The measured concentration of some pharmaceutical active compounds in some of the aquatic environment in European countries.
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Barely three months into the new year and we are happy to announce a monumental milestone reached - 150 million downloads.
\n\nThis achievement solidifies IntechOpen’s place as a pioneer in Open Access publishing and the home to some of the most relevant scientific research available through Open Access.
\n\nWe are so proud to have worked with so many bright minds throughout the years who have helped us spread knowledge through the power of Open Access and we look forward to continuing to support some of the greatest thinkers of our day.
\n\nThank you for making IntechOpen your place of learning, sharing, and discovery, and here’s to 150 million more!
\n\n\n\n\n'}],latestNews:[{slug:"intechopen-supports-asapbio-s-new-initiative-publish-your-reviews-20220729",title:"IntechOpen Supports ASAPbio’s New Initiative Publish Your Reviews"},{slug:"webinar-introduction-to-open-science-wednesday-18-may-1-pm-cest-20220518",title:"Webinar: Introduction to Open Science | Wednesday 18 May, 1 PM CEST"},{slug:"step-in-the-right-direction-intechopen-launches-a-portfolio-of-open-science-journals-20220414",title:"Step in the Right Direction: IntechOpen Launches a Portfolio of Open Science Journals"},{slug:"let-s-meet-at-london-book-fair-5-7-april-2022-olympia-london-20220321",title:"Let’s meet at London Book Fair, 5-7 April 2022, Olympia London"},{slug:"50-books-published-as-part-of-intechopen-and-knowledge-unlatched-ku-collaboration-20220316",title:"50 Books published as part of IntechOpen and Knowledge Unlatched (KU) Collaboration"},{slug:"intechopen-joins-the-united-nations-sustainable-development-goals-publishers-compact-20221702",title:"IntechOpen joins the United Nations Sustainable Development Goals Publishers Compact"},{slug:"intechopen-signs-exclusive-representation-agreement-with-lsr-libros-servicios-y-representaciones-s-a-de-c-v-20211123",title:"IntechOpen Signs Exclusive Representation Agreement with LSR Libros Servicios y Representaciones S.A. de C.V"},{slug:"intechopen-expands-partnership-with-research4life-20211110",title:"IntechOpen Expands Partnership with Research4Life"}]},book:{item:{type:"book",id:"6851",leadTitle:null,fullTitle:"New Uses of Micro and Nanomaterials",title:"New Uses of Micro and Nanomaterials",subtitle:null,reviewType:"peer-reviewed",abstract:"A fundamental part of modern technology is composed of devices that use special materials as main components. Since the last few decades of the last century and even more recently, a remarkable development has been achieved in new micro- and nanostructured materials with compositional structures and production methods that open unprecedented technological, economic, and ecological perspectives due to high yields, economies of scale, the possibility of reducing weight and size, and the low environmental impact of the equipment that contains them. This book offers a collection of excellent studies that use state-of-the-art methodologies developed by professional researchers from different countries in diverse areas of materials. In this way, this book is particularly useful to academics, scientists, practicing researchers, and postgraduate students whose work relates to the latest nanomaterial technologies.",isbn:"978-1-78984-174-9",printIsbn:"978-1-78984-173-2",pdfIsbn:"978-1-83881-736-7",doi:"10.5772/intechopen.73361",price:119,priceEur:129,priceUsd:155,slug:"new-uses-of-micro-and-nanomaterials",numberOfPages:160,isOpenForSubmission:!1,isInWos:null,isInBkci:!1,hash:"49e0ab8961c52c159da40dd3ec039be0",bookSignature:"Marcelo Rubén Pagnola, Jairo Useche Vivero and Andres Guillermo Marrugo",publishedDate:"October 10th 2018",coverURL:"https://cdn.intechopen.com/books/images_new/6851.jpg",numberOfDownloads:8102,numberOfWosCitations:9,numberOfCrossrefCitations:7,numberOfCrossrefCitationsByBook:1,numberOfDimensionsCitations:13,numberOfDimensionsCitationsByBook:1,hasAltmetrics:1,numberOfTotalCitations:29,isAvailableForWebshopOrdering:!0,dateEndFirstStepPublish:"February 14th 2018",dateEndSecondStepPublish:"March 7th 2018",dateEndThirdStepPublish:"May 6th 2018",dateEndFourthStepPublish:"July 25th 2018",dateEndFifthStepPublish:"September 23rd 2018",currentStepOfPublishingProcess:5,indexedIn:"1,2,3,4,5,6,7",editedByType:"Edited by",kuFlag:!1,featuredMarkup:null,editors:[{id:"112233",title:"Dr.Ing.",name:"Marcelo Rubén",middleName:null,surname:"Pagnola",slug:"marcelo-ruben-pagnola",fullName:"Marcelo Rubén Pagnola",profilePictureURL:"https://mts.intechopen.com/storage/users/112233/images/2164_n.jpg",biography:"Dr. Marcelo Pagnola is a member Researcher of the CONICET and Assistant Professor in the Faculty of Engineering of the University of Buenos Aires. Develops research in Soft and Hard Magnetic Materials areas; amorphous; micro and nanostructured production, by fast cooling production technology, and computational study in routes production. He is currently Director of the Magnetic Materials Plant in the INTECIN (UBA-CONICET) institute, author and co-author of several Invention patents and has a high experience in Technology Transfer to the specific industrial sector. Author of more than forty publications, in congresses and in national and international journals, and director of different national and international projects of scientific collaboration and technology transfer. Guest professor for the dictation of doctorate courses in Materials and Processes in Latin American and Caribbean technological universities.",institutionString:null,position:null,outsideEditionCount:0,totalCites:0,totalAuthoredChapters:"1",totalChapterViews:"0",totalEditedBooks:"1",institution:{name:"University of Buenos Aires",institutionURL:null,country:{name:"Argentina"}}}],equalEditorOne:null,equalEditorTwo:null,equalEditorThree:null,coeditorOne:{id:"234596",title:"Dr.",name:"Jairo",middleName:null,surname:"Useche Vivero",slug:"jairo-useche-vivero",fullName:"Jairo Useche Vivero",profilePictureURL:"https://mts.intechopen.com/storage/users/234596/images/6798_n.jpg",biography:"Is Titular Professor of Mechanical Engineering at the Universidad Tecnológica de Bolivar (UTB) at Cartagena de Indias (Colombia, South America). Dr. Useche received his Dr.Eng. in Mechanical Engineering from the State University of Campinas, Brasil. He received his B.S. in Mechanical Engineering at Universidad Tecnológica de Bolivar and his M.S. in Mechanical Engineering at the Universidad de los Andes, Colombia.\n\nTheir research and consulting expertise includes structural mechanics, structural reliability of buried pipes, pipes and structural panels under blast loads, composite mechanics of naval structures and control of fracture in plates.\n\nCurrently he is the president of the Mechanics of Material Regional Symposium SMEC 2008, 2009, 2011, 2014 and 2016. He is on the scientific committee of Colombian Congress in Numerical Methods - CCMN 2011, CCMN 2013, CCMN 2016 and CCMN 2017",institutionString:null,position:null,outsideEditionCount:0,totalCites:0,totalAuthoredChapters:"0",totalChapterViews:"0",totalEditedBooks:"0",institution:null},coeditorTwo:{id:"243844",title:"Dr.",name:"Andres Guillermo",middleName:"Guillermo",surname:"Marrugo",slug:"andres-guillermo-marrugo",fullName:"Andres Guillermo Marrugo",profilePictureURL:"https://mts.intechopen.com/storage/users/243844/images/6799_n.jpg",biography:"Is currently an Associate Professor in the Department of Mechanical and Mechatronics Engineering at the Technological University of Bolivar, Colombia, where he did his BE in Mechatronics Engineering (Summa Cum Laude). He received his PhD in Optical Engineering (Cum Laude) and an MSc in Photonics from the Technical University of Catalonia, Spain. He was the recipient of the Honours Diploma for Young Researchers from the Spanish Optical Society (SEDOPTICA). His research interests include optical metrology, biomedical image analysis, computer vision, and image processing.",institutionString:null,position:null,outsideEditionCount:0,totalCites:0,totalAuthoredChapters:"0",totalChapterViews:"0",totalEditedBooks:"0",institution:null},coeditorThree:null,coeditorFour:null,coeditorFive:null,topics:[{id:"14",title:"Materials Science",slug:"materials-science"}],chapters:[{id:"62080",title:"The Atomic Layer Deposition Technique for the Fabrication of Memristive Devices: Impact of the Precursor on Pre-deposited Stack Materials",doi:"10.5772/intechopen.78937",slug:"the-atomic-layer-deposition-technique-for-the-fabrication-of-memristive-devices-impact-of-the-precur",totalDownloads:905,totalCrossrefCites:1,totalDimensionsCites:1,hasAltmetrics:0,abstract:"Atomic layer deposition (ALD) is a standard technique employed to grow thin-film oxides for a variety of applications. We describe the technique and demonstrate its use for obtaining memristive devices. The metal/insulator/metal stack is fabricated by means of ALD-grown HfO2, deposited on top of a highly doped Si substrate with an SiO2 film and a Ti electrode. Enhanced device capabilities (forming free, self-limiting current, non-crossing hysteretic current-voltage features) are presented and discussed. Careful analysis of the stack structure by means of X-ray reflectometry, atomic force microscopy, and secondary ion mass spectroscopy revealed a modification of the device stack from the intended sequence, HfO2/Ti/SiO2/Si. Analytical studies unravel an oxidation of the Ti layer which is addressed for the use of the ozone precursor in the HfO2 ALD process. A new deposition process and the model deduced from impedance measurements support our hypothesis: the role played by ozone on the previously deposited Ti layer is found to determine the overall features of the device. Besides, these ALD-tailored multifunctional devices exhibit rectification capability and long enough retention time to deserve their use as memory cells in a crossbar architecture and multibit approach, envisaging other potential applications.",signatures:"Cynthia P. Quinteros, Alex Hardtdegen, Mariano Barella, Federico\nGolmar, Félix Palumbo, Javier Curiale, Susanne Hoffmann-Eifert and\nPablo Levy",downloadPdfUrl:"/chapter/pdf-download/62080",previewPdfUrl:"/chapter/pdf-preview/62080",authors:[{id:"246627",title:"Dr.",name:"Pablo",surname:"Levy",slug:"pablo-levy",fullName:"Pablo Levy"},{id:"248632",title:"Dr.",name:"Cynthia",surname:"Quinteros",slug:"cynthia-quinteros",fullName:"Cynthia Quinteros"},{id:"257726",title:"MSc.",name:"Alexander",surname:"Hardtdegen",slug:"alexander-hardtdegen",fullName:"Alexander Hardtdegen"},{id:"257727",title:"Dr.",name:"Susanne",surname:"Hoffmann-Eifert",slug:"susanne-hoffmann-eifert",fullName:"Susanne Hoffmann-Eifert"},{id:"257728",title:"Dr.",name:"Mariano",surname:"Barella",slug:"mariano-barella",fullName:"Mariano Barella"},{id:"257729",title:"Dr.",name:"Federico",surname:"Golmar",slug:"federico-golmar",fullName:"Federico Golmar"},{id:"257730",title:"Dr.",name:"Félix",surname:"Palumbo",slug:"felix-palumbo",fullName:"Félix Palumbo"},{id:"257731",title:"Dr.",name:"Javier",surname:"Curiale",slug:"javier-curiale",fullName:"Javier Curiale"}],corrections:null},{id:"62981",title:"Mechanisms of Significant Precipitation Hardening in a Medium Carbon Bainitic Steel by Complex Nanocarbides Composed of Nb, Ti and V",doi:"10.5772/intechopen.80273",slug:"mechanisms-of-significant-precipitation-hardening-in-a-medium-carbon-bainitic-steel-by-complex-nanoc",totalDownloads:911,totalCrossrefCites:0,totalDimensionsCites:0,hasAltmetrics:0,abstract:"Precipitation-hardening behavior of various medium carbon bainitic steels with added elements of Nb, Ti and V was systematically investigated. Complex nanocarbides composed of Nb, Ti and V precipitated after aging in the steel with multiple additions of all the elements, whereas those with added individual elements were simple MC types. The amount of precipitation hardening (ΔHv) after aging at 873 K of the former steel was approximately 90 ΔHv, while those of the latter were less than 40 ΔHv at best. Therefore, significant precipitation hardening took place by multiple element addition. The different amount of precipitation hardening depending on added elements was reasonably understood by considering misfit parameters between carbides and ferrite matrix.",signatures:"Makoto Okonogi, Takuya Hara and Hiromi Miura",downloadPdfUrl:"/chapter/pdf-download/62981",previewPdfUrl:"/chapter/pdf-preview/62981",authors:[{id:"256222",title:"Prof.",name:"Hiromi",surname:"Miura",slug:"hiromi-miura",fullName:"Hiromi Miura"}],corrections:null},{id:"61386",title:"Elaboration of Nanoporous Copper via Chemical Composition Design of Amorphous Precursor Alloys",doi:"10.5772/intechopen.77222",slug:"elaboration-of-nanoporous-copper-via-chemical-composition-design-of-amorphous-precursor-alloys",totalDownloads:900,totalCrossrefCites:0,totalDimensionsCites:1,hasAltmetrics:0,abstract:"Au-group (Ag, Au) and Pt-group (Ni, Pd, Pt) metals have lower surface diffusion coefficients than Cu and are defined as LSD. The chemical composition has been designed based on the differences in diffusion coefficients, and the micro-alloying of 1 at % LSD metals with the Ti60Cu40 amorphous precursor alloy results in the formation of bi-continuous nanoporous copper (NPC) with finer nanoporous structure. LSD-stabilized NPCs have the smallest characteristic pore sizes of 7 nm and 6 nm after dealloying amorphous Ti60Cu39Pd1 and Ti60Cu39Pt1 precursor alloys, while NPC had a pore size of 39 nm after dealloying the amorphous Ti60Cu40 alloy. The refining factor increases approximately from 3.7 for Ti60Cu39Ag1 to 1780 for Ti60Cu39Pt1 precursors due to the dramatic decrease in the surface diffusivity during both preferential dissolution and rearrangement of Cu adatoms. The elaboration efficiencies of Ti60Cu40 alloy with addition of 1 at.