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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:"9984",leadTitle:null,fullTitle:"Geophysics and Ocean Waves Studies",title:"Geophysics and Ocean Waves Studies",subtitle:null,reviewType:"peer-reviewed",abstract:"The book “Geophysics and Ocean Waves Studies” presents the collected chapters in two sections named “Geophysics” and “Ocean Waves Studies”. The first section, “Geophysics”, provides a thorough overview of using different geophysical methods including gravity, self-potential, and EM in exploration. Moreover, it shows the significance of rock physics properties and enhanced oil recovery phases during oil reservoir production. The second section, “Ocean Waves Studies”, is intended to provide the reader with a strong description of the latest developments in the physical and numerical description of wind-generated and long waves, including some new features discovered in the last few years. The section is organized with the aim to introduce the reader from offshore to nearshore phenomena including a description of wave dissipation and large-scale phenomena (i.e., storm surges and landslide-induced tsunamis). This book shall be of great interest to students, scientists, geologists, geophysicists, and the investment community.",isbn:"978-1-78985-445-9",printIsbn:"978-1-78985-372-8",pdfIsbn:"978-1-78985-446-6",doi:"10.5772/intechopen.87807",price:119,priceEur:129,priceUsd:155,slug:"geophysics-and-ocean-waves-studies",numberOfPages:184,isOpenForSubmission:!1,isInWos:null,isInBkci:!1,hash:"271d086381f9ba04162b0dc7cd57755f",bookSignature:"Khalid S. Essa, Marcello Di Risio, Daniele Celli and Davide Pasquali",publishedDate:"March 17th 2021",coverURL:"https://cdn.intechopen.com/books/images_new/9984.jpg",numberOfDownloads:5113,numberOfWosCitations:0,numberOfCrossrefCitations:9,numberOfCrossrefCitationsByBook:1,numberOfDimensionsCitations:16,numberOfDimensionsCitationsByBook:1,hasAltmetrics:0,numberOfTotalCitations:25,isAvailableForWebshopOrdering:!0,dateEndFirstStepPublish:"October 16th 2019",dateEndSecondStepPublish:"March 24th 2020",dateEndThirdStepPublish:"May 23rd 2020",dateEndFourthStepPublish:"August 11th 2020",dateEndFifthStepPublish:"October 10th 2020",currentStepOfPublishingProcess:5,indexedIn:"1,2,3,4,5,6,7",editedByType:"Edited by",kuFlag:!1,featuredMarkup:null,editors:[{id:"102766",title:"Prof.",name:"Khalid S.",middleName:null,surname:"Essa",slug:"khalid-s.-essa",fullName:"Khalid S. Essa",profilePictureURL:"https://mts.intechopen.com/storage/users/102766/images/system/102766.jpg",biography:"Dr. Khalid S. Essa obtained his B.Sc. with honors (1997), M.Sc. (2001) and Ph.D. (2004) in Geophysics from the Faculty of Science, Cairo University. He joined the staff of Cairo University (1997) and was appointed a research Professor of potential field methods in the Department of Geophysics (2014). He has undertaken affiliated post-doctoral visits to Strasbourg University, France (2018-2019), Charles University in Prague, Czech (2014-2015) and Western Michigan University, USA (2006-2007). He has authored more than 70 technical papers and served as an Editor and external reviewer for many top journals. He attended several International Geophysical Conferences in USA, Australia and France. He was a member in SEG, AGU, AAPG, EAGE and EGS. Also, he is a member of the National committee for Geodesy and Geophysics, Academy of Scientific Research and Technology, Egypt (2020-2023) and member of the Petroleum and Mineral Resources Research Council, Sector of Quality Councils, Academy of Scientific Research and Technology, Egypt (2018-2021). He has been awarded the Award of Prof. Nasry Matari Shokry in Applied Geology, Academy of Scientific Research & Technology (2017) and the Award of Cairo University for Scientific Excellence in Interdisciplinary, Multidisciplinary and Future Sciences (2017).",institutionString:"Cairo University",position:null,outsideEditionCount:0,totalCites:0,totalAuthoredChapters:"4",totalChapterViews:"0",totalEditedBooks:"2",institution:{name:"Cairo University",institutionURL:null,country:{name:"Egypt"}}}],equalEditorOne:null,equalEditorTwo:null,equalEditorThree:null,coeditorOne:{id:"15209",title:"Prof.",name:"Marcello",middleName:null,surname:"Di Risio",slug:"marcello-di-risio",fullName:"Marcello Di Risio",profilePictureURL:"https://mts.intechopen.com/storage/users/15209/images/system/15209.jpg",biography:"Marcello Di Risio is a full professor (academic discipline: Hydraulic Structures, Maritime Engineering, and Hydrology) at the Civil, Construction-Architectural and Environmental Engineering Department of the University of L'Aquila, Italy. He is the Head of the Laboratory of Environmental and Maritime Hydraulics (LIam) at the same department. He received his Ph.D. in 2005 from the Roma Tre University, Italy and held a research grant at the Tor Vergata University of Rome, Italy. From 2008-2020, he served as a researcher and associate professor at the University of L'Aquila, Italy. He has acted as chief scientist and coordinator of several research projects, funded by public and private bodies. With many years of experience in the field of hydraulic and maritime construction, his main research topics are: mathematical and experimental modeling of coastal morphodynamic and hydrodynamic phenomena, landslide-generated waves, maritime and hydraulic works, hydraulic and coastal risk analysis, real-time identification systems of tidal waves, real-time forecasting systems of wave motion and water levels, and development of devices for energy extraction from waves.",institutionString:"University of L'Aquila",position:null,outsideEditionCount:0,totalCites:0,totalAuthoredChapters:"3",totalChapterViews:"0",totalEditedBooks:"0",institution:{name:"University of L'Aquila",institutionURL:null,country:{name:"Italy"}}},coeditorTwo:{id:"309494",title:"Dr.",name:"Daniele",middleName:null,surname:"Celli",slug:"daniele-celli",fullName:"Daniele Celli",profilePictureURL:"https://mts.intechopen.com/storage/users/309494/images/system/309494.jpg",biography:"Daniele Celli is currently a Post Doctorate student at the Department of Civil, Construction-Architectural and Environmental Engineering (DICEAA) of the University of L’Aquila. In 2015, he received his Master’s Degree (cum laude) in Civil Engineering and in 2019 he received his Ph.D. (cum laude) in Risk and Environmental, Territorial and Building Development at the Technical University of Bari. His research interests are focused on coastal structures, water wave generation and propagation, physical and numerical modeling of wave-structure interaction and wave-soil-structure interaction, wave energy assessment and extraction, coastal hydrodynamics, and morphodynamics.",institutionString:"University of L'Aquila",position:null,outsideEditionCount:0,totalCites:0,totalAuthoredChapters:"0",totalChapterViews:"0",totalEditedBooks:"0",institution:{name:"University of L'Aquila",institutionURL:null,country:{name:"Italy"}}},coeditorThree:{id:"309493",title:"Dr.",name:"Davide",middleName:null,surname:"Pasquali",slug:"davide-pasquali",fullName:"Davide Pasquali",profilePictureURL:"https://mts.intechopen.com/storage/users/309493/images/system/309493.jpg",biography:"Davide Pasquali is currently a Research Fellow in the Department of Civil, Construction-Architectural and Environmental Engineering (DICEAA) at the University of L’Aquila. In 2011, he received his Master’s Degree (cum laude) in Civil Engineering and in 2015 he received his Ph.D. in Civil Engineering at the University of L’Aquila. His research interests are focused on water wave generation and propagation, coastal hydrodynamic and morphodynamic, physical and numerical modeling of wave-structure interaction, wave energy assessment and extraction, risk analysis, and marine sediments transport.",institutionString:"University of L'Aquila",position:null,outsideEditionCount:0,totalCites:0,totalAuthoredChapters:"1",totalChapterViews:"0",totalEditedBooks:"0",institution:{name:"University of L'Aquila",institutionURL:null,country:{name:"Italy"}}},coeditorFour:null,coeditorFive:null,topics:[{id:"225",title:"Geophysics",slug:"geophysics"}],chapters:[{id:"71855",title:"Combined Gravity or Self-Potential Anomaly Formula for Mineral Exploration",doi:"10.5772/intechopen.92139",slug:"combined-gravity-or-self-potential-anomaly-formula-for-mineral-exploration",totalDownloads:335,totalCrossrefCites:0,totalDimensionsCites:0,hasAltmetrics:0,abstract:"A combined gravity and/or self-potential anomaly formula is utilized to estimate the model parameters of the buried geologic structures represented by simple geometric. The simple geometric shapes (spheres, cylinders, and sheets) are not really found but often applied to reduce the nonuniqueness in interpreting the gravity and self-potential data. Numerous approaches through the combined formula such as least squares, Werner deconvolution, and the particle swarm optimization method are used. The application of these methods was demonstrated by applying a synthetic gravity and self-potential example without and with 10% random noise to compare their efficiency in estimating the model parameters of the buried structures. Besides, they were applied to two field data for mineral exploration. The appraised model parameter values from each method were compared together and with those published in literature.",signatures:"Khalid S. Essa and Mahmoud Elhussein",downloadPdfUrl:"/chapter/pdf-download/71855",previewPdfUrl:"/chapter/pdf-preview/71855",authors:[{id:"102766",title:"Prof.",name:"Khalid S.",surname:"Essa",slug:"khalid-s.-essa",fullName:"Khalid S. Essa"},{id:"208891",title:"Dr.",name:"Mahmoud",surname:"Elhussein",slug:"mahmoud-elhussein",fullName:"Mahmoud Elhussein"}],corrections:null},{id:"72198",title:"Long Wire Electromagnetic Measurements (Turam EM)",doi:"10.5772/intechopen.91387",slug:"long-wire-electromagnetic-measurements-turam-em-",totalDownloads:532,totalCrossrefCites:0,totalDimensionsCites:0,hasAltmetrics:0,abstract:"In Scandinavia, EM measurements have traditionally been popular in sulfide ore exploration. The EM methods using a stationary cable loop or a long wire on the ground surface were called Turam. The wire was grounded by electrodes at the ends. The name, Turam meaning two coils, got the name after the measurement system using two coils measuring the quotient and the phase difference of the vertical field. The measurements were performed in the frequency domain, with frequencies around 400 Hz. Using a large cable loop or a long wire grounded at both ends has advantages as energizing transmitter, which should be utilized in deep exploration. The fall-off rate for the primary field is small, and the electric field can be directed in line with strike direction or the direction of the axis of the mineralization. Examples of the interaction between the energizing cable and the conducting half-space are illustrated by computed models. The grounding points can be shifted with repeated measurements for each grounding position. Both man-made and geological noise can be reduced in this way. Field examples are given in the chapter.",signatures:"Ole Bernt Lile",downloadPdfUrl:"/chapter/pdf-download/72198",previewPdfUrl:"/chapter/pdf-preview/72198",authors:[{id:"313912",title:"Prof.",name:"Ole",surname:"Bernt Lile",slug:"ole-bernt-lile",fullName:"Ole Bernt Lile"}],corrections:null},{id:"72011",title:"Rock Physics: Recent History and Advances",doi:"10.5772/intechopen.92161",slug:"rock-physics-recent-history-and-advances",totalDownloads:1002,totalCrossrefCites:2,totalDimensionsCites:4,hasAltmetrics:0,abstract:"This chapter presents the basics of rock physics, the science exploring quantitative relations between various properties (attributes) of the holistic object we call natural rock. This chapter includes several sections, starting with the history and basics; proceeding to the effects of the pore fluid on rock properties; discussing several variables that influence the elastic properties of rocks; presenting selected theories that relate the elastic properties to the porosity, mineralogy, and texture of rocks; and introducing the latest development, digital rock physics. Data examples shown here illustrate qualitative reasoning. Equations are presented as well to mathematically express the conceptual theories discussed. Most importantly, rock physics references are listed to help the reader become willing to delve deeper into the topic and start applying rock physics theories, concepts, and ideas to field data.",signatures:"Jack Dvorkin",downloadPdfUrl:"/chapter/pdf-download/72011",previewPdfUrl:"/chapter/pdf-preview/72011",authors:[{id:"315484",title:"Prof.",name:"Jack",surname:"Dvorkin",slug:"jack-dvorkin",fullName:"Jack Dvorkin"}],corrections:null},{id:"70319",title:"Enhanced Oil Recovery: Chemical Flooding",doi:"10.5772/intechopen.90335",slug:"enhanced-oil-recovery-chemical-flooding",totalDownloads:725,totalCrossrefCites:1,totalDimensionsCites:4,hasAltmetrics:0,abstract:"The enhanced oil recovery phase of oil reservoirs production usually comes after the water/gas injection (secondary recovery) phase. The main objective of EOR application is to mobilize the remaining oil through enhancing the oil displacement and volumetric sweep efficiency. The oil displacement efficiency enhances by reducing the oil viscosity and/or by reducing the interfacial tension, while the volumetric sweep efficiency improves by developing a favorable mobility ratio between the displacing fluid and the remaining oil. It is important to identify remaining oil and the production mechanisms that are necessary to improve oil recovery prior to implementing an EOR phase. Chemical enhanced oil recovery is one of the major EOR methods that reduces the residual oil saturation by lowering water-oil interfacial tension (surfactant/alkaline) and increases the volumetric sweep efficiency by reducing the water-oil mobility ratio (polymer). In this chapter, the basic mechanisms of different chemical methods have been discussed including the interactions of different chemicals with the reservoir rocks and fluids. In addition, an up-to-date status of chemical flooding at the laboratory scale, pilot projects and field applications have been reported.",signatures:"Ahmed Ragab and Eman M. Mansour",downloadPdfUrl:"/chapter/pdf-download/70319",previewPdfUrl:"/chapter/pdf-preview/70319",authors:[{id:"277274",title:"Dr.",name:"Eman M.",surname:"Mansour",slug:"eman-m.-mansour",fullName:"Eman M. Mansour"}],corrections:null},{id:"72024",title:"High-Resolution Numerical Simulation of Surface Wave Development under the Action of Wind",doi:"10.5772/intechopen.92262",slug:"high-resolution-numerical-simulation-of-surface-wave-development-under-the-action-of-wind",totalDownloads:677,totalCrossrefCites:2,totalDimensionsCites:2,hasAltmetrics:0,abstract:"The paper describes the numerical experiments with a three-dimensional phase-resolving model based on the initial potential equation of motion with free surface at deep water in the periodic domain written in the surface-following nonstationary curvilinear nonorthogonal coordinate system. The numerical scheme is based on Fourier-transform method. The vertical velocity on surface is calculated by solving the three-dimensional Poisson equation for the velocity potential. The velocity potential is represented as a sum of linear and nonlinear components. The linear component is described by Laplace equation. The nonlinear component is calculated by solution of the three-dimensional Poisson equation with the iterated right-hand side. The model includes some algorithms for calculation of the energy input from wind as well as for calculation of breaking and high-frequency dissipation. Initially, the conditions are assigned as a set of small waves corresponding to JONSWAP spectrum at high wave number. In response to waves’ growth, the spectrum shifts to lower wave numbers. The evolution of spectrum is generally in an agreement with the observed data. The wave spectrum and the spectra of different rates of energy transformation as well as the statistical characteristics of wave field for different stages of development are described.",signatures:"Dmitry Chalikov",downloadPdfUrl:"/chapter/pdf-download/72024",previewPdfUrl:"/chapter/pdf-preview/72024",authors:[{id:"316767",title:"Prof.",name:"Dmitry",surname:"Chalikov",slug:"dmitry-chalikov",fullName:"Dmitry Chalikov"}],corrections:null},{id:"72908",title:"Surface Gravity Wave Modeling in Tropical Cyclones",doi:"10.5772/intechopen.93275",slug:"surface-gravity-wave-modeling-in-tropical-cyclones",totalDownloads:419,totalCrossrefCites:2,totalDimensionsCites:3,hasAltmetrics:0,abstract:"Tropical cyclones are among the deadliest geophysical phenomena on earth. Tropical cyclone-generated wave fields are of interest both scientifically for understanding wind–wave-ocean interaction physics and operationally for predicting potentially hazardous conditions for ship navigation and coastal regions. This chapter briefly reviews the development of third generation wave models, the improvements of their input/dissipation source functions, and their applications in tropical cyclone generated surface wave predictions. Discussion on the status of coupled atmosphere-wave-ocean modeling in tropical cyclone predictions are given at the end of the chapter prompted by the growing scientific evidence on the importance of sea state on air-sea fluxes under extreme wind conditions.",signatures:"Yalin Fan, Paul Hwang and John Yu",downloadPdfUrl:"/chapter/pdf-download/72908",previewPdfUrl:"/chapter/pdf-preview/72908",authors:[{id:"320023",title:"Dr.",name:"Yalin",surname:"Fan",slug:"yalin-fan",fullName:"Yalin Fan"},{id:"323382",title:"Dr.",name:"Paul",surname:"Hwang",slug:"paul-hwang",fullName:"Paul Hwang"},{id:"323383",title:"Mr.",name:"John",surname:"Yu",slug:"john-yu",fullName:"John