000), also with FVIII (Qadura et al., 2009; Delignat et al., 2007; Goudemand et al., 2006; Yoshioka et al., 2003; Fijnvandraat et al, 1997). The B cell epitopes mutated, produced FVIII inhibitory antibody is reduced, and some one proposed that this phenomenon is safe vaccine for people with hemophilia (Parker et al, 2004). Antibody production against FVIII has been studied in hemophilia patients and indicates that most nonsense mutations and large deletions in FVIII gene and chromosomal recombination lead to produce FVIII inhibitory antibody (Schwaab et al., 1995). Treatment of hemophilia by FVIII overdose administration is effective for producer antibodies hemophilia patients (Scandella et al., 2000).
\n\t\t\t\tThe OBI (BDD- rpFVIII) was introduced by Ipsen and Inspiration Biopharmaceuticals Inc Company and passed clinical trial phases 1 and 2. It shows porcine FVIII biochemical properties and procoagulant activity and less immunogenicity than plasma derived pFVIII (Toschi, 2010).
\n\t\t\t\tIn 1960 Los Angeles Red Cross Blood Center was treated hemophilia patients using anti hemophilic globin (Rapaport et al., 1960). 1-Deamino-8-d-arginine vasopressin (DDAVP) (a FVII autologous) have been used instead of plasma derived factors for treatment of hemophilia A and B (Mannucci et al., 1977). Hultin and colleagues were used cyclophosphamide as immunosuppression drug for antibody producer hemophilia patients (Hultin et al., 1976). Lian et al. were treated hemophilia using cyclophosphamide, vincristine and prednisone (CVP) (Lian et al., 1989). Blatt et al were removed FVIII inhibitory antibody with prothrombin complex concentrates (PCC) (Blatt et al., 1977). Paleyanda and colleagues were transferred FVIII cDNA into pig lactate system; the pig was produced FVIII more than 10 times as normal plasma (Paleyanda et al., 1997). Specific thrombin anticoagulant Bivalirudin (Krolick, 2005) and monoclonal antibody Retoximab (Franchini, 2007; Wiestner et al., 2002) are also used for hemophilia treatment and patients with FVIII autoantibody, respectively. Idiotype vaccines will neutralize anti human FVIII antibody in hemophilia A patients (Lacroix-Desmazes et al., 2002).
\n\t\t\t\tProduction and characterization of recombinant FVIII for the treatment of hemophilia was conducted in 1984 for the first time (Toole et al., 1984; Wood et al., 1984). Use of recombinant proteins to replace clotting factors and treatment of hemophilia opened a new arena in treatment of disease. Circulating blood factors are the first generation recombinant proteins and second generation drugs made by recombinant DNA and protein engineering technology cause changes in proteins for specific applications, like FVIIa (Levy & Levi, 2009; Pipe, 2008). FVII alone or in combination with its analogues have been used to reduce bleeding (Lauritzen el al., 2008a; Lauritzen et al., 2008b; Allen et al., 2007). Use of recombinant FVIIa for hemophilia patients with FVIII antibody (Obergfell et al., 2010; Margaritis, 2010; Margaritis et al., 2010), also people who have bleeding into the joint or prevent bleeding in surgery is economically efficient (Stephens et al., 2007).
\n\t\t\tFor the first time in 1996, Connelly et al were administrated intravenous hemophilia dog by adenovirus containing hFVIII gene in which related protein was detectable in plasma for two weeks (Connelly et al., 1996a). Connelly and colleagues were injected adenovirus containing BDD- hFVIII gene through the tail artery into mice; hFVIII was detected in plasma by ELISA method (Connelly et al., 1999; Connelly et al. 1995). Dwarki and colleagues were transfected fibroblast by retrovirus containing BDD- FVIII gene, transfected fibroblasts were transferred into mice, human FVIII was observed in plasma after one week (Dwarki et al., 1995). Connelly et al were transferred adenovirus containing hFVIII gene into mice, hFVIII was stable in mouse for five months. (Connelly et al., 1996b). Ill et al were prepared suitable plasmid with necessary elements for FVIII expression in liver cells (Ill et al., 1997). Zhang et al were prepared a mini-adenovirus containing FVIII -equipped human albumin gene promoter for hemophilia A gene therapy. This structure was transferred to cell line; the hFVIII was consistently produced in mouse transferred ell line (Zhang et al., 1999). Gene therapy of hemophilia were done by liver cell transfected by adeno associated viruses or lentiviral viruses containing FVIII and FIX. Also use non-viral vector is also considered. Antibody production in gene therapy of hemophilia with FVIII and FIX can be depended on vector serotype (viral), expression rate (a long time, especially in the liver), the promoter used, method of gene delivery and transduced cell types (Margaritis et al., 2009; Ohmori et al., 2008; VandenDriessche et al., 2003; Chuah et al., 2001).
\n\t\t\t\tTo overcome adenovirus toxicity phenomena, Andrews and colleagues were used adenovirus defected early genes E1, E2a, E3, E4 (four-generation defected vector), and transferred albumin promoter –controlled FVIII gene into mice, but was not suitable for use in vivo (Andrews et al., 2001). Chuah et al were inhibited bleeding in hemophilia A SCID mice using intravenous injection of adenovirus carrying BDD -FVIII gene (Chuah et al., 2003). Shi et al believed that platelet/ megakaryocyte is a target for hemophilia A gene therapy, they were transferred equipted specific platelet glycoprotein IIb promoter BDD- hFVIII to Domi cells, hFVIII was biosynthesised (Shi et al., 2003). Sarkar and colleagues were transferred AAV carrying hFVIII to deficient FVIII mice through portal, intravenous and spleen injections, they observed secreted hFVIII in transgenic animals but no in neonatal animal (Sarkar et al., 2003). Scallan et al were transferred FVIII gene into mice by AAV2 vector. The construct was equipped with liver cell specific promoter (Scallan et al., 2003). Kang and colleagues were used liver specific promoter equipted FIV retrovirus containing BDD- hFVIII gen for intravenous injection in hemophilia mice, hFVIII was secreted in mice for months without anti FVIII antibody production (Kang et al., 2005). Kumaran et al were treated hemophilia mice by cell therapy, a mixture of hepatocytes, liver endothelial sinusoids and liver kupffer cells was injected into mice peritoneum, FVIII was observed in mouse blood (Kumaran et al., 2005). Jiang et al were transferred FVIII in to hemophilia dog by AAV types 2, 5, 6 and 8, their report indicated that the performance of virus types 2 and 5 for gene therapy is more than viruses type 6 and 8 (Jiang et al., 2006). Sarkar et al believed that gene therapy duration in the dog with AAV8 containing FVIII have prolonged up to two years (Sarkar et al., 2006). Durable gene therapy based on AAV containing FVIII have also been reported by McCormack and colleagues (McCormack et al., 2006). Shi and colleagues findings suggest that targeted FVIII gene expression by platelets specific promoter is effective in the treatment of hemophilia A (Shi et al., 2006). Shi and colleagues were suggested that ectopic expression of FVIII in platelets with lentiviral virus via bone marrow gene therapy is effective for human hemophilia treatment They were transferred lentiviral vector containing FVIII - Induced glycoprotein IIb platelet specific promoter into null mice bone marrow, the permanent secretion of FVIII in platelets lysates mice was observed. (Shi et al., 2007). Liu and colleagues were targeted rDNA of HL7702 hepatocytes by non-viral vector pHrneo containing FVIII gene for treatment of hemophilia (Liu et al., 2007). Doering has been transferred swine FVIII gene into mouse bone marrow mesenchymal cells for hemophilia treatment (Doering, 2008). Ishiwata and colleagues have been treated hemophilia mice using AAV8 vector containing canine BDD -FVIII gene (Ishiwata et al., 2009). Sabatino and colleagues report indicated that canine BDD- FVIII dogs is stable than human BDD- FVIII, it can be considered in the hemophilia treatment (Sabatino et al., 2009). Doering et al were transferred hFVIII - sFVIII hybrid in to hematopoietic stem cells with lentiviral vector; cells expressed FVIII more than 100-8 times of cells transfected with hFVIII only (Doering et al., 2009). Zatloukal and colleagues report suggested that expressed FVIII would be observed if the adenovirus containing FVIII -transfected fibroblasts or mayoblasts move into liver or spleen cells, but do not observe in the transfected muscle cells (Zatloukal et al., 1995). Because there are no acceptable phenotypic correction of hemophilia mice, Liars was used induced pluri potent stem cell therapy technology, these cells suggested converting into all cells and can be transfected by recombinant AAV or lentiviral vectors (Liars, 2011). Studies conducted so far suggest that blood factors gene therapy with AAV in animal muscle (dogs and mice) was healthy for FIX, but did not sufficiently much success for FVIII (Haurigot et al., 2010; Wang & Herzog, 2005). It is believed that the clinical correction of hemophilia B depends on the dose of vector transfer into muscular hosts (mice and dogs) (Hagstrom et al., 2000; Kay et al., 2000).