% Pt-group elements are higher than those of Au-group elements. The homogeneous distribution of LSD elements in both the precursors and final stabilized NPCs played a key role in restriction of the long-distance diffusion of Cu adatoms. LSD-stabilized NPCs are able to have an ultrafine nanoporosity with a pore size almost one order smaller than that from LSD-free alloys.",signatures:"Zhenhua Dan, Fengxiang Qin, Izumi Muto, Nobuyoshi Hara and Hui\nChang",downloadPdfUrl:"/chapter/pdf-download/61386",previewPdfUrl:"/chapter/pdf-preview/61386",authors:[{id:"250556",title:"Prof.",name:"Zhenhua",surname:"Dan",slug:"zhenhua-dan",fullName:"Zhenhua Dan"},{id:"251527",title:"Prof.",name:"Fengxiang",surname:"Qin",slug:"fengxiang-qin",fullName:"Fengxiang Qin"},{id:"251528",title:"Prof.",name:"Izumi",surname:"Muto",slug:"izumi-muto",fullName:"Izumi Muto"},{id:"251529",title:"Prof.",name:"Nobuyoshi",surname:"Hara",slug:"nobuyoshi-hara",fullName:"Nobuyoshi Hara"},{id:"251530",title:"Prof.",name:"Hui",surname:"Chang",slug:"hui-chang",fullName:"Hui Chang"}],corrections:null},{id:"62264",title:"Sub-2 μm Silica Particles in Chiral Separation",doi:"10.5772/intechopen.79063",slug:"sub-2-m-silica-particles-in-chiral-separation",totalDownloads:1109,totalCrossrefCites:0,totalDimensionsCites:1,hasAltmetrics:1,abstract:"For decades, the race for the shortest chromatogram with the best resolution and separation efficiency has been the focus of researchers and manufacturers. Considerable advancement has been attained in the field of separation science with the widespread applications and outstanding performance of nanomaterials. According to the van Deemter equation, sub-2 micron particles employed in a conventional HPLC short column should subsequently result in analysis time reduction and efficiency improvements without the drawbacks of high pressure associated with sub-2 micron particles. This chapter provides comprehensive discussion about the applications of the new sub 2 microns silica particles in chiral separation of racemates.",signatures:"Diana Ibrahim and Ashraf Ghanem",downloadPdfUrl:"/chapter/pdf-download/62264",previewPdfUrl:"/chapter/pdf-preview/62264",authors:[{id:"248201",title:"Prof.",name:"Ashraf",surname:"Ghanem",slug:"ashraf-ghanem",fullName:"Ashraf Ghanem"},{id:"257715",title:"BSc.",name:"Diana",surname:"Ibrahim",slug:"diana-ibrahim",fullName:"Diana Ibrahim"}],corrections:null},{id:"62176",title:"Polymeric Micro- and Nanosystems for Wood Artifacts Preservation",doi:"10.5772/intechopen.79135",slug:"polymeric-micro-and-nanosystems-for-wood-artifacts-preservation",totalDownloads:1039,totalCrossrefCites:3,totalDimensionsCites:5,hasAltmetrics:0,abstract:"The complex methods of diagnosis investigation of the wood artifacts state and proper materials for their protection against decay are very important goals in cultural heritage. This chapter focuses on the recent trends in micro- and nanostructured polymer systems for application in cultural heritage and on wood preservation, especially. The synthesis, properties, and applications, as well as the relevant analysis techniques to reveal the structures and properties of polymer systems, are discussed, too. To overcome the specific problems that exist for wood artifacts, some aspects should be treated: effects of the environmental factors, as moisture and pollutant absorption into the wood fibers, over-exposure effect of sun or artificial light sources, biological attack of different microorganisms, and the effects of the protective and decorative coatings.",signatures:"Rodica-Mariana Ion, Ramona-Marina Grigorescu, Lorena Iancu, Paul\nGhioca and Nicoleta Radu",downloadPdfUrl:"/chapter/pdf-download/62176",previewPdfUrl:"/chapter/pdf-preview/62176",authors:[{id:"28004",title:"Dr.",name:"Nicoleta",surname:"Radu",slug:"nicoleta-radu",fullName:"Nicoleta Radu"},{id:"171504",title:"Prof.",name:"Rodica-Mariana",surname:"Ion",slug:"rodica-mariana-ion",fullName:"Rodica-Mariana Ion"},{id:"243710",title:"MSc.",name:"Lorena",surname:"Iancu",slug:"lorena-iancu",fullName:"Lorena Iancu"},{id:"248937",title:"Dr.",name:"Ramona Marina",surname:"Grigorescu",slug:"ramona-marina-grigorescu",fullName:"Ramona Marina Grigorescu"},{id:"248939",title:"Mr.",name:"Paul",surname:"Ghioca",slug:"paul-ghioca",fullName:"Paul Ghioca"}],corrections:null},{id:"63139",title:"Magnetic Materials by Melt Spinning Method, Structural Characterization, and Numerical Modeling",doi:"10.5772/intechopen.77368",slug:"magnetic-materials-by-melt-spinning-method-structural-characterization-and-numerical-modeling",totalDownloads:987,totalCrossrefCites:0,totalDimensionsCites:1,hasAltmetrics:1,abstract:"Chill block melt spinning is used in industrial processes for the production of metallic glasses. It is a rapid solidification process whereby a liquid metal is ejected at high pressure and temperature via a nozzle onto a rotating wheel solidifying in the form of a ribbon. In this work, starting from an alloy with the composition of Fe78Si9B13 (% at.) reproduces the melt spinning technique to get the amorphous magnetic material. A CFD3D model based on the finite volume method (FVM) is proposed. For this purpose, the OpenFoam® open source code is used. In the ribbon production stage, it has been observed that the turbulence involved in the first reported transient lasts a few milliseconds, enough time to study the process with high-speed cameras. We measure the ejection speed by using optical flow on the melt contour. This enables us to check defects in the ribbons, which are predicted with the computational model, such as the case of cracks caused by irregularities in the first formation of the solid layer. The temperature measurement method relies on the fact that the digital camera is sensitive to electromagnetic radiation between 400 and 1000 nm in wavelength and the fact that the image gray level, which is proportional to the temperature T, provided the background illumination level is negligible.",signatures:"Marcelo Rubén Pagnola, Jairo Useche Vivero and Andrés G.\nMarrugo",downloadPdfUrl:"/chapter/pdf-download/63139",previewPdfUrl:"/chapter/pdf-preview/63139",authors:[{id:"234588",title:"Dr.",name:"Marcelo",surname:"Pagnola",slug:"marcelo-pagnola",fullName:"Marcelo Pagnola"},{id:"255253",title:"Dr.",name:"Jairo",surname:"Useche Vivero",slug:"jairo-useche-vivero",fullName:"Jairo Useche Vivero"},{id:"255254",title:"Dr.",name:"Andres",surname:"Marrugo",slug:"andres-marrugo",fullName:"Andres Marrugo"}],corrections:null},{id:"62878",title:"Nanomaterials in Structural Engineering",doi:"10.5772/intechopen.79995",slug:"nanomaterials-in-structural-engineering",totalDownloads:1221,totalCrossrefCites:2,totalDimensionsCites:3,hasAltmetrics:0,abstract:"Development of structural engineering, daring structures with record spans or heights, meets two serious obstacles—the limitations of traditionally used materials and the need of continuous monitoring of new structures subjected to complex loads, including those of dynamic nature. Considering the responsibility for the life of people and the budget of new structures, the need of constant monitoring is inevitable. This is why structural engineers seek for new solutions; among them, smart structures based on self-monitoring materials seem to be one of the most attractive proposals. It is still an unexplored area, but current research shows a high potential of the use of composites reinforced by carbon-based nanomaterials as self-sensing structural materials. Nanomaterials also influence other important features of structural materials, such as microstructure, mechanical, and transport-related properties. In this chapter, we present the state of art of the use of nanomaterials in structural engineering in various areas including mechanical and electrical properties as well as issues referring to durability.",signatures:"Małgorzata Krystek and Marcin Górski",downloadPdfUrl:"/chapter/pdf-download/62878",previewPdfUrl:"/chapter/pdf-preview/62878",authors:[{id:"246152",title:"Dr.",name:"Marcin",surname:"Gorski",slug:"marcin-gorski",fullName:"Marcin Gorski"},{id:"263764",title:"MSc.",name:"Małgorzata",surname:"Krystek",slug:"malgorzata-krystek",fullName:"Małgorzata Krystek"}],corrections:null},{id:"62107",title:"Nanostructured Oxide Semiconductor Compounds with Possible Applications for Gas Sensors",doi:"10.5772/intechopen.79079",slug:"nanostructured-oxide-semiconductor-compounds-with-possible-applications-for-gas-sensors",totalDownloads:1030,totalCrossrefCites:1,totalDimensionsCites:1,hasAltmetrics:0,abstract:"Nanostructured oxide semiconductor compounds have gained a big importance, in basic and mostly in applicative researches, due to their unique properties, and their increased potential of utilization as sensors in various electronic and optoelectronic devices. The development of devices based on semiconductor materials as gas sensors has been visible during the recent years, due to their low manufacturing cost. Because the basic materials and the manufacturing processes are critical for gas sensors high performance, they need to be studied and capitalized in practice. Among the new technologies, the production of nanocrystalline materials and hybrid structures offer huge opportunities to improve sensitivity, selectivity and response time, as a consequence of the intensification of gas-sensor interaction. In this study, a series of nanostructured oxide semiconductor compounds with a spinel-type structure and perovskite, respectively, based on transition metals and synthesized by the sol-gel self-combustion method, with possible applications for resistive gas sensors, are presented.",signatures:"Corneliu Doroftei and Liviu Leontie",downloadPdfUrl:"/chapter/pdf-download/62107",previewPdfUrl:"/chapter/pdf-preview/62107",authors:[{id:"246571",title:"Ph.D.",name:"Corneliu",surname:"Doroftei",slug:"corneliu-doroftei",fullName:"Corneliu Doroftei"},{id:"258326",title:"Prof.",name:"Liviu",surname:"Leontie",slug:"liviu-leontie",fullName:"Liviu Leontie"}],corrections:null}],productType:{id:"1",title:"Edited Volume",chapterContentType:"chapter",authoredCaption:"Edited by"},subseries:null,tags:null},relatedBooks:[{type:"book",id:"6320",title:"Advances in Glass Science and Technology",subtitle:null,isOpenForSubmission:!1,hash:"6d0a32a0cf9806bccd04101a8b6e1b95",slug:"advances-in-glass-science-and-technology",bookSignature:"Vincenzo M. 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\r\n\tAcademicians and policy-makers are always searching for new econometric methods to answer specific policy questions. More importantly, the advent in the advances of computing power has enabled more advanced econometric techniques to be computed with ease. Econometrics uses statistical methods and real-world data to predict and establish specific trends within economics and other social sciences.
\r\n\r\n\tThis volume attempts to explore the practical aspects of econometrics to economics, and other social sciences that use econometric methods. This volume is expected to cover a broad range of topics that include but are not limited to spatial econometrics, time series, forecasting, and machine learning, This volume hopes to attract dynamic stochastic general equilibrium (DSGE) models which are gaining prominence in applied macroeconomics. This proposed volume could serve as a reference for academicians, researchers, policy-makers, graduate students, and very abled undergraduate students who are seeking current research on the various applications of econometrics as used in research and to answer specific policy questions.
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Working knowledge of MATHLAB and Dynare.\n\nResearch Fellow, Global Labor Organization (GLO), Oct.2017 to present\nAcademic and Professional Profiles \nResearch gate Profile:https: // www. researchgate. net/ profile/ Brian_ Sloboda\nORCID:https: // orcid. org/ 0000-0003-0007-1725\nGoogle Scholar Profile https: // scholar. google. com/ citations? user= RSLTrCsAAAAJ&hl= en\nEducation: Ph.D. Economics, Southern Illinois University at Carbondale,1997.\nThesis: The Economic Impact of Southern Illinois University on the State of Illinois: The Human Capital Approach\nM.S. Economics, Southern Illinois University at Carbondale,1992.\nB.A. Economics, Rowan University,1990.Minor: Mathematics.\nFields of Interest: Regional Economics, Economic Growth, Labor Economics, Economic and Statistical Education",institutionString:"University of Maryland, Global Campus",position:null,outsideEditionCount:0,totalCites:0,totalAuthoredChapters:"0",totalChapterViews:"0",totalEditedBooks:"0",institution:null}],coeditorOne:null,coeditorTwo:null,coeditorThree:null,coeditorFour:null,coeditorFive:null,topics:[{id:"7",title:"Business, Management and Economics",slug:"business-management-and-economics"}],chapters:null,productType:{id:"1",title:"Edited Volume",chapterContentType:"chapter",authoredCaption:"Edited by"},personalPublishingAssistant:{id:"429339",firstName:"Jelena",lastName:"Vrdoljak",middleName:null,title:"Ms.",imageUrl:"https://mts.intechopen.com/storage/users/429339/images/20012_n.jpg",email:"jelena.v@intechopen.com",biography:"As an Author Service Manager, my responsibilities include monitoring and facilitating all publishing activities for authors and editors. From chapter submission and review to approval and revision, copyediting and design, until final publication, I work closely with authors and editors to ensure a simple and easy publishing process. I maintain constant and effective communication with authors, editors and reviewers, which allows for a level of personal support that enables contributors to fully commit and concentrate on the chapters they are writing, editing, or reviewing. I assist authors in the preparation of their full chapter submissions and track important deadlines and ensure they are met. I help to coordinate internal processes such as linguistic review, and monitor the technical aspects of the process. As an ASM I am also involved in the acquisition of editors. Whether that be identifying an exceptional author and proposing an editorship collaboration, or contacting researchers who would like the opportunity to work with IntechOpen, I establish and help manage author and editor acquisition and contact."}},relatedBooks:[{type:"book",id:"1591",title:"Infrared Spectroscopy",subtitle:"Materials Science, Engineering and Technology",isOpenForSubmission:!1,hash:"99b4b7b71a8caeb693ed762b40b017f4",slug:"infrared-spectroscopy-materials-science-engineering-and-technology",bookSignature:"Theophile Theophanides",coverURL:"https://cdn.intechopen.com/books/images_new/1591.jpg",editedByType:"Edited by",editors:[{id:"37194",title:"Dr.",name:"Theophile",surname:"Theophanides",slug:"theophile-theophanides",fullName:"Theophile Theophanides"}],productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}},{type:"book",id:"3161",title:"Frontiers in Guided Wave Optics and Optoelectronics",subtitle:null,isOpenForSubmission:!1,hash:"deb44e9c99f82bbce1083abea743146c",slug:"frontiers-in-guided-wave-optics-and-optoelectronics",bookSignature:"Bishnu Pal",coverURL:"https://cdn.intechopen.com/books/images_new/3161.jpg",editedByType:"Edited by",editors:[{id:"4782",title:"Prof.",name:"Bishnu",surname:"Pal",slug:"bishnu-pal",fullName:"Bishnu Pal"}],productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}},{type:"book",id:"371",title:"Abiotic Stress in Plants",subtitle:"Mechanisms and Adaptations",isOpenForSubmission:!1,hash:"588466f487e307619849d72389178a74",slug:"abiotic-stress-in-plants-mechanisms-and-adaptations",bookSignature:"Arun Shanker and B. 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Pharmaceutical active compounds are natural or synthetic chemicals that can be found in over-the-counter therapeutic drugs and veterinary drugs. They induce pharmacological effect and give significant benefits to human beings. A continuous release of these chemical compounds into aquatic environment has been increased due to the increase of general use of pharmaceutical compounds in human and veterinary medicines. Figure 1 illustrates the routes of releasing the pharmaceutical compounds into water. These routes include wastewater effluents, human and animal excreta, sewage sludge, medical and industrial waste and land fill leaching [1].
