Table 1.Average thermodynamic entities (ΔH°f, ΔG°f, S°, Cp and V) of liquid water and ice.
\\n\\n
\\n"}]',published:!0,mainMedia:{caption:"Milestone",originalUrl:"/media/original/124"}},components:[{type:"htmlEditorComponent",content:'
Barely three months into the new year and we are happy to announce a monumental milestone reached - 150 million downloads.
\n\nThis achievement solidifies IntechOpen’s place as a pioneer in Open Access publishing and the home to some of the most relevant scientific research available through Open Access.
\n\nWe are so proud to have worked with so many bright minds throughout the years who have helped us spread knowledge through the power of Open Access and we look forward to continuing to support some of the greatest thinkers of our day.
\n\nThank you for making IntechOpen your place of learning, sharing, and discovery, and here’s to 150 million more!
\n\n\n\n\n'}],latestNews:[{slug:"intechopen-supports-asapbio-s-new-initiative-publish-your-reviews-20220729",title:"IntechOpen Supports ASAPbio’s New Initiative Publish Your Reviews"},{slug:"webinar-introduction-to-open-science-wednesday-18-may-1-pm-cest-20220518",title:"Webinar: Introduction to Open Science | Wednesday 18 May, 1 PM CEST"},{slug:"step-in-the-right-direction-intechopen-launches-a-portfolio-of-open-science-journals-20220414",title:"Step in the Right Direction: IntechOpen Launches a Portfolio of Open Science Journals"},{slug:"let-s-meet-at-london-book-fair-5-7-april-2022-olympia-london-20220321",title:"Let’s meet at London Book Fair, 5-7 April 2022, Olympia London"},{slug:"50-books-published-as-part-of-intechopen-and-knowledge-unlatched-ku-collaboration-20220316",title:"50 Books published as part of IntechOpen and Knowledge Unlatched (KU) Collaboration"},{slug:"intechopen-joins-the-united-nations-sustainable-development-goals-publishers-compact-20221702",title:"IntechOpen joins the United Nations Sustainable Development Goals Publishers Compact"},{slug:"intechopen-signs-exclusive-representation-agreement-with-lsr-libros-servicios-y-representaciones-s-a-de-c-v-20211123",title:"IntechOpen Signs Exclusive Representation Agreement with LSR Libros Servicios y Representaciones S.A. de C.V"},{slug:"intechopen-expands-partnership-with-research4life-20211110",title:"IntechOpen Expands Partnership with Research4Life"}]},book:{item:{type:"book",id:"7999",leadTitle:null,fullTitle:"Free Radical Medicine and Biology",title:"Free Radical Medicine and Biology",subtitle:null,reviewType:"peer-reviewed",abstract:"Although free radicals perform some useful immune functions, they can also damage healthy cells through a process called oxidation. Antioxidants reduce the effect of free radicals by binding together with these harmful molecules, decreasing their destructive power. This book highlights various issues of free radical biology from the perspective of antioxidant defense mechanisms. It also provides useful information on gene modulation, radiation-generated reactive oxygen species-induced apoptosis in cancer, and environmental aspects associated with free radicals’ exposure on living systems.",isbn:"978-1-78985-144-1",printIsbn:"978-1-78985-143-4",pdfIsbn:"978-1-83962-595-4",doi:"10.5772/intechopen.77829",price:119,priceEur:129,priceUsd:155,slug:"free-radical-medicine-and-biology",numberOfPages:130,isOpenForSubmission:!1,isInWos:null,isInBkci:!1,hash:"083e5d427097d368a3f8a02bd6c76bf8",bookSignature:"Kusal Das, Swastika Das, Mallanagouda Shivanagouda Biradar, Varaprasad Bobbarala and S. Subba Tata",publishedDate:"July 15th 2020",coverURL:"https://cdn.intechopen.com/books/images_new/7999.jpg",numberOfDownloads:6108,numberOfWosCitations:2,numberOfCrossrefCitations:24,numberOfCrossrefCitationsByBook:1,numberOfDimensionsCitations:43,numberOfDimensionsCitationsByBook:1,hasAltmetrics:1,numberOfTotalCitations:69,isAvailableForWebshopOrdering:!0,dateEndFirstStepPublish:"January 10th 2019",dateEndSecondStepPublish:"February 27th 2019",dateEndThirdStepPublish:"April 28th 2019",dateEndFourthStepPublish:"July 17th 2019",dateEndFifthStepPublish:"September 15th 2019",currentStepOfPublishingProcess:5,indexedIn:"1,2,3,4,5,6",editedByType:"Edited by",kuFlag:!1,featuredMarkup:null,editors:[{id:"187859",title:"Prof.",name:"Kusal",middleName:"K.",surname:"Das",slug:"kusal-das",fullName:"Kusal Das",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bSBDeQAO/Profile_Picture_1623411145568",biography:"Kusal K. Das is a Distinguished Chair Professor of Physiology, Shri B. M. Patil Medical College and Director, Centre for Advanced Medical Research (CAMR), BLDE (Deemed to be University), Vijayapur, Karnataka, India. Dr. Das did his M.S. and Ph.D. in Human Physiology from the University of Calcutta, Kolkata. His area of research is focused on understanding of molecular mechanisms of heavy metal activated low oxygen sensing pathways in vascular pathophysiology. He has invented a new method of estimation of serum vitamin E. His expertise in critical