\n\t\t\tActivated FVII is used as recombinant factor VII (rFVII) can go around process dependent coagulation FVIII and FIX (Mackman et al., 2007), it helps blood coagulation through extrinsic pathway. It is an ideal choice in the treatment of patients with FVIII producing antibodies and hemophilia patients to be considered (Johannessen etal., 2000; Lauritzen et al., 2008a). FVII is used in patient`s surgery with hemophilia A (Lauritzen et al., 2008a) also effective in term of homostatic process (Hedner et al., 2000; Kenet et al., 1999). The VIIa (Novoseven; rhFVIIa) has been achieved great success in treating patients with hemophilia. On the FVIII or FIX defects or presence of inhibitory antibodies, FVIIa – tissue factor complex will activate coagulation FX. FVIIa can activate coagulation cascade which cause clot formation and bleeding is inhibited (Hong & Stachnik, 2010; Levy & Levi, 2009). The main drug problems are short half-life (3-6 hours) and highly price (Ramanarayana et al., 2011; Puetz, 2010; Agersø et al., 2011; ), more than one full dose of medication, especially for homeostasis regulation during surgeries are required. Hence, research groups around the world are trying different methods of gene transfer to express stable FVIIa in cells without the need to drug re administration (Ramanarayana et al., 2011). After biosynthesis of rhFVII as zymogen, it will be cut by proteases and biologically active through purification process (Huntington, 2009). The produced protein will breaks down at Arg152 and Ile153 to FVIIa. It is proposed that FVII gene transfer eliminates short half-life of rFVII and FVIII inhibitory antibody production (Ramanarayana et al., 2011). Emamgholipour et al (2009) and Margaritis (2010) established furin enzyme digestion site between Arg152 and Ile153 to generate FVIIa from FVII zymogene break down inside the targeted cell during FVII gene therapy strategy (Figure 6). Margaritis and colleagues were successfully corrected canine hemophilia B with this method
\n\t\t\t\tMutagenesis method to create furin digestion site on the FVII protein (Proposed based on
(Margaritis et al., 2004). Margaritis and colleagues were injected the mice through gene therapy by AAV contained FVII gene, FVII was produced in host cells (Margaritis et al., 2004). Miller et al were injected mice muscle myoblasts with plasmids coding FVIII and FVII cDNA (muscle specific elements and poly A were placed on both sides of genes); they were observed FVII and related antibody after 4-5 days. They believed that post translation modification process was occurred in the muscle cells (Miller et al., 1995). Tomokiyo and colleagues showed that the composition of plasma FVIIa and FXa in the treatment of monkeys hemophilia B more effective than FVIIa alone (Tomokiyo et al., 2003). Ohmori et al have been used ectopic expression FVIIa in platelets to hemophilia A treatment, they were transferred SIV containing platelet glycoprotein Ib alpha specific promoter into bone marrow cells, was lead to FVII expression on the platelets surface. This construct was corrected mouse hemophilia A phenotype (Ohmori et al., 2008). Margaritis have been treated canine hemophilia by AAV containing FVII through the portal vein (Margaritis et al., 2009). To overcome the repeated injection problem, Obergfell and colleagues were studied hemophilia treatment and suggested permanent expression of FVII in canine hemophilia model through gene therapy method (Obergfell et al., 2010).
\n\t\t\tThere are some reported of FVIII and FIX gene transfer by viral vectors in animal models, but no evidence so far reported successful treatment of human hemophilia gene therapy by this method. Researchers have used FVII to overcome antibody production in treatment of FVIII deficiency. Despite several reports of curing hemophilia A with FVII in animals, there is no yet successful reported in human.
\n\t\t\tMethods proposed for the future: reviewing the history of hemophilia gene therapy by viral vectors, identified several reasons that cannot be sure of the viruses used for gene transfer:
\n\t\t\tApplication of viruses is associated with inappropriate chromosomal insertion and makes the undesirable point mutations (Nakai et al., 2003; Miller et al., 2002).
Viruses are carcinogens (Check, 2003).
The viruses will cause the host immune response (Lefesvre et al., 2003) which is temporarily being transgene.
Because viruses genome are great than non-viral vectors the sequences of the viruses cannot be controlled by reseaechers.
Preparation of this vector requires a lot of time and money.
Although non-viral gene transfer is less efficient than virus vector but have been told no above disadvantages and their use for gene transfer in human can be safer than viruses. Vectors are suggested to be prepared as non-viral vector for targeting the rDNA locus of human genome by homologous recombination method, and as ex vivo gene transfer in humans to be done with them.
\n\t\tThis work was supported by Iran National Science Foundation (project no.843083) and was done in Cellular and Molecular Biology Research Center of Shahid Beheshti University of Medical Sciences, the author’s thanks directors.
\n\t\tIn the last decade, industrial manufacturing such as healthcare, smart grids based on Cyber-Physical Internet of Thing Systems (CPIoTS) has been widespread [1]. In this context, IIoT network, which is characterized by the unified network physical layer, the QoS constraints, the autonomous connection requirements, is considered one of the key issues. The rapid increase in data amounts with diverse QoS requirements [2] brings several challenges in order to meet the complex requirements, as well as resource and QoS requirements with high data rate and low latency. In fact, the advanced 5G technology has a significant potential to provide IIoT QoS satisfactory [3]. With their architectural approaches which are founded on a unified physical layer, addressing the diverging performance requirements in terms scalability and availability still a hot challenges topic. Today’s drastic digital transformations empowered by emerging technology like Edge Computing, Software Defined Networking (SDN), Network Function Virtualization (NFV), and LoRaWAN can bring smart services for network candidates [4]. Network slicing (NS) is the key solution that provides smart service’s connectivity with diverse QoS requirements. Using deep RL at each LoRa agent in the environment. Each agent considered to be a Deep Q-learning (DQL) brain interacts with the environment to find the best action on their parameters that brings the best reward. In addition, it introduces the FL approach to provide better RL based action on each agent, to maximize QoS, and hence throughput revenue. However, NS provides the network availability as a service following the slice instances exploiting NFV and SDN [5]. In this context, a Mini Batch GD and GMM framework is proposed in [7] to provides radio resources for the virtual slice member. In addition, a LoRa network slicing technique based on Maximum Likelihood Estimation proposed, in [6], to allocate network resources in inter and intra mode. Meanwhile, recently supervised learning approach-based resource allocation is also proposed to manage network resources, but due to the training data unavailability or the high computational training process, are not appropriate for large-scale network and cannot satisfy dynamic slices requirements.
RL technique can improve efficient resource management by interacting with the environment, in which Q-learning is the widely used. The RL agent learns the association between taken action and the received feedback in terms of reward. It follows a policy, which is updated according to the maximized revenue via several action series. Therefore, high-quality policies building in a centralized network architecture faces a major challenge, especially when the space of state features is restricted. To deal with these issues, Federated Learning (FL) has been suggested as a decentralized tool for machine learning, which is designed to be a global learning system. In this context, the aim of this work is to propose a deep federated reinforcement learning (DFRL), to equip the slice member with the required channel resources, by tuning LoRa TP and SF parameters [8].
The leftover of this chapter is organized in six sections. Section 2 presents the related work of this chapter. In Section 3, we give a brief overview on the Industrial IoT, the federated learning, and the network slicing. We highlight, in Section 5, the proposed slicing architecture and the system model. After that, in Section 6, the relation between wireless sensor network (WSN) and the IIoT is well highlighted. Next, the proposed slicing resource reservation-based DFRL framework is presented in Section 6. Section 7 evaluates the simulation results. Finally, Section 8 concludes the chapter.
Recently, several articles have investigated the many challenges typical of the network slicing approach. In particular, in [9] the authors propose an online auction algorithm to realize a resource allocation framework, capable of guaranteeing the diversity of services to users and high levels of social welfare. Differently, the work in [10] deals with a new resource allocation framework to automatically and automatically size the capacity and size of network slices. In this chapter, resource partitioning is done based on both available network bandwidth and LoRa configurations parameters resulting in an optimal trade-off between traffic and network aspects. The authors of [11] focus on the design and implementation of a dynamic slicing sharing system to ensure minimum user throughput requirements. Therefore, it addresses three sub-issues: admission control, resource allocation, and user abandonment issues. The contextualization of the placement of VNFs to the network slicing problem is presented in [12], where, in particular, the topological information of the network is exploited to provide an appropriate deployment of functions, with regard to different service classes. Moreover, the placement problem of VNFs has also been addressed in [13], which considers the function decomposition and the sub-functions sharing, a profitable heuristic algorithm is proposed based on Linear integer programming formulation of the VNF placement problem. Further, in the work [14], a formulation of mixed integer linear program is exploited to process the number identification of VNFs to use, which aims to meet specific service requirements. To solve the placing VNFs problem in a federated cloud, the coalition formation game is proposed in [14]. Alternatively, a Pareto analysis of the VNF placement problem is the subject of [15]. In [16], a network partitioning policy is developed to take into account the social well-being and the supplier profit of the network. Finally, special cases for the VNF placement problem are discussed and analyzed in [17].
The problem of bandwidth slicing in software-defined networks is studied in [18], where price spikes are exploited to indicate the presence of traffic spikes and network congestion. This work provides a time-based price analysis combined with a Stackelberg game, in which the gain of SP Internet is the gain of income. In a different way, the work cited in [19] studies the correlation between the network slices size and the resource pricing strategy. In addition, an algorithm to vary the prices is proposed by the authors in [19], with the aim of maximizing both the customer profit and the SP. Although FL has not been used in the field of network slicing research, FL has recently reached attention and several papers have presented its use, the methods cited in [20, 21] being prime examples of’such a branch of literature. In [20], a new aggregation data scheme for wireless computation is proposed. The strategy exploits the signal overlay property of the wireless channels. Differently, articles [22, 20] focus on maximizing the number of devices involved in the aggregation process, also taking into account the minimization of aggregation error. Thus, it contextualize the FL in an MEC system and apply the distributed gradient descent method to identify the best compromise between local updates and global aggregations, aiming to minimize the loss function, in taking into account certain resource constraints. Likewise, the article in [21] analyzes the MEC environment and presents the application of hybrid filtering on stacked encoders to predict fluctuation in file popularity in the content caching problem. Moreover, the article cited [23] modifies the proposed, federated averaging algorithm with the stochastic gradient descent algorithm, to train the data in a distributed way, thus reducing communication costs. The multitasking learning problem is studied in the work cited in [24], authors proposed a new Mocha contextual optimization approach that used in combination with the FL system. The work cited in [25] analyzed the End-to-end delay in a blockchain framework, in which an FL blockchain structure is developed to perform a distributed consensus strategy. In order to improve the transmission and computational costs in a hybrid IoT-MEC network, authors in [26] proposed to use the FL powered by the multiple deep reinforcement learning agents. In addition, ultra-dense scenarios are also considered in [27], where an approach based on the technique of deep learning of short-term long-term memory is applied to forecast local network traffic in order to avoid congestion.
