These books synthesize perspectives of renowned scientists from the world’s most prestigious institutions - from Fukushima Renewable Energy Institute in Japan to Stanford University in the United States, including Columbia University (US), University of Sidney (AU), University of Miami (USA), Cardiff University (UK), and many others.
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This collaboration embodied the true essence of Open Access by simplifying the approach to OA publishing for Academic editors and authors who contributed their research and allowed the new research to be made available free and open to anyone anywhere in the world.
\\n\\n
To celebrate the 50 books published, we have gathered them at one location - just one click away, so that you can easily browse the subjects of your interest, download the content directly, share it or read online.
IntechOpen and Knowledge Unlatched formed a partnership to support researchers working in engineering sciences by enabling an easier approach to publishing Open Access content. Using the Knowledge Unlatched crowdfunding model to raise the publishing costs through libraries around the world, Open Access Publishing Fee (OAPF) was not required from the authors.
\n\n
Initially, the partnership supported engineering research, but it soon grew to include physical and life sciences, attracting more researchers to the advantages of Open Access publishing.
\n\n\n\n
These books synthesize perspectives of renowned scientists from the world’s most prestigious institutions - from Fukushima Renewable Energy Institute in Japan to Stanford University in the United States, including Columbia University (US), University of Sidney (AU), University of Miami (USA), Cardiff University (UK), and many others.
\n\n
This collaboration embodied the true essence of Open Access by simplifying the approach to OA publishing for Academic editors and authors who contributed their research and allowed the new research to be made available free and open to anyone anywhere in the world.
\n\n
To celebrate the 50 books published, we have gathered them at one location - just one click away, so that you can easily browse the subjects of your interest, download the content directly, share it or read online.
\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:"5222",leadTitle:null,fullTitle:"Cannabinoids in Health and Disease",title:"Cannabinoids in Health and Disease",subtitle:null,reviewType:"peer-reviewed",abstract:"This book provides a comprehensive overview of current knowledge of cannabinoid\nactivity in human physiology and points out the importance of endocannabinoid system\nfor the maintenance of human health and treatment of diseases. Each chapter\nhas been organized with the aim to cover basic concepts in the modulation of endocannabinoid system in both physiological and pathological conditions, thanks to\nthe integration of data from experimental animal models and clinical observations.\nA special focus has been put on the medical use of cannabinoids and on the targeting\nof endocannabinoid system as new therapeutic strategy for the prevention and\ntreatment of human diseases. Taken together, this book targets a wide audience of\nbasic and clinical scientists, teachers and students interested in gaining a better understanding in the field of cannabinoids.",isbn:"978-953-51-2430-6",printIsbn:"978-953-51-2429-0",pdfIsbn:"978-953-51-4198-3",doi:"10.5772/61595",price:119,priceEur:129,priceUsd:155,slug:"cannabinoids-in-health-and-disease",numberOfPages:258,isOpenForSubmission:!1,isInWos:1,isInBkci:!0,hash:"d684a703afd17dc97d18480a982e5316",bookSignature:"Rosaria Meccariello and Rosanna Chianese",publishedDate:"June 15th 2016",coverURL:"https://cdn.intechopen.com/books/images_new/5222.jpg",numberOfDownloads:18603,numberOfWosCitations:38,numberOfCrossrefCitations:19,numberOfCrossrefCitationsByBook:2,numberOfDimensionsCitations:48,numberOfDimensionsCitationsByBook:2,hasAltmetrics:1,numberOfTotalCitations:105,isAvailableForWebshopOrdering:!0,dateEndFirstStepPublish:"September 28th 2015",dateEndSecondStepPublish:"October 19th 2015",dateEndThirdStepPublish:"January 23rd 2016",dateEndFourthStepPublish:"April 22nd 2016",dateEndFifthStepPublish:"July 6th 2016",currentStepOfPublishingProcess:5,indexedIn:"1,2,3,4,5,6,8,9",editedByType:"Edited by",kuFlag:!1,featuredMarkup:null,editors:[{id:"143980",title:"Prof.",name:"Rosaria",middleName:null,surname:"Meccariello",slug:"rosaria-meccariello",fullName:"Rosaria Meccariello",profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:"Dr. Rosaria Meccariello obtained a degree in Biological Sciences from the University of Naples Federico II, Italy, and a PhD in Comparative Endocrinology from\r\nthe University of Padova, Italy. Currently, she is Associate Professor of Biology at\r\nthe Department of Movement and Wellness Sciences at the University of Naples\r\n'Parthenope,” Italy. She has published more than 130 papers in peer-reviewed international journals, books, proceedings and abstract books. She has experience as\r\na reviewer for international journals and has served as an editor for scientific books,\r\nspecial issues and e-books. Dr. Meccariello is an expert in biology of reproduction,\r\nspermatogenesis, the hypothalamus-pituitary-gonad axis, central and local activity\r\nof GnRH, endocannabinoid and kisspeptin systems, and epigenetics.",institutionString:"University of Naples Parthenope",position:null,outsideEditionCount:0,totalCites:0,totalAuthoredChapters:"4",totalChapterViews:"0",totalEditedBooks:"3",institution:{name:"Parthenope University of Naples",institutionURL:null,country:{name:"Italy"}}}],equalEditorOne:null,equalEditorTwo:null,equalEditorThree:null,coeditorOne:{id:"244717",title:"Dr.",name:"Rosanna",middleName:null,surname:"Chianese",slug:"rosanna-chianese",fullName:"Rosanna Chianese",profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:"Dr. Rosanna Chianese received her degree in biology from the University of Naples Federico II, Italy, in 2004. In 2006, she carried out a training at the University of Washington, Seattle, USA, during her PhD studies in comparative endocrinology (University of Padova, Italy). For the biennium 2009/2011, she obtained a research fellowship for the project 'Mesothelioma and biomarkers” at the Second University of Naples (SUN), Italy. Currently, she is an assistant professor at the Department of Experimental Medicine, SUN. She has experience as reviewer for international journals and since 2005, she has published 25 articles in international journals, 1 book chapter for InTech and 22 abstracts for national and international conferences. Dr. Chianese also teaches face-to-face cellular biology course at SUN.",institutionString:null,position:null,outsideEditionCount:0,totalCites:0,totalAuthoredChapters:"2",totalChapterViews:"0",totalEditedBooks:"0",institution:{name:'University of Campania "Luigi Vanvitelli"',institutionURL:null,country:{name:"Italy"}}},coeditorTwo:null,coeditorThree:null,coeditorFour:null,coeditorFive:null,topics:[{id:"992",title:"Pharmacology",slug:"complementary-medicine-pharmacology"}],chapters:[{id:"50857",title:"The Endocannabinoid System in Human Physiology",doi:"10.5772/63818",slug:"the-endocannabinoid-system-in-human-physiology",totalDownloads:1979,totalCrossrefCites:1,totalDimensionsCites:2,hasAltmetrics:0,abstract:null,signatures:"Rosanna Chianese and Rosaria Meccariello",downloadPdfUrl:"/chapter/pdf-download/50857",previewPdfUrl:"/chapter/pdf-preview/50857",authors:[{id:"143980",title:"Prof.",name:"Rosaria",surname:"Meccariello",slug:"rosaria-meccariello",fullName:"Rosaria Meccariello"}],corrections:null},{id:"50674",title:"Endocannabinoid Signaling in Neural Circuits of the Olfactory and Limbic System",doi:"10.5772/63214",slug:"endocannabinoid-signaling-in-neural-circuits-of-the-olfactory-and-limbic-system",totalDownloads:1617,totalCrossrefCites:1,totalDimensionsCites:8,hasAltmetrics:0,abstract:"The endocannabinoid system with cannabinoid receptors, specifically cannabinoid receptor type 1 (CB1R), and their endogenous activators, the endocannabinoids, has emerged as an important neuromodulator system. Our understanding of the endocannabinoid system has significantly advanced in limbic system areas such as the hippocampus and the amygdala. However, the study of this signaling system in the olfactory pathway is still in its infancy. Here, we review the role of endocannabinoids as signaling molecules in activity-dependent regulation of dynamically changing neural networks in the limbic and olfactory system and the relevance of the endocannabinoid system for synaptic plasticity. We highlight the prospects for cannabinoid-based therapies in the treatment of various brain disorders and the role of endocannabinoids as neuroprotective agents. An increased understanding of cannabinoid signaling has the potential to pave the way for developing cannabis-related substances as medications.",signatures:"Thomas Heinbockel, Ze-Jun Wang, Edward A. Brown and Paul T.\nAustin",downloadPdfUrl:"/chapter/pdf-download/50674",previewPdfUrl:"/chapter/pdf-preview/50674",authors:[{id:"70569",title:"Dr.",name:"Thomas",surname:"Heinbockel",slug:"thomas-heinbockel",fullName:"Thomas Heinbockel"},{id:"185616",title:"Dr.",name:"Ze-Jun",surname:"Wang",slug:"ze-jun-wang",fullName:"Ze-Jun Wang"},{id:"185617",title:"Mr.",name:"Edward",surname:"Brown",slug:"edward-brown",fullName:"Edward Brown"},{id:"185618",title:"Mr.",name:"Paul",surname:"Austin",slug:"paul-austin",fullName:"Paul Austin"}],corrections:null},{id:"50651",title:"The Potential Therapeutic Role of the Cannabinoid System in Neurological Disorders of the Basal Ganglia: An Overview",doi:"10.5772/63375",slug:"the-potential-therapeutic-role-of-the-cannabinoid-system-in-neurological-disorders-of-the-basal-gang",totalDownloads:1535,totalCrossrefCites:0,totalDimensionsCites:1,hasAltmetrics:0,abstract:"Cannabinoid pharmacology has been explored as a therapeutic option for handling pathologies and conditions of varying nature. In regard to neurological disorders, cannabinoid chemistry has been explored for the regulation of hyperkinetic symptoms, anti-inflammation, neuroprotection, and neurodegeneration, a collective goal of many preclinical studies. The enhancement and improvement of the endogenous cannabinergic responses of the human body in both physiological and pathological conditions, together with the overall consequential effects of the modulation of its elements, are currently under strict scrutiny and undeniably possess incalculable value that might support the hypothesis aiming to improve the endocannabinoid tone with therapeutic purposes. Therefore, this chapter reviews the mechanisms known to be present in the course of several disorders of the basal ganglia, as well as the available treatments exploring this novel approach.",signatures:"Gabriela Aguilera and Abel Santamaría",downloadPdfUrl:"/chapter/pdf-download/50651",previewPdfUrl:"/chapter/pdf-preview/50651",authors:[{id:"178440",title:"Ph.D.",name:"Abel",surname:"Santamaria",slug:"abel-santamaria",fullName:"Abel Santamaria"},{id:"184809",title:"MSc.",name:"Gabriela",surname:"Aguilera",slug:"gabriela-aguilera",fullName:"Gabriela Aguilera"}],corrections:null},{id:"50166",title:"Cannabinoids and Motor Control of the Basal Ganglia: Therapeutic Potential in Movement Disorders",doi:"10.5772/62438",slug:"cannabinoids-and-motor-control-of-the-basal-ganglia-therapeutic-potential-in-movement-disorders",totalDownloads:1604,totalCrossrefCites:1,totalDimensionsCites:4,hasAltmetrics:0,abstract:"Cannabinoid receptors in the brain appear to be intimately involved in the motor control. Cannabinoid CB1 receptors are densely located in the basal ganglia (BG), a forebrain system that integrates cortical information to coordinate motor activity regulating signals. In fact, the administration of plant-derived, synthetic or endogenous cannabinoids produces several effects on motor function. These effects are paralleled to changes in the levels of different neurotransmitters in the BG, including GABA, dopamine and glutamate, all of which are important players in movement control.",signatures:"Teresa Morera-Herreras, Cristina Miguelez, Asier Aristieta, María Torrecilla, José Ángel Ruiz-Ortega and Luisa Ugedo",downloadPdfUrl:"/chapter/pdf-download/50166",previewPdfUrl:"/chapter/pdf-preview/50166",authors:[{id:"178735",title:"Dr.",name:"Teresa",surname:"Morera-Herreras",slug:"teresa-morera-herreras",fullName:"Teresa Morera-Herreras"},{id:"179364",title:"Dr.",name:"Maria",surname:"Torrecilla",slug:"maria-torrecilla",fullName:"Maria Torrecilla"},{id:"179365",title:"Dr.",name:"Cristina",surname:"Miguelez",slug:"cristina-miguelez",fullName:"Cristina Miguelez"},{id:"179366",title:"Dr.",name:"Asier",surname:"Aristieta",slug:"asier-aristieta",fullName:"Asier Aristieta"},{id:"179367",title:"Dr.",name:"Jose Angel",surname:"Ruiz-Ortega",slug:"jose-angel-ruiz-ortega",fullName:"Jose Angel Ruiz-Ortega"},{id:"179368",title:"Prof.",name:"Luisa",surname:"Ugedo",slug:"luisa-ugedo",fullName:"Luisa Ugedo"}],corrections:null},{id:"50856",title:"Therapeutic Potential of Nonpsychoactive Cannabinoids by Targeting at Glycine Receptors",doi:"10.5772/63360",slug:"therapeutic-potential-of-nonpsychoactive-cannabinoids-by-targeting-at-glycine-receptors",totalDownloads:1720,totalCrossrefCites:0,totalDimensionsCites:1,hasAltmetrics:1,abstract:"The glycine receptors (GlyRs) have been identified as major inhibitory neurotransmission receptors in the brain since the mid of last century. Unfortunately, no therapeutic agent has been developed from targeting these receptors. Accumulating evidence has suggested that GlyRs are one primary target for exogenous and endogenous cannabinoids in the central nervous system. Cannabinoids enhance the function of GlyRs in various neurons in the brain. However, this line of research has been largely ignored since little is known about the molecular mechanism and behavioral implication of cannabinoid modulation of GlyRs. Recent studies using various experimental approaches have explored molecular insights into cannabinoid-GlyR interaction and shed light on the molecular basis of nonpsychoactive cannabinoid modulation of GlyRs. Emerging evidence has suggested that cannabinoid modulation of GlyRs can contribute to some of the cannabis-induced therapeutic effects. In this chapter, I discuss recent development in studies of mechanism and therapeutic potential of cannabinoid modulation of GlyR subunits. This research direction shows considerable promise toward the development of novel therapeutic agents acting at defined modulatory sites of GlyRs in the treatment of various chronic pain, neuromotor disorders, and other GlyR deficiency diseases.",signatures:"Li Zhang",downloadPdfUrl:"/chapter/pdf-download/50856",previewPdfUrl:"/chapter/pdf-preview/50856",authors:[{id:"179194",title:"Dr.",name:"Li",surname:"Zhang",slug:"li-zhang",fullName:"Li Zhang"}],corrections:null},{id:"50397",title:"Dietary Omega-6/Omega-3 and Endocannabinoids: Implications for Brain Health and Diseases",doi:"10.5772/62498",slug:"dietary-omega-6-omega-3-and-endocannabinoids-implications-for-brain-health-and-diseases",totalDownloads:2576,totalCrossrefCites:6,totalDimensionsCites:11,hasAltmetrics:1,abstract:"Omega-3 (ω-3) and omega-6 (ω-6) are polyunsaturated fatty acids (PUFAs) that play critical role in human health and have to be provided by food. In the brain, PUFAs are also precursors of endocannabinoids. The aim of this chapter is to review the existing literature on how dietary PUFAs impact on the endocannabinoid system in the brain and what are the consequences for brain function and dysfunction. In this chapter, we will first describe how PUFAs enter the brain, what are their metabolism processes and roles in brain function. We will describe the pathways from PUFAs to endocannabinoid production. Then, we will review the literature on how dietary ω-6/ω-3 ratio impacts the endocannabinoid system, in terms of endocannabinoid levels, proteins and endocannabinoid-dependent synaptic plasticity. In the next part, we will describe what we know about the interactions between PUFAs and endocannabinoids in neurological and neuropsychiatric disorders. Finally, we will conclude on the possible implications of the interactions between dietary PUFAs and endocannabinoids in the normal and pathological brain. In particular, we will discuss how dietary PUFAs, as homeostatic regulators of endocannabinoids, can constitute interesting therapeutic strategies for the prevention and/or treatment of neurological disorders with endocannabinoids impairment.",signatures:"Clémentine Bosch-Bouju and Sophie Layé",downloadPdfUrl:"/chapter/pdf-download/50397",previewPdfUrl:"/chapter/pdf-preview/50397",authors:[{id:"178351",title:"Dr.",name:"Sophie",surname:"Layé",slug:"sophie-laye",fullName:"Sophie Layé"}],corrections:null},{id:"50549",title:"The Endocannabinoid-Like Derivative Oleoylethanolamide at the Gut–Brain Interface: A “Lipid Way” to Control Energy Intake and Body Weight",doi:"10.5772/63147",slug:"the-endocannabinoid-like-derivative-oleoylethanolamide-at-the-gut-brain-interface-a-lipid-way-to-con",totalDownloads:1927,totalCrossrefCites:2,totalDimensionsCites:3,hasAltmetrics:0,abstract:"In the last three decades, we witnessed a concomitant major increase in lifespan and a worldwide increasing incidence of chronic diseases such as obesity and type 2 diabetes. Disruption of energy homeostasis and systemic inflammation appear as common traits of these epidemic human diseases. The conventional endocannabinoid (eCB) system encompasses two G-protein–coupled receptors (GPCRs), their endogenous ligands (anandamide and 2-AG), and the enzymes essential for eCB biosynthesis and hydrolytic inactivation. Nonetheless, the family of eCB-like derivatives is growing constantly including other N-acylethanolamines (NAEs) and 2-monoacylglycerols (2-MAGs) that do not bind canonical CB receptors rather