Yu"}],corrections:null},{id:"72288",title:"Simplified Methods for Storm Surge Forecast and Hindcast in Semi-Enclosed Basins: A Review",doi:"10.5772/intechopen.92171",slug:"simplified-methods-for-storm-surge-forecast-and-hindcast-in-semi-enclosed-basins-a-review",totalDownloads:600,totalCrossrefCites:0,totalDimensionsCites:0,hasAltmetrics:1,abstract:"It is widely known that small and semi-enclosed basins could be inclined to storm surge events. This is mainly due to either the meteorological exposition, to the presence of a continental shelf or to their shape. These storm surges can induce coastal flooding and consequent problems in terms of infrastructure stability and damage to touristic activities or, in some cases, threaten human life. Therefore, in order to manage the risk, coastal managers or policymakers need to have forecast or hindcast tools. They must help to take preventive actions that may be done previously to the occurrence of natural phenomena and to carry out simultaneous actions useful during the occurrence of the event. This work aims at answering these necessities presenting a review of two methods for storm surge forecast and hindcast in semi-enclosed basins.",signatures:"Davide Pasquali",downloadPdfUrl:"/chapter/pdf-download/72288",previewPdfUrl:"/chapter/pdf-preview/72288",authors:[{id:"309493",title:"Dr.",name:"Davide",surname:"Pasquali",slug:"davide-pasquali",fullName:"Davide Pasquali"}],corrections:null},{id:"73416",title:"Physical and Numerical Modeling of Landslide-Generated Tsunamis: A Review",doi:"10.5772/intechopen.93878",slug:"physical-and-numerical-modeling-of-landslide-generated-tsunamis-a-review",totalDownloads:411,totalCrossrefCites:2,totalDimensionsCites:3,hasAltmetrics:0,abstract:"Landslide-generated tsunamis represent a serious source of hazard for many coastal and lacustrine communities. The understanding of the complex physical phenomena that govern the tsunami generation, propagation and interaction with the coast is essential to reduce and mitigate the tsunamis risk. Experimental, analytical, and numerical models have been extensively used (both as separated tools and in conjunction) to shed light on these complicated natural events. In this work, a non-exhaustive update of the state of the art related to the physical and numerical modeling techniques of landslide-generated tsunamis, with a special focus on those studies published in the last ten years, is provided. As far as numerical models are concerned, a special attention is paid to the most recently developed Computational Fluid Dynamics (CFD) techniques, whose development and application have experienced a boost up the last decade.",signatures:"Alessandro Romano",downloadPdfUrl:"/chapter/pdf-download/73416",previewPdfUrl:"/chapter/pdf-preview/73416",authors:[{id:"321581",title:"Dr.",name:"Alessandro",surname:"Romano",slug:"alessandro-romano",fullName:"Alessandro Romano"}],corrections:null},{id:"73801",title:"Hydrodynamics of Regular Breaking Wave",doi:"10.5772/intechopen.94449",slug:"hydrodynamics-of-regular-breaking-wave",totalDownloads:413,totalCrossrefCites:0,totalDimensionsCites:0,hasAltmetrics:0,abstract:"Turbulence and undertow currents play an important role in surf-zone mixing and transport processes; therefore, their study is fundamental for the understanding of nearshore dynamics and the related planning and management of coastal engineering activities. Pioneering studies qualitatively described the features of breakers in the outer region of the surf zone. More detailed information on the velocity field under spilling and plunging breakers can be found in experimental works, where single-point measurement techniques, such as Hot Wire Anemometry and Laser Doppler Anemometry (LDA), were used to provide maps of the flow field in a time-averaged or ensemble-averaged sense. Moreover, the advent of non-intrusive measuring techniques, such as Particle Image Velocimetry (PIV) provided accurate and detailed instantaneous spatial maps of the flow field. However, by correlating spatial gradients of the measured velocity components, the instantaneous vorticity maps could be deduced. Moreover, the difficulties of measuring velocity due to the existence of air bubbles entrained by the plunging jet have hindered many experimental studies on wave breaking encouraging the development of numerical model as useful tool to assisting in the interpretation and even the discovery of new phenomena. Therefore, the development of an WCSPH method using the RANS equations coupled with a two-equation k–ε model for turbulent stresses has been employed to study of the turbulence and vorticity distributions in in the breaking region observing that these two aspects greatly influence many coastal processes, such as undertow currents, sediment transport and action on maritime structures.",signatures:"Diana De Padova and Michele Mossa",downloadPdfUrl:"/chapter/pdf-download/73801",previewPdfUrl:"/chapter/pdf-preview/73801",authors:[{id:"320394",title:"Prof.",name:"Michele",surname:"Mossa",slug:"michele-mossa",fullName:"Michele Mossa"},{id:"328068",title:"Dr.",name:"Diana",surname:"De Padova",slug:"diana-de-padova",fullName:"Diana De Padova"}],corrections:null}],productType:{id:"1",title:"Edited Volume",chapterContentType:"chapter",authoredCaption:"Edited by"},subseries:null,tags:null},relatedBooks:[{type:"book",id:"7315",title:"Minerals",subtitle:null,isOpenForSubmission:!1,hash:"f0d5c2a9a5f37e6effcb8486c661d217",slug:"minerals",bookSignature:"Khalid S. 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\r\n\tThe book explains and educates the reader regarding normal sexual function, sexual dysfunction, and sexual dysfunction disorders both in males and females. The objective of the book will be to highlight the importance of sex education and explain normal human sexuality. With the growing number of males and females reporting sexual dysfunction the need for a ready reckoner of sexual dysfunction may be relevant and necessary.
\r\n\r\n\tThe book will have chapters on normal human sexuality, sexual health, Sexual dysfunction in the male and female, sexual dysfunction disorders related to libido, orgasm, ejaculation, erection, and genetic or hormonal or developmental or sexuo-erotic orientation defects.
\r\n\r\n\tThe book will also highlight the importance of sex counselors and therapists.
\r\n\tThere will be a chapter on secondary causes of sexual dysfunction disorders related to diabetes, cardiovascular disease, and obesity. A chapter on remedial measures to enhance sexual activity and maintain human relationships will be discussed. As there is a growing number of cancer survivors a chapter on cancer-related sexual dysfunction will be welcomed for including it.
Wide varieties of textile materials are available in the market. Each of them is meant for a particular purpose; ranging from covering nakedness, decoration to medical purpose [1]. Moisture content (MC) and moisture regain (MR) are some of the important properties to be considered for chosen these materials for intending purpose. Generally, natural fibers are of relatively high MC and MR when compared with man-made fibers [2]. Hence, they are more prone to microbial attack than their man-made counterparts, due to combination of fiber’s moisture and warm environment (body temperature between 36 and 38°C) that favors microbial growth on textile substrates.
Therefore, many textile materials especially those from natural source are potential media for microbial growth in their unmodified form. The major demerits of microbial growth in textile materials are offensive odor, discoloration, staining and mechanical strength reduction. At times, microbial growth on clothing materials may cause dermal infection on the skin of the wearers [1]. These effects are more likely to occur in natural textile materials. They are disliked by textile manufacturers and therefore, need to be avoided to the barest maximum [3]. Several researchers have tried in one way or the other to work on textile fibers (especially the natural fibers) in order to reduce the rate at which they get attacked by microorganisms. Bhuiyan et al. [3] reported
This section will focus on after-treatments modification of natural fibers, since they are more associated with microbial attacks.
The after-treatment of these fibers is meant to modify their surfaces for combating microorganisms when in contact with them. Although, some of the chemical finishing agents do not only modify the surface of textile materials but as well form chemical bond with textile matrix. The commonly used reagents for production of antimicrobial textile materials are silver compounds/composites and quaternary ammonium compounds [5]. High cost and environmental awareness on these compounds made researchers to be looking for low cost and environment friendly alternative from naturally derived materials. The reagents reported for this purpose are chitosan, natural and synthetic dyes [6].
How these reagents perform their roles as antimicrobial agents on textiles will be discussed in the below sub-sections.
Silver in form of chloride, nano-particle, organo-silver or composite is used as antimicrobial agent for textile material. The application of these antimicrobial agents to man-made textile materials (silk inclusive) can be through pad-dry, coating, spray, foam technique or can be done directly by their inclusion in spinning dope during spinning operation. Their application on natural textile materials is often done through exhaustion in aqueous solution or done during dyeing operation [7]. Addition of stabilizing agent (e.g. propylene glycol, sodium salt of alkyl sulfate, polyethylamine, polyethylpyrrolidine, dendrimers etc.) to any of these antimicrobial agents during aqueous application performs triple functions. Foremost, it prevents precipitation/agglomeration of the antimicrobial agent in solution. Polymeric stabilizing agents form silver–polymer giant molecules that enhance performance of antimicrobial agent in natural textile substrates and lastly, it reduces probability of Ag+ bleeding out from textile substrates [2].
The way and manner silver performs anti-microbial function in textile substrates is yet to be clearly identified [2]. The general belief is that Ag+ will be released slowly from silver–polymer complex in textile matrix or surface and diffused into the microbial cell(s) when in contact with micro-organisms. Diffusion of Ag+ into the microbial cell’s site hinders activities of microorganisms and finally destroys them. This action is usually a very fast action that occurs within few minutes of contact with microorganisms. Although, silver radical (Ag*) may be formed along with Ag+ released from silver–polymer complex or formed separately instead of the release of Ag+. When in contact with microorganisms, Ag* attacks microbial cell’s protein structure, destroys it and kills the microorganisms. Although, silver antimicrobial agent applied to natural textile substrates through exhaustion are usually active for more than fifty cycles of laundry operation, but the slow release of Ag+/Ag* from silver–polymer complex results into reduction in quantity of available silver in the functional textiles [5]. The one applied through pad-dry, coating, spray or foam technique may no longer active after few laundry operations. These antimicrobial agents are used for production of cloths for active underwear garment, socks and sport wears. They are equally useful in production of antimicrobial cloths for medical applications, such as towels, wound dressing, mattresses spread sheets and pillow cases [7].
Silica matrix stabilizes silver nanoparticles (Figure 1) induced exceptional antimicrobial property onto textile substrates. Silver nanoparticles are weakly held within the silica matrix by physical forces and the release of Ag+ for attacking microorganism is gradual over a long period of time. Application of antimicrobial film prepared from mixture of silver nanoparticles and fluoroalkyl siloxane (FAS) on textile substrates induces a better antimicrobial functional property on textiles [2].
Silver nanoparticles weakly held in silica matrix.
It is essentially useful in production of clothing materials for medical applications and home textiles [3].
However, high cost of silver containing substances made researchers to be looking for low cost and effective alternatives as antimicrobial agents for inducing antimicrobial property onto the textile substrates [5].
Quaternary ammonium compounds (Figure 2) are applied to textile substrates as antimicrobial agents through sol–gel chemistry.
Trimethylsilyl-propyldimethyloctadecyl ammonium chloride.
Organic–inorganic gel network structure of quaternary ammonium compound can be applied in continuous liquid phase through pad-dry-cure process to form thin film of about 10 nm thickness on textile surface [2]. Prior to curing process between temperature of 140 and 170°C, the thin nano-composite of quaternary ammonium compound film links to textile substrate (e.g. cotton) through covalent bond formation (Figure 3) [6, 7].
Propyldimethyloctadecylammonium chloro silicone pad-dry-cured textile substrate.
The covalent bond formed imparts excellent durability to the textile through strong bond of attraction between the antimicrobial thin film and textile substrate. It also gives a control action of cationic quaternary ammonium compound against microorganism when in contact with textile surface. The cationic charge on the antimicrobial agent formed complex with anionic charged microbial cell membrane, thereby hindering microbial activity and finally kill the microorganism [2]. Just like in Ag+ nanoparticles treated antimicrobial textiles, Quaternary ammonium compound treated cloths are equally useful for medical and domestic applications such as towels, wound dressing, mattresses spread sheets and pillow cases, mattresses and window blind.
Recent investigation has shown possibility of preparing antimicrobial precursor mixture from combination of quaternary ammonium compound and fluoroalkyl siloxane (Figure 4). Application of this antimicrobial mixture on textile substrates inhibits microbial growth very effectively. The unique features of this antimicrobial mixture besides the primary property are lowering tendency of adhesion of microorganism to textile substrates (by lowering fiber surface energy), importation of oleophobic and superhydrophobic properties to the textile fibers [2]. Therefore, it can be said that textile material treated with this mixture will possess multi-functional properties for use in production of out-door textiles (non-skin contact textiles), such as marquees, tarpaulins and awnings.
Antimicrobial mixtures on cellulosic fiber.
Chitosan (2-amino-2-deoxy- (1, 4)-𝛽-D-glucopyranan) is a product of partial deacetylation reaction of chitin (Figure 5) obtained from shell of snails, crayfish, lobsters, cuttlefish, fungi cell walls, crabs and shrimps. It is most abundant natural polymer after cellulose. Chitosan is a polysaccharide with molecular structure similar to cellulose, apart from presence of nitrogen in its structure [6].
Deacetylation of chitin.
Chitosan has distinctive properties, such as antimicrobial activity, biodegradability, non-toxicity, solubility in both mineral and organic acids [7]. These properties account for its suitability as antimicrobial agent in textile production. Just like in Ag+, the mechanism of its antimicrobial activities is not clearly understood. Although, it is generally believed that interaction of positively charged chitosan amino group with negatively charged cell membrane of microorganism leads to inhibition of microbial growth and eventually results into their death [2]. Antimicrobial activity of chitosan can also be through binding of microbial DNA by chitosan, which results into microbial cell protein synthesis inhibition. Microorganisms’ inability to biosynthesize protein in chitosan environment leads to their death [7].
Chitosan can be applied onto textile fibers through exhaustion process and made crosslinked giant molecule in fiber matrix through curing process (other possible mode of applications are pad-dry, pad-dry-steam and pad-batch) [5]. It is first dissolved in acidic medium (of a known concentration) by introduction of a known weight of biopolymer in glacial acetic acid (known volume and concentration) for 1 h (ripening time) and the mixture stirred mechanically for 2 h for complete dissolution of chitosan. If the curing process will be through radiation, a known quantity of photoinitiator will be added and required volume will be made through addition of distilled water [7]. But if curing process will be through thermal, required volume of distilled water will be added without addition of photoinitiator. Textile fiber will then be inserted into the prepared chitosan solution to be coated through exhaustion process, followed by drying at 70°C for about 1 h and cured for 30 min in presence of ultraviolet radiation (for photo chitosan cured fibers) or at 170°C (for thermally cured fibers-chitosan) [5]. During the curing process chitosan enters into fiber matrix in linear biopolymer form and undergoes crosslinking reaction. The curing process makes the treated fibers durable, even after several laundry operations [7].
Like in the case of quaternary ammonium compounds, functional antimicrobial property of mixture of chitosan and silver nanoparticles has been reported by researchers to be better than that of individual agent. Therefore, coating textile fibers with mixture of chitosan and silver nanoparticles imparts very good antimicrobial property onto them [4]. Chitosan or chitosan/Ag+ coated textile materials are very good as surgical garments, gloves and face masks. As a matter of fact, textile materials made of these antimicrobial agents are going to be good wears for Covid-19 front line workers and general populace to combat the current pandemic virus.