This chapter aims to address the problem of network slicing using deep federated RL at each LoRa agent in the environment. Each agent considered to be a Deep Q-learning (DQL) brain interacts with the environment to find the best action on their parameters that brings the best reward. In addition, it introduces the FL approach to provide better RL-based action on each agent, to maximize QoS, and hence throughput revenue.
The development and evolution of modern information and communication technologies lead us to the Fourth Industrial Revolution, in which the Industrial Internet of Things (IIoT) is supposed to be one of the key aspects to realize the industry 4.0. With an unprecedented increase in the number of Internet of Things (IoT) devices and emerging applications, a large amount of traffic is created every day. Such an increase represents a heavy load on the Internet network and also requires significant investments for the upgrade of the infrastructure. However, with the development of big data analysis and artificial intelligence (AI) techniques such as deep learning (DL) and machine learning (ML), the data collected can be effectively exploited for many purposes. From a communication point of view, the last few years have seen the emergence of AI applications in various fields. For example, ML is used to study efficient antenna selection in multi-antenna wireless systems [28], DL is used to handle the computational offload problem in IoT systems with edge computing [29], and Deep reinforcement learning (DRL) is used to optimize resource allocation issues at the edge of the network, such as traffic classification, edge caching, network security, and data offload [30]. However, conventional AI models generally require central processing of the data collected from all users on the network, i.e. users have to upload their own data to a central server to train the learning model. However, a key concern with central learning is data privacy, i.e., some users want to keep track of their local data and do not want to transmit their local data to the central server. Training the learning model centrally requires a central cloud with extremely powerful compute and storage capabilities. Meanwhile, recent advancements in computer hardware and the proliferation of smart devices in our daily lives have shown that every IoT device can be equipped with reasonable levels of compute and storage, which is closely comparable to a desktop computer there was. is 10 years old [31]. Therefore, the standard ML model is not easily applicable to large scale IoT networks and cannot exploit the availability of distributed computing. This requires a new learning model that leaves training data distributed across individual IoT devices instead of being centralized.
Motivated by this problem, Google invented the concept of federated learning (FL) for on-device learning and data privacy preservation [32]. Using the FL approach, each IoT device can train its model based on locally collected data. Local data from IoT devices does not need to be sent to the centralized cloud. The centralized cloud only needs to collect the updated local training model from individual users. Due to its characteristics, FL has been adopted in many applications, for example FL for improving Google keyboard suggestions [33], FL for healthcare [34], and FL for smart city detection [35]. To illustrate the concept of FL, an overview of FL in IoT systems is shown in Figure 1. In general, each IoT device has its own set of data and the aggregation server can either be located at the edge of the network or in a virtual cloud in the remote cloud computing system [36]. Each FL model has its own advantages and disadvantages, depending on various factors. For example, FL with the server at the edge of the network is suitable for applications requiring low latency, location awareness and contextual information on the network while cloud-based FL is suitable for applications with IoT devices massive over multiple regions and computing power requirements/storage capacities.
An overview of FL in IoT systems.
Recently, the integration of DL models with IoT and edge devices has become more popular, which provides real-time analytics with limited resources [60]. Thus, Federated DL (FDL) allows Industry 4.0 companies to integrate DL into IoT devices and provides a secure framework using FL, as shown in Figure 2. DL is computationally expensive, which requires resources and an expensive framework. Thus, the decentralization of DL models is a multidimensional problem that requires a framework of new technologies to integrate DL with advanced computing and the IIoT. The main goal of FDL is to provide the IIoT with advanced capabilities using optimized DL that would turn Industry 4.0 factories into smart factories. Some of the parameters required to create the FDL model in IIoT are the FDL model, FDL networking, FDL security, and FDL optimization.
Federated DL in IIoT.
An FDL model can be implemented on both client side and server side. On the client side, private networks are defined, the DL model of which is tuned and optimized from the general model present in the cloud. Optimized and fitted models are then deployed on the client side, where the model is trained with data generated locally from the end device. Finally, the final device contains a highly quantized and compressed FDL model. On the server side, the model in the cloud is continuously updated by differentially integrating the gradients of each private network. Each local DL network in turn is responsible for continuously uploading and uploading the currently updated gradients to the cloud model. Thus, a distributed selective stochastic gradient descent approach is presented in [37] which can be applied in the cloud model to frequently update the local private model. The first decentralized model called”Model chain” uses blockchain technology [38, 39] to allow the preservation of confidentiality in the transfer of data. In addition to this, asynchronous stochastic gradient descent can also be used when a single model can be trained in parallel among all devices, aggregated and processed.
Regarding FDL communication and networking, is that the main benefit of using FDL is to run DL models in IoT devices and involve the model in the decision making process. This type of decentralized DL process improves the robustness, operational efficiency and reliability of IoT devices. FDL provides two types of communication, namely intra-communication channel and inter-communication channel. Train transmits data between all levels of the framework. FDL communicates between the IoT and the cloud tier where the cloud-optimized model is deployed on the end device. However, security and confidentiality must be maintained in the FDL during communication. In inter communication channels, the components of each layer communicate with each other in three different ways, such as cloud, edge, and end device. The main objective of FDL is to minimize intra-communication and to maximize inter-communication, which would greatly reduce the cost of communication. By the way, to maintain privacy and security, FDL builds DL models that do not expose information about the data to the cloud. Security issue on the server side includes sharing of DL models on the cloud that leads to confidentiality and security risk. Security issue on the client side is done by encrypting the data during the training process before sending it to the cloud server. Some mechanisms and homomorphic encryption technique controls the amount of data to be shared on the cloud. Since peripherals have limited memory and computational requirements, DL models must be optimized so that they can be deployed to IoT or peripherals efficiently. In terms of hardware optimization, the GPU provides low-power computation that reduces computation time. The FPGA and Google’s Tensor Processing Unit [40] are other DL devices that enhance DL network processing. In terms of memory optimization, algorithms such as shared memory allocation algorithms for DL models can be used. Dynamic scheduling [41] is one of the main processes used to improve performance on a cloud server.
At the heart of the IIoT are the WSNs, that include of multi-functional nodes, low-cost, along with sensing, have both communication and processing capabilities. In order to communicate wirelessly over short distances, these little, inexpensive sensor nodes have built-in transceivers and processors. They are densely exploited in an area of interest to collect sensory data, by coordinating and collaboratively exchanging information by training ad hoc wireless networks. Due to the small size and the batteries use, Sensor nodes are limited in processing, communication, and power. A unique feature of WSNs is their network processing attribute, whereby sensor nodes do not send raw sense data directly to the gateway but merge it locally to make it more consistent and save significant communication costs. Their application field is multiple and they are now ubiquitous components of intelligent environments, due to their unique attributes. Their various area of application covers home, surveillance, military, smart city, patient health monitoring, automation, etc. WSNs are used in telehealth applications in patient healthcare monitoring scenarios. As example, to monitor patients with chronic diseases and regularly check their various parameters such as heart rate, blood sugar and send this information wirelessly to a doctor remotely for further diagnosis. In order to help the elderly and disabled in their daily tasks, the WSNs are also used.
Indeed, they have seen major deployments in a diversity of applications, including agriculture, industrial process automation and control, transportation, and supply chain management over the past decades. Due to their ubiquitous presence and considering the potential benefits of these networks, such as simple deployment, cheap installation cost, no cabling cost, less complexity and mobility, they are increasingly used. in IIoT applications, which gave rise to IWSNs. WSNs can be used in an IIoT environment such as automation and control, process monitoring, and safety and emergency applications. In automation and process control applications, several tasks may require active nodes named actuators, which have the capability to act autonomously on the physical environment based on the detected measurements. For example, in the automation and control of feedback-based chemical processes, sensors measure temperature; if the temperature crosses a certain threshold value, they inform the actuators to reduce the temperature to a desired value so that the process remains in a stable state. Such applications place strict constraints on low latency and reliability because the sensor measurements must reach the actuator in a timely and reliable manner in order for the valve control action to be performed on time [42].
Today’s sensor nodes have more processing power, longer battery life and memory, due to recent technological improvements compared to the first resource-constrained sensor nodes. This allowed them to be used in IIoT applications and resulted in IWSN. IWSN makes processes independent and autonomous, especially in difficult areas, to get actuation and control information, sensory. Sensor nodes in the WSN field detect process variables (e.g. temperature, pressure, etc.) and pass them to the well or gateway. The sink then passes it to the process controller whose job is to control the process variable under some required value. The receiver is responsible for the sensor network management and is controlled and managed by the host application management. The Network and Security Manager is responsible for entire network monitoring and ensuring security against attacks. Therefore, WSN has the potential to improve production processes and quality of products without compromising the IIoT QoS. Actuation and control, and sensing, are also imperative in majority industrial applications. In these applications, the sensors detect the data and the actuators act on the data based on certain control decisions made by the process controller.
To implement FL’s full potential in IIoT and IWSN, there are still several fundamental challenges that need to be addressed. In this section, we describe the challenges followed by very promising opportunities to meet those challenges.
Indeed, the FL deployment on IIoT and IWSN networks relies deeply on the computational resources and memory of edge devices. Consequently, people often focus only on the IoT devices capabilities to gather data while ignoring their limited memory and compute resources, which makes it hard for most IoT and sensor devices to finish local computation with massive data or sophisticated models. In order to address this challenge, lightweight AI techniques have been explored, which can be implemented in resource-constrained FL-IoT and WSN environments, such as improved resource management approaches to accelerate FL training on devices.
In the multi-device settings, participants under the FL framework have various system resources, such as compute and memory resources. As the trend in machine learning is for larger and deeper models, the hardware heterogeneity within the IIoT and IWSN systems pose several challenges for the FL structure. They could easily train large models as devices with powerful memory and computing resources while other devices with limited resources could only train smaller models. Reader speed will also vary across devices, even for the same model size, which can trigger the problem of asynchronous communication discussed above. Due to the availability of the resources, an FL framework for IIoT and IWSN should provide a graceful adaptation of data and compute load on diverse devices.