other orphan G-protein–coupled receptors or peroxisome proliferator-activated nuclear receptors (PPARs). Here, we focus on the recent knowledge gathered on one such PPAR endocannabinoid ligand, oleoylethanolamide (OEA), from the identification of its synthesis in the small intestine to its anorexiant function with particular emphasis on our discovery of the main brain neurotransmitters system involved in its satiating effects.",signatures:"Maria Beatrice Passani and Roberto Coccurello",downloadPdfUrl:"/chapter/pdf-download/50549",previewPdfUrl:"/chapter/pdf-preview/50549",authors:[{id:"178510",title:"Ph.D.",name:"Roberto",surname:"Coccurello",slug:"roberto-coccurello",fullName:"Roberto Coccurello"}],corrections:null},{id:"50317",title:"Cannabinoid CB1/CB2 Receptors in the Heart: Expression, Regulation, and Function",doi:"10.5772/62822",slug:"cannabinoid-cb1-cb2-receptors-in-the-heart-expression-regulation-and-function",totalDownloads:2097,totalCrossrefCites:6,totalDimensionsCites:12,hasAltmetrics:1,abstract:"Endocannabinoids exert their actions in the heart and vessels, at least in part, by stimulating the cannabinoid CB1 and the CB2 receptor subtypes which belong to a group of seven transmembrane-spanning receptors and are coupled to Gi/o-proteins. Activation of cardiovascular CB1 receptors leads to depressed cardiac contractility and hypotension. Conversely, in most studies, the CB1 receptor antagonists are cardioprotective against ischemia–reperfusion injury, myocardial ischemia, heart failure, and cardiomyopathies. Evidence to date indicates that CB2 receptor activation is cardioprotective. CB2 receptor-mediated effects such as anti-inflammation and anti-fibrosis may be in part opposite to the actions of the CB1 receptor. The aim of this review is to up-date on recent experimental findings and controversies on the role of endocannabinoid system in the myocardial injury with emphasis on pathophysiological processes such as left ventricular remodeling, cardiac fibrosis, hypertrophy, and endothelial dysfunction. Recent experimental studies employing genetic deficiency of CB1 and CB2 receptors and endocannabinoid anandamide metabolizing enzymes are reviewed. Moreover, the protective mechanisms which are mediated by cannabinoid receptors during ischemic preconditioning as well as in the early and late phase after myocardial infarction are discussed in the context of possible therapeutic implications.",signatures:"Elena Kaschina",downloadPdfUrl:"/chapter/pdf-download/50317",previewPdfUrl:"/chapter/pdf-preview/50317",authors:[{id:"32266",title:"Dr.",name:"Elena",surname:"Kaschina",slug:"elena-kaschina",fullName:"Elena Kaschina"}],corrections:null},{id:"50351",title:"The Role for the Endocannabinoid System in Cardioprotection and Myocardial Adaptation",doi:"10.5772/62485",slug:"the-role-for-the-endocannabinoid-system-in-cardioprotection-and-myocardial-adaptation",totalDownloads:1566,totalCrossrefCites:2,totalDimensionsCites:4,hasAltmetrics:1,abstract:"Results from different studies showing CB2 receptor-associated cardioprotective action are still fairly controversial and no single specific mechanism could be identified. Several groups investigated the involvement of the endocannabinoid system in cellular systems and function of cardiomyocytes, fibroblasts, macrophages and endothelial cells. While some studies are limited in their translational relevance, a few recent studies describe a myocardial ischemia and reperfusion scenario in a fashion comparable to the clinical situation. Recent studies provided evidence for involvement of the CB2 receptor–endocannabinoid axis in prevention of cardiomyocyte apoptosis including modulation of antioxidative enzymes and contractile elements expression. CB2 receptor has further been shown to specifically modulate the inflammatory response and macrophage function after myocardial ischemia. These effects have an impact on the subsequent myocardial remodeling, where the CB2 receptor modulates function of myofibroblasts, collagen production and limitation of myocardial infarction size. Recent experimental and clinical data showed the association of the endocannabinoid system in myocardial hypertrophy. In conclusion, increasing amount of evidence supports a crucial role of the endocannabinoid system in cardioprotection and myocardial remodeling, while some of them even suggest model-independent systemic effects in adaptation of cardiomyocytes or components of the extracellular matrix.",signatures:"Oliver Dewald and Georg D. Duerr",downloadPdfUrl:"/chapter/pdf-download/50351",previewPdfUrl:"/chapter/pdf-preview/50351",authors:[{id:"178354",title:"Dr.",name:"Oliver",surname:"Dewald",slug:"oliver-dewald",fullName:"Oliver Dewald"},{id:"185056",title:"Dr.",name:"Georg",surname:"Duerr",slug:"georg-duerr",fullName:"Georg Duerr"}],corrections:null},{id:"50593",title:"Cannabinoids: Drug or Medication?",doi:"10.5772/63172",slug:"cannabinoids-drug-or-medication-",totalDownloads:1985,totalCrossrefCites:0,totalDimensionsCites:2,hasAltmetrics:0,abstract:"This chapter aims at exploring the use and misuse of cannabinoids as it has become a major societal issue. In the first section, we describe the historical use of cannabis as a natural cure in ancient civilizations. We then explore the current use of cannabinoids in medicine, which includes innovative strategies for treating various diseases such as multiple sclerosis or cancer‐induced pain. In the second section, we consider how the discovery and characterization of the endocannabinoid system have increased knowledge of this system's mode of action. Consumption of cannabis for recreational use however is a significant public health issue today. Scientific advances are confronted with the adverse health effects that are demonstrated in preclinical and clinical studies based on the psychotic and addictive properties of this compound. In the third section, we therefore provide an overview of the recent findings on the endocannabinoid system using animal models with proposed molecular mechanisms and potential interactions with other neuromodulatory systems like the opioid system. Finally, through alternative strategies to current treatments with both phyto‐ and synthetic cannabinoids, we try to reconcile the beneficial aspects of the use of cannabinoids for medication and the aspects associated with addictive properties.",signatures:"Léa Giron and Katia Befort",downloadPdfUrl:"/chapter/pdf-download/50593",previewPdfUrl:"/chapter/pdf-preview/50593",authors:[{id:"179154",title:"Dr.",name:"Katia",surname:"Befort",slug:"katia-befort",fullName:"Katia Befort"},{id:"179388",title:"MSc.",name:"Léa",surname:"Giron",slug:"lea-giron",fullName:"Léa Giron"}],corrections:null}],productType:{id:"1",title:"Edited Volume",chapterContentType:"chapter",authoredCaption:"Edited by"},subseries:null,tags:null},relatedBooks:[{type:"book",id:"7995",title:"Epigenetics",subtitle:null,isOpenForSubmission:!1,hash:"33c1f5868ce0c29fbde6eafdc50af702",slug:"epigenetics",bookSignature:"Rosaria Meccariello",coverURL:"https://cdn.intechopen.com/books/images_new/7995.jpg",editedByType:"Edited by",editors:[{id:"143980",title:"Prof.",name:"Rosaria",surname:"Meccariello",slug:"rosaria-meccariello",fullName:"Rosaria Meccariello"}],equalEditorOne:null,equalEditorTwo:null,equalEditorThree:null,productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}},{type:"book",id:"6079",title:"Spermatozoa",subtitle:"Facts and Perspectives",isOpenForSubmission:!1,hash:"2d4488814a6ea68efcd3544209c9e4d2",slug:"spermatozoa-facts-and-perspectives",bookSignature:"Rosaria Meccariello and Rosanna Chianese",coverURL:"https://cdn.intechopen.com/books/images_new/6079.jpg",editedByType:"Edited by",editors:[{id:"143980",title:"Prof.",name:"Rosaria",surname:"Meccariello",slug:"rosaria-meccariello",fullName:"Rosaria Meccariello"}],equalEditorOne:null,equalEditorTwo:null,equalEditorThree:null,productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}},{type:"book",id:"4625",title:"Complementary Therapies for the Body, Mind and Soul",subtitle:null,isOpenForSubmission:!1,hash:"48cd88cd7a6ffb4ade0088448e5ac56b",slug:"complementary-therapies-for-the-body-mind-and-soul",bookSignature:"Marcelo Saad",coverURL:"https://cdn.intechopen.com/books/images_new/4625.jpg",editedByType:"Edited by",editors:[{id:"51991",title:"Prof.",name:"Marcelo",surname:"Saad",slug:"marcelo-saad",fullName:"Marcelo Saad"}],equalEditorOne:null,equalEditorTwo:null,equalEditorThree:null,productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}},{type:"book",id:"1591",title:"Infrared Spectroscopy",subtitle:"Materials Science, Engineering and Technology",isOpenForSubmission:!1,hash:"99b4b7b71a8caeb693ed762b40b017f4",slug:"infrared-spectroscopy-materials-science-engineering-and-technology",bookSignature:"Theophile Theophanides",coverURL:"https://cdn.intechopen.com/books/images_new/1591.jpg",editedByType:"Edited by",editors:[{id:"37194",title:"Dr.",name:"Theophile",surname:"Theophanides",slug:"theophile-theophanides",fullName:"Theophile Theophanides"}],equalEditorOne:null,equalEditorTwo:null,equalEditorThree:null,productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}},{type:"book",id:"3161",title:"Frontiers in Guided Wave Optics and Optoelectronics",subtitle:null,isOpenForSubmission:!1,hash:"deb44e9c99f82bbce1083abea743146c",slug:"frontiers-in-guided-wave-optics-and-optoelectronics",bookSignature:"Bishnu Pal",coverURL:"https://cdn.intechopen.com/books/images_new/3161.jpg",editedByType:"Edited by",editors:[{id:"4782",title:"Prof.",name:"Bishnu",surname:"Pal",slug:"bishnu-pal",fullName:"Bishnu Pal"}],equalEditorOne:null,equalEditorTwo:null,equalEditorThree:null,productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}},{type:"book",id:"371",title:"Abiotic Stress in Plants",subtitle:"Mechanisms and Adaptations",isOpenForSubmission:!1,hash:"588466f487e307619849d72389178a74",slug:"abiotic-stress-in-plants-mechanisms-and-adaptations",bookSignature:"Arun Shanker and B. 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\r\n\tThe pipeline system is an integral part of our current civilization. All across the globe, it ensures the economical transmission of essential fluids to different industries, including oil and gas production, food processing, residential and industrial buildings, water supply, pulp and paper mills, pharmaceutical/medical manufacturing, and chemical manufacturing. Pipeline transportation plays a significant role in running the world economy, similar to the contribution of blood vessels in ensuring life. In this background, it is imperative to disseminate a comprehensive understanding of the fundamental and advanced knowledge in various disciplines of pipeline engineering. The successful design, construction, and operation of a pipeline require establishing a balance of production, cost, safety, and integrity. This book intends to provide the reader with a comprehensive overview of the current state-of-the-art in technology, networks, modeling, and management with a specific focus on the most important evidence-based developments in this important area. The exploration of the technological details would competently support the decision-making process.
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\n\t\t\t
1. Introduction
\n\t\t\t
Learning is the nature for human being. For example, a school-student learns a subject by doing exercise and home-work. Then, a school-teacher grades the school-student’s works. From this student and teacher interaction, the ability of the student mastering the subject is a feedback that the previous teaching method is successful or failure. As a result, the teacher will change the teaching method to improve the student ability for mastering the subject. This is a picture that the reinforcement learning (RL) agent learns the environment.
\n\t\t\t
Process control mainly focuses on controlling variable such as pressure, level, flow, temperature, pH, level in the process industries. However, the methodologies and principles are the same as in all control fields. The early successful application control strategy in process control is in evolution of the PID controller and Ziegler-Nichols tuning method (Ziegler and Nichols, 1942). Till nowadays, 95% of the controllers implemented in the process industries are PID-type (Chidambaram and See, 2002). However, as (i) the industrial demands (ii) the computational capabilities of controllers and (iii) complexity of systems under control increase, so the challenge is to implement advanced control algorithms.
\n\t\t\t
There have been commercial successes of the intelligent control methods, but the dominating controller in process industries is still by far the PID-controller (Chidambaram and See, 2002). This stands to the fact that a simple and general purpose automatic controller (for example PID) is demanded in process industries. Therefore, designing advanced controllers are to address the industrial user demand. This is the reason that a learning method called model-free learning control (MFLC) is introduced. The MFLC algorithm is based on a well known Q-learning algorithm (Watkins, 1989).
\n\t\t\t
Successful applications of RL are well documented in the recent literature, including learning to control mobile robots (Bucak and Zohdy, 2001), sustained inverted flight on an autonomous helicopter (Ng et al., 2004), and learning to minimize average wait time in elevators (Crites and Barto, 1996). However, only few articles can be found regarding RL applications for process control: multi-step actions based on RL was fruitfully applied for thermostat control (Schoknecht and Riedmiller, 2003), and one of the authors successfully applied RL for modeling for optimization in bath reactors by making the most effective use of cumulative data and an approximate model (Martinez, 2000). The reason for the difference between robotics and process control is possibly the nature of the control task in each field: typically in robotics the degrees of freedom for control are significantly high whereas in process plants are much more constrained. However with the shift from regulation to optimization and supervisory control the area is entering into a set of problems where RL can become the alternative choice.
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This chapter discusses novel, yet simple to implement learning system in process control based on RL algorithms. As the ability to store and process large amounts of data in computer’s memory and processor increases by time, this ability has made feasible the use of learning methods in systems for business, scientific and engineering, and medical decision-making. The proposed MFLC is mainly for nonlinear, complex, and time-varying chemical processes for which the development of a first-principles model is too costly in terms of time and money. The state-action space is defined using a symbolic representation and control incremental constraints. The state space is based on length errors of the system regarding a goal state. In this chapter, the MFLC approach is discussed for process control.
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This proposed technique is then tested on two laboratory plants: pH control and oxidation plants. Industrial pH control has received considerable attentions in literature (see Kalafatis et al., 2005 and references therein). However, as the inherent characteristics (time-varying, nonlinear and buffer capacity) of pH process dynamic are extremely difficult to model and predict in wastewater treatment plant, then a general purpose control strategy is a very challenging problem. As result most wastewater treatment plant uses on-off pH control.
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The issues are more complicated when oxidation reduction potential (ORP) is used to guarantee on-specification discharge by regulating the residence time. The ORP sensor measures the presence oxidizer or reducer in the solution and not the concentration of a given chemical species (McPherson, 1993). Many researchers find some processes are near optimal in certain ORP values (Peng et al., 2002; Baeza et al., 2000; Kwan, 2005). Clearly, it is a challenge to use ORP sensor for controlling the load to a wastewater oxidation process.
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This chapter is organized as follows: a MFLC algorithm for designing controller for chemical process control is given in section 2. In section 3, the application for a simulated buffer tank control is discussed. Laboratory online applications are discussed in section 4 for pH and ORP control processes.
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2. MFLC algorithms
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From the different proposed RL algorithms (Sutton and Barto, 1998), this paper proposes a Model-Free Learning Control (MFLC) where the basic Q-learning algorithm is combined with symbolic states which are frequently visited to address process control problems related to wastewater oxidation plants. The resulting value function, which is a mapping of history of visited states and executed actions to cumulative rewards, gives a clue for the learning controller to select an action in a given state. Through this function, the agent takes into account that taking an action in the current state will provide a given cumulative future reward derived from the control task at hand. This predicted value is used by the controller policy for selecting an action from those available in each visited symbolic state. This MFLC can be seen in Figure 1. The value of the reinforcement at each time reflects the control task objectives (Sutton and Barto, 1998), in process control problem it is proposed to involve control energy costs and error tolerance. The “situation” block is used to generate the symbolic state from plant readings and control task specification.
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Figure 1.