These are developed in laboratory, from existing natural coloring materials to alleviate demerits fund in natural dyes/pigments. Some of the demerits of natural coloring matters are poor fastness properties, low yield, irreproducibility, lack of uniformity and high cost. Therefore, synthetic coloring matters are relatively cheap, reproducible and have uniform hue, very good to excellent fastness properties and high yield [1, 8]. Previous studies reported bio-based synthetic dyes to possess antibiotic, antiviral, antifungal, anti-oxidant, anticancer, anti-malarial, anti-inflammatory and ultraviolet protective properties [9].
These coloring matters are many and they are mostly applied onto textile fibers through exhaustion process. Pigments are mostly applied through coating or printing process [8].
It was reported by researchers that many synthetic dyes (especially Schiff base dyes) have antimicrobial property. In previous study, it was reported that synthesized novel 1, 3-bis[(furan-2-l) methylene]thiourea functional dyed wool and cotton fabrics have above 70% anti-fungi inhibition against
Natural dyes are generally soluble in water and as a result, they are usually applied onto textile fibers through exhaustion technique [8]. Due to environmental awareness, there is interest restoration in the use of natural dyes for coloration of textiles. Besides this major reason of their application on textiles, many of them do impart antimicrobial property onto the textiles. The way and manner of their antimicrobial activity on textile fibers has not been clearly defined. Although, it was reported by Soares et al. [10] that antimicrobial active compounds in dyes are phenolics, terpenoids and anthraquinones. The cationic charge on these compounds interacts with anionic charged microbial cell wall to resist cell growth and facilitate microbial death.
Poor fastness properties that are associated with natural dye dyed fibers are usually overcome through the use of metal salts or compounds as mordant. If metal salt like silver nitrate is used as mordant prior to dyeing of textile material with natural dye, dual enrichment given to the dye on fiber matrix are formation of covalent bond between dye molecule-metal ions and fiber matrix and antimicrobial property enhancement of the natural dye dyed fibers [2]. If natural mordant like chitosan solution is used as mordant prior to dyeing process of the fiber, amino cationic charge on chitosan boosts antimicrobial property of the dye through degradation of proteineous microbial cell wall of microorganism. It equally enhances color strength of the dyed fibers [3]. Antimicrobial synergic effect of chitosan and natural dye called henna on jute fibers was studied against
The antimicrobial chemical reagents can be applied onto the textile fibers through (i) exhaustion and (ii) coating/dry pad techniques depending on interaction of fiber matrix with antimicrobial agents [10].
Antimicrobial agents that chemically react with fibers are applied on fibers through this technique. Antimicrobial natural and synthetic dyes are usually applied through this technique [1].
Exhaustion technique involves solubilization of antimicrobial agent in a suitable solvent, immersion of the fibers in the solution and stirs the mixture for specific period of time at a particular temperature. At the end of reaction period, the treated fibers will be washed under running tap water to get rid of unattached antimicrobial molecules [11].
Antimicrobial agents that cannot bind chemically with textile fibers are applied onto fibers through coating/dry pad technique. Chitosan is a good example of antimicrobial agent that can be applied onto fibers through this technique. A detail on this technique has been discussed in Section 2.3.
The fibers reported for inherent antimicrobial properties are flax, bamboo, hemp and kapok cellulosic fibers with cationic functional group according to Soares et al. [10]. Others are wool and chitosan fibers with amine functional groups [2]. The cellulosic antimicrobial fibers function through interaction of their polycationic functional group with anionic components of microbs resulting into permeability of the microbial cell wall, which eventually leads into death of microorganisms.
The textile fibers with amine functional group (wool and chitosan) resist microorganisms through linkage of cationic amine group with thio group of microbial cellular enzymes, hindering growth and activities of microorganisms and of course results into their death [1]. Chitosan yarns prepared through wet spinning of dilute acetic acid solubilized chitosan fibers in appropriate alkaline coagulating bath are usually used for industrial scale production of wound bandage. Large scale production of fabric from chitosan fibers is yet to be reported due to low mechanical strength of chitosan yarn. In medical wound dressing and sutures, chitosan performs its wound healing ability through diffusion to the site of bacterial growth, reacts with anionic function group in bacteria and puncture the cell wall to kill the bacteria [2].
Treatment of textile fibers with antimicrobial agents is very essential because textile materials are potential media for microbial growth. Microbial growth is undesirable to textiles due to formation of offensive odor, discoloration and degradation. It also makes the textile consumers uncomfortable and occasionally it causes skin problems. Treatment of textiles with silver compounds/nanoparticles, quaternary ammonium compounds, chitosan, synthetic and natural dyes or combinations of these agents alleviates textile materials from aforementioned inherent microbial demerits. Antimicrobial functional textiles are good materials to be used in production of surgical gowns, gloves, socks and body masks for containing microbial borne diseases like ebola and pandemic Covid-19.
The author hereby acknowledge assistance rendered by Dr. MA Adebayo of Chemistry Department, Federal University of Technology Akure for the success of this research work.
The author declares no conflict of interest.
Nature has provided innumerable examples of very efficient solutions to complex problems with seemingly simple rules. With these as inspiration, many engineering problems are tackled using bioinspired techniques. A few of bioinspired techniques are evolutionary and genetic algorithms, stigmergy, hidden Markov models, belief networks, neural networks, etc. These are applicable in a wide variety of domains from robotics [1], communication systems, routing [2], building construction [3], scheduling, optimization, machine intelligence, etc. The brain is a very efficient computing element capable of performing complex tasks. This is possible due to massively parallel computation being performed by the vast number of cells called neurons in the brain while consuming very little energy. This has inspired a domain of algorithms and techniques called artificial intelligence (AI) where machines are programmed to learn and then solve complex tasks. The recent advances in high performance computing and theoretical advances into statistical learning methodologies have enabled a widespread use of AI techniques for tasks such as pattern recognition, natural language understanding, speech recognition, computer vision, odor recognition, machine translation, medical diagnosis, gaming, autonomous driving, path planning, autonomous robots, financial market modeling and the list goes on. Solving these kinds of problems with efficiency is not possible with the traditional computing paradigms. These algorithms are mimicking biology or are inspired from biology to tackle the above problems. For example, it is not humanly possible to have traditional software program coded to classify an image of a simple object such as a cup with reasonable accuracy, considering the innumerable variations available in terms of shape, size, color, etc. However, this is a trivial task for a human being as our brains learn to identify the salient features of an object. The inner working of the brains, especially the way it processes information is the inspiration behind a class of AI techniques called neural networks.
\nAI requires a large amount of compute power while churning through massive amounts of data. Today’s real-world tasks require different sets of AI models with different modalities to interact with each other, hence needing a large pipeline with complex data dependencies. Training is time-consuming, while needing efficient multi-accelerator parallelization. Even with such advances we are nowhere close to the compute power or the efficiency of a human brain. Human brain is still a mystery and is a very actively researched topic. Several neuron models are proposed to mimic various aspects of how the brain works with the limited understand we have up till now.
\nSpiking neural networks (SNNs) are networks made up of interconnected computing elements called neurons. SNNs try to mimic biology to incorporate the efficiencies found in nature. These neurons use spikes to communicate with each other. SNNs are third generation of neural networks [4] and are gaining popularity due to its potential for very low energy dissipation due to their event-driven and asynchronous operation. SNNs are also interesting because of their ability learn in a distributed way using a technique called Spike Timing Dependent Plasticity (STDP) learning [5]. STDP relies on sparsely encoded spiking information among local neurons. SNNs are capable of learning rich spatio-temporal information [6]. In principle, SNNs can be fault tolerant due to its ability to re-learn and adapt the connections with other neurons, akin to how the brains learn. Also SNNs can natively interface with specialized hardware sensors which mimic biological vision (Dynamic Vision Sensor) and hearing (Dynamic Audio Sensor) [7] as they directly transduce sensory information to spikes.
\nIn the rest of the chapter, a brief introduction on neuron biology and artificial neuron models is presented, followed by discussion on information representation as spikes, different learning methodologies, tools, and platforms available for simulating and implementing SNNs and finally few case studies as examples of SNN usage.
\nIn this section, a brief overview of the biological neuron processes is provided to understand the inference and learning dynamics of SNNs. A few popular neuron models are discussed at a high level to make the reader aware of the diversity of such research and its use in SNNs.
\nComplex living organisms have specialized cells called neurons, which are the fundamental unit of central nervous system. Neurons can transmit and receive signals in the form of electrical impulses. In a human brain, there are an estimated 200 billion neurons. Also, there are several different types of neurons in the body. In general, a neuron consists of a cell body or soma consisting of cell machinery, nucleus, dendrites, and an axon as shown in \nFigure 1\n.
\nNeurons (by unknown author, licensed under CC BY-SA
The dendrites receive information from other neurons, and this causes a voltage buildup on the cell body. When this membrane potential reaches a certain threshold, an electrical impulse is generated, and the axon transmits this spike away from the cell body to other neurons. After a spike is generated, the neuron returns to a lower potential called resting potential. Also, immediately after a spike is generated, the neuron cannot generate another spike for a short duration called the refractory period. The axon terminates at axon terminals which interface with dendrites of other neurons; this is called as a synapse. A synapse is connection between a pre synaptic neuron (which generates electrical impulse) and a postsynaptic neuron (receives the spike information) as shown in \nFigure 1\n. The synapse is not a direct connection, instead it consists of a gap called synaptic cleft as shown in \nFigure 2\n. Discussion about astrocyte cells is presented later in Section 4.5.
\nNeuronal synapse along with astrocyte cells (author created).
When an electrical impulse reaches the synapse, the presynaptic neuron releases certain chemicals called neurotransmitters into the synaptic cleft. The postsynaptic neuron picks up these neurotransmitters eventually causing the postsynaptic neurons membrane potential to either increase or decrease. The brain learns by strengthening or weakening the existing synaptic connections or by making new synaptic connections or dissolving those which are no longer needed. In this way, the synapses make the brain plastic and provide the ability to learn. Also, the strength of the synapse also matters for learning as it can modulate the amount of neurotransmitters released in the synaptic cleft resulting in a stronger or weaker synapse and depending on the type of neurotransmitters released, the synapse can be excitatory or inhibitory. An excitatory synapse is one which would increase the membrane potential of the post synaptic neuron; conversely, an inhibitory synapse would decrease the membrane potential. Based on these fundamental concepts, several researchers have proposed various neuron models over the decades. We do not yet fully understand the inner workings of brains and is still an active field of research. New neuron models are being proposed frequently as our understanding of biology increases. A few neuron models are listed below, followed by an overview of select models.
\nSome of the models proposed try to mimic biology for the purpose of understanding and modeling neuro-physiological processes and some models more oriented toward computing purposes. A few of neuron models to consider are McCulloch and Pitts [8], Hodgkin-Huxley [9], Perceptron [10], Izhikevich [11] Integrate and fire [12], Leaky integrate-and-fire [13], Quadratic integrate-and-fire [14], Exponential integrate-and-fire [15], Generalized integrate-and-fire [16], Time-varying integrate-and-fire model [17], Integrate-and-fire or burst [18], Resonate-and-fire [19], and Bayesian neuron model [20].
\nHodgkin and Huxley [9] studied the giant axon of the squid and found currents induced by different types of ions namely sodium ions, potassium ions, and leakage current due to calcium ions. The cell consists of voltage-dependent ion channels which regulate the concentration of these ions across the cell membrane. For the sake of simplicity, at a high level, the total membrane current is the sum of current induced by membrane capacitance and the ion channel currents as shown in Eq. (1), where \n
They also describe gating variables to control the ion channels and the resting potential of the cell. When the membrane potential increases significantly above the resting potential, the gating variable activates and then deactivates the channels resulting in a spike. This is a very simplified model and has several limitations [21].
\nIzhikevich neuron model [11] is more biologically plausible as shown in equations below.
\nWhere \n
Izhikevich neuron model [
Over time, if a biological neuron does not spike, then any potential builtup would dissipate. This phenomenon is modeled by several variations of Leaky Integrate and Fire (LIF) models. LIF neuron model is very popular due to its ease of implementation as a software model and for developing dedicated hardware models. Digital hardware implementation is more popular than the analog variants, again due to its simplicity of design, fabrication, and scalability.
\nA typical generic LIF model adapted for discrete implementation [22] is represented as:
\nSynaptic integration
\nLeak integration
\nThreshold, fire and reset
\nWhere \n
Bayesian neuron (BN) model is proposed in [20]. BN model is a stochastic neuron model. When the membrane potential reaches the threshold a BN model fires a spike stochastically. It generates a spike based on a Poisson process where neuron \n
Where the weight of the synapse between
To generate a Poisson process with time-varying rate \n
\n\n
SNNs understand the language of spikes, and it is necessary to decide what is the best possible way to represent real-world data to achieve best possible training of the network and efficient inference. Different coding techniques model different aspects of input spectrum. Some of the spike coding techniques are described below to get an intuition of signal representation using spikes.
\nWith rate coded spike trains, the information is encoded in the number of spikes over a specified temporal window. The firing rate \n
Evidence of rate coding is experimentally shown in sensory and motor systems [24]. The number of spikes emitted by the receptor neuron increases with the force applied to the muscle.
\nIf the rate \n
Therefore, the instantaneous firing rate is
\nThe expected number of spikes for the temporal window \n
To summarize, the experimental procedure of counting spikes over a time \n
The Peri-stimulus-time histogram and the average time-dependent firing rate [
A spike train \n
The instantaneous firing rate is the expectation over trials.
\nAn empirical estimate of the instantaneous firing rate can be deduced as shown in Eq. (18). It implies that the PSTH as described above represents the instantaneous firing rate.
\nThe average firing rate can be computed for a single neuron, or for a population of neurons representing a class over a single run or over several trials. Rate coding over a time window is suitable for representing the strength of stimulation. On the other hand, population-based rate coding could convey the same information by employing several neurons in a shorter temporal window. The latter trades quick response over a number of neurons. There is evidence of Purkinje neurons demonstrating information coding which is not just firing rate but also the timing and duration of nonfiring, quiescent periods [25, 26].
\nIf the time of spike occurrence in a temporal window carries information, then such coding is referred to as temporal coding. In such coding schemes the quiescent periods and the spiking time both carry information. There are several evidences in biology demonstrating this behavior [27, 28]. A typical temporal code is shown in \nFigure 5A\n, where the time interval of spike to start of stimulus caries information. These are sometimes referred to as pulse codes. Another variation is Rank Order Coding, which uses the relative timing of spikes across a population of cells. Rank order codes look at time to spike across the neuron population and a rank order can be implied from the firing order among the neurons in the population as described in \nFigure 5B\n.
\nDifferent strategies for information coding with spikes (refer to [
There is evidence suggesting that simple temporal averaging of firing rate is too simplistic to model neuronal circuits in the brain [30]. To address some of the shortcomings, several derivations of coding schemes based on different combinations of above concepts are widely used. Few of the common schemes and some task specific coding schemes are Rate code, Time to spike code, Time-to-first-spike: Latency code [31], Reverse time to spike code, Weighted spike code [32], Burst code [33], Population code, Population rate, Rank order code [34], Phase-of-firing code [35, 36], Place code [37], etc. \nFigure 5\n summarizes a few coding strategies. These coding schemes require appropriate algorithms for converting real-world data to spikes and vice versa. A few common conversion techniques are discussed in the next section.
\nSNNs understand the language of spikes; therefore, we must transform the real-world data to appropriate spike representation and subsequently transform the output spikes to real-world formats for human consumption. There are several encoding and decoding algorithms available to achieve this goal. Several heuristics are also employed. Some of the coding techniques mentioned above infer a specific coding/decoding scheme. Based on the nature of application (such as images, audio, video, financial data, user activity data), one must choose which is the best approach.