Communication overload is considered to be one of the main challenges in FL-based IIoT and IWSN environments. Currently, most IoT and WSN devices communicate using wireless networks that have a much lower bandwidth than the wired network bandwidth. As more and more devices join the system, the communication problem arises when the clients have different resource allocations. The limited network bandwidth not only makes the communication between clients and the server inefficient, but also triggers the presence of late clients, which fail to share their local update with the server during the communication cycle. To meet this challenge, some key ideas can be used, such as decentralized training, data compression and participant selection.
The IoT devices prevalence also poses an attractive target in the real-world deployment for adversaries seeking to launch attacks, such as identity theft, phishing, and distributed denial of service (DDoS). Many IoT and ISN devices do not have the compute resources to do so, although these attacks can be easily defended by installing security patches. It is critical for the IIoT andd IWSN systems to detect the malicious or broken IoT devices that will ruin the model training with limited resource. To address this challenge, one of the promising directions is to implement a lightweight security protocol in the IIoT andd IWSN systems for the detection of broken and malicious devices.
Undeniably, the IIoT and IWSN ecosystems continue to evolve at a breakneck pace, exceeding all growth expectations and ubiquity barriers. From sensor to cloud, this giant network keeps breaking technological bounds in several domains, and wireless sensor nodes are expected to be predominant as the number of IoT devices grows toward the trillions to connect the unconnected world and things. However, their future in the IIoT and IWSN ecosystems still seems foggy, where several challenges, such as device’s connectivity, artificial intelligence (AI) at the edge, security and privacy concerns, growing energy needs, the right technologies to be used and keep pulling in opposite directions. To address these issues, which are caused by the complexity and variability of the environment, advanced computing related technologies are widely applied. However, the edge computing is limited by cost, volume, power consumption, and other conditions, so the capacity of edge computing cannot be fully exploited. So that edge computing fully exploits its characteristics of flexible management, federated and collaborative execution and heterogeneous environment, the reconfigurable real-time computer system based on FPGA SoC is strongly recommended. The system, as depicted in Figure 3 can be built in real time as needed, by the characteristics of the FPGA SoC, including its reconfigurability, partial and total and precise clock control.
Reconfigurable edge computing system based on FPGA SoC.
A multi-threaded huge number, computing requirements, and parallel heterogeneous data processing are persistently proposed in many environments of manufacturing. However, depending on the multi-environment’s requirements with different multiple tasks and several scenes, a single algorithm can no longer face the requirements so that numerous complicated tasks require the algorithm to be reconfigured and replaced. Without a doubt, the FPGA employment gratifies this multitude of requirements. However, it can rebuild the logic of the chip by means of configuration and reconfiguration of the resources inside the chip to form hardware with different functions by means of software. Therefore, in addition to the programmability and flexibility of the software, the FPGA also exhibits high throughput, low power, and low latency characteristics. In addition, due to its rich In-Output, FPGA SoCs are also very relevant for use On-chip protocols applications and interface conversion. The main benefits from employing FPGA for the edge computing are as follows:
A constant throughput can be provided by the FPGA with a constant load size-based application, so that can integrate multiple service requests from several sensors in the IoT.
Large-scale temporal and spatial parallelism is provided by the FPGA with fine granularity, so that ensures a high concurrency and high dependency algorithm with high acceleration performance.
Compared with the processor, the FPGA has the lower power consumption and faster computing speed, which can provide the stability and lower task energy consumption.
The 5G network infrastructure design should focus on attentive consideration of software control, hardware infrastructure, and interconnection between them. In this context, we consider a network slicing architecture consisting of a set of IIoT slices
Deep federated RL-based network slicing architecture.
This slice set
where
however,
We assume that agents, by sharing its self models based on the Q-network experiences, collaborate to receive global rewards from the federated orchestrator. While the orchestrator collects these models to builds a global network model that provides an optimal actions, on LoRa parameters, that maximize QoS revenue [43, 44].
The considered network consists of two agents, called as agent
where
At this stage, the Mean Square Error (MSE), is defined for agents
while
Training and testing phases.
The proposed framework has been implemented in Python language using TensorFlow-gpu package on Intel Xeon E5-2620 v4 2x 8-Core with 64 GB RAM. Also, the NVIDIA GK110BGL [Tesla K40c] is used to improve speed during the training phase.
We provide, in this section, the mean percentage of Packet Loss Rate (PLR) for IIoT devices, as denoted in Figures 6–8, and compare it to the PLR within MBGD scheme [7].
PLR of UCLE.
PLR of HCLE.
PLR of LCLE.
However, by increasing the devices, PLR will increase subsequently. This return to the data rate, that when increase, the number of successful transmitted packet increase accordingly. While it is not the case when throughput is low. We remark also, in Figures 6–8, that UCLE and HCLE slices have a reduced PLR compared to LCLE. However, this due to the reliability and efficiency constraints dedicated for this slice which is not the case in LCLE slice that consider only the load. Compared with the slice results using the MBGD technique, we could obviously note the efficiency of the proposed federated scheme in supporting dynamic slicing strategy by reducing PLR over than 9
This prospective chapter presents a future outlook on low-end motes in the IIoT and IWSN eras. Following a detailed discussion of the trends and challenges posed by the IIoT and IWSN paradigm to low-end devices, it discusses how modern reconfigurable platforms are the perfect candidate to meet the ever-evolving industrial environments. Indeed, in this chapter, we proposed a federated network slicing based on deep reinforcement learning techniques for channels and bandwidth management based LoRa promising technology that meet IIoT and IWSN network service requirements based on the SDN, NFV, network slicing, and deep reinforcement learning techniques. Each LoRa GW plays an agent role, in the environment, and profits from the learning experience provided by the other coexist agents via the global federated model.
In the case of future studies, this chapter introduced comprehensive review and several research lines, especially one attractive future line is related to the integration of FPGA SoC at the edge to build a smart factory as well as IIoT and IWSN environments with environmentally friendly capabilities and functionalities. In addition, future research is needed to fully embrace cloud services and new ways of connectivity in order to get the full benefits of the new Edge FPGA SoC technology.
J=1…j | IIoT network slices set |
K=1…k | LoRa gateways (agents) set |
I=1…i | IIoT devices set associated to each slice |
B=1…b | channel bandwidth set |
C=1…c | LoRa-GW’s channels set |
αi∈01,∀i∈Ij,k | device’s admission and association index to slice |
∀i∈Ij,k | device i assigned to slice j on gateway k |
TP | transmission power |
SF | spreading factor |
ϕi,∀i∈Ij,k | throughput of device i |
di,∀i∈Ij,k | delay of device i |
uQoSj,k | quality of service metric for slice j on GW k |
pit,∀i∈Ij,k | the power allocated for each device i |
uEEj,k | energy efficiency metric for slice j on GW k |
pir | the received power |
uRELj,k | reliability metric for slice j on GW k |
Urmj,k,∀k∈K,∀j∈J | the global slice utility revenues metric |
SATℛ | state, action, transition function, reward |
α and β | agent α and agent β |
γ | discount factor |
θα,θβ | DQL network parameters (weights) |
θg | DNN network parameters (weights) |
Dα,Dβ | reply memories to store transitions |
IoT | internet of things |
IIoT | industrial IoT |
IWSN | industrial wireless sensor network |
AI | artificial intelligence |
ML | machine learning |
DL | deep learning |
QoS | quality of service |
RL | reinforcement learning |
DRL | deep reinforcement learning |
FL | federated learning |
DFL | deep federated learning |
DFRL | deep federated reinforcement learning |
CPIToS | cyber-physical internet of thing systems |
5G | fifth generation network |
SDN | software defined network |
NFV | network function virtualization |
NS | network slicing |
DQL | deep Q-learning |
GD | gradient descent |
GMM | gaussian mixture model |
SP | service provide |
MEC | mobile edge computing |
GPU | graphic processor unit |
FPGA | field programmable gate array |
UCLE | ultra critical of latency and efficiency |
HCLE | high critical of latency and efficiency |
LCLE | low critical of latency and efficiency |
GW | gateway |