MFLC architecture based on Q-Learning
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A central part of RL algorithms is the estimation of the so-called Q-function, which gives the benefit of applying action a\n\t\t\t\t\n\t\t\t\t\tt\n\t\t\t\t when the system is in state s\n\t\t\t\tt. This function is denoted by Q(s\n\t\t\t\tt, a\n\t\t\t\tt). To learn this Q-function it is necessary to take into account the benefit now and in the future: when action a\n\t\t\t\tt has been selected and applied to the environment, the system moves to a new state, s\n\t\t\t\tt+1, and receives a reinforcement signal, r\n\t\t\t\tt+1; The value function for state-action pairs, Q(s\n\t\t\t\tt, a\n\t\t\t\tt), is updated by the basic learning rule:
\n\t\t\t\n\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\tA\n\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\t\ts\n\t\t\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\t\t\tt\n\t\t\t\t\t\t\t\t\t\t\t+\n\t\t\t\t\t\t\t\t\t\t\t1\n\t\t\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\n\t\t\t\t\n\t\t\tis the set of possible actions in the next symbolic state.
The learning rate, 0 1, is a tuning parameter, that can be used to optimize the speed of learning (Although too small learning rates might induce slow learning, while too large learning rates might induce oscillations).
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The discount factor, γ, is used to weight near term reinforcements more heavily than distant future reinforcements: If γ is small, the agent learns to behave only for short-term reward; the closer γ is to 1 the greater the weight assigned to long-term reinforcements.
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2.1. MFLC state-action space
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A central issue in Reinforcement Learning algorithms is the definition of the states. In MFLC the states are defined based on the control objective and control constraints, as follows:
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In a SISO implementation of the MFLC approach, the control task is defined as the ability to achieve and maintain a given process variable inside a specification band r-d and r+d, as shown in Figure 2. The width of this band is defined based on the tolerance of the system (which depends on measurement noise, disturbances and systems specification) and referred to as the goal band, and corresponds to the goal state, where the learning control system operates (it is now assumed, without loss of generality, that it is exactly in the middle of the working range).
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Figure 2.
Symbolic states definition in MFLC
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To describe the rest of the symbolic states, it is considered that the process may be in h states from the goal state to the maximum positive or negative error of the system, f (Selecting h is a trade-off: this number must be large enough to describe all the different behaviours of the process, but small enough to reduce learning time and the size of the Q-value matrix).
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If needed, the "length" of each state can be calculated as follows:
In MFLC, the control signal u\n\t\t\t\t\t\n\t\t\t\t\t\tt\n\t\t\t\t\t is calculated by varying the previous control signal in a magnitude calculated from the difference of the numerical values of the selected optimal action, a\n\t\t\t\t\t\n\t\t\t\t\t\tt\n\t\t\t\t\t, with respect to the wait action, a\n\t\t\t\t\t\n\t\t\t\t\t\tw\n\t\t\t\t\t (action corresponding to maintaining the previous control signal). That is,
This gives a PI-like structure, which simplifies initialization and tuning for the end user (k is the tuning parameter defining the aggresiviness of the controller). At each state there is only a finite set of possible actions (see Figure 3). These actions are selected based on the systems description: in particular from the limitations on the minimum and maximum variations of the control signal, as follows:
As expected, not all the actions may be available at each state: only a constrained set of the actions is available depending of the symbolic state, e.g. if the error is very small, the only actions available are those that correct a small error.
where is a parameter that gives the degree of overlapping with neighboring states (selected such that \n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\t\tN\n\t\t\t\t\t\t\t\t\t\ta\n\t\t\t\t\t\t\t\t\t\ts\n\t\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\tis integer. Then, the available actions for every state ranges from \n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\t\ta\n\t\t\t\t\t\t\t\t\t\tp\n\t\t\t\t\t\t\t\t\t\tj\n\t\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\tto\n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\t\ta\n\t\t\t\t\t\t\t\t\t\tb\n\t\t\t\t\t\t\t\t\t\tj\n\t\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t (except in the goal state, where only the wait action can be selected). The idea is presented in Figure 3. Those available actions can be calculated as
So far, the SISO implementation has been presented. For MIMO system the simplest methodology would be used several learning controllers that interact between them.
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Next section discusses the application of the proposed MFLC for a buffer tank control. The application is to maintain smoothly the out flow of the tank and to keep the level of the tank to avoid overflow and empty.
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3. Buffer tank control
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Buffer tanks are very common in the process industry to alleviate the impact downstream of disturbances in temperature, concentration, and flow rate in important process streams (Faanes and Skogestad, 2003). In industry, buffer tanks are known under many different names, such as intermediate storage vessels, hold up tanks, surge drums, accumulators, inventories, mixing tanks, continuous stirred tank reactors (CSTR), and neutralization vessels. Typically, the buffer tank shown in Figure 4 is subject to significant and unsystematic variations in its inflow rate. For example, if the downstream is fed to a heater, fast changes in its feed give temperature variations which affect the rest of the process. Also, a buffer tank is often installed to avoid propagation of disturbances from batch operations to continuous processes. Furthermore, a buffer tank is also installed between operation units to allow a more flexible operation. Therefore, the task of controlling a buffer tank is such that the outflow rate must be changed smoothly despite significant variations in its incoming flow rate. To avoid overflow and empty, the level in the tank needs to be constantly varied within its operation minimum and maximum limits. However, the tank has a limited capacity that should be used appropriately. Thus, keeping the tank level in limitation is also an important component of the control task to be learnt.
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These tanks are usually used as examples to check novel control algorithms, as they are simple to understand and easy to reproduce. For example, a neuro-fuzzy controller is proposed by Tani et al. (1996) for controlling a buffer tank using a predictive inductive model (neural network) and fuzzy decision rules.
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Figure 4.
Buffer tank
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A very simple approach to control a buffer tanks using the proposed MFLC is now presented. For designing controller using MFLC, the designer should define how big the Q-table and reward function can be. The learner will interact online with the environment and learn providing best actions to fulfil the requirement. Once the learner’s parameters are defined, they can be used for other similar processes.
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3.1. Problem definition
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The tank has A=100 cm2 and a level constrain 0<h<50 cm. Clearly, the learning system is allowed to variate the level of the tank within its minimum and maximum capacity. Another limitation is that the controller can only manipulate the valve opening in the range 0u100%. The learning controller must comply these limitations: The agent will be punished if it generates an action that causes the system to be outside this limitation.
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The main objective of the proposed MFLC is to bring the outflow inside the goal band; the process responses are allowed to ocsillate within the band. Therefore, in the case of the buffer tank control, the goal band is selected to outflow within ± 2% error of the desired outflow (reference). On the other hand, the system allows the level to vary 60% from the head of the tank: The remaining 40% is for safety.
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3.2. Design parameters
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In this example, the goal band is defined as ± 1 l/m from the reference. Let reference, r see Figure 2, be 50 l/m and therefore, the parameter d is 1 and f is 5 l/m. The agent also has limitation 0.1u0.3 in the variation of the manipulated variable with regard to the previous control signal. The gain controller, k, is introduced to be 110-4. By taking = 1.5, therefore, there are 600 available actions in every symbolic state. For each available action, the controller will receive a positive reward (see equation 13) if the next response is inside the goal band. Meanwhile, if the next response is reaching the lower and upper bound output constrains, the selected action is punished. If the next state is not in the goal state, the selection of the action will also be negatively rewarded. That is :
The discounted factor, , is set to 0.9 while the learning rate, , is set to a value of 0.1. The policy for selecting an action is -greedy policy, with = 0.1. The probability for selecting an optimal action from those available in each state is 90%.
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3.3. Simulation results and discussion
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The inflow rate into a simulated buffer tank is introduced as in Figure 5 (a), which is a sinusoidal signal with amplitude 20, from an average value of 50 l/m. The level evolution can be seen in Figure 5(b). The control signal, which is the opening of the out-flow valve, is shown in Figure 5 (c). Clearly, the controller opens the valve widely when the system observes that the level of the tank is lower; otherwise, the opening of the valve is reduced when the level of the tank is high to maintain outflow as constant as possible. As a result, the outflow of the system remains in the defined goal band; as shown in Figure 5 (d). The noise observes in outflow is because the agent has finite-discrete action space. Thus, the controller objectives are fulfilled: the controller is capable to learn to avoid abrupt changes in the out flow.
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Next section discusses the online laboratory application of the proposed MFLC to control pH and oxidation processes.
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Figure 5.
Incoming and outcoming signal for learning to control buffer tank; (a) inflow signal, (b) liquid level in the tank, and (c) output manipulation flow.
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4. Online laboratory assessment
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The proposed algorithm has been tested for a view towards real-world applications in the laboratory plants. The first application is for controlling a pH process during wastewater treatment, which is known as a representative example of highly nonlinear, time-varying and difficult to model process plant, mainly resulting from interactions between many different chemical species. Thus, this pH process is very difficult to control using standard control techniques. Secondly, the MFLC algorithm is tested to control oxidation processes at certain ORP values corresponding to on-specification discharge.
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4.1. pH control
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pH control in neutralization process is a ubiquitous problem encountered many process control industry (see Kalafatis et al., 2005 and references therein). For example, the pH value is controlled in chemical processes such as fermentation, precipitation, oxidation, flotation and solvent extraction process. Also, control of pH in food and beverage production (such as in bread, liquor, beer, soy sauce, cheese, and milk production) is an important issue because the enzymatic reactions are affected by the pH value of the process and each has its an optimum pH which is critical to the yield. Other parameters involved in controlling pH process are chemical equilibrium, kinetic, thermodynamic and mixing problems. Considering all these influencing factors in controller design is an overwhelming task. On the other hand, the process buffer capacity varies with time, which is unknown and dramatically changes process gain. This can be understood as, for example, if either the concentration in the inlet flow or the composition of the feed changes, the shape of the titration curve will be drastically altered. This means that the process nonlinearity becomes time dependent and the system moves among several titration curves. Other characteristics include the dissociation of weak acids and bases or their salts involved in the solution determine the number of hydrogen ions. All weak species have the property, called buffering, to resist change in pH. A weak acid, for example, is not completely dissociated, so it can absorb hydrogen ion by converting them to undissociated acid molecules. Also, due to the nonlinear dependence of the pH value on the amount of titrated reactant the process will be inherently nonlinear. Therefore, it is difficult to develop a sound mathematical model of the pH process for designing a proper controller.
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Many researchers proposed control strategies based on the titration curve (see Wright and Kravaris, 1991 and references therein). Wiener models are used for controller design by Kalafatis et al. (2005). These types of controllers are difficult to implement due to the complexity of the resulting control structures. Also, the designed controller is not a general purpose one, namely as the acid-base system change, the controller needs to be redesigned.
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Intelligent controllers have been proposed by some researchers as alternative strategies, applying fuzzy control, neural networks or different combination of intelligent and model-based methods (Edgar and Postlethwaite, 2000; Krishnapura and Jutan, 2000; Mwembeshi et al., 2004; Fuente et al., 2006). As discussed in these cited references, tight and robust pH control are often difficult to achieve due to the inherent uncertain, nonlinear and time varying characteristics of pH neutralization processes. Also, the controller needs a huge number training examples in order to guarantee stability and performance.
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In this section, the MFLC design strategy is assessed experimentally. The experimental setup consists of a CSTR (Figure 6) where a process stream (sodium acetate) is titrated with a solution of hydrochloric acid (HCl) to maintain at a certain pH value outflow stream. The solution of process stream is prepared for various concentration levels. However, the titrating stream is prepared using 1% concentration. To have the desirable outflow pH level, the controller manipulates titrating flow into the CSTR and it is assumed that the mixing in the tank is homogeneous; therefore, the concentration in the effluent stream is similar to the concentration in the reactor.
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The control variable u\n\t\t\t\t\t\tt\n\t\t\t\t\t is the flowrate of the titrating stream (normalized to the maximum value), which is applied using a peristaltic pump (ISMATEC MS-1 REGLO/6-160).
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The output variable, y\n\t\t\t\t\t\tt\n\t\t\t\t\t, is the logarithmic hydrogen ion concentration (pH) in the reactor. The pH value in the mixture is measured using an Ag-AgCl electrode (Crison 52-00) and transmitted using a pH-meter (Kent EIL9143). The electrode dynamic response presents appreciable and asymmetric inertia. The pH measured and the control signals are transmitted through an A/D interface (ComputerBoards CIO-AD16, 0-5V). The plant is controlled and monitored with a standard PC, using Matlab and the Real-Time Toolbox for online control.
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Figure 6.
Typical pH neutralization process plant.
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The pH plant shown in Figure 6 is a typical laboratory set-up existing in the Department of Systems Engineering, University of Valladolid. The neutralization reactor is to overflow, hence the volume of liquid in the tank is constant (1 litter).
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Parameters
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The control objective is to bring the pH being inside a goal band with d=0.1, selected based on the level of measurement noise and the desired operating range of pH. The controller gain, k, is selected to be 210-5 and incremental control is defined as -4.2 10-4<u<4.210-4. There are 5 available states for negative or positive error. Therefore, there are 11 states. Every state has 5 available actions, except in goal state which only requires the wait action. Action 22 is the wait action.
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In all the experiments the discounted factor, , is set to a value of 0.98 and the learning rate, , is set 0.1. The Q-value matrix is initialized using zero entries. At every time step, the selected action is based on an -greedy policy, with =0.1, to leave enough room for the learning controller to explore state and actions. Rewards are defined using the simple assignment function
Many experiments were carried out in the laboratory plant with different conditions, and with small variations in the algorithms and tuning parameters. For most cases, the application of the proposed MFLC controller to the laboratory plant showed good responses. Some responses of the plant for some changes in setpoint, compared with the responses for a PID in similar conditions can be seen in Figure 7 for the sodium acetate – hydrochloride acid system. The PID controller was tuned based on operating conditions at pH=5, where correction and proportional gains are chosen to be 0.01 and 0.001, respectively, whereas derivative and integral times are selected to be 1.
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The comparison shows that the responses of the proposed MFLC algorithm settle in the reference faster than the PID controller, when a similar time is spent for the parameters: PID gives higher peaks and some oscillations due to variations from the nominal conditions.
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Figure 7.
Output responses of the plant for NaCH3COO-HCl.
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Figure 8.
Control signals for NaCH3COO-HCl.
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Also the MFLC controller manipulates the actuator in a smoother than the one given by the PID controller (see Figure 8). Since MFLC allows a tolerance error of the process whenever the pH is within the control band, the control signal is very smooth when the pH is closer or within the control band, even if some exploration is carried out. The detailed discussion of the application MFLC to pH control is given in Syafiie et al. (2007a).
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4.2. ORP control in Fenton’s oxidation processes
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Nowadays a central issue in the treatment of industrial wastewaters is the elimination of certain organic pollutants, which are very harmful to health even in small concentrations. Some of them are phenols, which are usually efficiently and economically eliminated through oxidation using Fenton’s reagent. This Fenton’s reagent refers to iron-mediated hydroxyl (●OH) production by hydrogen peroxide (H2O2).
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The main issue is maintaining adequate values of hydroxil concentrations despite the huge number of chemical reactions involved (Laat and Gallard, 1999; Kwan, 2003). Unfortunately, it is very difficult to develop a sound mathematical model of the Fenton’s oxidation processes for control purposes. Some reactions are slow rate and others are relative fast, but refractory intermediate act as a bottleneck for the complete oxidation. Also, as the process is used to decompose organic compounds, many parallel reactions are involved. For more detailed discussion, see Syafiie et al. (2007b).
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Moreover, even if a detailed mathematical model were available (possible involving dozens of chemical reactions), it would be useless for real-time control, as it is not possible to measure in real-time the concentration of specific components (OH, Fe3+, Fe2+, etc): the only available sensors are pH (to measure H+ concentration) and ORP sensors to estimate the oxidizers activity (where ORP stands for oxidation-reduction potential). When using ORP for process control, it means that it is the present of the oxidizer or reducer that is being monitored, and not the chemical it is reacting with (McPherson, 1993). Thus, non-model based algorithms based on Reinforcement Learning ideas, such as the proposed MFLC algorithm would be very adequate to control this process.
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A schematic of the experimental setup used to test the proposed algorithm is shown in Figure 9: For elimination of phenols, it is known that the oxidation reaction for phenol breakdown operates optimally on 550 to 600 mV of ORP value (Kwan, 2003), so the setpoint of the first MFLC agent is set to 570mV. It is also known that Fenton\'s reaction must be conducted on the range of temperatures between 80 to 90 oC, which is regulated using a simple thermostat, to represent industrial practice. Also, level in the buffer tank is not controlled to represent industrial practice, although there are detectors for low and high values. The reaction occurs on pH values between 3 and 5, so in the pretreatment the wastewater is titrated with hydrochloride acid.
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The final part of the process is based on regulating pH to neutralize the drain (It would be dangerous for environment if the drain is released without neutralizing the pH). Therefore,. This neutralization is based on titrating the acidy stream (drain) with the base titrating flow (NaOH) to have pH around 7. Controlling pH of this strong acid-strong base system is known very difficult because the process is extremely nonlinear around the neutral pH, so it will be controlled using a second MFLC agent, designed following the methodology shown in previous section, coordinating with the first one.