\nRoutes of releasing the pharmaceutical compounds into the environment.
Depending on the biodegradability and hydrophobicity of these pharmaceutical active compounds, they are naturally reduced by dilution, degradation and adsorption in the environment. Thus, these compounds in water exist in a trace concentration level [2].
\nSome of the pharmaceutical active compounds used for birth control, heart medication and painkilling were detected in wastewater in the United State of America (USA) since more than 40 years ago [3, 4, 5]. Literature shows that the pharmaceutical active compounds enter the surface water through different sources such as excretion, bathing, effluent discharging, improper disposal of these compounds and veterinary facilities [1, 6, 7, 8]. In addition, a study conducted in the United Kingdom by Drinking Water Inspectorate reported that many classes of pharmaceutical active compounds are present in wastewater influent [9]. Table 1 represents several pharmaceutical active compounds that were detected in the aquatic environment of United Kingdom (UK) and other European countries [10, 11].
\nPharmaceutical active compounds | \nMaximum detected concentration (ng/L) | \nAquatic environment type | \n
---|---|---|
Bleomycin | \n19 (United Kingdom) | \nSewage | \n
Clotrimazole | \n34 (United Kingdom) | \nStream or river water | \n
Diclofenac | \n1200 (Germany) 41 (France) 40 (Finland) 64 (Austria) | \nSurface water | \n
Carbamazepine | \n110 (Germany) 800 (France) 370 (Finland) 64 (Austria) | \nSurface water | \n
Iopromide | \n910 (Germany) 17 (France) 211 (Austria) | \nSurface water | \n
Roxithromycin | \n560 (Germany) 37 (France) | \nSurface water | \n
Ibuprofen | \n530 (Germany) 120 (France) 65 (Finland) | \nSurface water | \n
Erythromycin | \n80 (United Kingdom) | \nRiver water | \n
Fluoxetine | \n290 (United Kingdom) | \nSewage | \n
Mefenamic acid | \n1440 (United Kingdom) | \nSewage | \n
Paracetamol | \n< 20 (United Kingdom) | \nSewage | \n
Propranolol | \n215 (United Kingdom) | \nRiver water | \n
Tamoxifen | \n42 (United Kingdom) | \nSewage | \n
Tetracycline | \n1000 (United Kingdom) | \nRiver water | \n
Trimethoprim | \n1288 (United Kingdom) | \nSewage | \n
The measured concentration of some pharmaceutical active compounds in some of the aquatic environment in European countries.
Pharmaceutical active compound | \nCarbon-based adsorbent | \nAdsorption capacity (mg/g) | \nReference | \n
---|---|---|---|
Clofibric acid | \nMesoporous silica SBA-15 | \n70 | \n[70] | \n
Ofloxacin | \nNonporous SiO2\n | \n2.1 | \n[71] | \n
Tetracycline | \nMesoporous silica | \n44.4 | \n[27] | \n
Cephalexin | \nAmberlite XAD-16 polymer | \n116 | \n[36] | \n
Nalidixic acid | \nPolystyrene-divinylbenzene, X16 | \n800 | \n[31] | \n
Penicillin | \nPolymer Amberlite XAD-16 | \n1401 | \n[34] | \n
Amoxicillin | \nBentonite clay | \n53.9 | \n[38] | \n
Flurbiprofen | \nOrganophilic montmorillonite clay | \n240 | \n[39] | \n
Tetracycline | \nNa-kaolinite | \n29 | \n[40] | \n
Kaolinite | \n3.8 | \n[72] | \n|
Rectorite clay | \n40 | \n[46] | \n|
Tetracycline | \nNaOH-activated carbon produced from macadamia nut shells | \n455.33 | \n[48] | \n
H3PO4-activated carbon produced from apricot nut shells | \n308.3 | \n[49] | \n|
Activated carbons produced by KOH activation of tyre pyrolysis char | \n312 | \n[50] | \n|
Commercial activated carbon | \n471 | \n[51] | \n|
Sulfamethoxazole | \nAC | \n185 | \n[53] | \n
Metronidazole | \nAC | \n93.21 | \n[53] | \n
CAC | \n328 | \n[52] | \n|
Amoxicillin | \nAC | \n221.8 | \n[73] | \n
Dimetridazole | \nCAC | \n186 | \n[52] | \n
Ronidazole | \nCAC | \n394 | \n[52] | \n
Tinidazole | \nCAC | \n385 | \n[52] | \n
Penicillin G | \nAC | \n315 | \n[56] | \n
Oxytetracycline | \nMWNT10 | \n190.2 | \n[54] | \n
Tetracycline | \nMWNTs | \n148 | \n[58] | \n
SWNTs | \n370 | \n||
Tylosin | \nK-MWNTs | \n270 | \n[58] | \n
K-SWNTs | \n466 | \n||
Carbamazepine | \nMWNT100 | \n41.4 | \n[58] | \n
Cephalexin | \nCellulose oxide | \n79 | \n[59] | \n
Fluoroquinolone | \nGoethite | \n49.6 | \n[61] | \n
Ciprofloxacin | \nHydrous oxides of Al (HAO) | \n13.6 | \n[64] | \n
Different adsorbents and their adsorption capacities for removal of pharmaceutical active compounds.
There is no international standard method for drinking water sampling and method of analysis for pharmaceutical active compounds. In addition, a few systematic monitoring studies on measuring the pharmaceutical active compounds in surface water, drinking water and ground water were conducted. Therefore, limited data are available on their occurrence in these aquatic environments to be used in assessing the potential health risk due to the exposure to a trace concentration level of pharmaceutical compounds. However, literature showed that the surface water and ground water sources affected by wastewater discharges have pharmaceutical active compound concentrations less than 100 ng/L, while these compounds were found in the drinking water with a concentration less than 50 ng/L [2].
\nThe presence of these compounds at trace concentration levels (nanogram to sub microgram per liter) in the aquatic environment has raised a question concerning the efficiency of wastewater treatment techniques in removing of the pharmaceutical active compounds. Many removal techniques such as chlorination, photocatalysis, adsorption, biodegradation and advanced oxidation or ozonation have been investigated for the removal of pharmaceutical active compounds from the aquatic environment [12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25]. Some of these techniques have different disadvantages such as their high cost, high energy consumption and formation of toxic by-products. Adsorption technique has many advantages over these techniques such as it works at mild operation conditions, requires low energy and is efficient and cost-effective. Therefore, it is a promising technique for the removal of pharmaceutical active compounds.
\nThe removal of pharmaceutical active compounds from water by adsorption is considered as one of the easiest and safest techniques since it is easy to design and operate and this technique does not produce any toxic wastes as a by-product and is capable of removing most forms of organic material. The adsorption process includes the accumulation of pharmaceutical compounds on the adsorbent’s surface. Hence, the selection of adsorbent must be precious. The adsorbent must have a capability to accumulate the pollutant from water with high surface area and high hydrophobicity. The efficiency of this technique is mainly depending on the functional group composition, surface area, pore size and the ash content. It also depends on the chemical parameters like temperature, polarity, pH, concentration of the adsorbate and the availability of other competing solutes. The adsorption process also depends on the mobility of the adsorbate molecules toward the external boundary layer of the adsorbent, active surface sites and surface pore size. Many researchers have studied the adsorption of pharmaceutical active compounds from wastewater using different types of adsorbents. Several materials as an adsorbent have been reported in the literature and listed in Table 2 and were tested and investigated for the pharmaceutical active compounds’ removal from aquatic environment, such as silica-based adsorbents [26, 27, 28, 29, 30], polymeric materials [31, 32, 33, 34, 35, 36, 37], clay [38, 39, 40, 41, 42, 43, 44, 45, 46, 47], carbonaceous materials [48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58] and other materials [59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71]. The next sections focus on carbonaceous materials as adsorbents, namely activated carbon and carbon nanotubes.
\nActivated carbon is a pure carbon graphite form with amorphous and highly porous structure. It contains different range of pore sizes starting from cracks to slits of molecular dimensions [73]. The first produced commercially activated carbon was in early nineteenth century from wood as a raw material. It has been used for water odor and taste control in 1930 [74]. Nowadays, activated carbon is produced from a wide range of raw organic materials and sources, such as sugar, shells, refinery coke, rice hulls and different types of wood. The main features of activated carbon that make it good as an adsorbent in the adsorption process are the following: (i) its high surface area, (ii) its porosity and (iii) its surface reactivity.
\nActivated carbon can be classified based on its activation process or its properties. Based on the activation process, the following are the main two categories based on the activation process:
Physically or thermally activated carbon: the activation process involves carbonization of organic raw materials at temperature ranging from 500°C to 600°C [75].
Chemically activated carbon: the activation process involves addition of some inorganic salts such as metallic chloride to activate the surface of carbon [76].
Mattson et al. [77] suggested another classification, which categorizes activated carbon to acidic or basic activated carbon:
Carbon activated at low temperature range from 200°C to 400°C: this develops an acidic surface that lowers the pH value of the solution. This activated carbon exhibits negative zeta potential and usually adsorbs basic and hydrophilic compounds.
Carbon activated at a high temperature range from 800°C to 1000°C: this develops basic surface that increases the pH value of the solution. Therefore, this type of activated carbon has a positive zeta potential and is usually used for adsorbing acidic organic compounds.
Commercially, activated carbon can be classified as three main types [78], and they are the following:
Powdered activated carbon (PAC): it has fine granules or powder with particle size less than 1.0 mm and average diameters ranging between 0.15 and 0.25 mm.
Granular activated carbon (GAC): it combines powdered activated carbon with a binder and forms cylindrical shape activated carbon particles with diameters from 0.8 to 130 mm. The main application for this form is for gas purification.
Impregnated activated carbon (IAC): it is impregnated with different inorganic ions.
Polymeric coated activated carbon, which is used in medical field applications.
The properties of activated carbon are influenced by the used raw materials and activation method in its preparation process. The porous graphite and graphene sheets that form the activated carbon are connected together and have π-orbitals in the benzene rings, which enable several modifications to be carried out on activated carbon. For example, cooling the activated carbon in the presence of oxygen can produce activated carbon rich with oxides and acidic functional groups, as a result, alter the positive zeta potential of basic activated carbon to negative to be used for different applications. In addition, the surface chemistry, pore structure (volume and diameter) and surface area of activated carbon depend significantly on the employed temperature in the preparation process [75, 79].
\nA wide range of raw materials can be used as a starting material for producing activated carbon as stated in Section 2.1.1. The following activation methods are used in activated carbon production:
Thermal activation: this physical process may involve two main steps: the first one to eliminate the volatile matters in the raw materials by carbonizing them thermally at a temperature ranging from 500°C to 600°C and in the second step the porosity and surface are improved by the gasification process. In the gasification process, a carbon dioxide CO2, methane or steam as an oxidizing gas is used at a high temperature of 800–1000°C [75].
Chemical activation: in this process, inorganic salts such as metallic chloride are added before the carbonization step to improve the micro-porosity as well as the surface area of the activated carbon [76].
Activated carbon (AC) is widely used in adsorption processes as filtration and purification materials. For instance, in water treatment, activated carbon is used to control taste and odor and to adsorb undesired suspended metals and pollutants [74]. Due to the high surface area and commercial availability of AC, it was studied for removal of different pharmaceutical active compounds. Table 3 summarizes some of these pharmaceuticals. For example, different types of activated carbon were used for removal of tetracycline (antibiotic drug) from aqueous media. Martins et al. [48] prepared activated carbon from macadamia shells as precursors, the yield was 19.79% and the prepared activated carbon’s surface area was 1524 m2/g. They used it for the tetracycline removal and it had 455.33 mg/g adsorption capacity. Muthanna et al. [80] reported that the activated carbon was used for removal of three pharmaceutical active compounds (i.e., tetracycline, penicillins and quinolones) and the used activated carbon has 1340.8 mg/g adsorption capacity for tetracycline. Chen et al. [81] studied the effect of the adsorption parameters (i.e., pH, contact time, initial concentration and temperature) on the removal of tetracycline from aqueous solution using rice husk ash (RHA). They found the adsorption capacity increased from 1.51 to 3.41 mg/g when the initial tetracycline concentration in the solution increased from 5 to 20 mg/l. Another study showed that activated carbon prepared via a chemical activation of apricot shells using phosphoric acid heated in air at 100 °C for 24 hours has 307.6 m2/g surface area and 308.3 mg/g adsorption capacity [49]. In 2016, an activated carbon (TPC-AC) was prepared from tires waste by their pyrolysis and then activated using potassium hydroxide [50]. The prepared adsorbent was tested for tetracycline removal and it has been found that the adsorption process was spontaneous and has adsorption capacity (312 mg/g) higher than the commercial activated carbon. Carl et al. [51] reported that the adsorption capacity of the commercial activated carbon for tetracycline is directly related to the density of π electrons in the graphene layers on activated carbon and the aromatic ring in the tetracycline.
\nSingle and multiwall carbon nanotube (CNT) materials are graphene sheets rolled-up tubular individually or more than one inside each other. CNTs were discovered by Sumio Ijima in 1991 at NEC Laboratory in Japan using the Arc discharge production method and then characterized using a transmission electron microscope [82]. CNTs have two different structures based on the rolling direction of graphene sheets: (i) armchair nanotube and (ii) zigzag nanotube structure [83] as shown in Figure 2.