\nImage pixel values are binned and proportional firing rates are assigned to different neurons in the receptive fields for each pixel neuron, hence generating random process with rate coding [38]. Since spikes have no polarity positive and negative spike, subchannels can be used to represent richer encoding of data. In threshold-based schemes, a spike is generated when the input signal intensity crosses a threshold. Real numbers are compared against different thresholds, and positive and negative spikes are produced accordingly which are rate coded [39]. BSA algorithm for encoding and decoding [40] is used for modeling brain-machine interfaces and neurological processes in the brain. The work presented by the authors of [41] provides details on step-forward (SF), and moving-window (MW) encoding schemes. In SF scheme, a baseline \n
Hebb postulated that synaptic efficacy increases from a presynaptic neuron if it repeatedly assists the post synaptic neuron [42]. This forms the fundamentals of STDP rule for learning. STDP mimics biology where a synapse is strengthened when a presynaptic spike occurs before a post synaptic spike in close intervals, this is called Long-Term Potentiation (LTP). On the other hand, the synapse is weakened if the post synaptic neuron fires before the presynaptic neuron in close intervals. This is called as Long-Term Depression (LTD). In biology neurons are highly selective due to lateral inhibition. This allows for them to learn discriminatory and unique features in an unsupervised manner leading to an emergent Winner Take All (WTA) behavior. Apart from this the biological system demonstrates homeostasis to maintain overall stability. These are key principles in SNN modeling. There are several ways to achieve WTA and homeostasis behavior, some directly modify the neuron state, others use neural circuits. One such example with a scalable neural circuit [43] is shown in \nFigure 6\n. A WTA network consists of inhibitor neurons suppressing the activation of other lateral symbol neurons as shown in \nFigure 6(a)\n. To assist in homeostasis a normalization of the excitations of one neural circuit compared to others can be achieved using a Normalized Winner Take All (NWTA) network as shown in \nFigure 6(b). Where an upper limit (UL) neuron uniformly inhibits all symbol neurons if they are firing beyond a desirable high threshold. On the contrary if the symbol neurons are firing below a desired low threshold, then the lower limit (LL) neuron triggers an excitor (Ex) neuron to uniformly boost the firing rate of all symbol neurons. In this manner all independent neural circuits within an SNN fire in the dynamic range of excitations of the overall network. Both hard and soft WTA behavior can be achieved based on the amount of inhibition generated. In Hard WTA only one symbol neuron is active whereas in soft WTA more than one symbol neuron is active providing richer context.
\n(a) Winner take all network (b) normalized winner take all network [
SNNs can learn in both unsupervised and supervised modes. WTA concepts are essential part of unsupervised learning as the neuron with highest excitation inhibits the lateral neurons the strongest hence enabling it to preferentially pick up unique features. Unsupervised learning is possible by employing a teacher signal which excites the specific neurons to fire thereby allowing it to learn the features represented by the input signal. STDP based learning has its advantages of being able to model spatio-tempotal dynamics. Where the spatial component refers to localized activity/learning and temporal component refers to additional information representation by the spike intervals along the time axis. With the constant advances in SNN research, native STDP based rules are catching up to the more popular backpropagation-based learning methods used in Artificial Neural Networks (ANN). STDP lends itself for efficient localized and distributed learning, which is a huge advantage over other learning methods. Also SNNs can be adapted to model memories in the form of Long Short-Term Memory networks [39] which shows that recurrent learning behavior is also possible. The following sub-sections discus few learning rules used in training SNNs along with a brief introduced to backpropagation-based learning.
\nA classic STDP rule [44] is shown in \nFigure 7\n. The STDP curve tries to approximate experimentally observed behavior.
\nClassic STDP curve [
Here \n
Where \n
There are two broad categorizations of STDP rules, additive and multiplicative STDP [38]. Multiplicative rule tends to be more stable than additive rule. In additive rules the weight changes are independent of current weight and requires additional constraints to keep the values in operating bounds. These weight changes however produce bimodal distribution resulting in strong competition. In multiplicative rule presented in [38], the weight change is inversely proportional to the current weight making it inherently stable and resulting in a unimodal distribution. This distribution lacks synaptic competition which is desirable for learning discriminative features. For such rules, competition must be introduced in a different method. The stable multiplicative rule is further explored below and simplified for efficient implementation. Here the STDP rule is modeled such that weight change of a synapse has an exponential dependence on its current weight as shown in \nFigure 8\n (a). Update for the weight \n
(a) Current weight vs weight change for learning rates (b) STDP windows (c) Comparison of Exp, 2P and Q2PS STDP rules [
If
\nthen,
\nIf
\nthen,
\nWhere \n
The Exp STDP rule requires an exponential and a multiplication operation for both LTP and LTD for each synapse. From the perspective of efficient digital hardware implementation these are expensive operations in terms of circuit area and computation time. Quantized 2-power shift rule (Q2PS), which approximates the Exp rule in Eq. (20) and Eq. (21) by removing both multiplication and exponential. The approximation is summarized in Eq. (22) and Eq. (23).
\nIf
\nIf
\nwhere \n
where \n
With the tremendous advances in the field of ANNs, a growing body of research is available on various statistical learning algorithms. ANNs are inspired by biology but they do not mimic it. ANNs are made up of artificial neuron models specifically tuned for compute purposes and model a biological neuron at a very abstract level. An artificial neuron computes weighted sum of input signals and then an activation function computes the neuron output. In these networks’ neurons transmit signals as real numbers. ANNs compute inference by transmitting the neuron signals in the forward direction. The learning happens usually via a method called Backpropagation. This algorithm computes the gradients based on the error signal produced by a cost function and propagates it back for each layer of neurons in the neural network. The weight updates are usually made using gradient descent algorithms. There are many flavors of gradient descent algorithms available in the literature. For back propagation to work the activation function must be differentiable. Unlike SNNs, where a spike is not differentiable. In general, ANNs have proven to be very effective in tackling a wide variety of problems. Using these algorithms as inspiration several modified STDP rules have been researched, one among them is discussed below. This overview is a very high-level introduction to some of the terminology required to understand the following section. The reader is encouraged to explore further on this topic.
\nThe Backpropagation-STDP (BP STDP) [45] algorithm uses the number of spikes in a spike trains as an approximation for the real value of an artificial neurons excitation. They also divide the time interval into sub-intervals such that each sub-interval contains zero or one spike.
\nIn supervised training, the weight adjustment is governed by the STDP model shown in Eq. (25) and Eq. (26), in conjunction with a teacher signal. The teacher signal when applied to target neurons undergo weight change based on STDP and non-target neurons undergo weight changes based on anti-STDP. Anti-STDP is the opposite of STDP where LTP and LTD equations are swapped. Target neurons are identified by spike trains with maximum spike frequency (\n
A target neuron would generate a spike \n
Stigmergy is a methodology where several independent agents produce an emergent behavior through indirect interaction among themselves. This is facilitated with the help of asynchronous communication through traces left in the environment by individual agents. Stigmergy has been observed in nature and widely researched upon especially in insect colonies, these principles have been applied towards solving various engineering problems. Recent advances in neuroscience have shown evidence of another type of cells called astrocytes working in tandem with neurons to regulate the behavior of the central nervous system [46]. Astrocytes are star shaped cells with several branches called as processes. The end of these branches called as end feet interface with a synapse by wrapping around it creating a region around the synaptic cleft called as microdomain as shown in \nFigure 2\n. Astrocytes also interface the neurons apart from the synapse providing a closed loop feedback mechanism. They also interface with other astrocytes like a synapse, instead this is called as a gap junction. Gap junction facilitates communication between astrocyte cells only through chemical means. Astrocytes are functionally very diverse and play a very important role, only a high-level concept with limited detail is introduced for understanding of relevant discussion. With the help of calcium ions as a signaling mechanism along with the help of neurotransmitters the astrocytes help regulate the efficiency of synaptic transmission. These cells play a critical role in maintaining homeostasis, modulating LTP, LTD and structural plasticity in the brain.
\nSpiking activity results in release of neurotransmitters and change in concentration among different ions in the microdomain and extra cellular space. These changes are monitored as traces for indirect communication by astrocytes. Astrocytes themselves behaving like an environment with calcium ion concentration gradients within the cell acting as a medium for other neuron agents to indirectly infer these changes. This interaction creates a feedback mechanism in an asynchronous and distributed manner [47]. \nFigure 9\n shows the emergent stigmergy pattern in the brain. Short term activity and long-term activity gets communicated over a distance to other synapses over a spatial domain. Greater the distance, lower would be the influence. The details about the stigmergy based brain plasticity is presented in [47], interested readers are encouraged to explore further. This is a relatively new discovery and extensive research is underway to understand the role of astrocytes in overall brain mechanics.
\nStigmergic interactions between astrocytes and neurons (modified from [
There are several spiking neural network simulation tools available which support biologically realistic neuron models for large scale networks. Some of the popular ones are:
\nBrian [48], is a free, open source simulator for spiking neural networks. This simulator is capable of running on several different platforms and is implemented in python making it extendable and easy to use.
\nNEST [49] is another simulator focusing on the dynamics, size and structure of neural systems both large and small. This tool is not intended for modeling the intricate biological details of a neuron.
\nNEURON [50] is simulation environment best suited for modeling individual neurons and their networks. This is popular among neuroscientists for its ability to handle complex models in a computationally efficient manner. Unlike above simulator, NEURON can handle morphological details of a neuron and is used to validate theoretical models with experimental data.
\nThe above tools are commonly used in modeling biologically realistic neuron modes. They have their own unique interfaces and low-level semantics. An effort is made to smooth things out with a tool independent API package developed on Python programming language called PyNN [51]. The PyNN framework provides API support to model SNNs at a high level of abstraction of all aspects of neuron modeling and SNN representation, including populations of neurons, connections, layers etc. Though this provides high level abstraction, it also provides the ability to program at a low level such as adjusting individual parameters at the neuron and synapse level. To make things easy PyNN provides a set of library implementation for neurons, synapses, STDP models etc. They also provide easy interfaces to model various connectivity patterns among neurons like; all-to-all, small-world, random distance-dependent etc. These APIs are simulator independent making the code portable across different supported simulation tools and neuromorphic hardware platforms. It is relatively straightforward to add support to any custom simulation tool. PyNN officially supports BRIAN, NEST and NEURON SNN simulation tools. It is also supported on SpiNNaker [52] and BrainScaleS-2 [53] neuromorphic hardware systems. There are several more simulation tools which work with PyNN.
\nCypress [54] is a C++ based SNN Simulation tool. This provides a C++ wrapper around PyNN APIs. Hence, extending the multi-platform reach of Cypress using C++ interface. It is also capable of executing networks remotely on neuromorphic compute platforms.
\nThe BrainScaleS-2 [53] is a mixed-signal accelerated neuromorphic system with analog neural core, digital connectivity along with embedded SIMD microprocessor. It is efficient for emulations of neurons, synapses, plasticity models etc. This hardware based system is capable of evaluating models up to ten thousand times faster than real time.
\nThe SpiNNaker [52] is another neuromorphic system custom built with digital multicore ARM processors. The SpiNNaker system (NM-MC-1) consists of custom chips each with eighteen cores sharing a local 128 MB RAM. The overall system scales to more than a million cores.
\nApart from the above tools and platforms the are many custom SNN tools available to model SNNs easily for machine learning purposes. ANNarchy (Artificial Neural Networks architect) [55] is a custom simulator for evaluating SNNs. This is implemented in C++ language, along with acceleration support provided using OpenMP/CUDA. The network definitions are provided using python interface.
\nNeuCube [6] is a development environment for creation of Brain-Like Artificial Intelligence. The computational architecture is suited for modeling SNN applications across several domain areas. This tool supports the latest neural network models for AI purpose. It supports PyNN interface, hence extending its versatility. This tool can run on CPU, GPU and SpiNNaker platforms, also a cloud version of the tool is available.
\nTrueNorth [56] is another neuromorphic platform capable of evaluating SNNs at faster than real time and at very low power. They demonstrate running state of the art neural networks on the hardware platform scaling up to 64 million neurons and 16 billion synapses while the system consumes only 70 W of power out of which only 15 W is consumed by the neuromorphic hardware components. The hardware supports inference only, with learning performed off chip.
\nLoihi [57] is the latest offering in the neuromorphic SNN hardware. This hardware approach gets rid of crossbar architecture, which is prevalent in most previous neuromorphic implementations, lending itself to greater amount of flexibility. Loihi is also capable of on-chip learning which is a huge advantage in terms of online learning of synapses.
\nOther simulators capable of modeling software based models and models for custom neuromorphic hardware are presented in [20, 58, 59, 60]. This is still an ongoing field of research and there are several more accelerator-based simulators available hence the reader is encouraged to explore further. Neuromorphic hardware using more exotic hardware devices like memristors and phase change memories are also an active area of research, they are yet to make it to mainstream consumption hence they are only mentioned here.
\nIn this section few case studies are presented to bolster the concepts discussed in this chapter. The topics covered here include STDP learning dynamics, probabilistic graphical models as SNNs, SNN with BP-STDP based learning and SNNs on Neuromorphic Hardware.
\nA SNN is trained [38] to classify handwritten digits from the MNIST dataset using the STDP based learning rules Exp, Q2PS and 2P presented in Section 4.2. The authors build a three-layer SNN as shown in \nFigure 10\n. The MNIST images are of 28x28 pixel dimensions, hence the input layer contains 784 neurons, one per image pixel. The second/hidden layer contains neurons for learning the features of the input images. The number of neurons in this layer is varied over different trials to evaluate the effectiveness of the learning rule. Finally, the third layer consists of 10 neurons for classifying the input with one neuron per class. The input layer encodes the pixel intensities with varying firing rate in the range of 0 Hz – 300 Hz. Each input neuron is fully connected to the hidden layer neurons similarly each hidden layer neuron is fully connected to the output/classification layer neurons. In this network all synapses are plastic with soft WTA connectivity implemented between input layer and hidden layer neurons to facilitate different neurons to pick up shared features. On the other hand, a hard WTA connectivity exists between hidden layer and the classification layer.
\nMNIST SNN architecture showing connectivity, input, learnt features, labels and t-SNE visualizations, along with accuracy results [
A qualitative analysis of the learning rule is depicted by the t-distributed stochastic neighbor embedding (t-SNE) [61] visualizations in \nFigure 10\n. The t-SNE algorithm maps high dimensional data points lying on different but related low-dimensional manifolds to lower dimensions by capturing local structure present in high dimensional data. The input layer firing rate visualizations show the clustering of digit classes in 2 dimensions based on raw pixel data which has 784 dimensions. Similarly, the second visualization is made using the firing rate based on the learnt features of hidden layer as input to the t-SNE algorithm with 100 dimensions. It can be clearly seen that the STDP rule produces tight clustering of input space which is projected on to the feature space. The classification layer further groups these features to its respective classes. Networks with different number of hidden layer neurons are experimented with and the results are shown in the bottom right side of \nFigure 10\n. The robustness of the learning method is also demonstrated with experiments yielding similar accuracies with additive Gaussian white noise along with the use of NWTA network.
\nAn inference network based on a probabilistic graphical model for sentence construction is created using Bayesian neurons. It consists of lexicons representing words and phrases. Here each lexicon is a WTA sub network.
\nThe network consists of two functional sections: word sub network and phrase sub network. Each symbol neuron in word sub network represents a possible word occurrence and each symbol neuron in phrase sub network represents a possible pair of words co-occurring. The synapses between the symbol neurons represent the log conditional probabilities of words and phrases co-occurring. This network is initialized to have same intrinsic potential across all symbol neurons resulting in same initial firing rate. Based on the synaptic weights the strongly connected neurons resonate and enhance each other while laterally inhibiting other symbol neurons within the lexicon WTA network. These winning neurons proportionally excite other symbol neurons across different lexicons. In this manner the network settles on a steady state firing rate which represents a contextually correct behavior. From each lexicon of the word sub network a symbol neuron is picked with highest firing rate representing a grammatically correct semantically meaningful sentence. The WTA connections in this network perform soft WTA action there by the facilitating the retention of contextual information. \nFigure 11\n (a) shows the network topology. For the experiments, random documents images are picked, and fuzzy character recognition is performed. Due to the fuzzy nature, each character position will result in several possible matches hence, multiple possible matches for each word position is possible as described in [62]. An example of lexicon set is [{we, wo, fe, fo, ne, no, ns, us} {must, musk, oust, onst, ahab, bust, chat} {now, noa, non, new, how, hew, hen, heu} {find, rind, tina} {the, fac, fro, kho} {other, ether}]. The SNN after evaluating the lexicons settles on a grammatically correct sentence as [we must now find the other] as seen in \nFigure 11\n (b).