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Figure 9.
Wastewater oxidation at a laboratory pilot plant
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In summary, the first agent in order to handle the oxidation process receives reading of the process variables: apart from ORP value in buffer tank, temperature of inlet stream, and level and temperature in buffer tank. From this information, the agent learns to perform actions to control the oxidation process using the MFLC algorithm. For start-up of the process, first the wastewater is pretreated by heating and pH regulation. Once the temperature of the process stream reaches 80ºC, the first agent starts the process (turn on the pump 2) and starts manipulating the Fenton’s reagent coming into the buffer tank (pump 3) to learn to handle the oxidation process.
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a)Parameters
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In this section, the selection of parameters for the MFLC agent that controls the oxidation process is discussed. The values of discounted factor γ=0.98 and learning rate α=0.1 from the previous study for pH control are maintain as the dynamics are similar. An ε-greedy policy is used, with parameter ε=0.1, to leave space for the agent to explore. To allow for sensor noise, the process goal is defined to be that the controller tolerates only d=5mV deviations from the setpoint r. In normal operation, states are defined for at most 100 mVolt for positive and negative error: thus, there are 41 states. The gain, k, is chosen to be 110-5: Thus, every state has 20 available actions. The reinforcement signal is simple defined to be:
The second agent, that controls the neutralization process, is the same as in the previous section, except that the controller gain is selected smaller, k = 510-7, because the process has higher gain.
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b)Online Experimental Results and Discussion
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Different experiments were carried out in the laboratory plant using the proposed MFLC agent. Some experiments are now shown for 1000 ppm phenol concentration, 10% FeSO4, 1% NaOH, 1% HCl and 30% H2O2\n\t\t\t\t
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Figure 10.
Oxidation control; (a) measured output, and (b) control signal
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One typical response of the phenol decomposition process, controlled by the proposed MFLC agent, after learning, can be seen in Figure 10 (a): it can be seen that the MFLC controller maintains the oxidation process around the desired ORP level. This is carried out despite the complex dynamics of the system; During the first 1000 seconds, the process responses was reaching fast the reference, but then the process responses went down (until around 3000 seconds), because of the sequence of slow reactions that consumed both oxidizer and catalyst. After the balancing reaction are reached, then the responses of the process slowly returns to the goal band by increasing the control signal (see Figure 10, b). Thus, the responses of the process are most of time being on the optimal range of the reaction (550 to 600 mV), so phenols are correctly oxidized.
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At the same time, the second agent manages the pH of the process on neutral range before it is discharged to environment. The responses of the neutralization process are plotted on Figure 11 (a). The second agents learns to manipulate the process to maintain it within the goal band, although there are some oscillations around the setpoint, as this is known to be a highly nonlinear process and the inlet composition changes with time, depending on the reactions in the buffer tank. The control signals (Figure 11, b) show that the agent actively manipulates the control signal when the process is outside the goal band.
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Figure 11.
pH process control; (a) measured output, and (b) control signal
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5. Conclusion
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This chapter has presented a proposal to apply RL algorithms for process control problems. This proposal (called MFLC algorithm) is based on the well known Q-learning algorithm, using an specific definition of symbolic states based on specifying tolerances on the outputs and constraints on the control and its variation. Also, the propose approach uses few and simple tuning parameters to simplify the presentation of these techniques to plant operators. The technique has been presented on a simple example (buffer tank) to present the ideas behind the algorithm (in particular, the parameter selection issue) and then some experimental results in wastewater control problems have been presented to show the applicability of the proposed ideas. It is shown that the control objectives are fulfilled by the proposed MFLC agents, with smooth manipulated variables. Thus, the proposed MFLC technique is promising for increasing the degree and type of automation that can be effectively used in process control.
\n\t\t
\n\t\n',keywords:null,chapterPDFUrl:"https://cdn.intechopen.com/pdfs/685.pdf",chapterXML:"https://mts.intechopen.com/source/xml/685.xml",downloadPdfUrl:"/chapter/pdf-download/685",previewPdfUrl:"/chapter/pdf-preview/685",totalDownloads:5204,totalViews:381,totalCrossrefCites:1,totalDimensionsCites:4,totalAltmetricsMentions:0,introChapter:null,impactScore:1,impactScorePercentile:55,impactScoreQuartile:3,hasAltmetrics:0,dateSubmitted:null,dateReviewed:null,datePrePublished:null,datePublished:"January 1st 2008",dateFinished:null,readingETA:"0",abstract:null,reviewType:"peer-reviewed",bibtexUrl:"/chapter/bibtex/685",risUrl:"/chapter/ris/685",book:{id:"2220",slug:"reinforcement_learning"},signatures:"S. Syafiie, F. Tadeo and E. Martinez",authors:null,sections:[{id:"sec_1",title:"1. Introduction",level:"1"},{id:"sec_2",title:"2. MFLC algorithms",level:"1"},{id:"sec_2_2",title:"2.1. MFLC state-action space",level:"2"},{id:"sec_4",title:"3. Buffer tank control",level:"1"},{id:"sec_4_2",title:"3.1. Problem definition",level:"2"},{id:"sec_5_2",title:"3.2. Design parameters",level:"2"},{id:"sec_6_2",title:"3.3. Simulation results and discussion",level:"2"},{id:"sec_8",title:"4. Online laboratory assessment ",level:"1"},{id:"sec_8_2",title:"4.1. pH control",level:"2"},{id:"sec_9_2",title:"4.2. ORP control in Fenton’s oxidation processes",level:"2"},{id:"sec_11",title:"5. Conclusion",level:"1"}],chapterReferences:[{id:"B1",body:'\n\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\tBaeza\n\t\t\t\t\t\t\tJ. A.\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\tFerreira\n\t\t\t\t\t\t\tE. 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Department of Systems Engineering and Automatic Control, University of Valladolid,, Spain,
Consejo Nacional de Investigaciones Científicas y Técnicas,, Argentina.
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1. Introduction
Epigenetics coined by Dr. Conrad H. Waddington is a branch of biology that studies the changes occurring in organisms resulting from changes in gene expression instead of the genetic sequence. Epigenetic mechanisms, some of which are reversible, can thus alter the phenotype without affecting the genotype. Epigenetic mechanisms regulate gene expression by affecting mainly the availability of the DNA for transcription by chemical modifications of the DNA base pairs without directly altering the DNA sequence, by affecting the architecture of the chromatin, and by the activity of non-coding RNAs. The DNA undergoes modifications such as methylation, whereas histones undergo modifications such as acetylation, phosphorylation, SUMOylation, ubiquitylation, etc. These modifications and other mechanisms govern the architecture of the chromatin. The architecture of chromatin determines which portion of the DNA can be expressed, and this depends on histones and non-histone chromatin-associated proteins such as the High mobility group (HMG) proteins [1]. Non-coding RNAs such as microRNAs (miRNAs), long non-coding RNAs, and small interfering RNAs have also been shown to affect epigenetic mechanisms [2, 3, 4]. In a genome, the collection of all the modifications that regulate gene expression is called its epigenome.
2. Factors affecting epigenetics
2.1 Histone modifications
2.1.1 Structure of chromatin
The negatively charged DNA, where the negative charge is due to the phosphate groups of its sugar-phosphate backbone, is electrostatically attracted to the positively charged lysine of the histone proteins. Two of each H2A, H2B, H3, and H4 histone proteins come together to form a histone octamer [5]. The DNA forms a complex with histone octamer to form a nucleosome. The nucleosome consists of about 146 base pairs of DNAs wrapped around the histone octamer in a superhelical fashion [6, 7]. Upon addition of H1 histone to the nucleosome, it forms a chromatosome, which consists of around 166 base pairs of DNAs wound around it. Two chromatosomes are connected by linker DNA [8]. The C-terminal domains of H2A and H2B, as well as the N-terminal domains of H2A, H2B, H3, and H4 extend from the globular nucleosome core and are called histone tails [9]. The region of chromatin where nucleosomes are densely packed is called heterochromatin. It is inaccessible to the transcription factors and polymerases and thus is a transcriptionally inactive region. However, the region of chromatin where nucleosomes are loosely packed is called euchromatin. The DNA in this region is accessible to the transcription factors and polymerases and thus it can be transcribed. Various modifications to the histone proteins allow the nucleosomes to be densely or loosely packed. These modifications shall be discussed below. There exist a variety of cross-talk among various modifications. This cross-talk is facilitated by “writers”, “readers”, and “erasers”. Writers are enzymes that add a modification to histones or DNA, similarly, erasers are enzymes that remove the modification. However, readers have a domain that recognizes and interprets the modified or unmodified site [10]. Histone modifications can be studied using chromatin immunoprecipitation assays (ChIP). In the presence of high-quality antibodies, ChIP assays can analyze even minute changes in histone modification and nucleosome structure [11]. Distribution and levels of endogenous histone H3 lysine modifications can be monitored using Fabs (fluorescently labeled specific antigen-binding fragments), without disturbing cell growth and embryo development [12].
2.1.2 Acetylation
Histone acetylation and deacetylation play a significant role in gene regulation. The N-terminal tail projecting from the histone core of the nucleosome contains positively charged lysine residues that undergo acetylation or deacetylation catalyzed by histone acetyltransferase (HAT) and histone deacetylase (HDAC), respectively. Acetylation removes the positive charges on histones, thus weakening the electrostatic attraction between histones and the phosphate-sugar backbone of the DNA, resulting in relaxed chromatin, which is associated with gene expression. Hence, histone acetylation is generally considered as an active histone marker. Generally, hyperacetylation leads to more relaxed chromatin whereas hypoacetylation leads to more condensed chromatin. Histone acetyltransferase CBP (cyclic-AMP response element-binding protein) acts in conjugation with p300, forming CBP/p300 complex, which is capable of recruiting other HATs, like PCAF (p300/CBP-associated factor) [13]. As many as 25 HATs have been identified so far and classified into five families—CBP/p300, SRC, MYST, TAFII250, and Gcn5-related N-acetyl-transferase. All HATs use acetyl-coenzyme A as an acetyl group donor [14]. Most active gene enhancers have been observed to show high levels of the H3K122ac mark (Table 1) [15].
Examples of HATs and their residues modified [15, 16, 17].
Humans show 18 HDACs, which are divided into four classes as shown in Table 2.
Class
Enzymes/Erasers
Properties
Class I (Rpd3-like proteins)
HDAC1 to 3 HDAC8
Catalyze zinc-dependent hydrolysis of acetylated histones
Class II (Hda1-like proteins)
HDAC4 to 7 HDAC9 HDAC10
Catalyze zinc-dependent hydrolysis of acetylated histones
Class III (Sir2-like proteins)
SIRT (sirtuins) 1 to 7
Utilize NAD+ during deacetylation to form nicotinamide and 2’-O-acetyl-ADP-ribose (metabolite)
Class IV
HDAC 11
Catalyze zinc-dependent hydrolysis of acetylated histones
Table 2.
Various classes of HDACs and their general properties [13].
2.1.3 Application of acetylation
Inactivation of CBP, such as through chromosomal translocation or bi-allelic mutations, has been observed to be correlated with oncogenic effects, observed to be involved in leukemia [18]. However, inhibition of CBP/p300 has shown antitumorigenic properties in regard to gastric cancers [19]. TATA-box binding protein associated factor 9 (TAF9) increases fatty acid β-oxidation and reduces lipid droplet accumulation is reportedly deacetylated by HDAC1, which regulates the capacity of TAF9 to mediate fatty acid β-oxidation and lipid droplet accumulation in nonalcoholic fatty liver disease (NAFLD) [20].
2.1.4 Methylation
Methylation of lysine residues of histone proteins (usually H3 and H4) is catalyzed by lysine methyltransferases (KMTs) and reversed by lysine demethylases (KDMs). This modification occurs post-transcriptionally. KDMs and KMTs also have shown roles in the regulation of the cell cycle [21]. In plants, DNA methylation tends to occur as a heritable epigenetic mark at the C-5 position of cytosine in the context of CG, CHG, and CHH (where H is A, C, or T) to form 5-methylcytosine.
2.1.4.1 Lysine methyltransferase (KMT)
Lysine methyltransferases (KMT) transfer a methyl group from S-adenosyl-L-methionine (SAM) onto the epsilon amino group of lysine residues of histone proteins. There are two classes of KMTs based on their catalytic domains: the SET domain-containing enzymes, and the one lacking SET domain. The latter is represented by KMT4, which is also known as Dot1L in humans. Both enzyme classes use S-adenosyl-L-methionine (SAM) as the methyl group donor [21]. The lysine of histone can be monomethylated, dimethylated, or trimethylated. For instance, trimethylated lysine 9 of histone H3 is represented as H3K9me3 and its monomethylated form is represented as H3K9me1.
2.1.4.2 Lysine demethylase (KDM)
Lysine demethylases remove the methyl group from the methylated epsilon amino group of lysine residues of histone proteins. KDM1A (also known as LSD1)—the first demethylase to be discovered—contains a flavin adenine dinucleotide-dependent monoamine oxidase domain that has been known to catalyze the demethylation of H3K4me2 and H3K4me1. Another class of KDMs employs jumonji (jmj) C domain to catalyze demethylation by oxidizing methyl groups. The cofactors of JmjC proteins are alpha-ketoglutarate, molecular oxygen, and Fe (II) [22]. Formaldehyde is one of the products of demethylase reactions (Table 3) [26].
Nature of methylase
Enzyme(s)/Writer(s)
Histone residue(s)
Mono-demethylases
KDM1B
H3K4
Di-demethylases
KDM8
H3K36
Tri-demethylases
KDM5A
H3K4
Table 3.
Examples of demethylases with their target histone residues [23, 24, 25].
2.1.5 Phosphorylation
Histone phosphorylation is a posttranslational modification instigated by DNA damage, entry into mitosis, or extracellular signals. It can trigger the binding of reader proteins and change the affinity of reader or writer proteins of other histone modifications [27]. Serine (S), threonine (T), and tyrosine (Y) are the sites of phosphorylation on histones. The mammalian 14–3-3 family of readers of the H3S10ph mark is composed of seven members that have been demonstrated to show interaction with around 700 different factors [28], including many chromatin-modifying proteins and transcriptional regulators, for instance, p53 [29]. 14–3-3 show increased affinity for the H3S10ph mark when the nearby lysine residues K9 or K14 are acetylated [30]. H3S10 is phosphorylated during mitosis by the action of Aurora B kinase, where data has suggested that this phosphorylation may function by displacing HP1 (Heterochromatin protein 1) from H3K9me, which otherwise plays a role in the compaction of chromatin. H3T3 phosphorylation catalyzed by Haspin kinase is required for appropriate metaphase chromosome alignment [31] (Table 4).
Histone residue (phosphorylated)
Kinase(s)/Writers
Function(s) of the phosphorylation mark
H1T18ph,
CDK2
—
H2AS1ph
Ribosomal protein S6 kinase alpha-5
Transcription inhibition.
H2AT119ph
NHK-1, Aurora B
Mitotic regulation of chromatin structure and function.
H2BS32ph
Protein kinase C (PKC)
Probable role in apoptosis-related nucleosomal DNA fragmentation.
H2BS36ph
AMPK
Direct transcriptional and chromatin regulatory pathways resulting in cellular response to stress.
H3T3ph
Haspin
Proper localization of chromosomal passenger complex (CPC) at centromere.
H3T11ph
Death associated protein-like kinase (Dlk)
Regulation of kinetochore assembly (during prophase to early anaphase) [34].
H3T6ph
PKC beta 1
Hormone dependent gene activation: Phosphorylation-dependent on androgen prevents LSD1-mediated H3K4demethylation.
H3S10ph
Aurora B
Dissociates HP1 from chromatin and prevents formation of condensed heterochromatin. Assists in condensation during cell-division; involved in transcription of certain genes.
H3T41ph
JAK2
Involved in hematopoietic differentiation.
H3T45ph
Protein kinase -C, S-phase kinase Cdc7-Dbf4
DNA replication, apoptosis, function in DNA damaged cells when DNA is nicked.
H3Y41ph
Tyrosine-protein kinase JAK2
H4S1
CK II
Repair of DNA damage, chromatin assembly, and mitosis.
H4H18 & H4H75
Unknown
Destabilization of histone octamer to facilitate DNA replication.
Table 4.
Some mammalian histone sites of phosphorylation [32, 33].