\nArmchair and zigzag structural forms of CNTs
The cylindrical shape of CNT nanostructure can have a length to diameter ration up to 132,000,000:1, which is significantly higher than any other materials [83]. This property was explained by the sp2 hybridization in the carbon atoms that CNTs are composed of in addition to the natural alignment of CNT into ropes attracted together by Van der Waals interaction [84].
\nCNTs form bundles of a highly complex network [85]. They have electrical conductivity that depends on the arrangement of the hexagonal rings along the tubular surface. Due to their extraordinary properties, such as large geometric aspect ratio, nanocavities and electrical conductivity, CNTs are considered as attractive candidates in many nanotechnological applications, including the removal of pharmaceutical compounds in water treatment processes. One of the main drawbacks of carbon nanotubes is that they do not have good suspension properties in aqueous and organic solvents that in turn has made CNTs’ use in industry limited [86]. This disadvantage can be overridden by modifying CNTs chemically with some hydrophilic functional groups that in turn increase CNTs’ suspension in water.
\nThe main distinct properties of the carbon nanotubes are categorized into the following:
Mechanical properties: due to the covalent sp2 bonds formed between the individual carbon atoms, CNTs have high strength and stiffness. According to the reported results, CNTs have elasticity higher than steel by 10–100 times with an elastic modulus 1Tpa [87]. A comparison between some materials, which have good mechanical properties, with CNTs is shown in Table 3.
Physical property | \nMaterial name | \n||||
---|---|---|---|---|---|
\n | MWCNTs | \nSWCNTs | \nWood | \nSteel | \nEpoxy | \n
Density (g/cm3) | \n2.6 | \n2.6 | \n0.6 | \n7.8 | \n1.25 | \n
Tensile strength (Gpa) | \n150 | \n150 | \n0.008 | \n0.4 | \n0.005 | \n
Young’s modulus (Gpa) | \n1200 | \n1054 | \n0.6 | \n208 | \n3.5 | \n
Comparison between CNTs and other materials.
Thermal conductivity: CNTs have thermal conductivity ranging from 2800 up to 6000 W/m K [88].
Electrical properties: CNT carbon-based material exhibits extraordinary electrical properties and it can be conducting or semiconducting material. The conductive CNTs are found to carry electrical current thousand times higher than copper material [89].
Chemical reactivity: CNTs can chemically be modified to make them highly soluble in aqueous and organic solutions as well as more efficient for certain applications. Their reactivity is related to the mismatching of π-orbitals, which are caused by the curvatures in CNTs’ structure. In general, smaller nanotube diameters result in increasing their reactivity. Moreover, the reported results showed that chemical modification of sidewalls or end caps of CNTs are also possible [90].
Based on the CNTs’ properties that have been discussed above, CNT materials and their modified structures are promising for different applications such as water treatment, environmental protection and pharmaceutical active compound removal, material science, medicinal chemistry and others.
\nCNTs are produced using different techniques, and the most common and widely used techniques are:
\nArc discharge technique. Arc discharge technique is the most common and simplest technique for CNT production. As mentioned earlier, CNTs were firstly discovered using this technique. In arc discharge technique, CNTs are produced at low pressure of helium inert gas or any other neutral gas [91]. They are produced through arc vaporization of two separated carbon rods in an enclosed system filled with inert gas [92]. One of the major disadvantages of CNT production using this technique is that the produced CNTs are not pure containing some of the catalytic metals; therefore, they require purification to remove these metals and get clean CNTs.
Laser ablation technique. In 1995, carbon nanotubes were synthesized using a laser beam to vaporize graphite at 1200°C [93]. The pulsed and continuous laser methods are the main two types of laser ablations. Much higher light intensity (100 kW/cm2) is used in the pulsed laser, compared to 12 kW/cm2 in case of the continuous laser type, which is the main difference between these two laser ablation technique types. In the laser ablation method, CNTs are produced and collected on a cooler surface in the reactor system as the vaporized carbon is condensed. In this technique, SWCNTs can be produced from graphite electrodes by adding metal-based catalysts such as Co, Fe and Ni to the system. However, MWCNTs are the main product when a pure graphite electrode is used [94].
Chemical vapor deposition (CVD) technique. Chemical vapor deposition technique is a simple process and it is believed to be the easiest technique for industrial production of CNTs. In this method, the desired CNT type and quality can be produced by controlling the system production parameters such as temperature, type of catalyst and type of carbon source gases. CVD technique consists of two main steps (catalyst preparation step and then CNT synthesis). In general, to produce CNTs, methane and carbon monoxide gases are dissociated into reactive carbon atoms using an energy source, and then these reactive atoms diffuse over a substrate that is coated by transition metals as a catalyst and heated at a temperature range from 500 to 1000°C [95].
A comparison between the previously discussed methods for CNT production is summarized in Table 4.
\nMethod | \nYield (%) | \nSENT | \nMINT | \nConcerns | \n
---|---|---|---|---|
Chemical vapor deposition | \n20–100% | \nLong tubes with diameters 0.6–4 nm | \nLong tubes with diameters 10–240 nm | \nNets are usually mints and often riddled with defects | \n
Arc discharge | \n30–90% | \nShort tubes with diameters 0.6–1.4 nm | \nShort tubes with inner diameter 1–3 nm | \nShort tubes with random sizes and directions and required purification | \n
Laser ablation (Vaporization) | \nUp to 70% | \nLong bundles of tubes with diameters 1–2 nm | \nNot suitable and too expensive | \nCostly and required high power | \n
Comparison between the three methods in terms of CNT production efficiency, type of CNTs produced, and the current drawback of each technology.
Carbon nanotubes with their excellent properties show considerable adsorption capability for removal of pharmaceutical active compounds. A study in 2009 found that the single wall carbon nanotubes (SWNTs) are more efficient for removal of tetracycline from aqueous solutions than multiwall carbon nanotubes (MWNTs), graphite and activated carbon [58]. This finding was explained through the molecular sieving effect, whereas the tetracycline is bulky molecules failed to seep through inner pores, which indicates the important role of molecules’ size and their accessibility into pores in the adsorbent materials. In 2016, Yu et al. [96] studied the adsorption performance of MWNTs for removal of ciprofloxacin and found the maximum adsorption capacity is 20 mg/g, which was obtained at pH 4 and 240 min that was attributed by the π-π interaction rather than hydrogen bonding and interaction with oxygenated functional groups on MWNTs. Another study by Yu et al. [97] showed that the maximum adsorption capacity of MWNTs for tetracycline was 269.54 mg/g, which achieved at 25°C and pH 5 within 80 min.
\nIn order to improve the performance and adsorption capacity of CNTs, different types of modifications can be performed such as graphitization, hydrolyzation, carboxylation and etching with potassium hydroxide (KOH). For example, Ji et al. [98, 99] modified the SWNTs and MWNTs by etching using KOH and tested the etched CNTs for three pharmaceutical active compounds (i.e., sulfamethoxazole, tetracycline and tylosin). They found the adsorption performance of the KOH modified SWNTs (K-SWNTs) and KOH modified MWNTs (K-MWNTs) for sulfamethoxazole and tetracycline was enhanced by around 56% and 84% compared to the unetched SWNTs and MWNTs, respectively. This has been explained by increasing the surface area of the etched CNTs.
\nGraphene is a two-dimensional carbonaceous nanomaterial formed from a layer of sp2 hybridized carbon atoms. The graphene nanomaterial has exceptional properties such as high specific surface area [98, 99], high electrocatalytic activity [100], great thermal conductivity [101], high stiffness and strength [102] and high speed electron mobility [103]. These unique physical properties attracted great interest of scientist and introduced it for different potential applications. Among these applications is the adsorptive removal of emerging pollutants such as pharmaceutical active compounds.
\nThe following are the common types of graphene:
Single layer graphene (SLG): it is one thick hexagonally arranged sp2 hybridized bonded carbon atoms. The dimensions of SLG vary from nano- to microscale. It can be suspended in an aqueous solution or adhered on a substrate.
Multilayer graphene (MLG): it consists of few flaks of single layer graphene and it is useful in the preparation of nanomaterial composites.
Graphene oxide: it is a single layer or multilayer graphene that has high oxygenated surface and prepared by exfoliation and chemical oxidation of graphite.
Reduced graphene oxide: it is that same as graphene oxide; however, the oxygenated functional groups are reduced chemically, thermally or biologically.
The graphene nanomaterials and their modified forms have extraordinary surface area and catalytic activity, and as a result, they can be used in several applications such as adsorptive removal of pharmaceutical active compounds [104, 105, 106, 107, 108, 109, 110, 111]. Gao et al. [106] investigated the adsorption performance of graphene oxide for tetracycline antibiotic from aqueous solution. They found that the adsorption of tetracycline achieved mainly through a π-π and cation-π interactions with a maximum monolayer adsorption capacity is 313 mg/g and it decreased with an increase in the solution pH or the sodium ions concentration. In 2017, Danna et al. [107] modified a graphene oxide with decafluorobiphenyl and then investigated the prepared adsorbent for removal of six pharmaceutical active compounds from water namely, carbamazepine, sulfamethoxazole, sulfadiazine, ibuprofen, paracetamol and phenacetin. They found that the adsorption capacities for these compounds are 340.5 μmol/g, 428.3 μmol/g, 214.7 μmol/g, 224.3 μmol/g, 350.6 μmol/g and 316.1 μmol/g, respectively. A study in 2014 showed that the adsorptive removal of acetaminophen, aspirin and caffeine from aqueous solution using graphene nanoplates (GNPs) was thermodynamically spontaneous and exothermic with adsorption capacities of 18.07 mg/g, 12.98 mg/g and 19.72 mg/g for acetaminophen, aspirin and caffeine, respectively [105].
\nThe surface area of graphene reduces significantly in solutions due to its aggregation, and as a result, the adsorption capacity of graphene is reduced, which is one of the main disadvantages associated with using graphene as adsorbents. Functionalization or modification of the graphene with certain functional group or metals can be the best solution to overcome that disadvantage as well as increase the adsorption capacity of graphene. Lin et al. [108] functionalized a graphene oxide with magnetic nanoparticles and then studied its adsorptive removal for four tetracycline (TC) pharmaceutical active compounds (i.e., tetracycline, oxytetracycline, chlortetracycline and doxycycline) from aqueous solution. They found that the solution pH and ionic strength had insignificant effect on the TC adsorption and the maximum adsorption capacity is 39.1 mg/g.
\nPharmaceutical active compounds are continuously released into aquatic environment via different routes (i.e., human and animal excreta, medical industry’s waste, wastewater effluent, sewage and landfill leaching). That release increases due to the increase of general use of pharmaceutical compounds in human and veterinary medicines. Therefore, these compounds should be removed from the contaminated water to prevent their accumulation, reduce the environmental pollution and provide an additional source of clean water. Removal of pharmaceutical active compounds from aquatic media can be achieved by either conventional or advanced methods. Among them, the adsorption technique has many advantages over the others. Several materials as adsorbents have been reported and discussed in the literature such as silica-based adsorbents, polymeric materials, clay, carbonaceous materials and other materials. Activated carbon, carbon nanotube and graphene oxide among carbonaceous materials show excellent performance and high adsorption capacity for pharmaceutical active compounds. As discussed in this chapter, the activated carbon can be activated using different methods (i.e., physical or chemical activation), while the carbon nanotube can be produced through using one of the following methods: (i) arc discharge, (ii) laser ablation and (iii) chemical vapor deposition. The physical (surface area and porosity) and chemical (functional groups) properties are significantly affected by the followed production method for these carbonaceous materials. Using freely available raw materials for the activated carbon and carbon nanotubes production and their modification with different nanoparticles and functional groups is the future prospect for the adsorptive removal of pharmaceutical active compounds from the aquatic environment.
\nThe support of the Center for Environment and Water in the research institute of King Fahd University of Petroleum and Minerals is highly acknowledged.
\nThe author declares that there are no conflicts of interest.
One of the most complex structures on this earth is the human brain with an estimated approximately weight of 3lbs. The human brain is so much sophisticated that it has given so many brilliant research works which seem superficial at first look likewise ultra-modern supercomputer, aircraft and one of the missile technologies LGM-30G Minuteman-III, etc. [1]. It controls one’s whole human body and consists of approximately 100 billion cells, known as a neuron, a part of the human nervous system. These neurons communicate with each other by sending an electrical potential (charge) down the axon and across the synapse to the very next neuron. Since neurons are not connected physically, it uses a chemical messenger entitled neurotransmitters, which crosses the synaptic gap to carry-forward messages to the next neuron [2]. This chemical messenger (neurotransmitters) then activates receptors corresponding to it in the postsynaptic neuron, this action generates postsynaptic currents this process keeps going on for the next synapse. As this communication passes current (electrical potential) using neurotransmitter, a chemical messenger, it can be considered as communication is a process that is electrical and chemical both.
As shown in Figure 1, the neurons are activated using an electrochemical concentration gradient, local current flows are produced.
Typical neurons structure.
EEG works as a good tool to explore brain activity and can detect changes within milliseconds. Depending upon the type of neuron, an action potential takes 0.5–130 milliseconds approximately to propagate across a single neuron. Whereas, other methods likewise fMRI and PET has time resolution in terms of seconds and minutes and makes these methods less efficient.
Moreover, EEG directly measures the brain’s electrical activity, whilst other methods such as SPECT, fMRI record changes in blood flow, or PET record changes in metabolic activity, which are indirect markers of electrical activity belonging to the brain. The electrical activity is a superposition of the huge number of electrical charges arising from multiple sources likewise brain cells i.e. neurons and artifacts. It is possible to place electrodes inside the human head via surgery for direct measurement from different centers in the human brain, but this is a painful and risky procedure for the subject [3, 4]. However, the desirable technique is to calculate electrical signals of interest invaded on the scalp as shown in the following Figure 2.
EEG electrodes placement on a subject, monitoring various sectors of the brain for activities.
Signals obtained by an above-maintained process are weighted sums of neuron activity, whose weights depend on the signal path from a specific brain cell to the connected electrodes. Since the same electrical potential is being recorded from more than one electrode, signals being occurred from those electrodes are supposed to be highly correlated [4]. Henceforth, Scientists and Researchers collect these recordings by attachment of tens or hundreds of electrodes, which are positioned in pairs, at various locations on the surface of the subject’s head. These electrical potentials (Charges) are tested simultaneously via individuals’ channels or amplifiers. Recording for each channel represents the difference in electrical potential between two areas under each electrode’s pair [5] as represented in Figure 3. In Figure 3, the differences between the two electrodes are measured through an operational amplifier for generating EEG signal recording. A machine that is used for this purpose is known as an electroencephalograph, and recordings collected through these amplifiers are known as electroencephalogram (EEG) signals.