\n(a) Sentence confabulation network, (b) confabulation results spike plot [
Using the learning rule presented in Section 4.4, the authors of [45] train SNNs to evaluate BP-STDP rule on the XOR problem, the iris dataset and the MNIST dataset. They show that the network can model the linearly inseparable XOR problem using an SNN with 2 input, 20 hidden and 2 output neurons. For the iris dataset they create a SNN with 4 input, 30 hidden and 3 output neurons. With this network they were able to achieve 96% accuracy which is comparable to ANN trained with traditional backpropagation with an accuracy of 96.7%. The SNN for MNIST dataset consists of 784 input neurons, 100 through 1500 hidden neurons and 10 output neurons. With this network they were able to achieve 97.2% classification accuracy.
\nDeep networks achieve higher accuracy in recognition tasks and in some cases outperform humans. Eedn framework is proposed in [63], which enables SNNs to be trained using backpropagation with batch normalization [64] and implement them on TrueNorth neuromorphic hardware. The Eedn trained networks are capable of achieving state-of-the-art accuracy across eight standard datasets of vision and speech. In this implementation the inference on hardware can be run at up to 2600 frames/s which is faster than real time while consuming very low power of at most 275 mW across their experiments. The network uses low precision ternary weights +1, 0 and − 1 for its synapses. A binary activation function with an approximate derivative is modeled to enable backpropagation. A hysteresis parameter is introduced in the weight update rule to avoid rapid oscillations of weights during learning. The input images are transduced by applying 12 different convolutional filter operators with binary outputs to get 12 channel input to the network as shown in \nFigure 12\n.
\nExample image from CIFAR10 (column 1) and the corresponding output of 12 typical transduction filters (columns 2–13) [
Experiments were performed on eight datasets using five different network sizes spanning across several TrueNorth chips. The results of the experiments are summarized in \nFigure 13\n.
\nAccuracy of different sized networks on eight datasets. For comparison, accuracy of state-of-the-art unconstrained approaches are shown as bold horizontal lines [
This chapter discussed several concepts and techniques, all of which are bio inspired. The case studies presented provide a strong basis to grasp the immense potential these algorithms provide in tackling the very complex problems of today, which were unimaginable without the advances in this field. This chapter specifically provided a beginner’s guide to the field of spiking neural networks. It presented a brief overview of neuron biology and notes on popular artificial neuron models. Information representation as spikes and how to transduce real world data to spikes and vice-versa was discussed which is similar to how brain represents information. Several tools for spiking neural network modeling and evaluation were provided for wholistic understanding and for experimental evaluation of one’s network models. A few case study examples are presented to understand the presented concepts and the scope of information presented in this chapter. This is an ongoing research and a very hot topic with substantially new concepts and discoveries being published every week. The motivation being the ability for machines to autonomously and efficiently perform tasks which were previously delegated to humans only along every aspect of our lives. This is a paradigm shift and research will continue to not only develop machine intelligence but also to understand the inner workings of our brains, our thoughts and advance the field of neuroscience.
\nThis chapter represents fundamental knowledge for understanding spiking neural networks. Some of the text and images are adopted from the available research literature. Rest of the work represents authors original contributions along with the co-authors of the following research contributions [20, 38, 39, 43, 60, 62]. I am thankful for the support of Dr. Qinru Qiu from Syracuse University and her research group members specifically Amar Shrestha in contributing during the original research.
\nartificial intelligence
\nartificial neural networks
\nBayesian neuron
\nbackpropagation-STDP
\nexcitor neuron
\nlower limit neuron
\nlong-term depression
\nlong-term potentiation
\nmoving-window
\nnormalized winner take all
\nperi-stimulus-time histogram
\nstep-forward
\nspiking neural network
\nspike timing dependent plasticity
\nt-distributed stochastic neighbor embedding
\nupper limit neuron
\nwinner take all
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Although typical biological treatments of water offer some advantages such as low cost and operability, many investigations referring to the removal of pesticides have suggested that in many cases they have low effectiveness due to the limited biodegradability of many agrochemicals. In recent years, research for new techniques for water detoxification to avoid these disadvantages has led to processes that involve light, which are called advanced oxidation processes (AOPs). Among the different semiconductor (SC) materials tested as potential photocatalysts, titanium dioxide (TiO2) is the most popular because of its photochemical stability, commercial availability, non-toxic nature and low cost, high photoactivity, ease of preparation in the laboratory, possibility of doping with metals and non-metals and coating on solid support. Thus, in the present review, we provide an overview of the recent research being developed to photodegrade pesticide residues in water using TiO2 as photocatalyst.",book:{id:"6407",slug:"application-of-titanium-dioxide",title:"Application of Titanium Dioxide",fullTitle:"Application of Titanium Dioxide"},signatures:"Nuria Vela, Gabriel Pérez-Lucas, José Fenoll and Simón Navarro",authors:[{id:"202983",title:"Dr.",name:"Simón",middleName:null,surname:"Navarro",slug:"simon-navarro",fullName:"Simón Navarro"},{id:"202988",title:"Dr.",name:"Nuria",middleName:null,surname:"Vela",slug:"nuria-vela",fullName:"Nuria Vela"},{id:"202989",title:"Dr.",name:"José",middleName:null,surname:"Fenoll",slug:"jose-fenoll",fullName:"José Fenoll"},{id:"206059",title:"Dr.",name:"Gabriel",middleName:null,surname:"Pérez-Lucas",slug:"gabriel-perez-lucas",fullName:"Gabriel Pérez-Lucas"}]}],mostDownloadedChaptersLast30Days:[{id:"55440",title:"Solubility Products and Solubility Concepts",slug:"solubility-products-and-solubility-concepts",totalDownloads:3084,totalCrossrefCites:6,totalDimensionsCites:7,abstract:"The chapter refers to a general concept of solubility product Ksp of sparingly soluble hydroxides and different salts and calculation of solubility of some hydroxides, oxides, and different salts in aqueous media. A (criticized) conventional approach, based on stoichiometry of a reaction notation and the solubility product of a precipitate, is compared with the unconventional/correct approach based on charge and concentration balances and a detailed physicochemical knowledge on the system considered, and calculations realized according to generalized approach to electrolytic systems (GATES) principles. 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The PA industry is spread out worldwide in Europe, Asia and America, including countries that operate phosphate rock (PR) mines and produce PA, phosphatic fertilizers and phosphate-based products.",book:{id:"5595",slug:"phosphoric-acid-industry-problems-and-solutions",title:"Phosphoric Acid Industry",fullTitle:"Phosphoric Acid Industry - Problems and Solutions"},signatures:"Benjamín Valdez Salas, Michael Schorr Wiener and Juan Ricardo\nSalinas Martinez",authors:[{id:"16436",title:"Dr.",name:"Michael",middleName:null,surname:"Schorr",slug:"michael-schorr",fullName:"Michael Schorr"}]},{id:"62941",title:"Inorganic Coordination Chemistry: Where We Stand in Cancer Treatment?",slug:"inorganic-coordination-chemistry-where-we-stand-in-cancer-treatment-",totalDownloads:2147,totalCrossrefCites:5,totalDimensionsCites:10,abstract:"Metals have unique characteristics such as variable coordination modes, redox activity, and reactivity being indispensable for several biochemical processes in cells. Due to their reactivity, their concentration is tightly regulated inside the cells, and abnormal concentrations are associated with many disorders, such as cancer. As such metal complexes turned out to be very attractive as potential anticancer agents. The discovery of cisplatin was a crucial moment, which prompted the interest in Pt(II) and other metal complexes as potential anticancer agents. This chapter highlights the state of the art on metal complexes in cancer therapy, highlighting their uptake mechanisms, biological targets, toxicity, and drug resistance. 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Cobalt has been substantial in both chemical reactions and within many compounds. Some of them are heterocyclic reactions, cobalt-based catalyst and cobalamin. Also, it discusses variety of applications of cobalt in a wide range of areas and toxicity of cobalt. The studies carried out in this area so far have enabled and will be continued to be responsible for producing unknown and difficult reactions. This survey of the recent literature illustrates the fact that many different approaches on cobalt and new cobalt compounds are being used in many different areas.",book:{id:"6133",slug:"cobalt",title:"Cobalt",fullTitle:"Cobalt"},signatures:"Yasemin Yildiz",authors:[{id:"208129",title:"Dr.",name:"Yasemin",middleName:null,surname:"Yıldız",slug:"yasemin-yildiz",fullName:"Yasemin Yıldız"}]},{id:"55301",title:"Recent Overview on the Abatement of Pesticide Residues in Water by Photocatalytic Treatment Using TiO2",slug:"recent-overview-on-the-abatement-of-pesticide-residues-in-water-by-photocatalytic-treatment-using-ti",totalDownloads:1990,totalCrossrefCites:9,totalDimensionsCites:26,abstract:"The water bodies’ pollution with phytosanitary products can pose a serious threat to aquatic ecosystems and drinking water resources. The usual appearance of pesticides in surface water, waste water and groundwater has driven the search for proper methods to remove persistent pesticides. Although typical biological treatments of water offer some advantages such as low cost and operability, many investigations referring to the removal of pesticides have suggested that in many cases they have low effectiveness due to the limited biodegradability of many agrochemicals. In recent years, research for new techniques for water detoxification to avoid these disadvantages has led to processes that involve light, which are called advanced oxidation processes (AOPs). Among the different semiconductor (SC) materials tested as potential photocatalysts, titanium dioxide (TiO2) is the most popular because of its photochemical stability, commercial availability, non-toxic nature and low cost, high photoactivity, ease of preparation in the laboratory, possibility of doping with metals and non-metals and coating on solid support. Thus, in the present review, we provide an overview of the recent research being developed to photodegrade pesticide residues in water using TiO2 as photocatalyst.",book:{id:"6407",slug:"application-of-titanium-dioxide",title:"Application of Titanium Dioxide",fullTitle:"Application of Titanium Dioxide"},signatures:"Nuria Vela, Gabriel Pérez-Lucas, José Fenoll and Simón Navarro",authors:[{id:"202983",title:"Dr.",name:"Simón",middleName:null,surname:"Navarro",slug:"simon-navarro",fullName:"Simón Navarro"},{id:"202988",title:"Dr.",name:"Nuria",middleName:null,surname:"Vela",slug:"nuria-vela",fullName:"Nuria Vela"},{id:"202989",title:"Dr.",name:"José",middleName:null,surname:"Fenoll",slug:"jose-fenoll",fullName:"José Fenoll"},{id:"206059",title:"Dr.",name:"Gabriel",middleName:null,surname:"Pérez-Lucas",slug:"gabriel-perez-lucas",fullName:"Gabriel Pérez-Lucas"}]}],onlineFirstChaptersFilter:{topicId:"83",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:18,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:139,numberOfOpenTopics:2,numberOfUpcomingTopics:0,issn:"2631-6218",doi:"10.5772/intechopen.71199",isOpenForSubmission:!0},{id:"6",title:"Infectious Diseases",numberOfPublishedBooks:13,numberOfPublishedChapters:122,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:21,numberOfOpenTopics:3,numberOfUpcomingTopics:0,issn:"2753-894X",doi:"10.5772/intechopen.100359",isOpenForSubmission:!0},{id:"23",title:"Education and Human Development",numberOfPublishedBooks:0,numberOfPublishedChapters:10,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:"13",text:"The collaboration with and support of the technical staff of IntechOpen is fantastic. The whole process of submitting an article and editing of the submitted article goes extremely smooth and fast, the number of reads and downloads of chapters is high, and the contributions are also frequently cited.",author:{id:"55578",name:"Antonio",surname:"Jurado-Navas",institutionString:null,profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bRisIQAS/Profile_Picture_1626166543950",slug:"antonio-jurado-navas",institution:{id:"720",name:"University of Malaga",country:{id:null,name:"Spain"}}}},{id:"6",text:"It is great to work with the IntechOpen to produce a worthwhile collection of research that also becomes a great educational resource and guide for future research endeavors.",author:{id:"259298",name:"Edward",surname:"Narayan",institutionString:null,profilePictureURL:"https://mts.intechopen.com/storage/users/259298/images/system/259298.jpeg",slug:"edward-narayan",institution:{id:"3",name:"University of Queensland",country:{id:null,name:"Australia"}}}}]},series:{item:{id:"14",title:"Artificial Intelligence",doi:"10.5772/intechopen.79920",issn:"2633-1403",scope:"Artificial Intelligence (AI) is a rapidly developing multidisciplinary research area that aims to solve increasingly complex problems. In today's highly integrated world, AI promises to become a robust and powerful means for obtaining solutions to previously unsolvable problems. This Series is intended for researchers and students alike interested in this fascinating field and its many applications.",coverUrl:"https://cdn.intechopen.com/series/covers/14.jpg",latestPublicationDate:"July 5th, 2022",hasOnlineFirst:!0,numberOfPublishedBooks:9,editor:{id:"218714",title:"Prof.",name:"Andries",middleName:null,surname:"Engelbrecht",slug:"andries-engelbrecht",fullName:"Andries Engelbrecht",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bRNR8QAO/Profile_Picture_1622640468300",biography:"Andries Engelbrecht received the Masters and PhD degrees in Computer Science from the University of Stellenbosch, South Africa, in 1994 and 1999 respectively. He is currently appointed as the Voigt Chair in Data Science in the Department of Industrial Engineering, with a joint appointment as Professor in the Computer Science Division, Stellenbosch University. Prior to his appointment at Stellenbosch University, he has been at the University of Pretoria, Department of Computer Science (1998-2018), where he was appointed as South Africa Research Chair in Artifical Intelligence (2007-2018), the head of the Department of Computer Science (2008-2017), and Director of the Institute for Big Data and Data Science (2017-2018). In addition to a number of research articles, he has written two books, Computational Intelligence: An Introduction and Fundamentals of Computational Swarm Intelligence.",institutionString:null,institution:{name:"Stellenbosch University",institutionURL:null,country:{name:"South Africa"}}},editorTwo:null,editorThree:null},subseries:{paginationCount:6,paginationItems:[{id:"22",title:"Applied Intelligence",coverUrl:"https://cdn.intechopen.com/series_topics/covers/22.jpg",isOpenForSubmission:!0,editor:{id:"27170",title:"Prof.",name:"Carlos",middleName:"M.",surname:"Travieso-Gonzalez",slug:"carlos-travieso-gonzalez",fullName:"Carlos Travieso-Gonzalez",profilePictureURL:"https://mts.intechopen.com/storage/users/27170/images/system/27170.jpeg",biography:"Carlos M. Travieso-González received his MSc degree in Telecommunication Engineering at Polytechnic University of Catalonia (UPC), Spain in 1997, and his Ph.D. degree in 2002 at the University of Las Palmas de Gran Canaria (ULPGC-Spain). He is a full professor of signal processing and pattern recognition and is head of the Signals and Communications Department at ULPGC, teaching from 2001 on subjects on signal processing and learning theory. His research lines are biometrics, biomedical signals and images, data mining, classification system, signal and image processing, machine learning, and environmental intelligence. He has researched in 52 international and Spanish research projects, some of them as head researcher. He is co-author of 4 books, co-editor of 27 proceedings books, guest editor for 8 JCR-ISI international journals, and up to 24 book chapters. He has over 450 papers published in international journals and conferences (81 of them indexed on JCR – ISI - Web of Science). He has published seven patents in the Spanish Patent and Trademark Office. He has been a supervisor on 8 Ph.D. theses (11 more are under supervision), and 130 master theses. He is the founder of The IEEE IWOBI conference series and the president of its Steering Committee, as well as the founder of both the InnoEducaTIC and APPIS conference series. He is an evaluator of project proposals for the European Union (H2020), Medical Research Council (MRC, UK), Spanish Government (ANECA, Spain), Research National Agency (ANR, France), DAAD (Germany), Argentinian Government, and the Colombian Institutions. He has been a reviewer in different indexed international journals (<70) and conferences (<250) since 2001. He has been a member of the IASTED Technical Committee on Image Processing from 2007 and a member of the IASTED Technical Committee on Artificial Intelligence and Expert Systems from 2011. \n\nHe has held the general chair position for the following: ACM-APPIS (2020, 2021), IEEE-IWOBI (2019, 2020 and 2020), A PPIS (2018, 2019), IEEE-IWOBI (2014, 2015, 2017, 2018), InnoEducaTIC (2014, 2017), IEEE-INES (2013), NoLISP (2011), JRBP (2012), and IEEE-ICCST (2005)\n\nHe is an associate editor of the Computational Intelligence and Neuroscience Journal (Hindawi – Q2 JCR-ISI). He was vice dean from 2004 to 2010 in the Higher Technical School of Telecommunication Engineers at ULPGC and the vice dean of Graduate and Postgraduate Studies from March 2013 to November 2017. He won the “Catedra Telefonica” Awards in Modality of Knowledge Transfer, 2017, 2018, and 2019 editions, and awards in Modality of COVID Research in 2020.