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Only bioactive glass possesses osteogenic property that stimulates proliferation and differentiation of osteoprogenitor cells and in some cases influencing the fibroblastic properties. But, this material has also some disadvantages such as short-term and low mechanical strength along with decreased fracture resistance; but, this was further minimised by ion doping that positively enhanced new bone formation. There are many metal ions such as magnesium (Mg), strontium (Sr), manganese (Mn), iron (Fe), zinc (Zn), silver (Ag) and some rare earths that have been doped successfully into bioactive glass to enhance their mechanical and biological properties. In some of the cases, mesoporous bioactive glass materials with or without such doping have also been employed (with homogeneous distribution of pores in the size ranging between 2 and 50 nm). These biomaterials can be served as scaffold for bone regeneration with adequate mechanical properties to restore bone defects and facilitate healing process by regeneration of soft tissues as well. This chapter encompasses the use of bioactive glass in bulk and mesoporous form with doped therapeutic ions, their role in bone tissue regeneration, use as delivery of growth factors as well as coating material for orthopaedic implants.",book:{id:"5164",slug:"advanced-techniques-in-bone-regeneration",title:"Advanced Techniques in Bone Regeneration",fullTitle:"Advanced Techniques in Bone Regeneration"},signatures:"Samit Kumar Nandi, Arnab Mahato, Biswanath Kundu and Prasenjit\nMukherjee",authors:[{id:"60514",title:"Dr.",name:"Samit",middleName:null,surname:"Nandi",slug:"samit-nandi",fullName:"Samit Nandi"}]},{id:"37120",doi:"10.5772/29607",title:"Trigeminocardiac Reflex in Neurosurgery - Current Knowledge and Prospects",slug:"the-trigeminocardiac-reflex-in-neurosurgery-current-knowledge-and-prospects",totalDownloads:3423,totalCrossrefCites:10,totalDimensionsCites:27,abstract:null,book:{id:"749",slug:"explicative-cases-of-controversial-issues-in-neurosurgery",title:"Explicative Cases of Controversial Issues in Neurosurgery",fullTitle:"Explicative Cases of Controversial Issues in Neurosurgery"},signatures:"Amr Abdulazim, Martin N. Stienen, Pooyan Sadr-Eshkevari, Nora Prochnow, Nora Sandu, Benham Bohluli and Bernhard Schaller",authors:[{id:"78171",title:"Prof.",name:"Bernhard",middleName:null,surname:"Schaller",slug:"bernhard-schaller",fullName:"Bernhard Schaller"},{id:"78525",title:"Mr.",name:"Amr",middleName:null,surname:"Abdulazim",slug:"amr-abdulazim",fullName:"Amr Abdulazim"},{id:"78530",title:"Dr",name:"Pooyan",middleName:null,surname:"Sadr-Eshkevari",slug:"pooyan-sadr-eshkevari",fullName:"Pooyan Sadr-Eshkevari"},{id:"126039",title:"Dr.",name:"Martin",middleName:"Nikolaus",surname:"Stienen",slug:"martin-stienen",fullName:"Martin Stienen"},{id:"126040",title:"Dr.",name:"Nora",middleName:null,surname:"Prochnow",slug:"nora-prochnow",fullName:"Nora Prochnow"},{id:"126041",title:"Dr.",name:"Benham",middleName:null,surname:"Bohluli",slug:"benham-bohluli",fullName:"Benham Bohluli"}]},{id:"26559",doi:"10.5772/28833",title:"Local Antibiotic Therapy in the Treatment of Bone and Soft Tissue Infections",slug:"local-antibiotic-therapy-in-the-treatment-of-bone-and-soft-tissue-infections",totalDownloads:6551,totalCrossrefCites:5,totalDimensionsCites:21,abstract:null,book:{id:"784",slug:"selected-topics-in-plastic-reconstructive-surgery",title:"Selected Topics in Plastic Reconstructive Surgery",fullTitle:"Selected Topics in Plastic Reconstructive Surgery"},signatures:"Stefanos Tsourvakas",authors:[{id:"75532",title:"Dr.",name:"Stefanos",middleName:null,surname:"Tsourvakas",slug:"stefanos-tsourvakas",fullName:"Stefanos Tsourvakas"}]}],mostDownloadedChaptersLast30Days:[{id:"65467",title:"Anesthesia Management for Large-Volume Liposuction",slug:"anesthesia-management-for-large-volume-liposuction",totalDownloads:5965,totalCrossrefCites:0,totalDimensionsCites:0,abstract:"The apparent easiness with which liposuction is performed favors that patients, young surgeons, and anesthesiologists without experience in this field ignore the many events that occur during this procedure. Liposuction is a procedure to improve the body contour and not a surgery to reduce weight, although recently people who have failed in their plans to lose weight look at liposuction as a means to contour their body figure. Tumescent liposuction of large volumes requires a meticulous selection of each patient; their preoperative evaluation and perioperative management are essential to obtain the expected results. The various techniques of general anesthesia are the most recommended and should be monitored in the usual way, as well as monitoring the total doses of infiltrated local anesthetics to avoid systemic toxicity. The management of intravenous fluids is controversial, but the current trend is the restricted use of hydrosaline solutions. The most feared complications are deep vein thrombosis, pulmonary thromboembolism, fat embolism, lung edema, hypothermia, infections and even death. The adherence to the management guidelines and prophylaxis of venous thrombosis/thromboembolism is mandatory.",book:{id:"6221",slug:"anesthesia-topics-for-plastic-and-reconstructive-surgery",title:"Anesthesia Topics for Plastic and Reconstructive Surgery",fullTitle:"Anesthesia Topics for Plastic and Reconstructive Surgery"},signatures:"Sergio Granados-Tinajero, Carlos Buenrostro-Vásquez, Cecilia\nCárdenas-Maytorena and Marcela Contreras-López",authors:[{id:"273532",title:"Dr.",name:"Sergio Octavio",middleName:null,surname:"Granados Tinajero",slug:"sergio-octavio-granados-tinajero",fullName:"Sergio Octavio Granados Tinajero"}]},{id:"42855",title:"Critical Care Issues After Major Hepatic Surgery",slug:"critical-care-issues-after-major-hepatic-surgery",totalDownloads:8909,totalCrossrefCites:2,totalDimensionsCites:2,abstract:null,book:{id:"3164",slug:"hepatic-surgery",title:"Hepatic Surgery",fullTitle:"Hepatic Surgery"},signatures:"Ashok Thorat and Wei-Chen Lee",authors:[{id:"52360",title:"Prof.",name:"Wei-Chen",middleName:null,surname:"Lee",slug:"wei-chen-lee",fullName:"Wei-Chen Lee"},{id:"157213",title:"Dr.",name:"Ashok",middleName:null,surname:"Thorat",slug:"ashok-thorat",fullName:"Ashok Thorat"}]},{id:"72175",title:"Fontan Operation: A Comprehensive Review",slug:"fontan-operation-a-comprehensive-review",totalDownloads:1252,totalCrossrefCites:2,totalDimensionsCites:2,abstract:"Since the first description of the Fontan operation in the early 1970s, a number of modifications have been introduced and currently staged, total cavopulmonary connection with fenestration has become the most commonly used multistage surgery in diverting the vena caval blood flow into the lungs. The existing ventricle, whether it is left or right, is utilized to supply systemic circuit. During Stage I, palliative surgery is performed, usually at presentation in the neonatal period/early infancy, on the basis of pathophysiology of the cardiac defect. During Stage II, a bidirectional Glenn procedure is undertaken in which the superior vena caval flow is diverted into the lungs at an approximate age of 6 months. During Stage IIIA, the blood flow from the inferior vena cava (IVC) is rerouted into the pulmonary arteries, typically by an extra-cardiac conduit along with a fenestration, generally around 2 years of age. During Stage IIIB, the fenestration is closed by transcatheter methodology 6–12 months after Stage IIIA. The evolution of Fontan concepts, the indications for Fontan surgery, and the results of old and current types of Fontan operation form the focus of this review.",book:{id:"9585",slug:"advances-in-complex-valvular-disease",title:"Advances in Complex Valvular Disease",fullTitle:"Advances in Complex Valvular Disease"},signatures:"P. Syamasundar Rao",authors:[{id:"68531",title:"Dr.",name:"P. Syamasundar",middleName:null,surname:"Rao",slug:"p.-syamasundar-rao",fullName:"P. 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Interventions meant to correct these conditions are commonly based on symmetrical models of appearance and do not take into account asymmetric organ weight distribution, asymmetries of respiratory mechanics, and dominant movement patterns that are reinforced in daily functional activities. A model of innate, human asymmetry derived from the theoretical framework of the Postural Restoration Institute® (PRI) explicitly describes the physiological, biomechanical, and respiratory components of human asymmetry. This model is important because it gives an accurate baseline for understanding predisposing factors for the development of postural disorders, which, without intervention, will likely progress to structural dysfunction. Clinical tests to evaluate tri-planar musculoskeletal relationships and function, developed by PRI, are based on this asymmetric model. These tests are valuable for assessing patient’s status in the context of human asymmetry and in guiding appropriate exercise prescription and progression. Balancing musculoskeletal asymmetry is the aim of PRI treatment. Restoration of relative balance decreases pain, restores improved alignment, and strengthens appropriate muscle function. It can also halt the progression of dysfunction and improve respiration, quality of life, and appearance. PRI’s extensive body of targeted exercise progressions are highly effective due to their basis in the tri-planar asymmetric human model.",book:{id:"5816",slug:"innovations-in-spinal-deformities-and-postural-disorders",title:"Innovations in Spinal Deformities and Postural Disorders",fullTitle:"Innovations in Spinal Deformities and Postural Disorders"},signatures:"Susan Henning, Lisa C. Mangino and Jean Massé",authors:[{id:"204825",title:"Dr.",name:"Susan",middleName:null,surname:"Henning",slug:"susan-henning",fullName:"Susan Henning"},{id:"206242",title:"Dr.",name:"Lisa C",middleName:null,surname:"Mangino",slug:"lisa-c-mangino",fullName:"Lisa C Mangino"},{id:"206245",title:"Dr.",name:"Jean",middleName:null,surname:"Massé",slug:"jean-masse",fullName:"Jean Massé"}]}],onlineFirstChaptersFilter:{topicId:"202",limit:6,offset:0},onlineFirstChaptersCollection:[],onlineFirstChaptersTotal:0},preDownload:{success:null,errors:{}},subscriptionForm:{success:null,errors:{}},aboutIntechopen:{},privacyPolicy:{},peerReviewing:{},howOpenAccessPublishingWithIntechopenWorks:{},sponsorshipBooks:{sponsorshipBooks:[],offset:0,limit:8,total:null},allSeries:{pteSeriesList:[{id:"14",title:"Artificial Intelligence",numberOfPublishedBooks:9,numberOfPublishedChapters:89,numberOfOpenTopics:6,numberOfUpcomingTopics:0,issn:"2633-1403",doi:"10.5772/intechopen.79920",isOpenForSubmission:!0},{id:"7",title:"Biomedical