Differential amplifier for EEG recording/signal.
Currently, so many different types of electroencephalographs are available; over which 10–20 system is the internationally standardized method for describing the location of scalp electrodes and is based upon the relationship between an electrode’s location and cerebral cortex underlying area and usually employs 21 electrodes. Its positions are determined by dividing the skull into the perimeters by connection of a few reference points lying on the human head.
In this, every perimeter has a letter, that helps in the identification of the lobe, and either a number or another letter for identification of the hemisphere location. Letters that are used are as follows:
“F”-Frontal lobe
“T”-Temporal lobe
“C”-Central lobe
“P”-Parietal lobe
“O”-Occipital lobe.
Furthermore, numbers (2, 4, 6, 8) refer to the right hemisphere, whereas odd numbers (1, 3, 5, 7) refer to the left hemisphere.
In the below-shown Figure 4, the “Z” refers to an electrode placed on the midline; the position of the electrode can be determined by the magnitude of the number, the smaller magnitude represents that electrode is much closer to the midline. The figure given below presents the actual electrode placement on the head and from these points, skull perimeters are measured in the transverse and the median planes [4].
The international 10–20 system seen from (a) left and (b) top (c) standard location and nomenclature of the intermediate 10% electrodes.
Figure 3.4 presents the system “10” and “20” shows the fact that the actual distances between two adjacent electrodes are in percentage of either 10% or 20% of the three main measurements:
nasion, is the delve at the upper portion of the nose, and in level with the eyes.
inion, is the bony lump at the base of the skull on the midline of the back of the head.
pre-auricular points and circumference of the head.
In the human brain, most of the neurons, which work in synchrony, possess common characteristics, that as much larger the amplitude (potential) of the electrical oscillations in microvolt (mV), will have much faster the neurons work together, and also much higher the frequency of the oscillations in Hertz (Hz). Hence, amplitude and frequency, and shape are important primary characteristics of human brain waves. EEGs are the recordings of these tiny electrical charges (potentials or waves) that are generally less than 300 μV [6]. EEG frequency bands or the brain rhythms arranged according to increased frequencies are shown in Figure 5.
Fundamental EEG bands classification.
The most common classification is based on the frequency of EEG signals (i.e. alpha, beta, theta, and delta). The brain waves with their frequency band and the corresponding brain activities are revealed in Table 1.
Name | Frequency band (Hz) | Predominantly brain activity |
---|---|---|
Delta | 0.5–4 | Sleeping |
Theta | 4–8 | Dreaming, Meditation |
Alpha | 8–13 | Relaxation |
Beta | 13–36 | Alert/Working Problem Solving |
Gamma | 36–100 | Multisensory semantic matching Perceptual function |
Electroencephalography (EEG) signal frequency bands.
The EEG signals have been broadly categorized into six classical categories as shown in Figure 5. They cause a high level of difficulty to interpret the huge amount of data/information being received from one single EEG recordings. Subsequently, it is highly required to understand every aspect of these categories, which have been explained below in brief:
The Alpha waves have been discovered around 1908 by Hans Berger. Its frequency ranges from 8 to 13 Hz and is usually seen in the posterior regions of the head on each side of an adult when the patient is relaxing [7]. It appears when closing the eyes and relaxing, and tends to attenuate with open eyes or alerting by any mental exertion.
Its frequency ranges from 14 Hz to about 30 Hz. Beta activity is a “fast” activity and is also called normal rhythm activity. It is usually seen on both sides of the hemisphere in symmetrical distribution and is most evident in the frontal areas. Sedative-hypnotic drugs affect this activity [7]. It may be missing or reduced in regions of cortical damage. It is accentuated in patients who are very anxious or have their eyes open.
It has a frequency range from 4 to 7 Hz and is classified as “slow” activity. It is found in every person during sleep and in meditation. It can be seen in the state of arousal for adults [7]. Excess theta in adults represents abnormal activity.
The Delta Waves have a frequency range of up to 4 Hz or below. It is likely to have a higher amplitude but has a low frequency. It is normal as the dominant rhythm in infants of up to one year and stages 3 and 4 of sleep. It is usually more prominent in the frontal part in adults and the posterior part in children [7].
Theta and delta waves are known collectively as slow waves.
Its frequency ranges from 30 to 100 Hz. Gamma rhythms represent the binding of an enormous collection of neurons assimilated for carrying out a certain cognitive or motor function [8].
The amplitude of EEG signals is very closely related to the level of consciousness of a person [9]. An example of these waves is shown below in Figure 6.
EEG activity is solely dependent on the level of the subject’s consciousness.
From Figure 6, the conclusion is drawn that the slow waves Theta and Delta occur in the third and fourth stages of human sleep. The awake condition presents a high level of consciousness with Beta waves. This 90 minutes of the cycle is repeated the whole night with repeated EEG wave activity.
The EEG signal is one of those signals which are most widely used for studying brain functions and for the diagnosis of neurological disorders by physicians, researchers, and scientists. A single misinterpretation can become a cause of misdiagnosis. Henceforth, it is imperative to have a very right and clear image about brain activities being represented by EEG signals shown in Figure 7. Skull’s low conductivity is the main reason for the poor spatial resolution of scalp EEG.
One second recording of clean pure EEG signal.
Furthermore, scalp EEG signals are highly sensitive to the movement of the subject and noises being introduced due to externally likewise human head activation, eye movements, musculature, nearby electrical device interference and because of one’s movement conductivity in the electrodes get varies or physicochemical reactions occurred at the electrode sites [6]. Some of the EEG artifacts distributions are displayed in Figure 8. All these additional activities are indirectly associated with the subject’s current cerebral process and are collectively referred to as background activities. Henceforth, EEG signals are highly enervated and mixed with these non-cerebral impulses known as artifacts or noise. These artifacts or noise fall into two major categories being considered as physiologic and extra-physiologic [5]. Only after removing these artifacts, a true diagnosis can be achieved. Physiologic Artifacts can be produced by any of any sources present in the human body that has an electric dipole or which can generate an electrical or magnetic field that can become a cause of physiologic artifacts.
ECG and EOG artifacts.
The following are the types of physiologic artifacts:
Muscle artifacts
Glossokinetic artifacts
Eye blink artifacts
Eye movement artifacts
ECG artifacts
Pulse artifacts
Respiration artifacts
Skin artifacts
The following are the types of extra-physiologic artifacts:
Electrode popping artifacts
Alternating current artifacts
Artifacts due to movements in the environment
Some of the most EEG corrupting artifacts are discussed as follows:
This is mainly used to measure the eye artifacts. Since these measurements are contaminants of EEG signal and so it is not possible to remove this kind of artifacts from the subtraction process only when the exact model of EOG diffusion across the scalp is available [2]. These artifacts are of two types:
I. Eye Blinking.
It is an artifact that is very common in EEG data. This artifact possesses a very high amplitude signal sometimes much greater than the EEG signals of interest. Further, it can corrupt data availed on all electrodes, even those signals too, that are at the back of the head [2].
II. Eye Movement.
It is occurring because of the reorientation of the retained corneal dipole [4]. Eye movement’s diffusion across the scalp is greater than that being produced by the eye blink artifact.
EOG artifact can be given in the following form:
where,
Cardiograph is generally used to measure pulse or heartbeat, which occurs by an electrode on or near a blood vessel as shown in Figure 8. The voltage recording changes due to the expansion and contraction of the vessel [2]. The artifact signal generally has frequency proximity to 1.2 Hz and appears as a sharp spike or smooth wave but it can have a variation that solely depends on the state of the patient. An example has been illustrated below where an EEG signal mixed with ECG/EKG signal and got corrupted due to line interference.
Electrocardiogram signal artifacts can represent by using the following equation:
Where
Electromyogram (EMG) artifacts could be produced because of some movement disorders. Essential tremor and Parkinson’s disease could also be responsible for rhythmic 4–6 Hz sinusoidal artifacts which may be mimicked cerebral activity [2].
Following equation shows the EMG signal:
Where.
and
Extra-physiologic Artifacts
These include interference due to electrical equipment, kinesiology artifacts because of the human body or movements of electrodes, and mechanical artifact because of human body movement.
The movement of the patient or even disturbance just during the electrodes settling could become the cause of electrode pops variations of the conduction between electrodes and the skin. Linguistically these signals appear either in the form of single or multiple sharp waveforms due to abrupt variations in the impedance. It can be easily identified by its characteristic appearance and its usual distribution, which is restricted to a single electrode [4]. In usual manners, sharp transients which occur at a single electrode should be considered artifacts, until it has not been proven. Figure 9a and Figure 9b present the pure EEG signal and motion artifact contaminated EEG signal. Figure 9b shows the high amplitude broad spectrum distribution because of motion artifact in the EEG signal.
(a) Original EEG signal (b) EEG signal contaminated with motion artifact.
Figure 9a shows the original EGG signal and (b) represents the motion artifact contaminated EEG signal. Figure 9b presented the motion artifacts contamination on the EEG signal.
Alternating Currents, ranging from 50 to 60 Hz, that is strong signals from Alternating Current (A/C) power supplies could also corrupt EEG data since it gets transferred to a recording device from the scalp electrodes. Issues co-related to power lines-based artifacts come into the picture when an active electrode has a higher impedance than impedance between the electrodes and the amplifier’s ground. In such kinds of scenarios, the amplifier’s ground starts to work as an active electrode which solely depends upon its location and implements/generates 50–60-Hz artifact. Usually for removal of these artifact notch filters are used, but still, it could produce a problem of useful information removal, furthermore lower frequency line noise and harmonics are undesirable [10]. If the line noise or harmonics produce in frequency bands of interest it interferes with EEG signals which occur in the same frequency band [9].
Power line noise as shown in Figure 10 can be presented mathematically as:
Line interference of 50 Hz.
In the above equation
During the recording process, there is always a possibility of occurrence of contamination in EEG data at multiple points. Over which most of the artifacts that occurred here belong biologically generated by sources and are external to the brain. By significant improvement in existing technology, these externally generated artifacts could be removed, thus it is important to study efficient de-noising (a process for noise removal) procedures that would be able to remove these biological overlays from EEG signals. Actual EEG recordings are the summation of artifacts with the pure EEG signal, and can be defined mathematically:
Where:-.
The presence of these artifacts introduces spikes that can create issues while reading neurological rhythms. So many methods have been proposed and presented by scientists and researchers to perform the artifacts removal process in EEG.
To remove artifacts from an EEG recording can be classified into two groups, which are following:
Artifact rejection—This method is used for removal of EEG signal that comprises the artifact and
Artifact correction—This method is used for the removal of artifacts from EEG signals while keeping and maintaining the pure EEG signal.
1. Basic Artifact Rejection.
The most commonly used de-noising techniques for eliminating all EEG epochs which comprise artifacts larger than some pre-defined threshold EEG voltage level, known as artifact rejection. This method is most commonly and widely used when a limited amount of data or artifacts such as EOG is available. These artifacts occur too frequently in nature that raises elimination of those epochs which are contaminated with the artifacts, which becomes the cause of considerable loss of information and which makes this process impractical for being used in clinical data. As EEG and some artifacts occupy the same frequency band, this method is not that effective [7].
2. Regression Method.
Conventionally artifacts correction processes used a regression-based approach which is based on either time domain or frequency domain [3]. In this method, after a clear measure of artifact signals, it is subtracted from EEG signals and has been recorded. The major issue that comes into existence is bi-directional contamination. As if artifacts potentials are capable of contaminating EEG recordings, then the electrical activity of the brain is also capable of contaminating the artifacts recordings. Henceforth, diminishing a linear combination of the recorded artifacts from the EEG recordings may not only abolish artifacts but also the cerebral activity of interest. Review work for these techniques is discussed in [4, 8].
3. Filtering Method
Low-pass filtering of the artifacts eliminates all high-frequency activity from EOG signal, from both cerebral and ocular origins [7]. Adaptive filtering usage before applying regression correction can substantially reduce issues produced due to bidirectional contamination [3]. However, it is imperative to use adaptive digital filters for artifact removal, which necessitates a suitable reference model for training the filter.
1. Principal Component Analysis (PCA).
These methods are based on EEG and artifacts decomposition into spatial components, which is inclusive of recognizing artifactual components and reassembling the EEG without those artifactual components that have been recognized, but it is problematic in the case of PCA. The PCA algorithm first decomposes the EEG signals into uncorrelated, but it is not required that these must be independent of each other which are spatially orthogonal and that’s why it cannot deal with higher-order statistical dependencies. Furthermore, it is not practically possible to completely separate artifacts from interested brain signals specifically when both of these signals have comparable amplitudes.
The following expression describes principal component decomposition:
where,
By maximizing the variance of
Successive principal components can easily be obtained iteratively by demising the first k principal components from
Now to find ϕk + 1,
Subject to
Alternatively, Singular Value Decomposition (SVD) is the simplest and efficient way that can be applied to find a centered data-matrix
Where
UD matrix constitutes principal component scores, which are variable coordinates in the case of principal components [3].
This method was developed to handle issues that occurred due to Blind Source Separation, abbreviated as BSS to form the components which must be as independent as possible [8] and can be represented mathematically:
Where
Where
After a thorough investigation and deep analysis and research work conclusion has been drawn that ICA provides much better results for de-noising [6]. A whole chapter has been devoted to describing ICA, which belongs to existing work in Single-Stage Artifact Removal Algorithm.
This algorithm has been developed by
Canonical correlation analysis (CCA) is first proposed by Hotelling. CCA is an algorithm for the determination of the linear association between two set variables. This is done with the help of the variance and covariance matrix of the data [6].
A set of linear combinations named A and B are considered as:
Let
This
This
This canonical pair will be calculated and separated by calculating self-correlation and a mutual decorrelation between input sources.
Wavelet Transform (WT) has good localization properties in the time and frequency domain [6], and so it is a widely accepted and successful method being used for de-noising [11]. Currently, so many approaches are available at the algorithmic level to de-noise using Wavelet Transform, which is mainly based on shrinkage, where the EEG signals get decomposed in the form of wavelets and then noise removal is performed using shrinkage and thresholding. The quality of Wavelet Transform in transforming a time-domain signal into time and frequency localization assists in comprehending the signal’s behavior in a much better way.