\n\nPublic References:\nResearcher ID http://www.researcherid.com/rid/N-5967-2014\nORCID https://orcid.org/0000-0002-4621-2768 \nScopus Author ID https://www.scopus.com/authid/detail.uri?authorId=6602376272\nScholar Google https://scholar.google.es/citations?user=G1ks9nIAAAAJ&hl=en \nResearchGate https://www.researchgate.net/profile/Carlos_Travieso",institutionString:null,institution:{name:"University of Las Palmas de Gran Canaria",institutionURL:null,country:{name:"Spain"}}},editorTwo:null,editorThree:null},{id:"23",title:"Computational Neuroscience",coverUrl:"https://cdn.intechopen.com/series_topics/covers/23.jpg",isOpenForSubmission:!0,editor:{id:"14004",title:"Dr.",name:"Magnus",middleName:null,surname:"Johnsson",slug:"magnus-johnsson",fullName:"Magnus Johnsson",profilePictureURL:"https://mts.intechopen.com/storage/users/14004/images/system/14004.png",biography:"Dr Magnus Johnsson is a cross-disciplinary scientist, lecturer, scientific editor and AI/machine learning consultant from Sweden. \n\nHe is currently at Malmö University in Sweden, but also held positions at Lund University in Sweden and at Moscow Engineering Physics Institute. \nHe holds editorial positions at several international scientific journals and has served as a scientific editor for books and special journal issues. \nHis research interests are wide and include, but are not limited to, autonomous systems, computer modeling, artificial neural networks, artificial intelligence, cognitive neuroscience, cognitive robotics, cognitive architectures, cognitive aids and the philosophy of mind. \n\nDr. Johnsson has experience from working in the industry and he has a keen interest in the application of neural networks and artificial intelligence to fields like industry, finance, and medicine. \n\nWeb page: www.magnusjohnsson.se",institutionString:null,institution:{name:"Malmö University",institutionURL:null,country:{name:"Sweden"}}},editorTwo:null,editorThree:null},{id:"24",title:"Computer Vision",coverUrl:"https://cdn.intechopen.com/series_topics/covers/24.jpg",isOpenForSubmission:!0,editor:{id:"294154",title:"Prof.",name:"George",middleName:null,surname:"Papakostas",slug:"george-papakostas",fullName:"George Papakostas",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002hYaGbQAK/Profile_Picture_1624519712088",biography:"George A. Papakostas has received a diploma in Electrical and Computer Engineering in 1999 and the M.Sc. and Ph.D. degrees in Electrical and Computer Engineering in 2002 and 2007, respectively, from the Democritus University of Thrace (DUTH), Greece. Dr. Papakostas serves as a Tenured Full Professor at the Department of Computer Science, International Hellenic University, Greece. Dr. Papakostas has 10 years of experience in large-scale systems design as a senior software engineer and technical manager, and 20 years of research experience in the field of Artificial Intelligence. Currently, he is the Head of the “Visual Computing” division of HUman-MAchines INteraction Laboratory (HUMAIN-Lab) and the Director of the MPhil program “Advanced Technologies in Informatics and Computers” hosted by the Department of Computer Science, International Hellenic University. He has (co)authored more than 150 publications in indexed journals, international conferences and book chapters, 1 book (in Greek), 3 edited books, and 5 journal special issues. His publications have more than 2100 citations with h-index 27 (GoogleScholar). His research interests include computer/machine vision, machine learning, pattern recognition, computational intelligence. \nDr. Papakostas served as a reviewer in numerous journals, as a program\ncommittee member in international conferences and he is a member of the IAENG, MIR Labs, EUCogIII, INSTICC and the Technical Chamber of Greece (TEE).",institutionString:null,institution:{name:"International Hellenic University",institutionURL:null,country:{name:"Greece"}}},editorTwo:null,editorThree:null},{id:"25",title:"Evolutionary Computation",coverUrl:"https://cdn.intechopen.com/series_topics/covers/25.jpg",isOpenForSubmission:!0,editor:{id:"136112",title:"Dr.",name:"Sebastian",middleName:null,surname:"Ventura Soto",slug:"sebastian-ventura-soto",fullName:"Sebastian Ventura Soto",profilePictureURL:"https://mts.intechopen.com/storage/users/136112/images/system/136112.png",biography:"Sebastian Ventura is a Spanish researcher, a full professor with the Department of Computer Science and Numerical Analysis, University of Córdoba. Dr Ventura also holds the positions of Affiliated Professor at Virginia Commonwealth University (Richmond, USA) and Distinguished Adjunct Professor at King Abdulaziz University (Jeddah, Saudi Arabia). Additionally, he is deputy director of the Andalusian Research Institute in Data Science and Computational Intelligence (DaSCI) and heads the Knowledge Discovery and Intelligent Systems Research Laboratory. He has published more than ten books and over 300 articles in journals and scientific conferences. Currently, his work has received over 18,000 citations according to Google Scholar, including more than 2200 citations in 2020. In the last five years, he has published more than 60 papers in international journals indexed in the JCR (around 70% of them belonging to first quartile journals) and he has edited some Springer books “Supervised Descriptive Pattern Mining” (2018), “Multiple Instance Learning - Foundations and Algorithms” (2016), and “Pattern Mining with Evolutionary Algorithms” (2016). He has also been involved in more than 20 research projects supported by the Spanish and Andalusian governments and the European Union. He currently belongs to the editorial board of PeerJ Computer Science, Information Fusion and Engineering Applications of Artificial Intelligence journals, being also associate editor of Applied Computational Intelligence and Soft Computing and IEEE Transactions on Cybernetics. Finally, he is editor-in-chief of Progress in Artificial Intelligence. He is a Senior Member of the IEEE Computer, the IEEE Computational Intelligence, and the IEEE Systems, Man, and Cybernetics Societies, and the Association of Computing Machinery (ACM). Finally, his main research interests include data science, computational intelligence, and their applications.",institutionString:null,institution:{name:"University of Córdoba",institutionURL:null,country:{name:"Spain"}}},editorTwo:null,editorThree:null},{id:"26",title:"Machine Learning and Data Mining",coverUrl:"https://cdn.intechopen.com/series_topics/covers/26.jpg",isOpenForSubmission:!0,editor:{id:"24555",title:"Dr.",name:"Marco Antonio",middleName:null,surname:"Aceves Fernandez",slug:"marco-antonio-aceves-fernandez",fullName:"Marco Antonio Aceves Fernandez",profilePictureURL:"https://mts.intechopen.com/storage/users/24555/images/system/24555.jpg",biography:"Dr. Marco Antonio Aceves Fernandez obtained his B.Sc. (Eng.) in Telematics from the Universidad de Colima, Mexico. He obtained both his M.Sc. and Ph.D. from the University of Liverpool, England, in the field of Intelligent Systems. He is a full professor at the Universidad Autonoma de Queretaro, Mexico, and a member of the National System of Researchers (SNI) since 2009. Dr. Aceves Fernandez has published more than 80 research papers as well as a number of book chapters and congress papers. He has contributed in more than 20 funded research projects, both academic and industrial, in the area of artificial intelligence, ranging from environmental, biomedical, automotive, aviation, consumer, and robotics to other applications. He is also a honorary president at the National Association of Embedded Systems (AMESE), a senior member of the IEEE, and a board member of many institutions. His research interests include intelligent and embedded systems.",institutionString:"Universidad Autonoma de Queretaro",institution:{name:"Autonomous University of Queretaro",institutionURL:null,country:{name:"Mexico"}}},editorTwo:null,editorThree:null},{id:"27",title:"Multi-Agent Systems",coverUrl:"https://cdn.intechopen.com/series_topics/covers/27.jpg",isOpenForSubmission:!0,editor:{id:"148497",title:"Dr.",name:"Mehmet",middleName:"Emin",surname:"Aydin",slug:"mehmet-aydin",fullName:"Mehmet Aydin",profilePictureURL:"https://mts.intechopen.com/storage/users/148497/images/system/148497.jpg",biography:"Dr. Mehmet Emin Aydin is a Senior Lecturer with the Department of Computer Science and Creative Technology, the University of the West of England, Bristol, UK. His research interests include swarm intelligence, parallel and distributed metaheuristics, machine learning, intelligent agents and multi-agent systems, resource planning, scheduling and optimization, combinatorial optimization. Dr. Aydin is currently a Fellow of Higher Education Academy, UK, a member of EPSRC College, a senior member of IEEE and a senior member of ACM. In addition to being a member of advisory committees of many international conferences, he is an Editorial Board Member of various peer-reviewed international journals. He has served as guest editor for a number of special issues of peer-reviewed international journals.",institutionString:null,institution:{name:"University of the West of England",institutionURL:null,country:{name:"United Kingdom"}}},editorTwo:null,editorThree:null}]},overviewPageOFChapters:{paginationCount:20,paginationItems:[{id:"82526",title:"Deep Multiagent Reinforcement Learning Methods Addressing the Scalability Challenge",doi:"10.5772/intechopen.105627",signatures:"Theocharis Kravaris and George A. 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(Eng.) in Telematics from the Universidad de Colima, Mexico. He obtained both his M.Sc. and Ph.D. from the University of Liverpool, England, in the field of Intelligent Systems. He is a full professor at the Universidad Autonoma de Queretaro, Mexico, and a member of the National System of Researchers (SNI) since 2009. Dr. Aceves Fernandez has published more than 80 research papers as well as a number of book chapters and congress papers. He has contributed in more than 20 funded research projects, both academic and industrial, in the area of artificial intelligence, ranging from environmental, biomedical, automotive, aviation, consumer, and robotics to other applications. He is also a honorary president at the National Association of Embedded Systems (AMESE), a senior member of the IEEE, and a board member of many institutions. His research interests include intelligent and embedded systems.",institutionString:"Universidad Autonoma de Queretaro",institution:{name:"Autonomous University of Queretaro",institutionURL:null,country:{name:"Mexico"}}}]},{type:"book",id:"7726",title:"Swarm Intelligence",subtitle:"Recent Advances, New Perspectives and Applications",coverURL:"https://cdn.intechopen.com/books/images_new/7726.jpg",slug:"swarm-intelligence-recent-advances-new-perspectives-and-applications",publishedDate:"December 4th 2019",editedByType:"Edited by",bookSignature:"Javier Del Ser, Esther Villar and Eneko Osaba",hash:"e7ea7e74ce7a7a8e5359629e07c68d31",volumeInSeries:2,fullTitle:"Swarm Intelligence - Recent Advances, New Perspectives and Applications",editors:[{id:"49813",title:"Dr.",name:"Javier",middleName:null,surname:"Del Ser",slug:"javier-del-ser",fullName:"Javier Del Ser",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",institutionURL:null,country:{name:"Spain"}}}]},{type:"book",id:"7656",title:"Fuzzy Logic",subtitle:null,coverURL:"https://cdn.intechopen.com/books/images_new/7656.jpg",slug:"fuzzy-logic",publishedDate:"February 5th 2020",editedByType:"Edited by",bookSignature:"Constantin Volosencu",hash:"54f092d4ffe0abf5e4172a80025019bc",volumeInSeries:3,fullTitle:"Fuzzy Logic",editors:[{id:"1063",title:"Prof.",name:"Constantin",middleName:null,surname:"Volosencu",slug:"constantin-volosencu",fullName:"Constantin Volosencu",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. 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He is also a well-regarded clinician-educator, mentoring medical students, residents, and nephrology fellows. He gives lectures every year on national and international stages and has authored book chapters on various topics. He is a fellow of the American Society of Nephrology and an active member of the International Society of Nephrology. Dr. Tang is currently serving on the medical advisory boards for the National Kidney Foundation and End-Stage Renal Disease Network.",institutionString:"Brown University",institution:{name:"Brown University",country:{name:"United States of America"}}},{id:"200252",title:"Dr.",name:"Theodoros",middleName:null,surname:"Aslanidis",slug:"theodoros-aslanidis",fullName:"Theodoros Aslanidis",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/200252/images/system/200252.png",biography:"Dr. Theodoros K. Aslanidis received an MD from Plovdiv Medical University, Bulgaria, and a Ph.D. from Aristotle University of Thessaloniki, Greece. After serving as a medical doctor in the Hellenic Army Force and as a rural physician at Outhealth Centre, Iraklia and Serres’ General Hospital, Greece, he completed anesthesiology specialty training at Hippokratio General Hospital of Thessaloniki. He also completed Critical Care subspecialty training at AHEPA University Hospital, and the Prehospital Emergency Medicine postgraduate program, Hellenic National Centre for Emergency Care. He served as an EMS physician and emergency communication center medic before moving to his current post as consultant-researcher at the Intensive Care Unit, St. Paul General Hospital of Thessaloniki, Greece. He also serves as a senior lecturer in the Research Faculty, College of Offshore and Remote Medicine, Pretty Bay, Malta.",institutionString:"Saint Paul General Hospital of Thessaloniki",institution:null},{id:"313921",title:"Dr.",name:"Hassan M.",middleName:null,surname:"Heshmati",slug:"hassan-m.-heshmati",fullName:"Hassan M. Heshmati",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/313921/images/system/313921.jpg",biography:"Dr. Hassan Massoud Heshmati is an endocrinologist with 46 years of experience in clinical research in academia (university-affiliated hospitals, Paris, France; Mayo Foundation, Rochester, MN, USA) and pharmaceutical companies (Sanofi, Malvern, PA, USA; Essentialis, Carlsbad, CA, USA; Gelesis, Boston, MA, USA). His research activity focuses on pituitary tumors, hyperthyroidism, thyroid cancers, osteoporosis, diabetes, and obesity. He has extensive knowledge in the development of anti-obesity products. Dr. Heshmati is the author of 299 abstracts, chapters, and articles related to endocrinology and metabolism. He is currently a consultant at Endocrinology Metabolism Consulting, LLC, Anthem, AZ, USA.",institutionString:"Endocrinology Metabolism Consulting, LLC",institution:null},{id:"418340",title:"Dr.",name:"Jyotirmoi",middleName:null,surname:"Aich",slug:"jyotirmoi-aich",fullName:"Jyotirmoi Aich",position:null,profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0033Y000038Ugi5QAC/Profile_Picture_2022-04-15T07:48:28.png",biography:"Biotechnologist with 15 years of research including 6 years of teaching experience. Demonstrated record of scientific achievements through consistent publication record (H index = 13, with 874 citations) in high impact journals such as Nature Communications, Oncotarget, Annals of Oncology, PNAS, and AJRCCM, etc. Strong research professional with a post-doctorate from ACTREC where I gained experimental oncology experience in clinical settings and a doctorate from IGIB where I gained expertise in asthma pathophysiology. A well-trained biotechnologist with diverse experience on the bench across different research themes ranging from asthma to cancer and other infectious diseases. An individual with a strong commitment and innovative mindset. Have the ability to work on diverse projects such as regenerative and molecular medicine with an overall mindset of improving healthcare.",institutionString:"DY Patil Deemed to Be University",institution:null},{id:"319365",title:"Assistant Prof.",name:"Manash K.",middleName:null,surname:"Paul",slug:"manash-k.