2.1.6 SUMOylation
Chromatin structure and gene expression are also regulated by small ubiquitin-like modifier (SUMO) conjugation. Along with altering substrate-protein or substrate-DNA interactions, SUMO can also block ubiquitin attachment sites [35]. The reversible attachment of mature SUMO proteins to the lysine (K) side chains of substrate proteins are regulated by an enzyme pathway analogous to the ubiquitin pathway. SUMO is expressed in all eukaryotes and is evolutionarily conserved. Humans express five SUMO paralogs, SUMO-1, −2, −3, −4 and − 5. Saccharomyces cerevisiae expresses only one SUMO ortholog—Smt3, which is similar to human SUMO-1.H4K12 in humans undergoes SUMOylation, which results in the recruitment of HDAC1 and heterochromatin protein 1 (HP1) – affecting transcription. The C-terminal of SUMO undergoes activation by Aos1/Uba2 SUMO-activating enzyme (E1), post which, it is transferred to the Ubc9 SUMO-conjugating enzyme (E2). SUMO ligase (E3) often aids in ligating SUMO to one or more lysine residues of the substrate. This modification is reversible by the action of SUMO proteases [36]. Unlike the initial idea of SUMOylation exclusively affecting transcription negatively, recent studies have shown that histones of many active genes are SUMOylated. Therefore, SUMO conjugation can have either negative or positive effects on transcription [37, 38].
2.1.7 Ubiquitination
Ubiquitination is the reversible process of transfer of ubiquitin to the histone core proteins (H2A, H2B, H3, H4). It is also known as ubiquitylation. Histone ubiquitination is involved in nearly all DNA-related processes such as DNA replication, transcription, and repair. Ubiquitin moiety consists of the 76-amino acid polypeptide, and hence is a bulky modification. In humans, ubiquitination of histone mainly occurs on the H2AK119ub1 and H2BK120ub1 catalyzed by an isopeptide bond formation between the carboxy-terminal glycine of ubiquitin and the epsilon-group of a lysine residue on the carboxy-terminal tail of histones. Ubiquitin transfer is an ATP-dependent process. The first step is adenylation of the C terminus of ubiquitin catalyzed by E1. Two of the known human ubiquitin E1 enzymes are UBA1 and UBA6. It was observed that UBA1 associates with DNA break by interacting with poly-ADP ribosylated proteins [39]. UBA1 might be the preferred nuclear E1 [40]. E2 enzyme receives ubiquitin moiety from E1 enzyme and conjugates it to the respective substrate. It has been observed that in vitro, E2 is capable of E3-independent ubiquitination [41]. E3 ubiquitin ligase acts as a scaffold by positioning the E2-ub complex close to the target lysine. This target lysine is nucleophilic toward the C-terminus of ubiquitin, resulting in bond formation [40]. There are about 500–1000 E3 enzymes in humans [42]. The lysine can be both poly or monoubiquitinated. Polyubiquitylation is irreversible and a signal for proteasomal degradation, however, monoubiquitination results in a regulatory signal, which is reversible upon the action of deubiquitinating enzymes (DUBs), which are ubiquitin-specific proteases—USPs/UBPs. Although histone ubiquitination has largely been correlated with open chromatin and active genes, it can have an inactivating effect as well. Another instance of chromatin cross-talk can be observed in Ref. to histone ubiquitylation. H2A ubiquitylation mediated by PRC1 usually represses gene expression, on the other hand, H2B ubiquitylation can activate as well as repress gene expression. Ubiquitinated H2B is required for H3K4 methylation, however, H2A blocks it and thereby results in chromatin compaction.
2.2 DNA methylation
DNA methylation includes the addition of a methyl group to the DNA at the 5′ position of the pyrimidine ring of cytosine residues. This results in 5-methylcytosine (5mC). DNA methylation usually takes place on CpG dinucleotide sequence. The region of the genome where CpG residues are concentrated is known as a CpG island. CpG islands are located on more than half of human gene promoters. Most CpG dinucleotides are methylated [43] whereas most CpG islands are unmethylated, especially those located in the promoter region of transcriptionally active genes. These CpG islands, upon undergoing methylation can lead to gene silencing through various mechanisms such as inhibiting or promoting the recruitment of regulatory elements to their respective binding sites. Cancer cells usually show hypermethylated CpG islands causing the silencing of tumor suppressor genes. The role of 5-mC does not merely depend on its abundance but also on its genetic context or surroundings, and its location within the different regions of a gene. Non-CpG methylation can be found in a context where CHH or a CHG are present (H being T, A, or C), which is found in plants and embryonic stem cells. Other DNA methylations such as N6-methyladenine is being studied as potential epigenetic mark [44]. 5mC is converted to 5hmC (5-hydroxymethyl cytosine). This has been observed to be catalyzed by ten-eleven translocation family proteins [45]. DNA is methylated by the action of DNA methyltransferases (DNMTs), of which DNMT 1 is ubiquitously expressed. It uses S-Adenosyl-L-methionine as a methyl group donor. Cytosine methylation patterns are inherited through cell division. This involves DNMT 1 having hemimethylated CpG dinucleotide specificity. Hence, based on the presence of methylation on the CpG dinucleotide in the complementary template strand, DNMT 1 can methylate CpGs in the newly synthesized DNA strand [43]. Studying DNA methylation is centered on three major approaches: (i) bisulfite conversion-based, (ii) methylation-sensitive-enzyme-restriction based (MSRE), and (iii) affinity enrichment based. The methylation signal generated by these assays is then analyzed by either DNA hybridization or sequencing. Bisulfite converted DNA is most commonly analyzed by microarray or Next Generation Sequencing [46]. Various techniques are employed for DNA methylation profiling such as pyrosequencing, bisulfite-PCR, ChIP seq (Chromatin Immunoprecipitation), bisulfite seq, and specialized RNA seq. Illumina sequencing of total genomic DNA known as whole-genome bisulfite sequencing (WGBS), is a high-throughput for DNA methylation analysis [47]. Since bisulfite sequencing results in the alteration of unmethylated cytosine into uracil, which upon PCR amplification is replicated as adenine, bisulfite-free approaches have gained traction attributing to their noninterference with the DNA sequence. Several bisulfite-free methods for the detection of methylation have been developed recently, such as TAPS (TET-assisted pyridine borane sequencing) [48] and cfNOMe (cell-free DNA-based Nucleosome Occupancy and Methylation profiling) [49]. Some key factors to be considered when choosing a method for DNA methylation analysis have been comprehensively reviewed in [50]. Additionally, in a recent study, it has been shown that minor experimental variations can significantly impact epigenome outcome measures and data interpretation [51].
DNA methylation is capable of altering chromatin structure and by extension gene expression. Histone modifications, transcription factors, ncRNAs, etc. in concert with DNA methylation affect chromatin and regulate gene expression [52].
3. Effect of epigenetics on health
Although plants and mammals have significant morphological dissimilarities and a long evolutionary history, the similarities on a fundamental level are striking. Epigenetic mechanisms discovered in mammals or plants are mostly relevant to both [53]. Nutrition and environment play a crucial role in the development of phenotypic characters, from prenatal development to later on in life. The most widely studied effect of epigenetics on health is in terms of cancer biomarkers that are studied in the form of DNA methylation. However, epigenetics has a broader impact on health. Epigenetics also play a major role in plant growth, development, and reproduction, especially in plant breeding. Epigenetics of human health has gained traction in complex disorders such as allergies, autoimmune diseases, memory, cancer, behavior plasticity, and psychological and neurodegenerative disorders. Some epigenetic marks can be reversible, and this has funneled researchers’ interest in epigenetic therapy. Epidrugs are drugs that target epigenetic marks responsible for epigenetic alterations. An example of these is histone deacetylase inhibitors [54]. Histone deacetylase inhibitors are being used as cancer therapeutic agents, all while some have received U.S. F.D.A. approval for treatment of multiple myeloma, cutaneous and peripheral T-cell lymphoma. Additionally, HDAC inhibitors are being used as antifibrotic, anti-inflammatory, and antidiabetic agents.
3.1 Effects of epigenetics on human health
Epigenetics play a significant role in various diseases such as cancers, autoimmune diseases, neurodegenerative diseases, congenital diseases, etc. HATs and HDACs modulate the transcriptional activity of nuclear factor-κB that results in downstream inflammatory gene expression levels that have been identified in the regulation of several diabetic key genes [55]. Cancer cells usually show hypermethylated CpG islands preceding promoters, and this leads to the silencing of tumor suppressor genes. This silencing allows cells to grow rapidly, leading to tumorigenesis. Imprinting, in genetics, delineates a condition where one of the two alleles for a gene pair is not expressed due to certain epigenetic modifications. This can lead to complications if the expressed allele is impaired, causing phenotypes such as susceptibility to certain microbes or chemical substances. Compared to healthy cells, malignant cells show decreased monoacetylated (H4ac) and trimethylated form of H4 (H4me3) [56]. DNA methylation patterns show a change in response to inherited genetic polymorphisms, exposures to environmental chemicals, and diet [57, 58, 59]. Histone acetylase inhibitors are a class of epidrugs. An epidrug Panobinostat, a non-selective histone deacetylase inhibitor, has been approved by the U.S. F.D.A. for the treatment of multiple myeloma [60].
Nutrition, being one of the most studied factors, has been understood to play an important role in epigenetics. Adverse antenatal nutritive conditions and postnatal health all have been observed to be correlated. Nutrients can either act directly by inhibiting epigenetic enzymes such as DNMT, HDAC, or by altering the substrate availability necessary for those enzymatic functions. Low dietary levels of folate, methionine, or selenium (all involved in methyl group donation or transfer) can lead to hypomethylation, which has been observed in neural tube defects, atherosclerosis, and cancer [61, 62, 63, 64, 65]. It has been observed that prenatal as well as early postnatal stress exposure have impacts on disease susceptibility [66]. DNA hypomethylation and histone acetylation are involved in the induction of gamma-globin expression [67]. A clinical trial is underway that deals with the down-regulation of BCL11A gene, which suppresses the production of fetal hemoglobin (HbF), resulting in an increase in the level of HbF, which has been shown to be therapeutic in patients with beta-hemoglobinopathies [68].
Endocrine Disrupting Chemicals (EDC), man-made chemicals known to alter endocrine functioning, that has been correlated with lower birth weight in children induce Adipogenesis. The epigenome is susceptible to the generation of new phenotypes in response to changes in environmental stimuli (Tables 5 and 6).
Year
Name of the scientist(s)
Conclusions drawn/discoveries made
1996
Korenke et al.
Studied monozygotic identical twin for x-linked adrenoleukodystrophy (ALD) gene and concluded that some non-genetic factors might be responsible for the difference in ALD phenotype. [69]
2005
Fraga, M. et al.
Epigenetic variations arise during the lifetime of monozygotic twins. [70]
Table 5.
A few twin studies that led to the foundation of twin studies in epigenetics [69, 70].
Genes/diseases/disorders
Epigenetic observation
Note
Diabetes
HATs & HDACs modulate transcriptional activity of nuclear factor-Κb.
Show downstream inflammatory gene expression levels identified in the regulation of diabetic key genes.
Cancer
Hypermethylated CpG islands preceding promoters.
Leads to the silencing of tumor-suppressing genes and hence tumorigenesis.
Cancer
Decreased acetylation at H4ac and decreased methylation at H4me3.
Caused due to Low dietary levels of folate, methionine, or selenium (all involved in methyl group donation or transfer) [61, 62, 63, 64, 65]
Immunity
Alterations in levels of acetylation and methylation.
Required to alter DNA accessibility to allow recombination for antigen specific responses. [71]
Endocrine Disrupting Chemicals (EDC) that have been correlated with lower birth weight in children induce Adipogenesis
DNA methylation variance was also observed along with adipogenesis in human. Mesenchymal stem cells [72] exposed to EDC.
Table 6.
Summary of effects of epigenetics on human health from the text [56, 61, 62, 63, 64, 65, 71].
3.2 Effects of epigenetics on plant health
Epigenetic change of plant genomes resembles that of mammals in that there is an analogous profile of histone marks and the DNA can be methylated at cytosine residues. Still, plant epigenomes are more susceptible to environmental influence than those in animals. Transgenerational epigenetic inheritance has a requirement that the epigenetic marks can be passed to the progeny. The variation in methylation of the same gene among different plants is known as epialleles [73]. Stable and heritable stress-induced modifications that cannot be reversed are being referred to as the epigenetic “stress memory”. Epigenetic marks that are heritable may affect the inheritable phenotypic variation of plants, impacting fitness, and hence are subject to natural selection. However, unlike inheritable inheritance, the epigenetic changes show unstableness and are affected by the climate [74, 75]. DNA hypomethylation induced by pathogen infections acts as a part of plant defense response in many species including the model plant Arabidopsis thaliana (Tables 7 and 8) [76].
Epigenetic observation
Note
DNA hypomethylation induced by pathogens infections
Part of plant defense response.
Hypermethylated genome regions in Arabidopsis accession Columbia-0
Tend to preferentially occur in shoots than in roots. [77]
Table 7.
Few epigenetic observations and their role in plant health [77].
Scientists, Year
Observed effect
Probable Cause
Sano et al., 1990
Induction of dwarf plants in rice
Demethylation of rice genomic DNA
Burn et al., 1993
Induction of flowering initiation
Vernalization treatments cause a reduction of DNA methylation levels.
Table 8.
Few observations having underlying epigenetic mechanisms [78, 79].
4. Conclusion
Epigenetic mechanisms play a crucial role in the phenotype of an organism. Epigenetic mechanisms include DNA modifications such as methylation, histone modifications such as SUMOylation, methylation, acetylation, phosphorylation, etc.—and action of non-coding RNAs. Recent technological advancements have made and will progressively make studying such modifications easier, more accurate, and cost-effective. Studying epigenetic modifications has provided insights into the inter-individual differences that genetics alone could not account for. Many phenotypes and diseases in humans and plants show underlying epigenetic marks at play from early on in the life of the organism, and some conditions or diseases can even manifest later on in life depending on their nutrition and environment. Histone modification reactivates gamma-globin gene expression in adults. Down-regulation of gamma-globin suppressing genes, which suppresses the production of fetal hemoglobin (HbF), results in an increase in the level of HbF, which has been shown to be therapeutic in patients with beta-hemoglobinopathies. Histone deacetylases are being used to treat various diseases such as multiple myeloma, cutaneous and peripheral T-cell myeloma. Epigenetics can be used for selective breeding of crops with desirable traits. As more would be understood about the various regulatory pathways involved in epigenetic mechanisms and more epigenetic modifications, it could revolutionize human disease prevention.
Acknowledgments
The authors would like to thank Dr. B.A. Mehere, Principal, and Dr. Utpal Dongre, Head of the Department of Biochemistry and Biotechnology, Dr. Ambedkar College, Deekshabhoomi, Nagpur, India, for providing research space and facility.
Conflict of interest
The authors declare no conflict of interest.
Fundings
No fund was received for this work from any funding agencies.