The Wavelet Transform could be defined as the following equation, which is the inner product or cross-correlation of {
where,
Empirical mode decomposition is a non-linear method to represent a non-stationary signal into the sum of zero-mean sub-components. This method decomposes a signal into several intrinsic mode functions through an iterative method known as sifting. At the first level, the Intrinsic Mode function (IMF1) is the mean of the upper and lower envelop of the original EEG signal x(t). Then the residual signal is obtained by subtracting IMF1 from x(t). This process is iterated till the stopping criterion is fulfilled (Residual signal energy content is close to zero). The remaining residual signal is
where,
Finally, the signal is reconstructed by adding all IMFs and residual signals as
The method of detecting IMFs is sensitive to the amalgam of undesired signal components present in surroundings. These noises affect the EMD process. Thus, mode mixing is used to overcome the disparate scale oscillations with amplitude in the near range of the IMFs peaks which can be available randomly in the whole dataset. Consequently, a more powerful and noise-assisted version of the EMD algorithm was presented termed as Ensemble Empirical Mode Decomposition (EEMD), which solves this mode mixing quandary and employs the average value of EMD ensembles that filters out the IMFs for the given signal. Moreover, this method also depends on the added noise amplitude to the input signal and the number of trials [6, 9].
In this Chapter, Electroencephalograph Signals and their generation process have been discussed; the EEG signal has been compared with fMRI and PET signals. The classification of the EEG signals on the amplitude, frequency, and shape have been elaborated in wave analysis of EEG, and applications of these components are presented.
The artifacts of EEG have been explained in detail. There are two main types of artifacts to be considered; namely, physiological and non-physiological artifacts. Non-physiological contain artifacts such as movement artifacts, electrode pop artifacts, sweat artifacts, and 50/60 Hz noise. Typically, these artifacts are not explicitly monitored, and as such, they need to be filtered out by their characteristics alone. For example, sweat artifacts tend to be of really low frequency, 50/60 Hz noise is contained within a narrow frequency band, and electrode pop artifacts are not necessarily time-aligned in two corresponding electrodes on the two sides of the scalp. Physiological artifacts take the form of ocular artifacts, cardiac artifacts, muscle artifacts, glossokinetic artifacts, and respiratory artifacts. Most of these artifacts can be monitored with another channel, which in turn can be used during the EEG artifact removal.
Subsequently, artifact removal methods have been classified in the form of artifact correction and artifact rejection. The artifact rejection comprises Regression and filtering as the main method. Whereas, artifact correction method comprises Principal Component Analysis (PCA), Independent Component Analysis (ICA), Canonical Correlation Analysis (CCA), Wavelet Transform (WT), and Empirical Mode Analysis (EMD). These all single-stage artifact removal methods and their implementation with results are discussed in the subsequent chapter.
The authors declare no conflict of interest.
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S. Lisar, Rouhollah Motafakkerazad, Mosharraf M. Hossain and Ismail M. M. Rahman",authors:[{id:"110740",title:"Dr.",name:"Ismail M.M.",middleName:null,surname:"Rahman",slug:"ismail-m.m.-rahman",fullName:"Ismail M.M. Rahman"}]},{id:"53211",doi:"10.5772/66416",title:"Biofloc Technology (BFT): A Tool for Water Quality Management in Aquaculture",slug:"biofloc-technology-bft-a-tool-for-water-quality-management-in-aquaculture",totalDownloads:16966,totalCrossrefCites:65,totalDimensionsCites:148,abstract:"Biofloc technology (BFT) is considered the new “blue revolution” in aquaculture. Such technique is based on in situ microorganism production which plays three major roles: (i) maintenance of water quality, by the uptake of nitrogen compounds generating in situ microbial protein; (ii) nutrition, increasing culture feasibility by reducing feed conversion ratio (FCR) and a decrease of feed costs; and (iii) competition with pathogens. The aggregates (bioflocs) are a rich protein-lipid natural source of food available in situ 24 hours per day due to a complex interaction between organic matter, physical substrate, and large range of microorganisms. This natural productivity plays an important role recycling nutrients and maintaining the water quality. The present chapter will discuss some insights of the role of microorganisms in BFT, main water quality parameters, the importance of the correct carbon-to-nitrogen ratio in the culture media, its calculations, and different types, as well as metagenomics of microorganisms and future perspectives.",book:{id:"5355",slug:"water-quality",title:"Water Quality",fullTitle:"Water Quality"},signatures:"Maurício Gustavo Coelho Emerenciano, Luis Rafael Martínez-\nCórdova, Marcel Martínez-Porchas and Anselmo Miranda-Baeza",authors:[{id:"146126",title:"Dr.",name:"Maurício Gustavo Coelho",middleName:null,surname:"Emerenciano",slug:"mauricio-gustavo-coelho-emerenciano",fullName:"Maurício Gustavo Coelho Emerenciano"},{id:"186970",title:"Prof.",name:"Marcel",middleName:null,surname:"Martínez-Porchas",slug:"marcel-martinez-porchas",fullName:"Marcel Martínez-Porchas"},{id:"186971",title:"Prof.",name:"Anselmo",middleName:null,surname:"Miranda-Baeza",slug:"anselmo-miranda-baeza",fullName:"Anselmo Miranda-Baeza"},{id:"195101",title:"Dr.",name:"Luis Rafael",middleName:null,surname:"Martínez-Córdoba",slug:"luis-rafael-martinez-cordoba",fullName:"Luis Rafael Martínez-Córdoba"}]},{id:"53194",doi:"10.5772/66561",title:"Impact of Wastewater on Surface Water Quality in Developing Countries: A Case Study of South Africa",slug:"impact-of-wastewater-on-surface-water-quality-in-developing-countries-a-case-study-of-south-africa",totalDownloads:7743,totalCrossrefCites:67,totalDimensionsCites:138,abstract:"Wastewater effluents are major contributors to a variety of water pollution problems. Most cities of developing countries generate on the average 30–70 mm3 of wastewater per person per year. Owing to lack of or improper wastewater treatment facilities, wastewater and its effluents are often discharged into surface water sources, which are receptacles for domestic and industrial wastes, resulting to pollution. The poor quality of wastewater effluents is responsible for the degradation of the receiving surface water body. Wastewater effluent should be treated efficiently to avert adverse health risk of the user of surface water resources and the aquatic ecosystem. The release of raw and improperly treated wastewater onto water courses has both short‐ and long‐term effects on the environment and human health. Hence, there should be proper enforcement of water and environmental laws to protect the health of inhabitants of both rural and urban communities. This study reports major factors responsible for the failing state of wastewater treatment facilities in developing countries, which includes poor operational state of wastewater infrastructure, design weaknesses, lack of expertise, corruption, insufficient funds allocated for wastewater treatment, overloaded capacities of existing facilities, and inefficient monitoring for compliance, among others.",book:{id:"5355",slug:"water-quality",title:"Water Quality",fullTitle:"Water Quality"},signatures:"Joshua N. Edokpayi, John O. Odiyo and Olatunde S. 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The use of aquatic organisms as bioindicators of metal pollution allowed the obtaining of valuable information about the acute and chronic toxicity on common Romanian aquatic species and the estimation of the environment quality. Laboratory toxicity results showed that Cd, As, Cu, Zn, Pb, Ni, Zr, and Ti have toxic to very toxic effects on Cyprinus carpio, and this observation could raise concerns because of its importance as a fishery resource. The benthic invertebrates’ analysis showed that bioaccumulation level depends on species, type of metals, and sampling sites. The metal analysis from the shells of three mollusk species showed that the metals involved in the metabolic processes (Fe, Mn, Zn, Cu, and Mg) were more accumulated than the toxic ones (Pb, Cd). The bioaccumulation factors of metals in benthic invertebrates were subunitary, which indicated a slow bioaccumulation process in the studied aquatic ecosystems. The preliminary aquatic risk assessment of Ni, Cd, Cr, Cu, Pb, As, and Zn on C. carpio revealed insignificant to moderate risk considering the measured environmental concentrations, acute and long-term effects and environmental compartment.",book:{id:"5355",slug:"water-quality",title:"Water Quality",fullTitle:"Water Quality"},signatures:"Stefania Gheorghe, Catalina Stoica, Gabriela Geanina Vasile, Mihai\nNita-Lazar, Elena Stanescu and Irina Eugenia Lucaciu",authors:[{id:"186964",title:"Dr.",name:"Stefania",middleName:null,surname:"Gheorghe",slug:"stefania-gheorghe",fullName:"Stefania Gheorghe"},{id:"194072",title:"Dr.",name:"Catalina",middleName:null,surname:"Stoica",slug:"catalina-stoica",fullName:"Catalina Stoica"}]},{id:"42035",doi:"10.5772/55354",title:"Arsenic in Groundwater: A Summary of Sources and the Biogeochemical and Hydrogeologic Factors Affecting Arsenic Occurrence and Mobility",slug:"arsenic-in-groundwater-a-summary-of-sources-and-the-biogeochemical-and-hydrogeologic-factors-affecti",totalDownloads:6209,totalCrossrefCites:6,totalDimensionsCites:47,abstract:null,book:{id:"3491",slug:"current-perspectives-in-contaminant-hydrology-and-water-resources-sustainability",title:"Current Perspectives in Contaminant Hydrology and Water Resources Sustainability",fullTitle:"Current Perspectives in Contaminant Hydrology and Water Resources Sustainability"},signatures:"Julia L. Barringer and Pamela A. Reilly",authors:[{id:"163098",title:"Dr.",name:"Julia",middleName:null,surname:"Barringer",slug:"julia-barringer",fullName:"Julia Barringer"},{id:"167449",title:"M.Sc.",name:"Pamela",middleName:"A.",surname:"Reilly",slug:"pamela-reilly",fullName:"Pamela Reilly"}]}],mostDownloadedChaptersLast30Days:[{id:"58138",title:"Water Pollution: Effects, Prevention, and Climatic Impact",slug:"water-pollution-effects-prevention-and-climatic-impact",totalDownloads:21554,totalCrossrefCites:18,totalDimensionsCites:38,abstract:"The stress on our water environment as a result of increased industrialization, which aids urbanization, is becoming very high thus reducing the availability of clean water. Polluted water is of great concern to the aquatic organism, plants, humans, and climate and indeed alters the ecosystem. The preservation of our water environment, which is embedded in sustainable development, must be well driven by all sectors. While effective wastewater treatment has the tendency of salvaging the water environment, integration of environmental policies into the actor firms core objectives coupled with continuous periodical enlightenment on the present and future consequences of environmental/water pollution will greatly assist in conserving the water environment.",book:{id:"6157",slug:"water-challenges-of-an-urbanizing-world",title:"Water Challenges of an Urbanizing World",fullTitle:"Water Challenges of an Urbanizing World"},signatures:"Inyinbor Adejumoke A., Adebesin Babatunde O., Oluyori Abimbola\nP., Adelani-Akande Tabitha A., Dada Adewumi O. and Oreofe Toyin\nA.",authors:[{id:"101570",title:"MSc.",name:"Babatunde Olufemi",middleName:null,surname:"Adebesin",slug:"babatunde-olufemi-adebesin",fullName:"Babatunde Olufemi Adebesin"},{id:"187738",title:"Dr.",name:"Adejumoke",middleName:"Abosede",surname:"Inyinbor",slug:"adejumoke-inyinbor",fullName:"Adejumoke Inyinbor"},{id:"188818",title:"Dr.",name:"Abimbola",middleName:null,surname:"Oluyori",slug:"abimbola-oluyori",fullName:"Abimbola Oluyori"},{id:"188819",title:"Mrs.",name:"Tabitha",middleName:null,surname:"Adelani-Akande",slug:"tabitha-adelani-akande",fullName:"Tabitha Adelani-Akande"},{id:"208501",title:"Dr.",name:"Adewumi",middleName:null,surname:"Dada",slug:"adewumi-dada",fullName:"Adewumi Dada"},{id:"208502",title:"Ms.",name:"Toyin",middleName:null,surname:"Oreofe",slug:"toyin-oreofe",fullName:"Toyin Oreofe"}]},{id:"24941",title:"Tsunami in Makran Region and Its Effect on the Persian Gulf",slug:"tsunami-in-makran-region-and-its-effect-on-the-persian-gulf",totalDownloads:7575,totalCrossrefCites:4,totalDimensionsCites:7,abstract:null,book:{id:"406",slug:"tsunami-a-growing-disaster",title:"Tsunami",fullTitle:"Tsunami - A Growing Disaster"},signatures:"Mohammad Mokhtari",authors:[{id:"52451",title:"Dr.",name:"Mohammad",middleName:null,surname:"Mokhtari",slug:"mohammad-mokhtari",fullName:"Mohammad Mokhtari"}]},{id:"24552",title:"Geology and Geotectonic Setting of the Basement Complex Rocks in South Western Nigeria: Implications on Provenance and Evolution",slug:"geology-and-geotectonic-setting-of-the-basement-complex-rocks-in-south-western-nigeria-implications-",totalDownloads:20808,totalCrossrefCites:2,totalDimensionsCites:25,abstract:null,book:{id:"1882",slug:"earth-and-environmental-sciences",title:"Earth and Environmental Sciences",fullTitle:"Earth and Environmental Sciences"},signatures:"Akindele O. Oyinloye",authors:[{id:"68497",title:"Prof.",name:"Akindele",middleName:null,surname:"Oyinloye",slug:"akindele-oyinloye",fullName:"Akindele Oyinloye"}]},{id:"66437",title:"Detection of Underground Water by Using GPR",slug:"detection-of-underground-water-by-using-gpr",totalDownloads:3101,totalCrossrefCites:0,totalDimensionsCites:0,abstract:"Water is the human vital requirement for life; in these days, decreasing of the fresh water increases the importance of the aquifer water. However, Upper Egypt is higher than north Egypt, so the water map continually changes daily, and the aquifer water is deeper than 10 m. The ground penetrating radar (GPR) system is used for underground water detection. GPR is a promising technology to detect and identify aquifer water or nonmetallic mines. One of the most serious components for the performance of GPR is the antenna system. The technology of the remote sensing and radar is rapidly developing, and it has led to the ultra-wideband electronic systems. All of these factors, such as miniaturized, low cost, possible compromise solution between depth and resolution, scanning in real time, easy to interpret, and decreased the false alarm, are important in designing the ground penetrating system. The electrical properties of the sand and fresh water layers are investigated using laboratory measurement and EM simulation. Different types of antenna may be used in GPR to operate over a frequency range for different penetration depth. Frequency-modulated continuous wave is also used for GPR and for through-the-wall applications. However, most of these kinds of antennas are limited by their large volume for certain applications. Therefore, a compact Vivaldi antenna with EBG and a compact planar printed quasi-Yagi antenna with meandered ground plane are designed to fulfill all above requirement.",book:{id:"6836",slug:"groundwater-resource-characterisation-and-management-aspects",title:"Groundwater",fullTitle:"Groundwater - Resource Characterisation and