-paul",fullName:"Manash K. Paul",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/319365/images/system/319365.png",biography:"Manash K. Paul is a Principal Investigator and Scientist at the University of California Los Angeles. He has contributed significantly to the fields of stem cell biology, regenerative medicine, and lung cancer. His research focuses on various signaling processes involved in maintaining stem cell homeostasis during the injury-repair process, deciphering lung stem cell niche, pulmonary disease modeling, immuno-oncology, and drug discovery. He is currently investigating the role of extracellular vesicles in premalignant lung cell migration and detecting the metastatic phenotype of lung cancer via machine-learning-based analyses of exosomal signatures. Dr. Paul has published in more than fifty peer-reviewed international journals and is highly cited. He is the recipient of many awards, including the UCLA Vice Chancellor’s award, a senior member of the Institute of Electrical and Electronics Engineers (IEEE), and an editorial board member for several international journals.",institutionString:"University of California Los Angeles",institution:{name:"University of California Los Angeles",country:{name:"United States of America"}}},{id:"349288",title:"Prof.",name:"Soumya",middleName:null,surname:"Basu",slug:"soumya-basu",fullName:"Soumya Basu",position:null,profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0033Y000035QxIDQA0/Profile_Picture_2022-04-15T07:47:01.jpg",biography:"Soumya Basu, Ph.D., is currently working as an Associate Professor at Dr. D. Y. Patil Biotechnology and Bioinformatics Institute, Dr. D. Y. Patil Vidyapeeth, Pune, Maharashtra, India. With 16+ years of trans-disciplinary research experience in Drug Design, development, and pre-clinical validation; 20+ research article publications in journals of repute, 9+ years of teaching experience, trained with cross-disciplinary education, Dr. Basu is a life-long learner and always thrives for new challenges.\r\nHer research area is the design and synthesis of small molecule partial agonists of PPAR-γ in lung cancer. She is also using artificial intelligence and deep learning methods to understand the exosomal miRNA’s role in cancer metastasis. Dr. Basu is the recipient of many awards including the Early Career Research Award from the Department of Science and Technology, Govt. of India. She is a reviewer of many journals like Molecular Biology Reports, Frontiers in Oncology, RSC Advances, PLOS ONE, Journal of Biomolecular Structure & Dynamics, Journal of Molecular Graphics and Modelling, etc. She has edited and authored/co-authored 21 journal papers, 3 book chapters, and 15 abstracts. She is a Board of Studies member at her university. She is a life member of 'The Cytometry Society”-in India and 'All India Cell Biology Society”- in India.",institutionString:"Dr. D.Y. Patil Vidyapeeth, Pune",institution:{name:"Dr. D.Y. Patil Vidyapeeth, Pune",country:{name:"India"}}},{id:"76477",title:"Prof.",name:"Mirza",middleName:null,surname:"Hasanuzzaman",slug:"mirza-hasanuzzaman",fullName:"Mirza Hasanuzzaman",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/76477/images/system/76477.png",biography:"Dr. Mirza Hasanuzzaman is a Professor of Agronomy at Sher-e-Bangla Agricultural University, Bangladesh. He received his Ph.D. in Plant Stress Physiology and Antioxidant Metabolism from Ehime University, Japan, with a scholarship from the Japanese Government (MEXT). Later, he completed his postdoctoral research at the Center of Molecular Biosciences, University of the Ryukyus, Japan, as a recipient of the Japan Society for the Promotion of Science (JSPS) postdoctoral fellowship. He was also the recipient of the Australian Government Endeavour Research Fellowship for postdoctoral research as an adjunct senior researcher at the University of Tasmania, Australia. Dr. Hasanuzzaman’s current work is focused on the physiological and molecular mechanisms of environmental stress tolerance. Dr. Hasanuzzaman has published more than 150 articles in peer-reviewed journals. He has edited ten books and written more than forty book chapters on important aspects of plant physiology, plant stress tolerance, and crop production. According to Scopus, Dr. Hasanuzzaman’s publications have received more than 10,500 citations with an h-index of 53. He has been named a Highly Cited Researcher by Clarivate. He is an editor and reviewer for more than fifty peer-reviewed international journals and was a recipient of the “Publons Peer Review Award” in 2017, 2018, and 2019. He has been honored by different authorities for his outstanding performance in various fields like research and education, and he has received the World Academy of Science Young Scientist Award (2014) and the University Grants Commission (UGC) Award 2018. He is a fellow of the Bangladesh Academy of Sciences (BAS) and the Royal Society of Biology.",institutionString:"Sher-e-Bangla Agricultural University",institution:{name:"Sher-e-Bangla Agricultural University",country:{name:"Bangladesh"}}},{id:"213308",title:"Associate Prof.",name:"Manuel Víctor",middleName:null,surname:"López-González",slug:"manuel-victor-lopez-gonzalez",fullName:"Manuel Víctor López-González",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/213308/images/10301_n.jpg",biography:null,institutionString:null,institution:{name:"University of Malaga",country:{name:"Spain"}}},{id:"169212",title:"Prof.",name:"Pavol",middleName:null,surname:"Svorc",slug:"pavol-svorc",fullName:"Pavol Svorc",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/169212/images/system/169212.jpg",biography:"Dr. Pavol Švorc is an Associate Professor, Doctor of the Natural Sciences, Philosophe Doctor. In 1982 he became a Doctor of the Natural Sciences from General Biology, Natural Faculty, Šafarik’s University in Košice. In 1995 he received a PhD. – Physiology and Patophysiology, Natural Faculty Šafarik’s University in Košice. In 2005 he became an Associate Professor from Normal and Patological Physiology, Medical Faculty, Šafarik’s University in Košice. From 1982 to 1983 Dr.Švorc worked as an independent specialist in the local museum in Poprad, Slovakia. In 1983 he started working as a lecturer at the Department of Physiology, Šafarik’s University in Kosice, Slovakia. From\r\n2011 until 2014 he was a Head of the Institute of Physiology and Pathophysiology, Medical Faculty, University of Ostrava, Czech Republic. His research interest includes:\r\nChronobiology of cardiovascular system, respiratory system and autonomic nervous system.",institutionString:"Pavol Josef Safarik University",institution:{name:"University of Pavol Jozef Šafárik",country:{name:"Slovakia"}}},{id:"187859",title:"Prof.",name:"Kusal",middleName:"K.",surname:"Das",slug:"kusal-das",fullName:"Kusal Das",position:null,profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bSBDeQAO/Profile_Picture_1623411145568",biography:"Kusal K. Das is a Distinguished Chair Professor of Physiology, Shri B. M. Patil Medical College and Director, Centre for Advanced Medical Research (CAMR), BLDE (Deemed to be University), Vijayapur, Karnataka, India. Dr. Das did his M.S. and Ph.D. in Human Physiology from the University of Calcutta, Kolkata. His area of research is focused on understanding of molecular mechanisms of heavy metal activated low oxygen sensing pathways in vascular pathophysiology. He has invented a new method of estimation of serum vitamin E. His expertise in critical experimental protocols on vascular functions in experimental animals was well documented by his quality of publications. He was a Visiting Professor of Medicine at University of Leeds, United Kingdom (2014-2016) and Tulane University, New Orleans, USA (2017). For his immense contribution in medical research Ministry of Science and Technology, Government of India conferred him 'G.P. Chatterjee Memorial Research Prize-2019” and he is also the recipient of 'Dr.Raja Ramanna State Scientist Award 2015” by Government of Karnataka. He is a Fellow of the Royal Society of Biology (FRSB), London and Honorary Fellow of Karnataka Science and Technology Academy, Department of Science and Technology, Government of Karnataka.",institutionString:"BLDE (Deemed to be University), India",institution:null},{id:"243660",title:"Dr.",name:"Mallanagouda Shivanagouda",middleName:null,surname:"Biradar",slug:"mallanagouda-shivanagouda-biradar",fullName:"Mallanagouda Shivanagouda Biradar",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/243660/images/system/243660.jpeg",biography:"M. S. Biradar is Vice Chancellor and Professor of Medicine of\nBLDE (Deemed to be University), Vijayapura, Karnataka, India.\nHe obtained his MD with a gold medal in General Medicine and\nhas devoted himself to medical teaching, research, and administrations. He has also immensely contributed to medical research\non vascular medicine, which is reflected by his numerous publications including books and book chapters. Professor Biradar was\nalso Visiting Professor at Tulane University School of Medicine, New Orleans, USA.",institutionString:"BLDE (Deemed to be University)",institution:{name:"BLDE University",country:{name:"India"}}},{id:"289796",title:"Dr.",name:"Swastika",middleName:null,surname:"Das",slug:"swastika-das",fullName:"Swastika Das",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/289796/images/system/289796.jpeg",biography:"Swastika N. Das is Professor of Chemistry at the V. P. Dr. P. G.\nHalakatti College of Engineering and Technology, BLDE (Deemed\nto be University), Vijayapura, Karnataka, India. She obtained an\nMSc, MPhil, and PhD in Chemistry from Sambalpur University,\nOdisha, India. Her areas of research interest are medicinal chemistry, chemical kinetics, and free radical chemistry. She is a member\nof the investigators who invented a new modified method of estimation of serum vitamin E. She has authored numerous publications including book\nchapters and is a mentor of doctoral curriculum at her university.",institutionString:"BLDEA’s V.P.Dr.P.G.Halakatti College of Engineering & Technology",institution:{name:"BLDE University",country:{name:"India"}}},{id:"248459",title:"Dr.",name:"Akikazu",middleName:null,surname:"Takada",slug:"akikazu-takada",fullName:"Akikazu Takada",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/248459/images/system/248459.png",biography:"Akikazu Takada was born in Japan, 1935. After graduation from\nKeio University School of Medicine and finishing his post-graduate studies, he worked at Roswell Park Memorial Institute NY,\nUSA. He then took a professorship at Hamamatsu University\nSchool of Medicine. In thrombosis studies, he found the SK\npotentiator that enhances plasminogen activation by streptokinase. He is very much interested in simultaneous measurements\nof fatty acids, amino acids, and tryptophan degradation products. By using fatty\nacid analyses, he indicated that plasma levels of trans-fatty acids of old men were\nfar higher in the US than Japanese men. . He also showed that eicosapentaenoic acid\n(EPA) and docosahexaenoic acid (DHA) levels are higher, and arachidonic acid\nlevels are lower in Japanese than US people. By using simultaneous LC/MS analyses\nof plasma levels of tryptophan metabolites, he recently found that plasma levels of\nserotonin, kynurenine, or 5-HIAA were higher in patients of mono- and bipolar\ndepression, which are significantly different from observations reported before. In\nview of recent reports that plasma tryptophan metabolites are mainly produced by\nmicrobiota. He is now working on the relationships between microbiota and depression or autism.",institutionString:"Hamamatsu University School of Medicine",institution:{name:"Hamamatsu University School of Medicine",country:{name:"Japan"}}},{id:"137240",title:"Prof.",name:"Mohammed",middleName:null,surname:"Khalid",slug:"mohammed-khalid",fullName:"Mohammed Khalid",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/137240/images/system/137240.png",biography:"Mohammed Khalid received his B.S. in Chemistry in July 2000, and his Ph.D. in Physical Chemistry in 2007 from the University of Khartoum, Sudan. In 2009 he joined the Dr. Ron Clarke research group at the School of Chemistry, Faculty of Science, University of Sydney, Australia as a postdoctoral fellow where he worked on the Interaction of ATP with the phosphoenzyme of the Na+, K+-ATPase, and Dual mechanisms of allosteric acceleration of the Na+, K+-ATPase by ATP. He then worked as Assistant Professor at the Department of Chemistry, University of Khartoum, and in 2014 was promoted to Associate Professor ranking. In 2011 he joined the staff of the Chemistry Department at Taif University, Saudi Arabia, where he is currently active as an Assistant Professor. His research interests include:\r\n(1) P-type ATPase Enzyme Kinetics and Mechanisms; (2) Kinetics and Mechanism of Redox Reactions; (3) Autocatalytic reactions; (4) Computational enzyme kinetics; (5) Allosteric acceleration of P-type ATPases by ATP; (6) Exploring of allosteric sites of ATPases and interaction of ATP with ATPases located in the cell membranes.",institutionString:"Taif University",institution:{name:"Taif University",country:{name:"Saudi Arabia"}}},{id:"63810",title:"Prof.",name:"Jorge",middleName:null,surname:"Morales-Montor",slug:"jorge-morales-montor",fullName:"Jorge Morales-Montor",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/63810/images/system/63810.png",biography:"Dr. Jorge Morales-Montor was recognized with the Lola and Igo Flisser PUIS Award for best graduate thesis at the national level in the field of parasitology. He received a fellowship from the Fogarty Foundation to perform postdoctoral research stay at the University of Georgia. He has 153 journal articles to his credit. He has also edited several books and published more than fifty-five book chapters. He is a member of the Mexican Academy of Sciences, Latin American Academy of Sciences, and the National Academy of Medicine. He has received more than thirty-five awards and has supervised numerous bachelor’s, master’s, and Ph.D. students. Dr. Morales-Montor is the past president of the Mexican Society of Parasitology.",institutionString:"National Autonomous University of Mexico",institution:{name:"National Autonomous University of Mexico",country:{name:"Mexico"}}},{id:"217215",title:"Dr.",name:"Palash",middleName:null,surname:"Mandal",slug:"palash-mandal",fullName:"Palash Mandal",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/217215/images/system/217215.jpeg",biography:null,institutionString:"Charusat University",institution:null},{id:"49739",title:"Dr.",name:"Leszek",middleName:null,surname:"Szablewski",slug:"leszek-szablewski",fullName:"Leszek Szablewski",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/49739/images/system/49739.jpg",biography:"Leszek Szablewski is a professor of medical sciences. He received his M.S. in the Faculty of Biology from the University of Warsaw and his PhD degree from the Institute of Experimental Biology Polish Academy of Sciences. He habilitated in the Medical University of Warsaw, and he obtained his degree of Professor from the President of Poland. Professor Szablewski is the Head of Chair and Department of General Biology and Parasitology, Medical University of Warsaw. Professor Szablewski has published over 80 peer-reviewed papers in journals such as Journal of Alzheimer’s Disease, Biochim. Biophys. Acta Reviews of Cancer, Biol. Chem., J. Biomed. Sci., and Diabetes/Metabol. Res. Rev, Endocrine. He is the author of two books and four book chapters. He has edited four books, written 15 scripts for students, is the ad hoc reviewer of over 30 peer-reviewed journals, and editorial member of peer-reviewed journals. Prof. Szablewski’s research focuses on cell physiology, genetics, and pathophysiology. He works on the damage caused by lack of glucose homeostasis and changes in the expression and/or function of glucose transporters due to various diseases. He has given lectures, seminars, and exercises for students at the Medical University.",institutionString:"Medical University of Warsaw",institution:{name:"Medical University of Warsaw",country:{name:"Poland"}}},{id:"173123",title:"Dr.",name:"Maitham",middleName:null,surname:"Khajah",slug:"maitham-khajah",fullName:"Maitham Khajah",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/173123/images/system/173123.jpeg",biography:"Dr. Maitham A. Khajah received his degree in Pharmacy from Faculty of Pharmacy, Kuwait University, in 2003 and obtained his PhD degree in December 2009 from the University of Calgary, Canada (Gastrointestinal Science and Immunology). Since January 2010 he has been assistant professor in Kuwait University, Faculty of Pharmacy, Department of Pharmacology and Therapeutics. His research interest are molecular targets for the treatment of inflammatory bowel disease (IBD) and the mechanisms responsible for immune cell chemotaxis. He cosupervised many students for the MSc Molecular Biology Program, College of Graduate Studies, Kuwait University. Ever since joining Kuwait University in 2010, he got various grants as PI and Co-I. He was awarded the Best Young Researcher Award by Kuwait University, Research Sector, for the Year 2013–2014. He was a member in the organizing committee for three conferences organized by Kuwait University, Faculty of Pharmacy, as cochair and a member in the scientific committee (the 3rd, 4th, and 5th Kuwait International Pharmacy Conference).",institutionString:"Kuwait University",institution:{name:"Kuwait University",country:{name:"Kuwait"}}},{id:"195136",title:"Dr.",name:"Aya",middleName:null,surname:"Adel",slug:"aya-adel",fullName:"Aya Adel",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/195136/images/system/195136.jpg",biography:"Dr. Adel works as an Assistant Lecturer in the unit of Phoniatrics, Department of Otolaryngology, Ain Shams University in Cairo, Egypt. Dr. Adel is especially interested in joint attention and its impairment in autism spectrum disorder",institutionString:"Ain Shams University",institution:{name:"Ain Shams University",country:{name:"Egypt"}}},{id:"94911",title:"Dr.",name:"Boulenouar",middleName:null,surname:"Mesraoua",slug:"boulenouar-mesraoua",fullName:"Boulenouar Mesraoua",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/94911/images/system/94911.png",biography:"Dr Boulenouar Mesraoua is the Associate Professor of Clinical Neurology at Weill Cornell Medical College-Qatar and a Consultant Neurologist at Hamad Medical Corporation at the Neuroscience Department; He graduated as a Medical Doctor from the University of Oran, Algeria; he then moved to Belgium, the City of Liege, for a Residency in Internal Medicine and Neurology at Liege University; after getting the Belgian Board of Neurology (with high marks), he went to the National Hospital for Nervous Diseases, Queen Square, London, United Kingdom for a fellowship in Clinical Neurophysiology, under Pr Willison ; Dr Mesraoua had also further training in Epilepsy and Continuous EEG Monitoring for two years (from 2001-2003) in the Neurophysiology department of Zurich University, Switzerland, under late Pr Hans Gregor Wieser ,an internationally known epileptologist expert. \n\nDr B. Mesraoua is the Director of the Neurology Fellowship Program at the Neurology Section and an active member of the newly created Comprehensive Epilepsy Program at Hamad General Hospital, Doha, Qatar; he is also Assistant Director of the Residency Program at the Qatar Medical School. \nDr B. Mesraoua's main interests are Epilepsy, Multiple Sclerosis, and Clinical Neurology; He is the Chairman and the Organizer of the well known Qatar Epilepsy Symposium, he is running yearly for the past 14 years and which is considered a landmark in the Gulf region; He has also started last year , together with other epileptologists from Qatar, the region and elsewhere, a yearly International Epilepsy School Course, which was attended by many neurologists from the Area.