Abbreviations
CBP
Cyclic-AMP response element-binding protein
CDK2
Cyclin-dependent kinase 2
cfNOMe
Cell-free DNA-based Nucleosome Occupancy and Methylation profiling
ChIP seq
Chromatin Immunoprecipitation
CPC
Chromosomal passenger complex
Dlk
Death associated protein-like kinase
DNMTs
DNA methyltransferases
DUBs
Deubiquitinating enzymes
HAT
Histone acetyltransferase
HbF
Fetal hemoglobin
HDAC
Histone deacetylase
HMG
High mobility group
HP1
Heterochromatin protein 1
jmj C
Jumonji
KDMs
Lysine demethylases
KMTs
Lysine methyltransferases
miRNAs
microRNAs
MSRE
Methylation-sensitive-enzyme-restriction based
NAFLD
Non-alcoholic fatty liver disease
ncRNAs
Non-coding RNAs
PCAF
p300/CBP-associated factor
PKC
Protein kinase C
SUMO
Small ubiquitin-like modifier
TAF9
TATA-box binding protein associated factor 9
TAPS
TET-assisted pyridine borane sequencing
USPs/UBPs
Ubiquitin specific proteases
WGBS
Whole-genome bisulfite sequencing
\n',keywords:"epigenetics, DNA methylation, histone modifications, phosphorylation, acetylation, ubiquitylation, SUMOylation, DNA methylation",chapterPDFUrl:"https://cdn.intechopen.com/pdfs/82388.pdf",chapterXML:"https://mts.intechopen.com/source/xml/82388.xml",downloadPdfUrl:"/chapter/pdf-download/82388",previewPdfUrl:"/chapter/pdf-preview/82388",totalDownloads:18,totalViews:0,totalCrossrefCites:0,dateSubmitted:"February 18th 2022",dateReviewed:"April 22nd 2022",datePrePublished:"July 13th 2022",datePublished:null,dateFinished:"June 25th 2022",readingETA:"0",abstract:"The mechanisms for epigenetic modifications include modification of histone proteins or modifications of the DNA itself (not affecting the DNA sequence). These include acetylation, methylation, phosphorylation, SUMOylation, ubiquitylation, etc. For example, DNA methylation (cytosine methylation) or histone acetylation (lysine acetylation). Recent studies have indicated that the activity of non-coding RNAs, such as microRNAs, long non-coding RNAs, and small interfering RNAs also affects epigenetic mechanisms. In a genome, the collection of all the modifications that regulate gene expression is called its epigenome. Improper occurrence of the epigenetic mechanisms can lead to deleterious health and behavioral effects. For instance, the most studied epigenetic modification is DNA hypermethylation, which leads to the silencing of antitumorigenic genes, and this has been shown to cause cancer. Various techniques are employed for DNA methylation profiling such as pyrosequencing, bisulfite-PCR, ChIP seq (Chromatin Immunoprecipitation), bisulfite seq, and specialized RNA seq. This chapter will introduce epigenetics, describe the different epigenetic mechanisms, and discuss in brief how to study these mechanisms and their effects on the plant as well as human health.",reviewType:"peer-reviewed",bibtexUrl:"/chapter/bibtex/82388",risUrl:"/chapter/ris/82388",signatures:"Jayisha Dhargawe, Rita Lakkakul and Pradip Hirapure",book:{id:"11098",type:"book",title:"Modifications of Biomolecules",subtitle:null,fullTitle:"Modifications of Biomolecules",slug:null,publishedDate:null,bookSignature:"Prof. Xianquan Zhan and Dr. Atena Jabbari",coverURL:"https://cdn.intechopen.com/books/images_new/11098.jpg",licenceType:"CC BY 3.0",editedByType:null,isbn:"978-1-80355-997-1",printIsbn:"978-1-80355-996-4",pdfIsbn:"978-1-80355-998-8",isAvailableForWebshopOrdering:!0,editors:[{id:"223233",title:"Prof.",name:"Xianquan",middleName:null,surname:"Zhan",slug:"xianquan-zhan",fullName:"Xianquan Zhan"}],productType:{id:"1",title:"Edited Volume",chapterContentType:"chapter",authoredCaption:"Edited by"}},authors:null,sections:[{id:"sec_1",title:"1. Introduction",level:"1"},{id:"sec_2",title:"2. Factors affecting epigenetics",level:"1"},{id:"sec_2_2",title:"2.1 Histone modifications",level:"2"},{id:"sec_2_3",title:"2.1.1 Structure of chromatin",level:"3"},{id:"sec_3_3",title:"Table 1.",level:"3"},{id:"sec_4_3",title:"2.1.3 Application of acetylation",level:"3"},{id:"sec_5_3",title:"Table 3.",level:"3"},{id:"sec_5_4",title:"2.1.4.1 Lysine methyltransferase (KMT)",level:"4"},{id:"sec_6_4",title:"Table 3.",level:"4"},{id:"sec_8_3",title:"Table 4.",level:"3"},{id:"sec_9_3",title:"2.1.6 SUMOylation",level:"3"},{id:"sec_10_3",title:"2.1.7 Ubiquitination",level:"3"},{id:"sec_12_2",title:"2.2 DNA methylation",level:"2"},{id:"sec_14",title:"3. Effect of epigenetics on health",level:"1"},{id:"sec_14_2",title:"3.1 Effects of epigenetics on human health",level:"2"},{id:"sec_15_2",title:"3.2 Effects of epigenetics on plant health",level:"2"},{id:"sec_17",title:"4. Conclusion",level:"1"},{id:"sec_18",title:"Acknowledgments",level:"1"},{id:"sec_21",title:"Conflict of interest",level:"1"},{id:"sec_18",title:"Fundings",level:"1"},{id:"sec_21",title:"Abbreviations",level:"1"}],chapterReferences:[{id:"B1",body:'Reeves R. Nuclear functions of the HMG proteins. Biochimica et Biophysica Acta (BBA)-Gene Regulatory Mechanisms. 2010;1799(1-2):3-14. DOI: 10.1016/j.bbagrm.2009.09.001'},{id:"B2",body:'Moutinho C, Esteller M. MicroRNAs and epigenetics. Advances in Cancer Research. 2017;1(135):189-220. DOI: 10.1016/bs.acr.2017.06.003'},{id:"B3",body:'Kazimierczyk M, Wrzesinski J. Long non-coding RNA epigenetics. International Journal of Molecular Sciences. 2021;22(11):6166. DOI: 10.3390/ijms22116166'},{id:"B4",body:'Xu W, Jiang X, Huang L. RNA interference technology. Comprehensive Biotechnology. 2019;560:560-575. DOI: 10.1016/B978-0-444-64046-8.00282-2'},{id:"B5",body:'Arents G, Burlingame RW, Wang BC, Love WE, Moudrianakis EN. 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Department of Biochemistry and Biotechnology, Dr. Ambedkar College, Nagpur, India
Department of Biochemistry and Biotechnology, Dr. Ambedkar College, Nagpur, India
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We believe financial barriers should not prevent researchers from publishing their findings. With the need to make scientific research more publicly available and support the benefits of Open Access, more and more institutions and funders are dedicating resources to assist faculty members and researchers cover Open Access Publishing Fees (OAPFs). In addition, IntechOpen provides several further options presented below, all of which are available to researchers, and could secure the financing of your Open Access publication.
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Paying the OAPF
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At IntechOpen, the majority of OAPFs are paid by an Author’s institution or funding agency - Institutions (73%) vs. Authors (23%).
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The first step in obtaining funds for your Open Access publication begins with your institution or library. IntechOpen’s publishing standards align with most institutional funding programs. Our advice is to petition your institution for help in financing your Open Access publication.
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However, as Open Access becomes a more commonly used publishing option for the dissemination of scientific and scholarly content, in addition to institutions, there are a growing number of funders who allow the use of grants for covering OA publication costs, or have established separate funds for the same purpose.
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Please consult our Open Access Funding page to explore some of these funding opportunities and learn more about how you could finance your IntechOpen publication. Keep in mind that this list is not definitive, and while we are constantly updating and informing our Authors of new funding opportunities, we recommend that you always check with your institution first.
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IntechOpen Waivers in Action
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For Authors who are unable to obtain funding from their institution or research funding bodies and still need help in covering publication costs, IntechOpen offers the possibility of applying for a Waiver.
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Our mission is to support Authors in publishing their research and making an impact within the scientific community. Currently, 14% of Authors receive full waivers and 6% receive partial waivers.
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While providing support and advice to all our international Authors, waiver priority will be given to those Authors who reside in countries that are classified by the World Bank as low-income economies. In this way, we can help ensure that the scientific work being carried out can make an impact within the worldwide scientific community, no matter where an Author might live.
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How to Apply for a Waiver
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The application process is open after your submitted manuscript has been accepted for publication. To apply, please fill out a Waiver Request Form and send it to your Author Service Manager. If you have an official letter from your university or institution showing that funds for your OA publication are unavailable, please attach that as well. The Waiver Request will normally be addressed within one week from the application date. All chapters that receive waivers or partial waivers will be designated as such online.
Feel free to contact us at funders@intechopen.com if you have any questions about Funding options or our Waiver program. If you have already begun the process and require further assistance, please contact your Author Service Manager, who is there to assist you!
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Note: All data represented above was collected by IntechOpen from 2013 to 2017.
At IntechOpen, the majority of OAPFs are paid by an Author’s institution or funding agency - Institutions (73%) vs. Authors (23%).
\n\n
The first step in obtaining funds for your Open Access publication begins with your institution or library. IntechOpen’s publishing standards align with most institutional funding programs. Our advice is to petition your institution for help in financing your Open Access publication.
\n\n
However, as Open Access becomes a more commonly used publishing option for the dissemination of scientific and scholarly content, in addition to institutions, there are a growing number of funders who allow the use of grants for covering OA publication costs, or have established separate funds for the same purpose.
\n\n
Please consult our Open Access Funding page to explore some of these funding opportunities and learn more about how you could finance your IntechOpen publication. Keep in mind that this list is not definitive, and while we are constantly updating and informing our Authors of new funding opportunities, we recommend that you always check with your institution first.
\n\n
IntechOpen Waivers in Action
\n\n
For Authors who are unable to obtain funding from their institution or research funding bodies and still need help in covering publication costs, IntechOpen offers the possibility of applying for a Waiver.
\n\n
Our mission is to support Authors in publishing their research and making an impact within the scientific community. Currently, 14% of Authors receive full waivers and 6% receive partial waivers.
\n\n
While providing support and advice to all our international Authors, waiver priority will be given to those Authors who reside in countries that are classified by the World Bank as low-income economies. In this way, we can help ensure that the scientific work being carried out can make an impact within the worldwide scientific community, no matter where an Author might live.
\n\n
How to Apply for a Waiver
\n\n
The application process is open after your submitted manuscript has been accepted for publication. To apply, please fill out a Waiver Request Form and send it to your Author Service Manager. If you have an official letter from your university or institution showing that funds for your OA publication are unavailable, please attach that as well. The Waiver Request will normally be addressed within one week from the application date. All chapters that receive waivers or partial waivers will be designated as such online.
Feel free to contact us at funders@intechopen.com if you have any questions about Funding options or our Waiver program. If you have already begun the process and require further assistance, please contact your Author Service Manager, who is there to assist you!
\n\n
Note: All data represented above was collected by IntechOpen from 2013 to 2017.
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Saxena",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bRET3QAO/Profile_Picture_2022-05-10T10:10:26.jpeg",institutionString:"King George's Medical University",institution:{name:"King George's Medical University",institutionURL:null,country:{name:"India"}}}],equalEditorOne:null,equalEditorTwo:null,equalEditorThree:null}]},subseriesFiltersForPublishedBooks:[{group:"subseries",caption:"Bacterial Infectious Diseases",value:3,count:2},{group:"subseries",caption:"Parasitic Infectious Diseases",value:5,count:4},{group:"subseries",caption:"Viral Infectious Diseases",value:6,count:7}],publicationYearFilters:[{group:"publicationYear",caption:"2022",value:2022,count:2},{group:"publicationYear",caption:"2021",value:2021,count:4},{group:"publicationYear",caption:"2020",value:2020,count:3},{group:"publicationYear",caption:"2019",value:2019,count:3},{group:"publicationYear",caption:"2018",value:2018,count:1}],authors:{paginationCount:189,paginationItems:[{id:"221831",title:"Prof.",name:"Niansheng",middleName:null,surname:"Tang",slug:"niansheng-tang",fullName:"Niansheng Tang",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/221831/images/system/221831.jpeg",biography:"Niansheng Tang is a Professor of Statistics and Dean of the School of Mathematics and Statistics, Yunnan University, China. He was elected a Yangtze River Scholars Distinguished Professor in 2013, a member of the International Statistical Institute (ISI) in 2016, a member of the board of the International Chinese Statistical Association (ICSA) in 2018, and a fellow of the Institute of Mathematical Statistics (IMS) in 2021. He received the ICSA Outstanding Service Award in 2018 and the National Science Foundation for Distinguished Young Scholars of China in 2012. He serves as a member of the editorial board of Statistics and Its Interface and Journal of Systems Science and Complexity. He is also a field editor for Communications in Mathematics and Statistics. His research interests include biostatistics, empirical likelihood, missing data analysis, variable selection, high-dimensional data analysis, Bayesian statistics, and data science. He has published more than 190 research papers and authored five books.",institutionString:"Yunnan University",institution:{name:"Yunnan University",country:{name:"China"}}},{id:"1177",title:"Prof.",name:"António",middleName:"J. R.",surname:"José Ribeiro Neves",slug:"antonio-jose-ribeiro-neves",fullName:"António José Ribeiro Neves",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/1177/images/system/1177.jpg",biography:"Prof. António J. R. Neves received a Ph.D. in Electrical Engineering from the University of Aveiro, Portugal, in 2007. Since 2002, he has been a researcher at the Institute of Electronics and Informatics Engineering of Aveiro. Since 2007, he has been an assistant professor in the Department of Electronics, Telecommunications, and Informatics, University of Aveiro. He is the director of the undergraduate course on Electrical and Computers Engineering and the vice-director of the master’s degree in Electronics and Telecommunications Engineering. He is an IEEE Senior Member and a member of several other research organizations worldwide. His main research interests are computer vision, intelligent systems, robotics, and image and video processing. He has participated in or coordinated several research projects and received more than thirty-five awards. He has 161 publications to his credit, including books, book chapters, journal articles, and conference papers. He has vast experience as a reviewer of several journals and conferences. As a professor, Dr. Neves has supervised several Ph.D. and master’s students and was involved in more than twenty-five different courses.",institutionString:null,institution:{name:"University of Aveiro",country:{name:"Portugal"}}},{id:"11317",title:"Dr.",name:"Francisco",middleName:null,surname:"Javier Gallegos-Funes",slug:"francisco-javier-gallegos-funes",fullName:"Francisco Javier Gallegos-Funes",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/11317/images/system/11317.png",biography:"Francisco J. Gallegos-Funes received his Ph.D. in Communications and Electronics from the Instituto Politécnico Nacional de México (National Polytechnic Institute of Mexico) in 2003. He is currently an associate professor in the Escuela Superior de Ingeniería Mecánica y Eléctrica (Mechanical and Electrical Engineering Higher School) at the same institute. His areas of scientific interest are signal and image processing, filtering, steganography, segmentation, pattern recognition, biomedical signal processing, sensors, and real-time applications.",institutionString:"Instituto Politécnico Nacional",institution:{name:"Instituto Politécnico Nacional",country:{name:"Mexico"}}},{id:"428449",title:"Dr.",name:"Ronaldo",middleName:null,surname:"Ferreira",slug:"ronaldo-ferreira",fullName:"Ronaldo Ferreira",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/428449/images/21449_n.png",biography:null,institutionString:null,institution:{name:"University of Aveiro",country:{name:"Portugal"}}},{id:"165328",title:"Dr.",name:"Vahid",middleName:null,surname:"Asadpour",slug:"vahid-asadpour",fullName:"Vahid Asadpour",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/165328/images/system/165328.jpg",biography:"Vahid Asadpour, MS, Ph.D., is currently with the Department of Research and Evaluation, Kaiser Permanente Southern California. He has both an MS and Ph.D. in Biomedical Engineering. He was previously a research scientist at the University of California Los Angeles (UCLA) and visiting professor and researcher at the University of North Dakota. He is currently working in artificial intelligence and its applications in medical signal processing. In addition, he is using digital signal processing in medical imaging and speech processing. Dr. Asadpour has developed brain-computer interfacing algorithms and has published books, book chapters, and several journal and conference papers in this field and other areas of intelligent signal processing. He has also designed medical devices, including a laser Doppler monitoring system.",institutionString:"Kaiser Permanente Southern California",institution:null},{id:"169608",title:"Prof.",name:"Marian",middleName:null,surname:"Găiceanu",slug:"marian-gaiceanu",fullName:"Marian Găiceanu",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/169608/images/system/169608.png",biography:"Prof. Dr. Marian Gaiceanu graduated from the Naval and Electrical Engineering Faculty, Dunarea de Jos University of Galati, Romania, in 1997. He received a Ph.D. (Magna Cum Laude) in Electrical Engineering in 2002. Since 2017, Dr. Gaiceanu has been a Ph.D. supervisor for students in Electrical Engineering. He has been employed at Dunarea de Jos University of Galati since 1996, where he is currently a professor. Dr. Gaiceanu is a member of the National Council for Attesting Titles, Diplomas and Certificates, an expert of the Executive Agency for Higher Education, Research Funding, and a member of the Senate of the Dunarea de Jos University of Galati. He has been the head of the Integrated Energy Conversion Systems and Advanced Control of Complex Processes Research Center, Romania, since 2016. He has conducted several projects in power converter systems for electrical drives, power quality, PEM and SOFC fuel cell power converters for utilities, electric vehicles, and marine applications with the Department of Regulation and Control, SIEI S.pA. (2002–2004) and the Polytechnic University of Turin, Italy (2002–2004, 2006–2007). He is a member of the Institute of Electrical and Electronics Engineers (IEEE) and cofounder-member of the IEEE Power Electronics Romanian Chapter. He is a guest editor at Energies and an academic book editor for IntechOpen. He is also a member of the editorial boards of the Journal of Electrical Engineering, Electronics, Control and Computer Science and Sustainability. Dr. Gaiceanu has been General Chairman of the IEEE International Symposium on Electrical and Electronics Engineering in the last six editions.",institutionString:'"Dunarea de Jos" University of Galati',institution:{name:'"Dunarea de Jos" University of Galati',country:{name:"Romania"}}},{id:"4519",title:"Prof.",name:"Jaydip",middleName:null,surname:"Sen",slug:"jaydip-sen",fullName:"Jaydip Sen",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/4519/images/system/4519.jpeg",biography:"Jaydip Sen is associated with Praxis Business School, Kolkata, India, as a professor in the Department of Data Science. His research areas include security and privacy issues in computing and communication, intrusion detection systems, machine learning, deep learning, and artificial intelligence in the financial domain. He has more than 200 publications in reputed international journals, refereed conference proceedings, and 20 book chapters in books published by internationally renowned publishing houses, such as Springer, CRC press, IGI Global, etc. Currently, he is serving on the editorial board of the prestigious journal Frontiers in Communications and Networks and in the technical program committees of a number of high-ranked international conferences organized by the IEEE, USA, and the ACM, USA. He has been listed among the top 2% of scientists in the world for the last three consecutive years, 2019 to 2021 as per studies conducted by the Stanford University, USA.",institutionString:"Praxis Business School",institution:null},{id:"320071",title:"Dr.",name:"Sidra",middleName:null,surname:"Mehtab",slug:"sidra-mehtab",fullName:"Sidra Mehtab",position:null,profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0033Y00002v6KHoQAM/Profile_Picture_1584512086360",biography:"Sidra Mehtab has completed her BS with honors in Physics from Calcutta University, India in 2018. She has done MS in Data Science and Analytics from Maulana Abul Kalam Azad University of Technology (MAKAUT), Kolkata, India in 2020. Her research areas include Econometrics, Time Series Analysis, Machine Learning, Deep Learning, Artificial Intelligence, and Computer and Network Security with a particular focus on Cyber Security Analytics. Ms. Mehtab has published seven papers in international conferences and one of her papers has been accepted for publication in a reputable international journal. She has won the best paper awards in two prestigious international conferences – BAICONF 2019, and ICADCML 2021, organized in the Indian Institute of Management, Bangalore, India in December 2019, and SOA University, Bhubaneswar, India in January 2021. Besides, Ms. Mehtab has also published two book chapters in two books. Seven of her book chapters will be published in a volume shortly in 2021 by Cambridge Scholars’ Press, UK. Currently, she is working as the joint editor of two edited volumes on Time Series Analysis and Forecasting to be published in the first half of 2021 by an international house. Currently, she is working as a Data Scientist with an MNC in Delhi, India.",institutionString:"NSHM College of Management and Technology",institution:{name:"Association for Computing Machinery",country:{name:"United States of America"}}},{id:"226240",title:"Dr.",name:"Andri Irfan",middleName:null,surname:"Rifai",slug:"andri-irfan-rifai",fullName:"Andri Irfan Rifai",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/226240/images/7412_n.jpg",biography:"Andri IRFAN is a Senior Lecturer of Civil Engineering and Planning. He completed the PhD at the Universitas Indonesia & Universidade do Minho with Sandwich Program Scholarship from the Directorate General of Higher Education and LPDP scholarship. He has been teaching for more than 19 years and much active to applied his knowledge in the project construction in Indonesia. His research interest ranges from pavement management system to advanced data mining techniques for transportation engineering. He has published more than 50 papers in journals and 2 books.",institutionString:null,institution:{name:"Universitas Internasional Batam",country:{name:"Indonesia"}}},{id:"314576",title:"Dr.",name:"Ibai",middleName:null,surname:"Laña",slug:"ibai-lana",fullName:"Ibai Laña",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/314576/images/system/314576.jpg",biography:"Dr. Ibai Laña works at TECNALIA as a data analyst. He received his Ph.D. in Artificial Intelligence from the University of the Basque Country (UPV/EHU), Spain, in 2018. He is currently a senior researcher at TECNALIA. His research interests fall within the intersection of intelligent transportation systems, machine learning, traffic data analysis, and data science. He has dealt with urban traffic forecasting problems, applying machine learning models and evolutionary algorithms. He has experience in origin-destination matrix estimation or point of interest and trajectory detection. Working with large volumes of data has given him a good command of big data processing tools and NoSQL databases. He has also been a visiting scholar at the Knowledge Engineering and Discovery Research Institute, Auckland University of Technology.",institutionString:"TECNALIA Research & Innovation",institution:{name:"Tecnalia",country:{name:"Spain"}}},{id:"314575",title:"Dr.",name:"Jesus",middleName:null,surname:"L. Lobo",slug:"jesus-l.