Management Aspects"},signatures:"Dalia N. Elsheakh and Esmat A. Abdallah",authors:[{id:"111813",title:"Dr.",name:"Dalia",middleName:null,surname:"Elsheakh",slug:"dalia-elsheakh",fullName:"Dalia Elsheakh"},{id:"111867",title:"Prof.",name:"Esmat",middleName:null,surname:"Abdallah",slug:"esmat-abdallah",fullName:"Esmat Abdallah"}]},{id:"57345",title:"Safe Drinking Water: Concepts, Benefits, Principles and Standards",slug:"safe-drinking-water-concepts-benefits-principles-and-standards",totalDownloads:6196,totalCrossrefCites:11,totalDimensionsCites:25,abstract:"Water is connected to every forms of life on earth. As a criteria, an adequate, reliable, clean, accessible, acceptable and safe drinking water supply has to be available for various users. The United Nation (UN) and other countries declared access to safe drinking water as a fundamental human right, and an essential step towards improving living standards. Access to water was one of the main goal of Millinium Development Goals (UN-MDGs) and it is also one of the main goal of the Sustainable Development Goals (SDGs). The UN-SDG goal 6 states that “Water sustains life, but safe clean drinking water defines civilization”. Despite these facts, there are inequalities in access to safe drinking water in the world. In some countries, sufficient freshwater is not available (physical scarcity); while in other countries, abundant freshwater is available, but it is expensive to use (economic scarcity). The other challenge is the increasing population of the world at an alarming rate, while the available freshwater resources almost remains constant. This chapter presents aspects of safe drinking water - background information, definition of water safety and access, benefits, principles and regulations, factors challenging the sustainable water supply and water quality standards and parameters.",book:{id:"6157",slug:"water-challenges-of-an-urbanizing-world",title:"Water Challenges of an Urbanizing World",fullTitle:"Water Challenges of an Urbanizing World"},signatures:"Megersa Olumana Dinka",authors:[{id:"206964",title:"Dr.",name:"Megersa Olumana",middleName:null,surname:"Dinka",slug:"megersa-olumana-dinka",fullName:"Megersa Olumana Dinka"}]}],onlineFirstChaptersFilter:{topicId:"125",limit:6,offset:0},onlineFirstChaptersCollection:[],onlineFirstChaptersTotal:0},preDownload:{success:null,errors:{}},subscriptionForm:{success:null,errors:{}},aboutIntechopen:{},privacyPolicy:{},peerReviewing:{},howOpenAccessPublishingWithIntechopenWorks:{},sponsorshipBooks:{sponsorshipBooks:[],offset:8,limit:8,total:0},allSeries:{pteSeriesList:[{id:"14",title:"Artificial Intelligence",numberOfPublishedBooks:9,numberOfPublishedChapters:90,numberOfOpenTopics:6,numberOfUpcomingTopics:0,issn:"2633-1403",doi:"10.5772/intechopen.79920",isOpenForSubmission:!0},{id:"7",title:"Biomedical Engineering",numberOfPublishedBooks:12,numberOfPublishedChapters:107,numberOfOpenTopics:3,numberOfUpcomingTopics:0,issn:"2631-5343",doi:"10.5772/intechopen.71985",isOpenForSubmission:!0}],lsSeriesList:[{id:"11",title:"Biochemistry",numberOfPublishedBooks:33,numberOfPublishedChapters:330,numberOfOpenTopics:4,numberOfUpcomingTopics:0,issn:"2632-0983",doi:"10.5772/intechopen.72877",isOpenForSubmission:!0},{id:"25",title:"Environmental Sciences",numberOfPublishedBooks:1,numberOfPublishedChapters:19,numberOfOpenTopics:4,numberOfUpcomingTopics:0,issn:"2754-6713",doi:"10.5772/intechopen.100362",isOpenForSubmission:!0},{id:"10",title:"Physiology",numberOfPublishedBooks:14,numberOfPublishedChapters:145,numberOfOpenTopics:4,numberOfUpcomingTopics:0,issn:"2631-8261",doi:"10.5772/intechopen.72796",isOpenForSubmission:!0}],hsSeriesList:[{id:"3",title:"Dentistry",numberOfPublishedBooks:9,numberOfPublishedChapters:140,numberOfOpenTopics:2,numberOfUpcomingTopics:0,issn:"2631-6218",doi:"10.5772/intechopen.71199",isOpenForSubmission:!0},{id:"6",title:"Infectious Diseases",numberOfPublishedBooks:13,numberOfPublishedChapters:123,numberOfOpenTopics:4,numberOfUpcomingTopics:0,issn:"2631-6188",doi:"10.5772/intechopen.71852",isOpenForSubmission:!0},{id:"13",title:"Veterinary Medicine and Science",numberOfPublishedBooks:11,numberOfPublishedChapters:112,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:22,numberOfOpenTopics:3,numberOfUpcomingTopics:0,issn:"2753-894X",doi:"10.5772/intechopen.100359",isOpenForSubmission:!0},{id:"23",title:"Education and Human Development",numberOfPublishedBooks:0,numberOfPublishedChapters:11,numberOfOpenTopics:1,numberOfUpcomingTopics:1,issn:null,doi:"10.5772/intechopen.100360",isOpenForSubmission:!0},{id:"24",title:"Sustainable Development",numberOfPublishedBooks:1,numberOfPublishedChapters:19,numberOfOpenTopics:5,numberOfUpcomingTopics:0,issn:"2753-6580",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. 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Prior to his appointment at Stellenbosch University, he has been at the University of Pretoria, Department of Computer Science (1998-2018), where he was appointed as South Africa Research Chair in Artifical Intelligence (2007-2018), the head of the Department of Computer Science (2008-2017), and Director of the Institute for Big Data and Data Science (2017-2018). 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He 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. 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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. 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He has both an MS and Ph.D. in Biomedical Engineering. He was previously a research scientist at the University of California Los Angeles (UCLA) and visiting professor and researcher at the University of North Dakota. He is currently working in artificial intelligence and its applications in medical signal processing. In addition, he is using digital signal processing in medical imaging and speech processing. Dr. Asadpour has developed brain-computer interfacing algorithms and has published books, book chapters, and several journal and conference papers in this field and other areas of intelligent signal processing. He has also designed medical devices, including a laser Doppler monitoring system.",institutionString:"Kaiser Permanente Southern California",institution:null},{id:"169608",title:"Prof.",name:"Marian",middleName:null,surname:"Găiceanu",slug:"marian-gaiceanu",fullName:"Marian Găiceanu",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/169608/images/system/169608.png",biography:"Prof. Dr. Marian Gaiceanu graduated from the Naval and Electrical Engineering Faculty, Dunarea de Jos University of Galati, Romania, in 1997. He received a Ph.D. (Magna Cum Laude) in Electrical Engineering in 2002. Since 2017, Dr. Gaiceanu has been a Ph.D. supervisor for students in Electrical Engineering. He has been employed at Dunarea de Jos University of Galati since 1996, where he is currently a professor. Dr. Gaiceanu is a member of the National Council for Attesting Titles, Diplomas and Certificates, an expert of the Executive Agency for Higher Education, Research Funding, and a member of the Senate of the Dunarea de Jos University of Galati. He has been the head of the Integrated Energy Conversion Systems and Advanced Control of Complex Processes Research Center, Romania, since 2016. He has conducted several projects in power converter systems for electrical drives, power quality, PEM and SOFC fuel cell power converters for utilities, electric vehicles, and marine applications with the Department of Regulation and Control, SIEI S.pA. (2002–2004) and the Polytechnic University of Turin, Italy (2002–2004, 2006–2007). He is a member of the Institute of Electrical and Electronics Engineers (IEEE) and cofounder-member of the IEEE Power Electronics Romanian Chapter. He is a guest editor at Energies and an academic book editor for IntechOpen. He is also a member of the editorial boards of the Journal of Electrical Engineering, Electronics, Control and Computer Science and Sustainability. Dr. Gaiceanu has been General Chairman of the IEEE International Symposium on Electrical and Electronics Engineering in the last six editions.",institutionString:'"Dunarea de Jos" University of Galati',institution:{name:'"Dunarea de Jos" University of Galati',country:{name:"Romania"}}},{id:"4519",title:"Prof.",name:"Jaydip",middleName:null,surname:"Sen",slug:"jaydip-sen",fullName:"Jaydip Sen",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/4519/images/system/4519.jpeg",biography:"Jaydip Sen is associated with Praxis Business School, Kolkata, India, as a professor in the Department of Data Science. His research areas include security and privacy issues in computing and communication, intrusion detection systems, machine learning, deep learning, and artificial intelligence in the financial domain. He has more than 200 publications in reputed international journals, refereed conference proceedings, and 20 book chapters in books published by internationally renowned publishing houses, such as Springer, CRC press, IGI Global, etc. Currently, he is serving on the editorial board of the prestigious journal Frontiers in Communications and Networks and in the technical program committees of a number of high-ranked international conferences organized by the IEEE, USA, and the ACM, USA. He has been listed among the top 2% of scientists in the world for the last three consecutive years, 2019 to 2021 as per studies conducted by the Stanford University, USA.",institutionString:"Praxis Business School",institution:null},{id:"320071",title:"Dr.",name:"Sidra",middleName:null,surname:"Mehtab",slug:"sidra-mehtab",fullName:"Sidra Mehtab",position:null,profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0033Y00002v6KHoQAM/Profile_Picture_1584512086360",biography:"Sidra Mehtab has completed her BS with honors in Physics from Calcutta University, India in 2018. She has done MS in Data Science and Analytics from Maulana Abul Kalam Azad University of Technology (MAKAUT), Kolkata, India in 2020. Her research areas include Econometrics, Time Series Analysis, Machine Learning, Deep Learning, Artificial Intelligence, and Computer and Network Security with a particular focus on Cyber Security Analytics. Ms. Mehtab has published seven papers in international conferences and one of her papers has been accepted for publication in a reputable international journal. She has won the best paper awards in two prestigious international conferences – BAICONF 2019, and ICADCML 2021, organized in the Indian Institute of Management, Bangalore, India in December 2019, and SOA University, Bhubaneswar, India in January 2021. Besides, Ms. Mehtab has also published two book chapters in two books. Seven of her book chapters will be published in a volume shortly in 2021 by Cambridge Scholars’ Press, UK. Currently, she is working as the joint editor of two edited volumes on Time Series Analysis and Forecasting to be published in the first half of 2021 by an international house. Currently, she is working as a Data Scientist with an MNC in Delhi, India.",institutionString:"NSHM College of Management and Technology",institution:{name:"Association for Computing Machinery",country:{name:"United States of America"}}},{id:"226240",title:"Dr.",name:"Andri Irfan",middleName:null,surname:"Rifai",slug:"andri-irfan-rifai",fullName:"Andri Irfan Rifai",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/226240/images/7412_n.jpg",biography:"Andri IRFAN is a Senior Lecturer of Civil Engineering and Planning. He completed the PhD at the Universitas Indonesia & Universidade do Minho with Sandwich Program Scholarship from the Directorate General of Higher Education and LPDP scholarship. He has been teaching for more than 19 years and much active to applied his knowledge in the project construction in Indonesia. His research interest ranges from pavement management system to advanced data mining techniques for transportation engineering. He has published more than 50 papers in journals and 2 books.",institutionString:null,institution:{name:"Universitas Internasional Batam",country:{name:"Indonesia"}}},{id:"314576",title:"Dr.",name:"Ibai",middleName:null,surname:"Laña",slug:"ibai-lana",fullName:"Ibai Laña",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/314576/images/system/314576.jpg",biography:"Dr. Ibai Laña works at TECNALIA as a data analyst. He received his Ph.D. in Artificial Intelligence from the University of the Basque Country (UPV/EHU), Spain, in 2018. He is currently a senior researcher at TECNALIA. His research interests fall within the intersection of intelligent transportation systems, machine learning, traffic data analysis, and data science. He has dealt with urban traffic forecasting problems, applying machine learning models and evolutionary algorithms. He has experience in origin-destination matrix estimation or point of interest and trajectory detection. Working with large volumes of data has given him a good command of big data processing tools and NoSQL databases. He has also been a visiting scholar at the Knowledge Engineering and Discovery Research Institute, Auckland University of Technology.",institutionString:"TECNALIA Research & Innovation",institution:{name:"Tecnalia",country:{name:"Spain"}}},{id:"314575",title:"Dr.",name:"Jesus",middleName:null,surname:"L. Lobo",slug:"jesus-l.-lobo",fullName:"Jesus L. Lobo",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/314575/images/system/314575.png",biography:"Dr. Jesús López is currently based in Bilbao (Spain) working at TECNALIA as Artificial Intelligence Research Scientist. In most cases, a project idea or a new research line needs to be investigated to see if it is good enough to take into production or to focus on it. That is exactly what he does, diving into Machine Learning algorithms and technologies to help TECNALIA to decide whether something is great in theory or will actually impact on the product or processes of its projects. So, he is expert at framing experiments, developing hypotheses, and proving whether they’re true or not, in order to investigate fundamental problems with a longer time horizon. He is also able to design and develop PoCs and system prototypes in simulation. He has participated in several national and internacional R&D projects.\n\nAs another relevant part of his everyday research work, he usually publishes his findings in reputed scientific refereed journals and international conferences, occasionally acting as reviewer and Programme Commitee member. Concretely, since 2018 he has published 9 JCR (8 Q1) journal papers, 9 conference papers (e.g. ECML PKDD 2021), and he has co-edited a book. He is also active in popular science writing data science stories for reputed blogs (KDNuggets, TowardsDataScience, Naukas). Besides, he has recently embarked on mentoring programmes as mentor, and has also worked as data science trainer.",institutionString:"TECNALIA Research & Innovation",institution:{name:"Tecnalia",country:{name:"Spain"}}},{id:"103779",title:"Prof.",name:"Yalcin",middleName:null,surname:"Isler",slug:"yalcin-isler",fullName:"Yalcin Isler",position:null,profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bRyQ8QAK/Profile_Picture_1628834958734",biography:"Yalcin Isler (1971 - Burdur / Turkey) received the B.Sc. degree in the Department of Electrical and Electronics Engineering from Anadolu University, Eskisehir, Turkey, in 1993, the M.Sc. degree from the Department of Electronics and Communication Engineering, Suleyman Demirel University, Isparta, Turkey, in 1996, the Ph.D. degree from the Department of Electrical and Electronics Engineering, Dokuz Eylul University, Izmir, Turkey, in 2009, and the Competence of Associate Professorship from the Turkish Interuniversity Council in 2019.