\n\nInternationally, Dr Mesraoua is an active and elected member of the Commission on Eastern Mediterranean Region (EMR ) , a regional branch of the International League Against Epilepsy (ILAE), where he represents the Middle East and North Africa(MENA ) and where he holds the position of chief of the Epilepsy Epidemiology Section; Dr Mesraoua is a member of the American Academy of Neurology, the Europeen Academy of Neurology and the American Epilepsy Society.\n\nDr Mesraoua's main objectives are to encourage frequent gathering of the epileptologists/neurologists from the MENA region and the rest of the world, promote Epilepsy Teaching in the MENA Region, and encourage multicenter studies involving neurologists and epileptologists in the MENA region, particularly epilepsy epidemiological studies. \n\nDr. Mesraoua is the recipient of two research Grants, as the Lead Principal Investigator (750.000 USD and 250.000 USD) from the Qatar National Research Fund (QNRF) and the Hamad Hospital Internal Research Grant (IRGC), on the following topics : “Continuous EEG Monitoring in the ICU “ and on “Alpha-lactoalbumin , proof of concept in the treatment of epilepsy” .Dr Mesraoua is a reviewer for the journal \"seizures\" (Europeen Epilepsy Journal ) as well as dove journals ; Dr Mesraoua is the author and co-author of many peer reviewed publications and four book chapters in the field of Epilepsy and Clinical Neurology",institutionString:"Weill Cornell Medical College in Qatar",institution:{name:"Weill Cornell Medical College in Qatar",country:{name:"Qatar"}}},{id:"282429",title:"Prof.",name:"Covanis",middleName:null,surname:"Athanasios",slug:"covanis-athanasios",fullName:"Covanis Athanasios",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/282429/images/system/282429.jpg",biography:null,institutionString:"Neurology-Neurophysiology Department of the Children Hospital Agia Sophia",institution:null},{id:"190980",title:"Prof.",name:"Marwa",middleName:null,surname:"Mahmoud Saleh",slug:"marwa-mahmoud-saleh",fullName:"Marwa Mahmoud Saleh",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/190980/images/system/190980.jpg",biography:"Professor Marwa Mahmoud Saleh is a doctor of medicine and currently works in the unit of Phoniatrics, Department of Otolaryngology, Ain Shams University in Cairo, Egypt. She got her doctoral degree in 1991 and her doctoral thesis was accomplished in the University of Iowa, United States. Her publications covered a multitude of topics as videokymography, cochlear implants, stuttering, and dysphagia. She has lectured Egyptian phonology for many years. Her recent research interest is joint attention in autism.",institutionString:"Ain Shams University",institution:{name:"Ain Shams University",country:{name:"Egypt"}}},{id:"259190",title:"Dr.",name:"Syed Ali Raza",middleName:null,surname:"Naqvi",slug:"syed-ali-raza-naqvi",fullName:"Syed Ali Raza Naqvi",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/259190/images/system/259190.png",biography:"Dr. Naqvi is a radioanalytical chemist and is working as an associate professor of analytical chemistry in the Department of Chemistry, Government College University, Faisalabad, Pakistan. Advance separation techniques, nuclear analytical techniques and radiopharmaceutical analysis are the main courses that he is teaching to graduate and post-graduate students. In the research area, he is focusing on the development of organic- and biomolecule-based radiopharmaceuticals for diagnosis and therapy of infectious and cancerous diseases. Under the supervision of Dr. Naqvi, three students have completed their Ph.D. degrees and 41 students have completed their MS degrees. He has completed three research projects and is currently working on 2 projects entitled “Radiolabeling of fluoroquinolone derivatives for the diagnosis of deep-seated bacterial infections” and “Radiolabeled minigastrin peptides for diagnosis and therapy of NETs”. He has published about 100 research articles in international reputed journals and 7 book chapters. Pakistan Institute of Nuclear Science & Technology (PINSTECH) Islamabad, Punjab Institute of Nuclear Medicine (PINM), Faisalabad and Institute of Nuclear Medicine and Radiology (INOR) Abbottabad are the main collaborating institutes.",institutionString:"Government College University",institution:{name:"Government College University, Faisalabad",country:{name:"Pakistan"}}},{id:"58390",title:"Dr.",name:"Gyula",middleName:null,surname:"Mozsik",slug:"gyula-mozsik",fullName:"Gyula Mozsik",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/58390/images/system/58390.png",biography:"Gyula Mózsik MD, Ph.D., ScD (med), is an emeritus professor of Medicine at the First Department of Medicine, Univesity of Pécs, Hungary. He was head of this department from 1993 to 2003. His specializations are medicine, gastroenterology, clinical pharmacology, clinical nutrition, and dietetics. His research fields are biochemical pharmacological examinations in the human gastrointestinal (GI) mucosa, mechanisms of retinoids, drugs, capsaicin-sensitive afferent nerves, and innovative pharmacological, pharmaceutical, and nutritional (dietary) research in humans. He has published about 360 peer-reviewed papers, 197 book chapters, 692 abstracts, 19 monographs, and has edited 37 books. He has given about 1120 regular and review lectures. He has organized thirty-eight national and international congresses and symposia. He is the founder of the International Conference on Ulcer Research (ICUR); International Union of Pharmacology, Gastrointestinal Section (IUPHAR-GI); Brain-Gut Society symposiums, and gastrointestinal cytoprotective symposiums. He received the Andre Robert Award from IUPHAR-GI in 2014. Fifteen of his students have been appointed as full professors in Egypt, Cuba, and Hungary.",institutionString:"University of Pécs",institution:{name:"University of Pecs",country:{name:"Hungary"}}},{id:"277367",title:"M.Sc.",name:"Daniel",middleName:"Martin",surname:"Márquez López",slug:"daniel-marquez-lopez",fullName:"Daniel Márquez López",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/277367/images/7909_n.jpg",biography:"Msc Daniel Martin Márquez López has a bachelor degree in Industrial Chemical Engineering, a Master of science degree in the same área and he is a PhD candidate for the Instituto Politécnico Nacional. His Works are realted to the Green chemistry field, biolubricants, biodiesel, transesterification reactions for biodiesel production and the manipulation of oils for therapeutic purposes.",institutionString:null,institution:{name:"Instituto Politécnico Nacional",country:{name:"Mexico"}}},{id:"196544",title:"Prof.",name:"Angel",middleName:null,surname:"Catala",slug:"angel-catala",fullName:"Angel Catala",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/196544/images/system/196544.jpg",biography:"Angel Catalá studied chemistry at Universidad Nacional de La Plata, Argentina, where he received a Ph.D. in Chemistry (Biological Branch) in 1965. From 1964 to 1974, he worked as an Assistant in Biochemistry at the School of Medicine at the same university. From 1974 to 1976, he was a fellow of the National Institutes of Health (NIH) at the University of Connecticut, Health Center, USA. 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The applications of this research cover many related fields, such as biotechnology and medicine, where, for example, Bioinformatics contributes to faster drug design, DNA analysis in forensics, and DNA sequence analysis in the field of personalized medicine. Personalized medicine is a type of medical care in which treatment is customized individually for each patient. Personalized medicine enables more effective therapy, reduces the costs of therapy and clinical trials, and also minimizes the risk of side effects. Nevertheless, advances in personalized medicine would not have been possible without bioinformatics, which can analyze the human genome and other vast amounts of biomedical data, especially in genetics. The rapid growth of information technology enabled the development of new tools to decode human genomes, large-scale studies of genetic variations and medical informatics. The considerable development of technology, including the computing power of computers, is also conducive to the development of bioinformatics, including personalized medicine. In an era of rapidly growing data volumes and ever lower costs of generating, storing and computing data, personalized medicine holds great promises. Modern computational methods used as bioinformatics tools can integrate multi-scale, multi-modal and longitudinal patient data to create even more effective and safer therapy and disease prevention methods. Main aspects of the topic are: Applying bioinformatics in drug discovery and development; Bioinformatics in clinical diagnostics (genetic variants that act as markers for a condition or a disease); Blockchain and Artificial Intelligence/Machine Learning in personalized medicine; Customize disease-prevention strategies in personalized medicine; Big data analysis in personalized medicine; Translating stratification algorithms into clinical practice of personalized medicine.",annualVolume:11403,isOpenForSubmission:!0,coverUrl:"https://cdn.intechopen.com/series_topics/covers/7.jpg",editor:{id:"351533",title:"Dr.",name:"Slawomir",middleName:null,surname:"Wilczynski",fullName:"Slawomir Wilczynski",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0033Y000035U1loQAC/Profile_Picture_1630074514792",institutionString:null,institution:{name:"Medical University of Silesia",institutionURL:null,country:{name:"Poland"}}},editorTwo:null,editorThree:null,editorialBoard:[{id:"5886",title:"Dr.",name:"Alexandros",middleName:"T.",surname:"Tzallas",fullName:"Alexandros Tzallas",profilePictureURL:"https://mts.intechopen.com/storage/users/5886/images/system/5886.png",institutionString:"University of Ioannina, Greece & Imperial College London",institution:{name:"University of Ioannina",institutionURL:null,country:{name:"Greece"}}},{id:"257388",title:"Distinguished Prof.",name:"Lulu",middleName:null,surname:"Wang",fullName:"Lulu Wang",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bRX6kQAG/Profile_Picture_1630329584194",institutionString:"Shenzhen Technology University",institution:{name:"Shenzhen Technology University",institutionURL:null,country:{name:"China"}}},{id:"225387",title:"Prof.",name:"Reda R.",middleName:"R.",surname:"Gharieb",fullName:"Reda R. Gharieb",profilePictureURL:"https://mts.intechopen.com/storage/users/225387/images/system/225387.jpg",institutionString:"Assiut University",institution:{name:"Assiut University",institutionURL:null,country:{name:"Egypt"}}}]},{id:"8",title:"Bioinspired Technology and Biomechanics",keywords:"Bioinspired Systems, Biomechanics, Assistive Technology, Rehabilitation",scope:'Bioinspired technologies take advantage of understanding the actual biological system to provide solutions to problems in several areas. Recently, bioinspired systems have been successfully employing biomechanics to develop and improve assistive technology and rehabilitation devices. The research topic "Bioinspired Technology and Biomechanics" welcomes studies reporting recent advances in bioinspired technologies that contribute to individuals\' health, inclusion, and rehabilitation. Possible contributions can address (but are not limited to) the following research topics: Bioinspired design and control of exoskeletons, orthoses, and prostheses; Experimental evaluation of the effect of assistive devices (e.g., influence on gait, balance, and neuromuscular system); Bioinspired technologies for rehabilitation, including clinical studies reporting evaluations; Application of neuromuscular and biomechanical models to the development of bioinspired technology.',annualVolume:11404,isOpenForSubmission:!0,coverUrl:"https://cdn.intechopen.com/series_topics/covers/8.jpg",editor:{id:"144937",title:"Prof.",name:"Adriano",middleName:"De Oliveira",surname:"Andrade",fullName:"Adriano Andrade",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bRC8QQAW/Profile_Picture_1625219101815",institutionString:null,institution:{name:"Federal University of Uberlândia",institutionURL:null,country:{name:"Brazil"}}},editorTwo:null,editorThree:null,editorialBoard:[{id:"49517",title:"Prof.",name:"Hitoshi",middleName:null,surname:"Tsunashima",fullName:"Hitoshi Tsunashima",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002aYTP4QAO/Profile_Picture_1625819726528",institutionString:null,institution:{name:"Nihon University",institutionURL:null,country:{name:"Japan"}}},{id:"425354",title:"Dr.",name:"Marcus",middleName:"Fraga",surname:"Vieira",fullName:"Marcus Vieira",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0033Y00003BJSgIQAX/Profile_Picture_1627904687309",institutionString:null,institution:{name:"Universidade Federal de Goiás",institutionURL:null,country:{name:"Brazil"}}},{id:"196746",title:"Dr.",name:"Ramana",middleName:null,surname:"Vinjamuri",fullName:"Ramana Vinjamuri",profilePictureURL:"https://mts.intechopen.com/storage/users/196746/images/system/196746.jpeg",institutionString:"University of Maryland, Baltimore County",institution:{name:"University of Maryland, Baltimore County",institutionURL:null,country:{name:"United States of America"}}}]},{id:"9",title:"Biotechnology - Biosensors, Biomaterials and Tissue Engineering",keywords:"Biotechnology, Biosensors, Biomaterials, Tissue Engineering",scope:"The Biotechnology - Biosensors, Biomaterials and Tissue Engineering topic within the Biomedical Engineering Series aims to rapidly publish contributions on all aspects of biotechnology, biosensors, biomaterial and tissue engineering. We encourage the submission of manuscripts that provide novel and mechanistic insights that report significant advances in the fields. Topics can include but are not limited to: Biotechnology such as biotechnological products and process engineering; Biotechnologically relevant enzymes and proteins; Bioenergy and biofuels; Applied genetics and molecular biotechnology; Genomics, transcriptomics, proteomics; Applied microbial and cell physiology; Environmental biotechnology; Methods and protocols. Moreover, topics in biosensor technology, like sensors that incorporate enzymes, antibodies, nucleic acids, whole cells, tissues and organelles, and other biological or biologically inspired components will be considered, and topics exploring transducers, including those based on electrochemical and optical piezoelectric, thermal, magnetic, and micromechanical elements. Chapters exploring biomaterial approaches such as polymer synthesis and characterization, drug and gene vector design, biocompatibility, immunology and toxicology, and self-assembly at the nanoscale, are welcome. Finally, the tissue engineering subcategory will support topics such as the fundamentals of stem cells and progenitor cells and their proliferation, differentiation, bioreactors for three-dimensional culture and studies of phenotypic changes, stem and progenitor cells, both short and long term, ex vivo and in vivo implantation both in preclinical models and also in clinical trials.",annualVolume:11405,isOpenForSubmission:!0,coverUrl:"https://cdn.intechopen.com/series_topics/covers/9.jpg",editor:{id:"126286",title:"Dr.",name:"Luis",middleName:"Jesús",surname:"Villarreal-Gómez",fullName:"Luis Villarreal-Gómez",profilePictureURL:"https://mts.intechopen.com/storage/users/126286/images/system/126286.jpg",institutionString:null,institution:{name:"Autonomous University of Baja California",institutionURL:null,country:{name:"Mexico"}}},editorTwo:null,editorThree:null,editorialBoard:[{id:"35539",title:"Dr.",name:"Cecilia",middleName:null,surname:"Cristea",fullName:"Cecilia Cristea",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002aYQ65QAG/Profile_Picture_1621007741527",institutionString:null,institution:{name:"Iuliu Hațieganu University of Medicine and Pharmacy",institutionURL:null,country:{name:"Romania"}}},{id:"40735",title:"Dr.",name:"Gil",middleName:"Alberto Batista",surname:"Gonçalves",fullName:"Gil Gonçalves",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002aYRLGQA4/Profile_Picture_1628492612759",institutionString:null,institution:{name:"University of Aveiro",institutionURL:null,country:{name:"Portugal"}}},{id:"211725",title:"Associate Prof.",name:"Johann F.",middleName:null,surname:"Osma",fullName:"Johann F. 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