Engineering",numberOfPublishedBooks:12,numberOfPublishedChapters:104,numberOfOpenTopics:3,numberOfUpcomingTopics:0,issn:"2631-5343",doi:"10.5772/intechopen.71985",isOpenForSubmission:!0}],lsSeriesList:[{id:"11",title:"Biochemistry",numberOfPublishedBooks:32,numberOfPublishedChapters:318,numberOfOpenTopics:4,numberOfUpcomingTopics:0,issn:"2632-0983",doi:"10.5772/intechopen.72877",isOpenForSubmission:!0},{id:"25",title:"Environmental Sciences",numberOfPublishedBooks:1,numberOfPublishedChapters:12,numberOfOpenTopics:4,numberOfUpcomingTopics:0,issn:"2754-6713",doi:"10.5772/intechopen.100362",isOpenForSubmission:!0},{id:"10",title:"Physiology",numberOfPublishedBooks:11,numberOfPublishedChapters:141,numberOfOpenTopics:4,numberOfUpcomingTopics:0,issn:"2631-8261",doi:"10.5772/intechopen.72796",isOpenForSubmission:!0}],hsSeriesList:[{id:"3",title:"Dentistry",numberOfPublishedBooks:8,numberOfPublishedChapters:129,numberOfOpenTopics:2,numberOfUpcomingTopics:0,issn:"2631-6218",doi:"10.5772/intechopen.71199",isOpenForSubmission:!0},{id:"6",title:"Infectious Diseases",numberOfPublishedBooks:13,numberOfPublishedChapters:113,numberOfOpenTopics:3,numberOfUpcomingTopics:1,issn:"2631-6188",doi:"10.5772/intechopen.71852",isOpenForSubmission:!0},{id:"13",title:"Veterinary Medicine and Science",numberOfPublishedBooks:11,numberOfPublishedChapters:106,numberOfOpenTopics:3,numberOfUpcomingTopics:0,issn:"2632-0517",doi:"10.5772/intechopen.73681",isOpenForSubmission:!0}],sshSeriesList:[{id:"22",title:"Business, Management and Economics",numberOfPublishedBooks:1,numberOfPublishedChapters:19,numberOfOpenTopics:3,numberOfUpcomingTopics:0,issn:"2753-894X",doi:"10.5772/intechopen.100359",isOpenForSubmission:!0},{id:"23",title:"Education and Human Development",numberOfPublishedBooks:0,numberOfPublishedChapters:5,numberOfOpenTopics:1,numberOfUpcomingTopics:1,issn:null,doi:"10.5772/intechopen.100360",isOpenForSubmission:!0},{id:"24",title:"Sustainable Development",numberOfPublishedBooks:0,numberOfPublishedChapters:15,numberOfOpenTopics:5,numberOfUpcomingTopics:0,issn:null,doi:"10.5772/intechopen.100361",isOpenForSubmission:!0}],testimonialsList:[{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"}}}},{id:"13",text:"The collaboration with and support of the technical staff of IntechOpen is fantastic. 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"}}}}]},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. In today's highly integrated world, AI promises to become a robust and powerful means for obtaining solutions to previously unsolvable problems. This Series is intended for researchers and students alike interested in this fascinating field and its many applications.",coverUrl:"https://cdn.intechopen.com/series/covers/14.jpg",latestPublicationDate:"June 11th, 2022",hasOnlineFirst:!0,numberOfPublishedBooks:9,editor:{id:"218714",title:"Prof.",name:"Andries",middleName:null,surname:"Engelbrecht",slug:"andries-engelbrecht",fullName:"Andries Engelbrecht",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bRNR8QAO/Profile_Picture_1622640468300",biography:"Andries Engelbrecht received the Masters and PhD degrees in Computer Science from the University of Stellenbosch, South Africa, in 1994 and 1999 respectively. 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). In addition to a number of research articles, he has written two books, Computational Intelligence: An Introduction and Fundamentals of Computational Swarm Intelligence.",institutionString:null,institution:{name:"Stellenbosch University",institutionURL:null,country:{name:"South Africa"}}},editorTwo:null,editorThree:null},subseries:{paginationCount:6,paginationItems:[{id:"22",title:"Applied Intelligence",coverUrl:"https://cdn.intechopen.com/series_topics/covers/22.jpg",isOpenForSubmission:!0,annualVolume:11418,editor:{id:"27170",title:"Prof.",name:"Carlos",middleName:"M.",surname:"Travieso-Gonzalez",slug:"carlos-travieso-gonzalez",fullName:"Carlos Travieso-Gonzalez",profilePictureURL:"https://mts.intechopen.com/storage/users/27170/images/system/27170.jpeg",biography:"Carlos M. Travieso-González received his MSc degree in Telecommunication Engineering at Polytechnic University of Catalonia (UPC), Spain in 1997, and his Ph.D. degree in 2002 at the University of Las Palmas de Gran Canaria (ULPGC-Spain). 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,annualVolume:11419,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,annualVolume:11420,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,annualVolume:11421,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,annualVolume:11422,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. His research interests include intelligent and embedded systems.",institutionString:"Universidad Autonoma de Queretaro",institution:{name:"Autonomous University of Queretaro",institutionURL:null,country:{name:"Mexico"}}},editorTwo:null,editorThree:null},{id:"27",title:"Multi-Agent Systems",coverUrl:"https://cdn.intechopen.com/series_topics/covers/27.jpg",isOpenForSubmission:!0,annualVolume:11423,editor:{id:"148497",title:"Dr.",name:"Mehmet",middleName:"Emin",surname:"Aydin",slug:"mehmet-aydin",fullName:"Mehmet Aydin",profilePictureURL:"https://mts.intechopen.com/storage/users/148497/images/system/148497.jpg",biography:"Dr. Mehmet Emin Aydin is a Senior Lecturer with the Department of Computer Science and Creative Technology, the University of the West of England, Bristol, UK. 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Singh",profilePictureURL:"https://mts.intechopen.com/storage/users/329385/images/system/329385.png",institutionString:"Punjab Technical University",institution:{name:"Punjab Technical University",institutionURL:null,country:{name:"India"}}}],equalEditorOne:null,equalEditorTwo:null,equalEditorThree:null},{type:"book",id:"8018",title:"Extracellular Matrix",subtitle:"Developments and Therapeutics",coverURL:"https://cdn.intechopen.com/books/images_new/8018.jpg",slug:"extracellular-matrix-developments-and-therapeutics",publishedDate:"October 27th 2021",editedByType:"Edited by",bookSignature:"Rama Sashank Madhurapantula, Joseph Orgel P.R.O. and Zvi Loewy",hash:"c85e82851e80b40282ff9be99ddf2046",volumeInSeries:23,fullTitle:"Extracellular Matrix - Developments and Therapeutics",editors:[{id:"212416",title:"Dr.",name:"Rama Sashank",middleName:null,surname:"Madhurapantula",slug:"rama-sashank-madhurapantula",fullName:"Rama Sashank Madhurapantula",profilePictureURL:"https://mts.intechopen.com/storage/users/212416/images/system/212416.jpg",institutionString:"Illinois Institute of Technology",institution:{name:"Illinois Institute of Technology",institutionURL:null,country:{name:"United States of America"}}}],equalEditorOne:null,equalEditorTwo:null,equalEditorThree:null},{type:"book",id:"9759",title:"Vitamin E in Health and Disease",subtitle:"Interactions, Diseases and Health Aspects",coverURL:"https://cdn.intechopen.com/books/images_new/9759.jpg",slug:"vitamin-e-in-health-and-disease-interactions-diseases-and-health-aspects",publishedDate:"October 6th 2021",editedByType:"Edited by",bookSignature:"Pınar Erkekoglu and Júlia Scherer Santos",hash:"6c3ddcc13626110de289b57f2516ac8f",volumeInSeries:22,fullTitle:"Vitamin E in Health and Disease - Interactions, Diseases and Health Aspects",editors:[{id:"109978",title:"Prof.",name:"Pınar",middleName:null,surname:"Erkekoğlu",slug:"pinar-erkekoglu",fullName:"Pınar Erkekoğlu",profilePictureURL:"https://mts.intechopen.com/storage/users/109978/images/system/109978.jpg",institutionString:"Hacettepe University",institution:{name:"Hacettepe University",institutionURL:null,country:{name:"Turkey"}}}],equalEditorOne:null,equalEditorTwo:null,equalEditorThree:null}]},subseriesFiltersForPublishedBooks:[{group:"subseries",caption:"Proteomics",value:18,count:4},{group:"subseries",caption:"Metabolism",value:17,count:6},{group:"subseries",caption:"Cell and Molecular Biology",value:14,count:9},{group:"subseries",caption:"Chemical Biology",value:15,count:13}],publicationYearFilters:[{group:"publicationYear",caption:"2022",value:2022,count:8},{group:"publicationYear",caption:"2021",value:2021,count:7},{group:"publicationYear",caption:"2020",value:2020,count:12},{group:"publicationYear",caption:"2019",value:2019,count:3},{group:"publicationYear",caption:"2018",value:2018,count:2}],authors:{paginationCount:229,paginationItems:[{id:"318170",title:"Dr.",name:"Aneesa",middleName:null,surname:"Moolla",slug:"aneesa-moolla",fullName:"Aneesa Moolla",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/318170/images/system/318170.png",biography:"Dr. Aneesa Moolla has extensive experience in the diverse fields of health care having previously worked in dental private practice, at the Red Cross Flying Doctors association, and in healthcare corporate settings. She is now a lecturer at the University of Witwatersrand, South Africa, and a principal researcher at the Health Economics and Epidemiology Research Office (HE2RO), South Africa. Dr. Moolla holds a Ph.D. in Psychology with her research being focused on mental health and resilience. In her professional work capacity, her research has further expanded into the fields of early childhood development, mental health, the HIV and TB care cascades, as well as COVID. She is also a UNESCO-trained International Bioethics Facilitator.",institutionString:"University of the Witwatersrand",institution:{name:"University of the Witwatersrand",country:{name:"South Africa"}}},{id:"419588",title:"Ph.D.",name:"Sergio",middleName:"Alexandre",surname:"Gehrke",slug:"sergio-gehrke",fullName:"Sergio Gehrke",position:null,profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0033Y000038WgMKQA0/Profile_Picture_2022-06-02T11:44:20.jpg",biography:"Dr. Sergio Alexandre Gehrke is a doctorate holder in two fields. The first is a Ph.D. in Cellular and Molecular Biology from the Pontificia Catholic University, Porto Alegre, Brazil, in 2010 and the other is an International Ph.D. in Bioengineering from the Universidad Miguel Hernandez, Elche/Alicante, Spain, obtained in 2020. In 2018, he completed a postdoctoral fellowship in Materials Engineering in the NUCLEMAT of the Pontificia Catholic University, Porto Alegre, Brazil. He is currently the Director of the Postgraduate Program in Implantology of the Bioface/UCAM/PgO (Montevideo, Uruguay), Director of the Cathedra of Biotechnology of