\n\nHe was Lecturer at Burdur Vocational School in Suleyman Demirel University (1993-2000, Burdur / Turkey), Software Engineer (2000-2002, Izmir / Turkey), Research Assistant in Bulent Ecevit University (2002-2003, Zonguldak / Turkey), Research Assistant in Dokuz Eylul University (2003-2010, Izmir / Turkey), Assistant Professor at the Department of Electrical and Electronics Engineering in Bulent Ecevit University (2010-2012, Zonguldak / Turkey), Assistant Professor at the Department of Biomedical Engineering in Izmir Katip Celebi University (2012-2019, Izmir / Turkey). He is an Associate Professor at the Department of Biomedical Engineering at Izmir Katip Celebi University, Izmir / Turkey, since 2019. In addition to academics, he has also founded Islerya Medical and Information Technologies Company, Izmir / Turkey, since 2017.\n\nHis main research interests cover biomedical signal processing, pattern recognition, medical device design, programming, and embedded systems. He has many scientific papers and participated in several projects in these study fields. He was an IEEE Student Member (2009-2011) and IEEE Member (2011-2014) and has been IEEE Senior Member since 2014.",institutionString:null,institution:{name:"Izmir Kâtip Çelebi University",country:{name:"Turkey"}}},{id:"339677",title:"Dr.",name:"Mrinmoy",middleName:null,surname:"Roy",slug:"mrinmoy-roy",fullName:"Mrinmoy Roy",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/339677/images/16768_n.jpg",biography:"An accomplished Sales & Marketing professional with 12 years of cross-functional experience in well-known organisations such as CIPLA, LUPIN, GLENMARK, ASTRAZENECA across different segment of Sales & Marketing, International Business, Institutional Business, Product Management, Strategic Marketing of HIV, Oncology, Derma, Respiratory, Anti-Diabetic, Nutraceutical & Stomatological Product Portfolio and Generic as well as Chronic Critical Care Portfolio. A First Class MBA in International Business & Strategic Marketing, B.Pharm, D.Pharm, Google Certified Digital Marketing Professional. Qualified PhD Candidate in Operations and Management with special focus on Artificial Intelligence and Machine Learning adoption, analysis and use in Healthcare, Hospital & Pharma Domain. Seasoned with diverse therapy area of Pharmaceutical Sales & Marketing ranging from generating revenue through generating prescriptions, launching new products, and making them big brands with continuous strategy execution at the Physician and Patients level. Moved from Sales to Marketing and Business Development for 3.5 years in South East Asian Market operating from Manila, Philippines. Came back to India and handled and developed Brands such as Gluconorm, Lupisulin, Supracal, Absolut Woman, Hemozink, Fabiflu (For COVID 19), and many more. In my previous assignment I used to develop and execute strategies on Sales & Marketing, Commercialization & Business Development for Institution and Corporate Hospital Business portfolio of Oncology Therapy Area for AstraZeneca Pharma India Ltd. Being a Research Scholar and Student of ‘Operations Research & Management: Artificial Intelligence’ I published several pioneer research papers and book chapters on the same in Internationally reputed journals and Books indexed in Scopus, Springer and Ei Compendex, Google Scholar etc. Currently, I am launching PGDM Pharmaceutical Management Program in IIHMR Bangalore and spearheading the course curriculum and structure of the same. I am interested in Collaboration for Healthcare Innovation, Pharma AI Innovation, Future trend in Marketing and Management with incubation on Healthcare, Healthcare IT startups, AI-ML Modelling and Healthcare Algorithm based training module development. I am also an affiliated member of the Institute of Management Consultant of India, looking forward to Healthcare, Healthcare IT and Innovation, Pharma and Hospital Management Consulting works.",institutionString:null,institution:{name:"Lovely Professional University",country:{name:"India"}}},{id:"310576",title:"Prof.",name:"Erick Giovani",middleName:null,surname:"Sperandio Nascimento",slug:"erick-giovani-sperandio-nascimento",fullName:"Erick Giovani Sperandio Nascimento",position:null,profilePictureURL:"https://intech-files.s3.amazonaws.com/0033Y00002pDKxDQAW/ProfilePicture%202022-06-20%2019%3A57%3A24.788",biography:"Prof. Erick Sperandio is the Lead Researcher and professor of Artificial Intelligence (AI) at SENAI CIMATEC, Bahia, Brazil, also working with Computational Modeling (CM) and HPC. He holds a PhD in Environmental Engineering in the area of Atmospheric Computational Modeling, a Master in Informatics in the field of Computational Intelligence and Graduated in Computer Science from UFES. He currently coordinates, leads and participates in R&D projects in the areas of AI, computational modeling and supercomputing applied to different areas such as Oil and Gas, Health, Advanced Manufacturing, Renewable Energies and Atmospheric Sciences, advising undergraduate, master's and doctoral students. He is the Lead Researcher at SENAI CIMATEC's Reference Center on Artificial Intelligence. In addition, he is a Certified Instructor and University Ambassador of the NVIDIA Deep Learning Institute (DLI) in the areas of Deep Learning, Computer Vision, Natural Language Processing and Recommender Systems, and Principal Investigator of the NVIDIA/CIMATEC AI Joint Lab, the first in Latin America within the NVIDIA AI Technology Center (NVAITC) worldwide program. He also works as a researcher at the Supercomputing Center for Industrial Innovation (CS2i) and at the SENAI Institute of Innovation for Automation (ISI Automação), both from SENAI CIMATEC. He is a member and vice-coordinator of the Basic Board of Scientific-Technological Advice and Evaluation, in the area of Innovation, of the Foundation for Research Support of the State of Bahia (FAPESB). He serves as Technology Transfer Coordinator and one of the Principal Investigators at the National Applied Research Center in Artificial Intelligence (CPA-IA) of SENAI CIMATEC, focusing on Industry, being one of the six CPA-IA in Brazil approved by MCTI / FAPESP / CGI.br. He also participates as one of the representatives of Brazil in the BRICS Innovation Collaboration Working Group on HPC, ICT and AI. He is the coordinator of the Work Group of the Axis 5 - Workforce and Training - of the Brazilian Strategy for Artificial Intelligence (EBIA), and member of the MCTI/EMBRAPII AI Innovation Network Training Committee. He is the coordinator, by SENAI CIMATEC, of the Artificial Intelligence Reference Network of the State of Bahia (REDE BAH.IA). He leads the working group of experts representing Brazil in the Global Partnership on Artificial Intelligence (GPAI), on the theme \"AI and the Pandemic Response\".",institutionString:"Manufacturing and Technology Integrated Campus – SENAI CIMATEC",institution:null},{id:"1063",title:"Prof.",name:"Constantin",middleName:null,surname:"Volosencu",slug:"constantin-volosencu",fullName:"Constantin Volosencu",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/1063/images/system/1063.png",biography:"Prof. Dr. Constantin Voloşencu graduated as an engineer from\nPolitehnica University of Timișoara, Romania, where he also\nobtained a doctorate degree. He is currently a full professor in\nthe Department of Automation and Applied Informatics at the\nsame university. Dr. Voloşencu is the author of ten books, seven\nbook chapters, and more than 160 papers published in journals\nand conference proceedings. He has also edited twelve books and\nhas twenty-seven patents to his name. He is a manager of research grants, editor in\nchief and member of international journal editorial boards, a former plenary speaker, a member of scientific committees, and chair at international conferences. His\nresearch is in the fields of control systems, control of electric drives, fuzzy control\nsystems, neural network applications, fault detection and diagnosis, sensor network\napplications, monitoring of distributed parameter systems, and power ultrasound\napplications. He has developed automation equipment for machine tools, spooling\nmachines, high-power ultrasound processes, and more.",institutionString:'"Politechnica" University Timişoara',institution:null},{id:"221364",title:"Dr.",name:"Eneko",middleName:null,surname:"Osaba",slug:"eneko-osaba",fullName:"Eneko Osaba",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/221364/images/system/221364.jpg",biography:"Dr. Eneko Osaba works at TECNALIA as a senior researcher. He obtained his Ph.D. in Artificial Intelligence in 2015. He has participated in more than twenty-five local and European research projects, and in the publication of more than 130 papers. He has performed several stays at universities in the United Kingdom, Italy, and Malta. Dr. Osaba has served as a program committee member in more than forty international conferences and participated in organizing activities in more than ten international conferences. He is a member of the editorial board of the International Journal of Artificial Intelligence, Data in Brief, and Journal of Advanced Transportation. He is also a guest editor for the Journal of Computational Science, Neurocomputing, Swarm, and Evolutionary Computation and IEEE ITS Magazine.",institutionString:"TECNALIA Research & Innovation",institution:{name:"Tecnalia",country:{name:"Spain"}}},{id:"275829",title:"Dr.",name:"Esther",middleName:null,surname:"Villar-Rodriguez",slug:"esther-villar-rodriguez",fullName:"Esther Villar-Rodriguez",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/275829/images/system/275829.jpg",biography:"Dr. Esther Villar obtained a Ph.D. in Information and Communication Technologies from the University of Alcalá, Spain, in 2015. She obtained a degree in Computer Science from the University of Deusto, Spain, in 2010, and an MSc in Computer Languages and Systems from the National University of Distance Education, Spain, in 2012. Her areas of interest and knowledge include natural language processing (NLP), detection of impersonation in social networks, semantic web, and machine learning. Dr. Esther Villar made several contributions at conferences and publishing in various journals in those fields. Currently, she is working within the OPTIMA (Optimization Modeling & Analytics) business of TECNALIA’s ICT Division as a data scientist in projects related to the prediction and optimization of management and industrial processes (resource planning, energy efficiency, etc).",institutionString:"TECNALIA Research & Innovation",institution:{name:"Tecnalia",country:{name:"Spain"}}},{id:"49813",title:"Dr.",name:"Javier",middleName:null,surname:"Del Ser",slug:"javier-del-ser",fullName:"Javier Del Ser",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/49813/images/system/49813.png",biography:"Prof. Dr. Javier Del Ser received his first PhD in Telecommunication Engineering (Cum Laude) from the University of Navarra, Spain, in 2006, and a second PhD in Computational Intelligence (Summa Cum Laude) from the University of Alcala, Spain, in 2013. He is currently a principal researcher in data analytics and optimisation at TECNALIA (Spain), a visiting fellow at the Basque Center for Applied Mathematics (BCAM) and a part-time lecturer at the University of the Basque Country (UPV/EHU). His research interests gravitate on the use of descriptive, prescriptive and predictive algorithms for data mining and optimization in a diverse range of application fields such as Energy, Transport, Telecommunications, Health and Industry, among others. In these fields he has published more than 240 articles, co-supervised 8 Ph.D. theses, edited 6 books, coauthored 7 patents and participated/led more than 40 research projects. He is a Senior Member of the IEEE, and a recipient of the Biscay Talent prize for his academic career.",institutionString:"Tecnalia Research & Innovation",institution:{name:"Tecnalia",country:{name:"Spain"}}},{id:"278948",title:"Dr.",name:"Carlos Pedro",middleName:null,surname:"Gonçalves",slug:"carlos-pedro-goncalves",fullName:"Carlos Pedro Gonçalves",position:null,profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bRcmyQAC/Profile_Picture_1564224512145",biography:'Carlos Pedro Gonçalves (PhD) is an Associate Professor at Lusophone University of Humanities and Technologies and a researcher on Complexity Sciences, Quantum Technologies, Artificial Intelligence, Strategic Studies, Studies in Intelligence and Security, FinTech and Financial Risk Modeling. He is also a progammer with programming experience in:\n\nA) Quantum Computing using Qiskit Python module and IBM Quantum Experience Platform, with software developed on the simulation of Quantum Artificial Neural Networks and Quantum Cybersecurity;\n\nB) Artificial Intelligence and Machine learning programming in Python;\n\nC) Artificial Intelligence, Multiagent Systems Modeling and System Dynamics Modeling in Netlogo, with models developed in the areas of Chaos Theory, Econophysics, Artificial Intelligence, Classical and Quantum Complex Systems Science, with the Econophysics models having been cited worldwide and incorporated in PhD programs by different Universities.\n\nReceived an Arctic Code Vault Contributor status by GitHub, due to having developed open source software preserved in the \\"Arctic Code Vault\\" for future generations (https://archiveprogram.github.com/arctic-vault/), with the Strategy Analyzer A.I. module for decision making support (based on his PhD thesis, used in his Classes on Decision Making and in Strategic Intelligence Consulting Activities) and QNeural Python Quantum Neural Network simulator also preserved in the \\"Arctic Code Vault\\", for access to these software modules see: https://github.com/cpgoncalves. He is also a peer reviewer with outsanding review status from Elsevier journals, including Physica A, Neurocomputing and Engineering Applications of Artificial Intelligence. 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Currently working as an Assistant Professor in the Department of Mathematics, Institute of Applied Science, Mangalayatan University, Aligarh. She taught so many courses of Mathematics of UG and PG level. Her research Area of Expertise is Functional Analysis & Sequence Spaces. She has been working on Ideal Convergence of double sequence. She has published 17 research papers in National and International Journals including Cogent Mathematics, Filomat, Journal of Intelligent and Fuzzy Systems, Advances in Difference Equations, Journal of Mathematical Analysis, Journal of Mathematical & Computer Science etc. She has also reviewed few research papers for the and international journals. 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He worked on the structure-function relationships of glycoconjugates and his main project was the investigations on the biological roles of the de-N-glycosylation enzymes (Endo-N-acetyl-β-D-glucosaminidase and peptide-N4-(N-acetyl-β-glucosaminyl) asparagine amidase). From 2002 he contributes to the understanding of the Blood-brain barrier functioning using proteomics approaches. He has published more than 70 papers. 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