-lobo",fullName:"Jesus L. Lobo",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/314575/images/system/314575.png",biography:"Dr. Jesús López is currently based in Bilbao (Spain) working at TECNALIA as Artificial Intelligence Research Scientist. In most cases, a project idea or a new research line needs to be investigated to see if it is good enough to take into production or to focus on it. That is exactly what he does, diving into Machine Learning algorithms and technologies to help TECNALIA to decide whether something is great in theory or will actually impact on the product or processes of its projects. So, he is expert at framing experiments, developing hypotheses, and proving whether they’re true or not, in order to investigate fundamental problems with a longer time horizon. He is also able to design and develop PoCs and system prototypes in simulation. He has participated in several national and internacional R&D projects.\n\nAs another relevant part of his everyday research work, he usually publishes his findings in reputed scientific refereed journals and international conferences, occasionally acting as reviewer and Programme Commitee member. Concretely, since 2018 he has published 9 JCR (8 Q1) journal papers, 9 conference papers (e.g. ECML PKDD 2021), and he has co-edited a book. He is also active in popular science writing data science stories for reputed blogs (KDNuggets, TowardsDataScience, Naukas). Besides, he has recently embarked on mentoring programmes as mentor, and has also worked as data science trainer.",institutionString:"TECNALIA Research & Innovation",institution:{name:"Tecnalia",country:{name:"Spain"}}},{id:"103779",title:"Prof.",name:"Yalcin",middleName:null,surname:"Isler",slug:"yalcin-isler",fullName:"Yalcin Isler",position:null,profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bRyQ8QAK/Profile_Picture_1628834958734",biography:"Yalcin Isler (1971 - Burdur / Turkey) received the B.Sc. degree in the Department of Electrical and Electronics Engineering from Anadolu University, Eskisehir, Turkey, in 1993, the M.Sc. degree from the Department of Electronics and Communication Engineering, Suleyman Demirel University, Isparta, Turkey, in 1996, the Ph.D. degree from the Department of Electrical and Electronics Engineering, Dokuz Eylul University, Izmir, Turkey, in 2009, and the Competence of Associate Professorship from the Turkish Interuniversity Council in 2019.\n\nHe was Lecturer at Burdur Vocational School in Suleyman Demirel University (1993-2000, Burdur / Turkey), Software Engineer (2000-2002, Izmir / Turkey), Research Assistant in Bulent Ecevit University (2002-2003, Zonguldak / Turkey), Research Assistant in Dokuz Eylul University (2003-2010, Izmir / Turkey), Assistant Professor at the Department of Electrical and Electronics Engineering in Bulent Ecevit University (2010-2012, Zonguldak / Turkey), Assistant Professor at the Department of Biomedical Engineering in Izmir Katip Celebi University (2012-2019, Izmir / Turkey). He is an Associate Professor at the Department of Biomedical Engineering at Izmir Katip Celebi University, Izmir / Turkey, since 2019. In addition to academics, he has also founded Islerya Medical and Information Technologies Company, Izmir / Turkey, since 2017.\n\nHis main research interests cover biomedical signal processing, pattern recognition, medical device design, programming, and embedded systems. He has many scientific papers and participated in several projects in these study fields. He was an IEEE Student Member (2009-2011) and IEEE Member (2011-2014) and has been IEEE Senior Member since 2014.",institutionString:null,institution:{name:"Izmir Kâtip Çelebi University",country:{name:"Turkey"}}},{id:"339677",title:"Dr.",name:"Mrinmoy",middleName:null,surname:"Roy",slug:"mrinmoy-roy",fullName:"Mrinmoy Roy",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/339677/images/16768_n.jpg",biography:"An accomplished Sales & Marketing professional with 12 years of cross-functional experience in well-known organisations such as CIPLA, LUPIN, GLENMARK, ASTRAZENECA across different segment of Sales & Marketing, International Business, Institutional Business, Product Management, Strategic Marketing of HIV, Oncology, Derma, Respiratory, Anti-Diabetic, Nutraceutical & Stomatological Product Portfolio and Generic as well as Chronic Critical Care Portfolio. A First Class MBA in International Business & Strategic Marketing, B.Pharm, D.Pharm, Google Certified Digital Marketing Professional. Qualified PhD Candidate in Operations and Management with special focus on Artificial Intelligence and Machine Learning adoption, analysis and use in Healthcare, Hospital & Pharma Domain. Seasoned with diverse therapy area of Pharmaceutical Sales & Marketing ranging from generating revenue through generating prescriptions, launching new products, and making them big brands with continuous strategy execution at the Physician and Patients level. Moved from Sales to Marketing and Business Development for 3.5 years in South East Asian Market operating from Manila, Philippines. Came back to India and handled and developed Brands such as Gluconorm, Lupisulin, Supracal, Absolut Woman, Hemozink, Fabiflu (For COVID 19), and many more. In my previous assignment I used to develop and execute strategies on Sales & Marketing, Commercialization & Business Development for Institution and Corporate Hospital Business portfolio of Oncology Therapy Area for AstraZeneca Pharma India Ltd. Being a Research Scholar and Student of ‘Operations Research & Management: Artificial Intelligence’ I published several pioneer research papers and book chapters on the same in Internationally reputed journals and Books indexed in Scopus, Springer and Ei Compendex, Google Scholar etc. Currently, I am launching PGDM Pharmaceutical Management Program in IIHMR Bangalore and spearheading the course curriculum and structure of the same. I am interested in Collaboration for Healthcare Innovation, Pharma AI Innovation, Future trend in Marketing and Management with incubation on Healthcare, Healthcare IT startups, AI-ML Modelling and Healthcare Algorithm based training module development. I am also an affiliated member of the Institute of Management Consultant of India, looking forward to Healthcare, Healthcare IT and Innovation, Pharma and Hospital Management Consulting works.",institutionString:null,institution:{name:"Lovely Professional University",country:{name:"India"}}},{id:"1063",title:"Prof.",name:"Constantin",middleName:null,surname:"Volosencu",slug:"constantin-volosencu",fullName:"Constantin Volosencu",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/1063/images/system/1063.png",biography:"Prof. Dr. Constantin Voloşencu graduated as an engineer from\nPolitehnica University of Timișoara, Romania, where he also\nobtained a doctorate degree. He is currently a full professor in\nthe Department of Automation and Applied Informatics at the\nsame university. Dr. Voloşencu is the author of ten books, seven\nbook chapters, and more than 160 papers published in journals\nand conference proceedings. He has also edited twelve books and\nhas twenty-seven patents to his name. He is a manager of research grants, editor in\nchief and member of international journal editorial boards, a former plenary speaker, a member of scientific committees, and chair at international conferences. His\nresearch is in the fields of control systems, control of electric drives, fuzzy control\nsystems, neural network applications, fault detection and diagnosis, sensor network\napplications, monitoring of distributed parameter systems, and power ultrasound\napplications. He has developed automation equipment for machine tools, spooling\nmachines, high-power ultrasound processes, and more.",institutionString:'"Politechnica" University Timişoara',institution:null},{id:"221364",title:"Dr.",name:"Eneko",middleName:null,surname:"Osaba",slug:"eneko-osaba",fullName:"Eneko Osaba",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/221364/images/system/221364.jpg",biography:"Dr. Eneko Osaba works at TECNALIA as a senior researcher. He obtained his Ph.D. in Artificial Intelligence in 2015. He has participated in more than twenty-five local and European research projects, and in the publication of more than 130 papers. He has performed several stays at universities in the United Kingdom, Italy, and Malta. Dr. Osaba has served as a program committee member in more than forty international conferences and participated in organizing activities in more than ten international conferences. He is a member of the editorial board of the International Journal of Artificial Intelligence, Data in Brief, and Journal of Advanced Transportation. He is also a guest editor for the Journal of Computational Science, Neurocomputing, Swarm, and Evolutionary Computation and IEEE ITS Magazine.",institutionString:"TECNALIA Research & Innovation",institution:{name:"Tecnalia",country:{name:"Spain"}}},{id:"275829",title:"Dr.",name:"Esther",middleName:null,surname:"Villar-Rodriguez",slug:"esther-villar-rodriguez",fullName:"Esther Villar-Rodriguez",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/275829/images/system/275829.jpg",biography:"Dr. Esther Villar obtained a Ph.D. in Information and Communication Technologies from the University of Alcalá, Spain, in 2015. She obtained a degree in Computer Science from the University of Deusto, Spain, in 2010, and an MSc in Computer Languages and Systems from the National University of Distance Education, Spain, in 2012. Her areas of interest and knowledge include natural language processing (NLP), detection of impersonation in social networks, semantic web, and machine learning. Dr. Esther Villar made several contributions at conferences and publishing in various journals in those fields. Currently, she is working within the OPTIMA (Optimization Modeling & Analytics) business of TECNALIA’s ICT Division as a data scientist in projects related to the prediction and optimization of management and industrial processes (resource planning, energy efficiency, etc).",institutionString:"TECNALIA Research & Innovation",institution:{name:"Tecnalia",country:{name:"Spain"}}},{id:"49813",title:"Dr.",name:"Javier",middleName:null,surname:"Del Ser",slug:"javier-del-ser",fullName:"Javier Del Ser",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/49813/images/system/49813.png",biography:"Prof. Dr. Javier Del Ser received his first PhD in Telecommunication Engineering (Cum Laude) from the University of Navarra, Spain, in 2006, and a second PhD in Computational Intelligence (Summa Cum Laude) from the University of Alcala, Spain, in 2013. He is currently a principal researcher in data analytics and optimisation at TECNALIA (Spain), a visiting fellow at the Basque Center for Applied Mathematics (BCAM) and a part-time lecturer at the University of the Basque Country (UPV/EHU). His research interests gravitate on the use of descriptive, prescriptive and predictive algorithms for data mining and optimization in a diverse range of application fields such as Energy, Transport, Telecommunications, Health and Industry, among others. In these fields he has published more than 240 articles, co-supervised 8 Ph.D. theses, edited 6 books, coauthored 7 patents and participated/led more than 40 research projects. He is a Senior Member of the IEEE, and a recipient of the Biscay Talent prize for his academic career.",institutionString:"Tecnalia Research & Innovation",institution:{name:"Tecnalia",country:{name:"Spain"}}},{id:"278948",title:"Dr.",name:"Carlos Pedro",middleName:null,surname:"Gonçalves",slug:"carlos-pedro-goncalves",fullName:"Carlos Pedro Gonçalves",position:null,profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bRcmyQAC/Profile_Picture_1564224512145",biography:'Carlos Pedro Gonçalves (PhD) is an Associate Professor at Lusophone University of Humanities and Technologies and a researcher on Complexity Sciences, Quantum Technologies, Artificial Intelligence, Strategic Studies, Studies in Intelligence and Security, FinTech and Financial Risk Modeling. He is also a progammer with programming experience in:\n\nA) Quantum Computing using Qiskit Python module and IBM Quantum Experience Platform, with software developed on the simulation of Quantum Artificial Neural Networks and Quantum Cybersecurity;\n\nB) Artificial Intelligence and Machine learning programming in Python;\n\nC) Artificial Intelligence, Multiagent Systems Modeling and System Dynamics Modeling in Netlogo, with models developed in the areas of Chaos Theory, Econophysics, Artificial Intelligence, Classical and Quantum Complex Systems Science, with the Econophysics models having been cited worldwide and incorporated in PhD programs by different Universities.\n\nReceived an Arctic Code Vault Contributor status by GitHub, due to having developed open source software preserved in the \\"Arctic Code Vault\\" for future generations (https://archiveprogram.github.com/arctic-vault/), with the Strategy Analyzer A.I. module for decision making support (based on his PhD thesis, used in his Classes on Decision Making and in Strategic Intelligence Consulting Activities) and QNeural Python Quantum Neural Network simulator also preserved in the \\"Arctic Code Vault\\", for access to these software modules see: https://github.com/cpgoncalves. He is also a peer reviewer with outsanding review status from Elsevier journals, including Physica A, Neurocomputing and Engineering Applications of Artificial Intelligence. Science CV available at: https://www.cienciavitae.pt//pt/8E1C-A8B3-78C5 and ORCID: https://orcid.org/0000-0002-0298-3974',institutionString:"University of Lisbon",institution:{name:"Universidade Lusófona",country:{name:"Portugal"}}},{id:"310576",title:"Prof.",name:"Erick Giovani",middleName:null,surname:"Sperandio Nascimento",slug:"erick-giovani-sperandio-nascimento",fullName:"Erick Giovani Sperandio Nascimento",position:null,profilePictureURL:"https://intech-files.s3.amazonaws.com/0033Y00002pDKxDQAW/ProfilePicture%202022-06-20%2019%3A57%3A24.788",biography:"Prof. Erick Sperandio is the Lead Researcher and professor of Artificial Intelligence (AI) at SENAI CIMATEC, Bahia, Brazil, also working with Computational Modeling (CM) and HPC. He holds a PhD in Environmental Engineering in the area of Atmospheric Computational Modeling, a Master in Informatics in the field of Computational Intelligence and Graduated in Computer Science from UFES. He currently coordinates, leads and participates in R&D projects in the areas of AI, computational modeling and supercomputing applied to different areas such as Oil and Gas, Health, Advanced Manufacturing, Renewable Energies and Atmospheric Sciences, advising undergraduate, master's and doctoral students. He is the Lead Researcher at SENAI CIMATEC's Reference Center on Artificial Intelligence. In addition, he is a Certified Instructor and University Ambassador of the NVIDIA Deep Learning Institute (DLI) in the areas of Deep Learning, Computer Vision, Natural Language Processing and Recommender Systems, and Principal Investigator of the NVIDIA/CIMATEC AI Joint Lab, the first in Latin America within the NVIDIA AI Technology Center (NVAITC) worldwide program. He also works as a researcher at the Supercomputing Center for Industrial Innovation (CS2i) and at the SENAI Institute of Innovation for Automation (ISI Automação), both from SENAI CIMATEC. He is a member and vice-coordinator of the Basic Board of Scientific-Technological Advice and Evaluation, in the area of Innovation, of the Foundation for Research Support of the State of Bahia (FAPESB). He serves as Technology Transfer Coordinator and one of the Principal Investigators at the National Applied Research Center in Artificial Intelligence (CPA-IA) of SENAI CIMATEC, focusing on Industry, being one of the six CPA-IA in Brazil approved by MCTI / FAPESP / CGI.br. He also participates as one of the representatives of Brazil in the BRICS Innovation Collaboration Working Group on HPC, ICT and AI. He is the coordinator of the Work Group of the Axis 5 - Workforce and Training - of the Brazilian Strategy for Artificial Intelligence (EBIA), and member of the MCTI/EMBRAPII AI Innovation Network Training Committee. He is the coordinator, by SENAI CIMATEC, of the Artificial Intelligence Reference Network of the State of Bahia (REDE BAH.IA). 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Currently working as an Assistant Professor in the Department of Mathematics, Institute of Applied Science, Mangalayatan University, Aligarh. She taught so many courses of Mathematics of UG and PG level. Her research Area of Expertise is Functional Analysis & Sequence Spaces. She has been working on Ideal Convergence of double sequence. She has published 17 research papers in National and International Journals including Cogent Mathematics, Filomat, Journal of Intelligent and Fuzzy Systems, Advances in Difference Equations, Journal of Mathematical Analysis, Journal of Mathematical & Computer Science etc. She has also reviewed few research papers for the and international journals. 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He is the president of the Travel Medicine Committee of the Pan-American Infectious Diseases Association (API), as well as the president of the Colombian Association of Infectious Diseases (ACIN). He is a member of the Committee on Tropical Medicine, Zoonoses, and Travel Medicine of ACIN. He is a vice-president of the Latin American Society for Travel Medicine (SLAMVI) and a Member of the Council of the International Society for Infectious Diseases (ISID). Since 2014, he has been recognized as a Senior Researcher, at the Ministry of Science of Colombia. He is a professor at the Faculty of Medicine of the Fundacion Universitaria Autonoma de las Americas, in Pereira, Risaralda, Colombia. He is an External Professor, Master in Research on Tropical Medicine and International Health, Universitat de Barcelona, Spain. He is also a professor at the Master in Clinical Epidemiology and Biostatistics, Universidad Científica del Sur, Lima, Peru. In 2021 he has been awarded the “Raul Isturiz Award” Medal of the API. Also, in 2021, he was awarded with the “Jose Felix Patiño” Asclepius Staff Medal of the Colombian Medical College, due to his scientific contributions to COVID-19 during the pandemic. He is currently the Editor in Chief of the journal Travel Medicine and Infectious Diseases. His Scopus H index is 47 (Google Scholar H index, 68).",institutionString:"Institución Universitaria Visión de las Américas, Colombia",institution:null},subseries:[{id:"3",title:"Bacterial Infectious Diseases",keywords:"Antibiotics, Biofilm, Antibiotic Resistance, Host-microbiota Relationship, Treatment, Diagnostic Tools",scope:"
\r\n\tThe era of antibiotics led us to the illusion that the problem of bacterial infection is over. However, bacterial flexibility and adaptation mechanisms allow them to survive and grow in extreme conditions. The best example is the formation of a sophisticated society of bacteria defined as a biofilm. Understanding the mechanism of bacterial biofilm formation has changed our perception of the development of bacterial infection but successfully eradicating biofilm remains a challenge. Considering the above, it is not surprising that bacteria remain a major public health threat despite the development of many groups of antibiotics. Additionally, increasing prevalence of acquired antibiotic resistance forces us to realize that we are far from controlling the development of bacterial infections. On the other hand, many infections are endogenous and result from an unbalanced relationship between the host and the microorganism. The increasing use of immunosuppressants, such as chemotherapy or organ transplantation, increases the incidence of patients highly susceptible to bacterial infections in the population.