the Catholic University of Murcia (Murcia, Spain), an Extraordinary Full Professor of the Catholic University of Murcia (Murcia, Spain) as well as the Director of the private center of research Biotecnos – Technology and Science (Montevideo, Uruguay). Applied biomaterials, cellular and molecular biology, and dental implants are among his research interests. He has published several original papers in renowned journals. In addition, he is also a Collaborating Professor in several Postgraduate programs at different universities all over the world.",institutionString:null,institution:{name:"Universidad Católica San Antonio de Murcia",country:{name:"Spain"}}},{id:"342152",title:"Dr.",name:"Santo",middleName:null,surname:"Grace Umesh",slug:"santo-grace-umesh",fullName:"Santo Grace Umesh",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/342152/images/16311_n.jpg",biography:null,institutionString:null,institution:{name:"SRM Dental College",country:{name:"India"}}},{id:"333647",title:"Dr.",name:"Shreya",middleName:null,surname:"Kishore",slug:"shreya-kishore",fullName:"Shreya Kishore",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/333647/images/14701_n.jpg",biography:"Dr. Shreya Kishore completed her Bachelor in Dental Surgery in Chettinad Dental College and Research Institute, Chennai, and her Master of Dental Surgery (Orthodontics) in Saveetha Dental College, Chennai. She is also Invisalign certified. She’s working as a Senior Lecturer in the Department of Orthodontics, SRM Dental College since November 2019. She is actively involved in teaching orthodontics to the undergraduates and the postgraduates. Her clinical research topics include new orthodontic brackets, fixed appliances and TADs. She’s published 4 articles in well renowned indexed journals and has a published patency of her own. Her private practice is currently limited to orthodontics and works as a consultant in various clinics.",institutionString:null,institution:{name:"SRM Dental College",country:{name:"India"}}},{id:"323731",title:"Prof.",name:"Deepak M.",middleName:"Macchindra",surname:"Vikhe",slug:"deepak-m.-vikhe",fullName:"Deepak M. Vikhe",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/323731/images/13613_n.jpg",biography:"Dr Deepak M.Vikhe .\n\n\t\n\tDr Deepak M.Vikhe , completed his Masters & PhD in Prosthodontics from Rural Dental College, Loni securing third rank in the Pravara Institute of Medical Sciences Deemed University. He was awarded Dr.G.C.DAS Memorial Award for Research on Implants at 39th IPS conference Dubai (U A E).He has two patents under his name. He has received Dr.Saraswati medal award for best research for implant study in 2017.He has received Fully funded scholarship to Spain ,university of Santiago de Compostela. He has completed fellowship in Implantlogy from Noble Biocare. \nHe has attended various conferences and CDE programmes and has national publications to his credit. His field of interest is in Implant supported prosthesis. Presently he is working as a associate professor in the Dept of Prosthodontics, Rural Dental College, Loni and maintains a successful private practice specialising in Implantology at Rahata.\n\nEmail: drdeepak_mvikhe@yahoo.com..................",institutionString:null,institution:{name:"Pravara Institute of Medical Sciences",country:{name:"India"}}},{id:"204110",title:"Dr.",name:"Ahmed A.",middleName:null,surname:"Madfa",slug:"ahmed-a.-madfa",fullName:"Ahmed A. Madfa",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/204110/images/system/204110.jpg",biography:"Dr. Madfa is currently Associate Professor of Endodontics at Thamar University and a visiting lecturer at Sana'a University and University of Sciences and Technology. He has more than 6 years of experience in teaching. His research interests include root canal morphology, functionally graded concept, dental biomaterials, epidemiology and dental education, biomimetic restoration, finite element analysis and endodontic regeneration. Dr. Madfa has numerous international publications, full articles, two patents, a book and a book chapter. Furthermore, he won 14 international scientific awards. Furthermore, he is involved in many academic activities ranging from editorial board member, reviewer for many international journals and postgraduate students' supervisor. Besides, I deliver many courses and training workshops at various scientific events. Dr. Madfa also regularly attends international conferences and holds administrative positions (Deputy Dean of the Faculty for Students’ & Academic Affairs and Deputy Head of Research Unit).",institutionString:"Thamar University",institution:null},{id:"210472",title:"Dr.",name:"Nermin",middleName:"Mohammed Ahmed",surname:"Yussif",slug:"nermin-yussif",fullName:"Nermin Yussif",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/210472/images/system/210472.jpg",biography:"Dr. Nermin Mohammed Ahmed Yussif is working at the Faculty of dentistry, University for October university for modern sciences and arts (MSA). Her areas of expertise include: periodontology, dental laserology, oral implantology, periodontal plastic surgeries, oral mesotherapy, nutrition, dental pharmacology. She is an editor and reviewer in numerous international journals.",institutionString:"MSA University",institution:null},{id:"204606",title:"Dr.",name:"Serdar",middleName:null,surname:"Gözler",slug:"serdar-gozler",fullName:"Serdar Gözler",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/204606/images/system/204606.jpeg",biography:"Dr. Serdar Gözler has completed his undergraduate studies at the Marmara University Faculty of Dentistry in 1978, followed by an assistantship in the Prosthesis Department of Dicle University Faculty of Dentistry. Starting his PhD work on non-resilient overdentures with Assoc. Prof. Hüsnü Yavuzyılmaz, he continued his studies with Prof. Dr. Gürbüz Öztürk of Istanbul University Faculty of Dentistry Department of Prosthodontics, this time on Gnatology. He attended training programs on occlusion, neurology, neurophysiology, EMG, radiology and biostatistics. In 1982, he presented his PhD thesis \\Gerber and Lauritzen Occlusion Analysis Techniques: Diagnosis Values,\\ at Istanbul University School of Dentistry, Department of Prosthodontics. As he was also working with Prof. Senih Çalıkkocaoğlu on The Physiology of Chewing at the same time, Gözler has written a chapter in Çalıkkocaoğlu\\'s book \\Complete Prostheses\\ entitled \\The Place of Neuromuscular Mechanism in Prosthetic Dentistry.\\ The book was published five times since by the Istanbul University Publications. Having presented in various conferences about occlusion analysis until 1998, Dr. Gözler has also decided to use the T-Scan II occlusion analysis method. Having been personally trained by Dr. Robert Kerstein on this method, Dr. Gözler has been lecturing on the T-Scan Occlusion Analysis Method in conferences both in Turkey and abroad. Dr. Gözler has various articles and presentations on Digital Occlusion Analysis methods. He is now Head of the TMD Clinic at Prosthodontic Department of Faculty of Dentistry , Istanbul Aydın University , Turkey.",institutionString:"Istanbul Aydin University",institution:{name:"Istanbul Aydın University",country:{name:"Turkey"}}},{id:"240870",title:"Ph.D.",name:"Alaa Eddin Omar",middleName:null,surname:"Al Ostwani",slug:"alaa-eddin-omar-al-ostwani",fullName:"Alaa Eddin Omar Al Ostwani",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/240870/images/system/240870.jpeg",biography:"Dr. Al Ostwani Alaa Eddin Omar received his Master in dentistry from Damascus University in 2010, and his Ph.D. in Pediatric Dentistry from Damascus University in 2014. Dr. Al Ostwani is an assistant professor and faculty member at IUST University since 2014. \nDuring his academic experience, he has received several awards including the scientific research award from the Union of Arab Universities, the Syrian gold medal and the international gold medal for invention and creativity. Dr. Al Ostwani is a Member of the International Association of Dental Traumatology and the Syrian Society for Research and Preventive Dentistry since 2017. He is also a Member of the Reviewer Board of International Journal of Dental Medicine (IJDM), and the Indian Journal of Conservative and Endodontics since 2016.",institutionString:"International University for Science and Technology.",institution:{name:"Islamic University of Science and Technology",country:{name:"India"}}},{id:"42847",title:"Dr.",name:"Belma",middleName:null,surname:"Işik Aslan",slug:"belma-isik-aslan",fullName:"Belma Işik Aslan",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/42847/images/system/42847.jpg",biography:"Dr. Belma IşIk Aslan was born in 1976 in Ankara-TURKEY. After graduating from TED Ankara College in 1994, she attended to Gazi University, Faculty of Dentistry in Ankara. She completed her PhD in orthodontic education at Gazi University between 1999-2005. Dr. Işık Aslan stayed at the Providence Hospital Craniofacial Institude and Reconstructive Surgery in Michigan, USA for three months as an observer. She worked as a specialist doctor at Gazi University, Dentistry Faculty, Department of Orthodontics between 2005-2014. She was appointed as associate professor in January, 2014 and as professor in 2021. Dr. Işık Aslan still works as an instructor at the same faculty. She has published a total of 35 articles, 10 book chapters, 39 conference proceedings both internationally and nationally. Also she was the academic editor of the international book 'Current Advances in Orthodontics'. She is a member of the Turkish Orthodontic Society and Turkish Cleft Lip and Palate Society. She is married and has 2 children. Her knowledge of English is at an advanced level.",institutionString:"Gazi University Dentistry Faculty Department of Orthodontics",institution:null},{id:"178412",title:"Associate Prof.",name:"Guhan",middleName:null,surname:"Dergin",slug:"guhan-dergin",fullName:"Guhan Dergin",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/178412/images/6954_n.jpg",biography:"Assoc. Prof. Dr. Gühan Dergin was born in 1973 in Izmit. He graduated from Marmara University Faculty of Dentistry in 1999. He completed his specialty of OMFS surgery in Marmara University Faculty of Dentistry and obtained his PhD degree in 2006. In 2005, he was invited as a visiting doctor in the Oral and Maxillofacial Surgery Department of the University of North Carolina, USA, where he went on a scholarship. Dr. Dergin still continues his academic career as an associate professor in Marmara University Faculty of Dentistry. He has many articles in international and national scientific journals and chapters in books.",institutionString:null,institution:{name:"Marmara University",country:{name:"Turkey"}}},{id:"178414",title:"Prof.",name:"Yusuf",middleName:null,surname:"Emes",slug:"yusuf-emes",fullName:"Yusuf Emes",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/178414/images/6953_n.jpg",biography:"Born in Istanbul in 1974, Dr. Emes graduated from Istanbul University Faculty of Dentistry in 1997 and completed his PhD degree in Istanbul University faculty of Dentistry Department of Oral and Maxillofacial Surgery in 2005. He has papers published in international and national scientific journals, including research articles on implantology, oroantral fistulas, odontogenic cysts, and temporomandibular disorders. Dr. Emes is currently working as a full-time academic staff in Istanbul University faculty of Dentistry Department of Oral and Maxillofacial Surgery.",institutionString:null,institution:{name:"Istanbul University",country:{name:"Turkey"}}},{id:"192229",title:"Ph.D.",name:"Ana Luiza",middleName:null,surname:"De Carvalho Felippini",slug:"ana-luiza-de-carvalho-felippini",fullName:"Ana Luiza De Carvalho Felippini",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/192229/images/system/192229.jpg",biography:null,institutionString:"University of São Paulo",institution:{name:"University of Sao Paulo",country:{name:"Brazil"}}},{id:"256851",title:"Prof.",name:"Ayşe",middleName:null,surname:"Gülşen",slug:"ayse-gulsen",fullName:"Ayşe Gülşen",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/256851/images/9696_n.jpg",biography:"Dr. Ayşe Gülşen graduated in 1990 from Faculty of Dentistry, University of Ankara and did a postgraduate program at University of Gazi. \nShe worked as an observer and research assistant in Craniofacial Surgery Departments in New York, Providence Hospital in Michigan and Chang Gung Memorial Hospital in Taiwan. \nShe works as Craniofacial Orthodontist in Department of Aesthetic, Plastic and Reconstructive Surgery, Faculty of Medicine, University of Gazi, Ankara Turkey since 2004.",institutionString:"Univeristy of Gazi",institution:null},{id:"255366",title:"Prof.",name:"Tosun",middleName:null,surname:"Tosun",slug:"tosun-tosun",fullName:"Tosun Tosun",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/255366/images/7347_n.jpg",biography:"Graduated at the Faculty of Dentistry, University of Istanbul, Turkey in 1989;\nVisitor Assistant at the University of Padua, Italy and Branemark Osseointegration Center of Treviso, Italy between 1993-94;\nPhD thesis on oral implantology in University of Istanbul and was awarded the academic title “Dr.med.dent.”, 1997;\nHe was awarded the academic title “Doç.Dr.” (Associated Professor) in 2003;\nProficiency in Botulinum Toxin Applications, Reading-UK in 2009;\nMastership, RWTH Certificate in Laser Therapy in Dentistry, AALZ-Aachen University, Germany 2009-11;\nMaster of Science (MSc) in Laser Dentistry, University of Genoa, Italy 2013-14.\n\nDr.Tosun worked as Research Assistant in the Department of Oral Implantology, Faculty of Dentistry, University of Istanbul between 1990-2002. \nHe worked part-time as Consultant surgeon in Harvard Medical International Hospitals and John Hopkins Medicine, Istanbul between years 2007-09.\u2028He was contract Professor in the Department of Surgical and Diagnostic Sciences (DI.S.C.), Medical School, University of Genova, Italy between years 2011-16. \nSince 2015 he is visiting Professor at Medical School, University of Plovdiv, Bulgaria. \nCurrently he is Associated Prof.Dr. at the Dental School, Oral Surgery Dept., Istanbul Aydin University and since 2003 he works in his own private clinic in Istanbul, Turkey.\u2028\nDr.Tosun is reviewer in journal ‘Laser in Medical Sciences’, reviewer in journal ‘Folia Medica\\', a Fellow of the International Team for Implantology, Clinical Lecturer of DGZI German Association of Oral Implantology, Expert Lecturer of Laser&Health Academy, Country Representative of World Federation for Laser Dentistry, member of European Federation of Periodontology, member of Academy of Laser Dentistry. Dr.Tosun presents papers in international and national congresses and has scientific publications in international and national journals. He speaks english, spanish, italian and french.",institutionString:null,institution:{name:"Istanbul Aydın University",country:{name:"Turkey"}}},{id:"171887",title:"Prof.",name:"Zühre",middleName:null,surname:"Akarslan",slug:"zuhre-akarslan",fullName:"Zühre Akarslan",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/171887/images/system/171887.jpg",biography:"Zühre Akarslan was born in 1977 in Cyprus. She graduated from Gazi University Faculty of Dentistry, Ankara, Turkey in 2000. \r\nLater she received her Ph.D. degree from the Oral Diagnosis and Radiology Department; which was recently renamed as Oral and Dentomaxillofacial Radiology, from the same university. \r\nShe is working as a full-time Associate Professor and is a lecturer and an academic researcher. \r\nHer expertise areas are dental caries, cancer, dental fear and anxiety, gag reflex in dentistry, oral medicine, and dentomaxillofacial radiology.",institutionString:"Gazi University",institution:{name:"Gazi University",country:{name:"Turkey"}}},{id:"256417",title:"Associate Prof.",name:"Sanaz",middleName:null,surname:"Sadry",slug:"sanaz-sadry",fullName:"Sanaz Sadry",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/256417/images/8106_n.jpg",biography:null,institutionString:null,institution:null},{id:"272237",title:"Dr.",name:"Pinar",middleName:"Kiymet",surname:"Karataban",slug:"pinar-karataban",fullName:"Pinar Karataban",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/272237/images/8911_n.png",biography:"Assist.Prof.Dr.Pınar Kıymet Karataban, DDS PhD \n\nDr.Pınar Kıymet Karataban was born in Istanbul in 1975. After her graduation from Marmara University Faculty of Dentistry in 1998 she started her PhD in Paediatric Dentistry focused on children with special needs; mainly children with Cerebral Palsy. She finished her pHD thesis entitled \\'Investigation of occlusion via cast analysis and evaluation of dental caries prevalance, periodontal status and muscle dysfunctions in children with cerebral palsy” in 2008. She got her Assist. Proffessor degree in Istanbul Aydın University Paediatric Dentistry Department in 2015-2018. ın 2019 she started her new career in Bahcesehir University, Istanbul as Head of Department of Pediatric Dentistry. In 2020 she was accepted to BAU International University, Batumi as Professor of Pediatric Dentistry. She’s a lecturer in the same university meanwhile working part-time in private practice in Ege Dental Studio (https://www.egedisklinigi.com/) a multidisciplinary dental clinic in Istanbul. Her main interests are paleodontology, ancient and contemporary dentistry, oral microbiology, cerebral palsy and special care dentistry. She has national and international publications, scientific reports and is a member of IAPO (International Association for Paleodontology), IADH (International Association of Disability and Oral Health) and EAPD (European Association of Pediatric Dentistry).",institutionString:null,institution:null},{id:"202198",title:"Dr.",name:"Buket",middleName:null,surname:"Aybar",slug:"buket-aybar",fullName:"Buket Aybar",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/202198/images/6955_n.jpg",biography:"Buket Aybar, DDS, PhD, was born in 1971. She graduated from Istanbul University, Faculty of Dentistry, in 1992 and completed her PhD degree on Oral and Maxillofacial Surgery in Istanbul University in 1997.\nDr. Aybar is currently a full-time professor in Istanbul University, Faculty of Dentistry Department of Oral and Maxillofacial Surgery. She has teaching responsibilities in graduate and postgraduate programs. Her clinical practice includes mainly dentoalveolar surgery.\nHer topics of interest are biomaterials science and cell culture studies. She has many articles in international and national scientific journals and chapters in books; she also has participated in several scientific projects supported by Istanbul University Research fund.",institutionString:null,institution:null},{id:"260116",title:"Dr.",name:"Mehmet",middleName:null,surname:"Yaltirik",slug:"mehmet-yaltirik",fullName:"Mehmet Yaltirik",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/260116/images/7413_n.jpg",biography:"Birth Date 25.09.1965\r\nBirth Place Adana- Turkey\r\nSex Male\r\nMarrial Status Bachelor\r\nDriving License Acquired\r\nMother Tongue Turkish\r\n\r\nAddress:\r\nWork:University of Istanbul,Faculty of Dentistry, Department of Oral Surgery and Oral Medicine 34093 Capa,Istanbul- TURKIYE",institutionString:null,institution:null},{id:"172009",title:"Dr.",name:"Fatma Deniz",middleName:null,surname:"Uzuner",slug:"fatma-deniz-uzuner",fullName:"Fatma Deniz Uzuner",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/172009/images/7122_n.jpg",biography:"Dr. Deniz Uzuner was born in 1969 in Kocaeli-TURKEY. After graduating from TED Ankara College in 1986, she attended the Hacettepe University, Faculty of Dentistry in Ankara. \nIn 1993 she attended the Gazi University, Faculty of Dentistry, Department of Orthodontics for her PhD education. After finishing the PhD education, she worked as orthodontist in Ankara Dental Hospital under the Turkish Government, Ministry of Health and in a special Orthodontic Clinic till 2011. Between 2011 and 2016, Dr. Deniz Uzuner worked as a specialist in the Department of Orthodontics, Faculty of Dentistry, Gazi University in Ankara/Turkey. In 2016, she was appointed associate professor. Dr. Deniz Uzuner has authored 23 Journal Papers, 3 Book Chapters and has had 39 oral/poster presentations. She is a member of the Turkish Orthodontic Society. 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