\r\n
\r\n\tThis topic will focus on the current challenges and advantages in the diagnosis and treatment of bacterial infections. We will discuss the host-microbiota relationship, the treatment of chronic infections due to biofilm formation, and the development of new diagnostic tools to rapidly distinguish between colonization and probable infection.
",annualVolume:11399,isOpenForSubmission:!0,coverUrl:"https://cdn.intechopen.com/series_topics/covers/3.jpg",editor:{id:"205604",title:"Dr.",name:"Tomas",middleName:null,surname:"Jarzembowski",fullName:"Tomas Jarzembowski",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bRKriQAG/Profile_Picture_2022-06-16T11:01:31.jpg",institutionString:"Medical University of Gdańsk, Poland",institution:null},editorTwo:{id:"484980",title:"Dr.",name:"Katarzyna",middleName:null,surname:"Garbacz",fullName:"Katarzyna Garbacz",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0033Y00003St8TAQAZ/Profile_Picture_2022-07-07T09:45:16.jpg",institutionString:"Medical University of Gdańsk, Poland",institution:null},editorThree:null,editorialBoard:[{id:"190041",title:"Dr.",name:"Jose",middleName:null,surname:"Gutierrez Fernandez",fullName:"Jose Gutierrez Fernandez",profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",institutionString:null,institution:{name:"University of Granada",institutionURL:null,country:{name:"Spain"}}},{id:"156556",title:"Prof.",name:"Maria Teresa",middleName:null,surname:"Mascellino",fullName:"Maria Teresa Mascellino",profilePictureURL:"https://mts.intechopen.com/storage/users/156556/images/system/156556.jpg",institutionString:"Sapienza University",institution:{name:"Sapienza University of Rome",institutionURL:null,country:{name:"Italy"}}},{id:"164933",title:"Prof.",name:"Mónica Alexandra",middleName:null,surname:"Sousa Oleastro",fullName:"Mónica Alexandra Sousa Oleastro",profilePictureURL:"https://mts.intechopen.com/storage/users/164933/images/system/164933.jpeg",institutionString:"National Institute of Health Dr Ricardo Jorge",institution:{name:"National Institute of Health Dr. Ricardo Jorge",institutionURL:null,country:{name:"Portugal"}}}]},{id:"4",title:"Fungal Infectious Diseases",keywords:"Emerging Fungal Pathogens, Invasive Infections, Epidemiology, Cell Membrane, Fungal Virulence, Diagnosis, Treatment",scope:"Fungi are ubiquitous and there are almost no non-pathogenic fungi. Fungal infectious illness prevalence and prognosis are determined by the exposure between fungi and host, host immunological state, fungal virulence, and early and accurate diagnosis and treatment. \r\nPatients with both congenital and acquired immunodeficiency are more likely to be infected with opportunistic mycosis. Fungal infectious disease outbreaks are common during the post- disaster rebuilding era, which is characterised by high population density, migration, and poor health and medical conditions.\r\nSystemic or local fungal infection is mainly associated with the fungi directly inhaled or inoculated in the environment during the disaster. The most common fungal infection pathways are human to human (anthropophilic), animal to human (zoophilic), and environment to human (soilophile). Diseases are common as a result of widespread exposure to pathogenic fungus dispersed into the environment. \r\nFungi that are both common and emerging are intertwined. In Southeast Asia, for example, Talaromyces marneffei is an important pathogenic thermally dimorphic fungus that causes systemic mycosis. Widespread fungal infections with complicated and variable clinical manifestations, such as Candida auris infection resistant to several antifungal medicines, Covid-19 associated with Trichoderma, and terbinafine resistant dermatophytosis in India, are among the most serious disorders. \r\nInappropriate local or systemic use of glucocorticoids, as well as their immunosuppressive effects, may lead to changes in fungal infection spectrum and clinical characteristics. Hematogenous candidiasis is a worrisome issue that affects people all over the world, particularly ICU patients. CARD9 deficiency and fungal infection have been major issues in recent years. Invasive aspergillosis is associated with a significant death rate. Special attention should be given to endemic fungal infections, identification of important clinical fungal infections advanced in yeasts, filamentous fungal infections, skin mycobiome and fungal genomes, and immunity to fungal infections.\r\nIn addition, endemic fungal diseases or uncommon fungal infections caused by Mucor irregularis, dermatophytosis, Malassezia, cryptococcosis, chromoblastomycosis, coccidiosis, blastomycosis, histoplasmosis, sporotrichosis, and other fungi, should be monitored. \r\nThis topic includes the research progress on the etiology and pathogenesis of fungal infections, new methods of isolation and identification, rapid detection, drug sensitivity testing, new antifungal drugs, schemes and case series reports. It will provide significant opportunities and support for scientists, clinical doctors, mycologists, antifungal drug researchers, public health practitioners, and epidemiologists from all over the world to share new research, ideas and solutions to promote the development and progress of medical mycology.",annualVolume:11400,isOpenForSubmission:!0,coverUrl:"https://cdn.intechopen.com/series_topics/covers/4.jpg",editor:{id:"174134",title:"Dr.",name:"Yuping",middleName:null,surname:"Ran",fullName:"Yuping Ran",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bS9d6QAC/Profile_Picture_1630330675373",institutionString:null,institution:{name:"Sichuan University",institutionURL:null,country:{name:"China"}}},editorTwo:null,editorThree:null,editorialBoard:[{id:"302145",title:"Dr.",name:"Felix",middleName:null,surname:"Bongomin",fullName:"Felix Bongomin",profilePictureURL:"https://mts.intechopen.com/storage/users/302145/images/system/302145.jpg",institutionString:null,institution:{name:"Gulu University",institutionURL:null,country:{name:"Uganda"}}},{id:"45803",title:"Ph.D.",name:"Payam",middleName:null,surname:"Behzadi",fullName:"Payam Behzadi",profilePictureURL:"https://mts.intechopen.com/storage/users/45803/images/system/45803.jpg",institutionString:"Islamic Azad University, Tehran",institution:{name:"Islamic Azad University, Tehran",institutionURL:null,country:{name:"Iran"}}}]},{id:"5",title:"Parasitic Infectious Diseases",keywords:"Blood Borne Parasites, Intestinal Parasites, Protozoa, Helminths, Arthropods, Water Born Parasites, Epidemiology, Molecular Biology, Systematics, Genomics, Proteomics, Ecology",scope:"Parasitic diseases have evolved alongside their human hosts. In many cases, these diseases have adapted so well that they have developed efficient resilience methods in the human host and can live in the host for years. Others, particularly some blood parasites, can cause very acute diseases and are responsible for millions of deaths yearly. Many parasitic diseases are classified as neglected tropical diseases because they have received minimal funding over recent years and, in many cases, are under-reported despite the critical role they play in morbidity and mortality among human and animal hosts. The current topic, Parasitic Infectious Diseases, in the Infectious Diseases Series aims to publish studies on the systematics, epidemiology, molecular biology, genomics, pathogenesis, genetics, and clinical significance of parasitic diseases from blood borne to intestinal parasites as well as zoonotic parasites. We hope to cover all aspects of parasitic diseases to provide current and relevant research data on these very important diseases. In the current atmosphere of the Coronavirus pandemic, communities around the world, particularly those in different underdeveloped areas, are faced with the growing challenges of the high burden of parasitic diseases. At the same time, they are faced with the Covid-19 pandemic leading to what some authors have called potential syndemics that might worsen the outcome of such infections. Therefore, it is important to conduct studies that examine parasitic infections in the context of the coronavirus pandemic for the benefit of all communities to help foster more informed decisions for the betterment of human and animal health.",annualVolume:11401,isOpenForSubmission:!0,coverUrl:"https://cdn.intechopen.com/series_topics/covers/5.jpg",editor:{id:"67907",title:"Dr.",name:"Amidou",middleName:null,surname:"Samie",fullName:"Amidou Samie",profilePictureURL:"https://mts.intechopen.com/storage/users/67907/images/system/67907.jpg",institutionString:null,institution:{name:"University of Venda",institutionURL:null,country:{name:"South Africa"}}},editorTwo:null,editorThree:null,editorialBoard:[{id:"188881",title:"Dr.",name:"Fernando José",middleName:null,surname:"Andrade-Narváez",fullName:"Fernando José Andrade-Narváez",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bRIV7QAO/Profile_Picture_1628834308121",institutionString:null,institution:{name:"Autonomous University of Yucatán",institutionURL:null,country:{name:"Mexico"}}},{id:"269120",title:"Dr.",name:"Rajeev",middleName:"K.",surname:"Tyagi",fullName:"Rajeev Tyagi",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bRaBqQAK/Profile_Picture_1644331884726",institutionString:"CSIR - Institute of Microbial Technology, India",institution:null},{id:"336849",title:"Prof.",name:"Ricardo",middleName:null,surname:"Izurieta",fullName:"Ricardo Izurieta",profilePictureURL:"https://mts.intechopen.com/storage/users/293169/images/system/293169.png",institutionString:null,institution:{name:"University of South Florida",institutionURL:null,country:{name:"United States of America"}}}]},{id:"6",title:"Viral Infectious Diseases",keywords:"Novel Viruses, Virus Transmission, Virus Evolution, Molecular Virology, Control and Prevention, Virus-host Interaction",scope:"The Viral Infectious Diseases Book Series aims to provide a comprehensive overview of recent research trends and discoveries in various viral infectious diseases emerging around the globe. The emergence of any viral disease is hard to anticipate, which often contributes to death. A viral disease can be defined as an infectious disease that has recently appeared within a population or exists in nature with the rapid expansion of incident or geographic range. This series will focus on various crucial factors related to emerging viral infectious diseases, including epidemiology, pathogenesis, host immune response, clinical manifestations, diagnosis, treatment, and clinical recommendations for managing viral infectious diseases, highlighting the recent issues with future directions for effective therapeutic strategies.",annualVolume:11402,isOpenForSubmission:!0,coverUrl:"https://cdn.intechopen.com/series_topics/covers/6.jpg",editor:{id:"158026",title:"Prof.",name:"Shailendra K.",middleName:null,surname:"Saxena",fullName:"Shailendra K. Saxena",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bRET3QAO/Profile_Picture_2022-05-10T10:10:26.jpeg",institutionString:"King George's Medical University",institution:{name:"King George's Medical University",institutionURL:null,country:{name:"India"}}},editorTwo:null,editorThree:null,editorialBoard:[{id:"188773",title:"Prof.",name:"Emmanuel",middleName:null,surname:"Drouet",fullName:"Emmanuel Drouet",profilePictureURL:"https://mts.intechopen.com/storage/users/188773/images/system/188773.png",institutionString:null,institution:{name:"Grenoble Alpes University",institutionURL:null,country:{name:"France"}}},{id:"188219",title:"Prof.",name:"Imran",middleName:null,surname:"Shahid",fullName:"Imran Shahid",profilePictureURL:"https://mts.intechopen.com/storage/users/188219/images/system/188219.jpeg",institutionString:null,institution:{name:"Umm al-Qura University",institutionURL:null,country:{name:"Saudi Arabia"}}},{id:"214235",title:"Dr.",name:"Lynn",middleName:"S.",surname:"Zijenah",fullName:"Lynn Zijenah",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bSEJGQA4/Profile_Picture_1636699126852",institutionString:null,institution:{name:"University of Zimbabwe",institutionURL:null,country:{name:"Zimbabwe"}}},{id:"178641",title:"Dr.",name:"Samuel Ikwaras",middleName:null,surname:"Okware",fullName:"Samuel Ikwaras Okware",profilePictureURL:"https://mts.intechopen.com/storage/users/178641/images/system/178641.jpg",institutionString:null,institution:{name:"Uganda Christian University",institutionURL:null,country:{name:"Uganda"}}}]}]}},libraryRecommendation:{success:null,errors:{},institutions:[]},route:{name:"profile.detail",path:"/profiles/360818",hash:"",query:{},params:{id:"360818"},fullPath:"/profiles/360818",meta:{},from:{name:null,path:"/",hash:"",query:{},params:{},fullPath:"/",meta:{}}}},function(){var t;(t=document.currentScript||document.scripts[document.scripts.length-1]).parentNode.removeChild(t)}()