experimental protocols on vascular functions in experimental animals was well documented by his quality of publications. He was a Visiting Professor of Medicine at University of Leeds, United Kingdom (2014-2016) and Tulane University, New Orleans, USA (2017). For his immense contribution in medical research Ministry of Science and Technology, Government of India conferred him 'G.P. Chatterjee Memorial Research Prize-2019” and he is also the recipient of 'Dr.Raja Ramanna State Scientist Award 2015” by Government of Karnataka. He is a Fellow of the Royal Society of Biology (FRSB), London and Honorary Fellow of Karnataka Science and Technology Academy, Department of Science and Technology, Government of Karnataka.",institutionString:"BLDE (Deemed to be University), India",position:null,outsideEditionCount:0,totalCites:0,totalAuthoredChapters:"3",totalChapterViews:"0",totalEditedBooks:"2",institution:null}],equalEditorOne:null,equalEditorTwo:null,equalEditorThree:null,coeditorOne:{id:"289796",title:"Dr.",name:"Swastika",middleName:null,surname:"Das",slug:"swastika-das",fullName:"Swastika Das",profilePictureURL:"https://mts.intechopen.com/storage/users/289796/images/system/289796.jpeg",biography:"Swastika N. Das is Professor of Chemistry at the V. P. Dr. P. G.\nHalakatti College of Engineering and Technology, BLDE (Deemed\nto be University), Vijayapura, Karnataka, India. She obtained an\nMSc, MPhil, and PhD in Chemistry from Sambalpur University,\nOdisha, India. Her areas of research interest are medicinal chemistry, chemical kinetics, and free radical chemistry. She is a member\nof the investigators who invented a new modified method of estimation of serum vitamin E. She has authored numerous publications including book\nchapters and is a mentor of doctoral curriculum at her university.",institutionString:"BLDEA’s V.P.Dr.P.G.Halakatti College of Engineering & Technology",position:null,outsideEditionCount:0,totalCites:0,totalAuthoredChapters:"1",totalChapterViews:"0",totalEditedBooks:"0",institution:{name:"BLDE University",institutionURL:null,country:{name:"India"}}},coeditorTwo:{id:"243660",title:"Dr.",name:"Mallanagouda Shivanagouda",middleName:null,surname:"Biradar",slug:"mallanagouda-shivanagouda-biradar",fullName:"Mallanagouda Shivanagouda Biradar",profilePictureURL:"https://mts.intechopen.com/storage/users/243660/images/system/243660.jpeg",biography:"M. S. Biradar is Vice Chancellor and Professor of Medicine of\nBLDE (Deemed to be University), Vijayapura, Karnataka, India.\nHe obtained his MD with a gold medal in General Medicine and\nhas devoted himself to medical teaching, research, and administrations. He has also immensely contributed to medical research\non vascular medicine, which is reflected by his numerous publications including books and book chapters. Professor Biradar was\nalso Visiting Professor at Tulane University School of Medicine, New Orleans, USA.",institutionString:"BLDE (Deemed to be University)",position:null,outsideEditionCount:0,totalCites:0,totalAuthoredChapters:"1",totalChapterViews:"0",totalEditedBooks:"0",institution:{name:"BLDE University",institutionURL:null,country:{name:"India"}}},coeditorThree:{id:"207119",title:"Dr.",name:"Varaprasad",middleName:null,surname:"Bobbarala PhD",slug:"varaprasad-bobbarala-phd",fullName:"Varaprasad Bobbarala PhD",profilePictureURL:"https://mts.intechopen.com/storage/users/207119/images/system/207119.jpg",biography:"Varaprasad Bobbarala has a doctorate from Andhra University\nwith a specialization in Biochemistry, Medicinal Chemistry,\nand Microbiology. He is currently editor-in-chief, associate\neditor, editorial board member as well as reviewer of dozens of\nhigh-impact international periodicals. He has authored/co-authored research and review articles in numerous peer-reviewed\nnational and international journals in various subjects related\nto biomedicine, pharmacy, and microbiology. Dr. Varaprasad previously served as\nthe Chief Scientist of Research and Development at Krisani Innovations Pvt. Ltd.,\nbefore his current role as the Chief Scientist and Director of Adhya Biosciences Pvt.\nLtd., India. He is currently working in the area of clinical diagnostics, antimicrobial\nresistance, drug discovery, production of commercially important chemicals by\nbiotechnology routes, isolation of bio-active metabolites, and bio-efficacy studies.",institutionString:"Adhya Biosciences",position:null,outsideEditionCount:0,totalCites:0,totalAuthoredChapters:"0",totalChapterViews:"0",totalEditedBooks:"2",institution:null},coeditorFour:{id:"293853",title:"Dr.",name:"S.",middleName:null,surname:"Subba Tata",slug:"s.-subba-tata",fullName:"S. Subba Tata",profilePictureURL:"https://mts.intechopen.com/storage/users/293853/images/system/293853.JPG",biography:"Dr. S. Subba Tata has M. Sc. (Biotechnology), M.Sc. (Botany), M.Tech. (Biotechnology) and Ph.D. Degree (Botany). He is an Assistant Professor at the Department of Botany, Andhra University, Visakhapatnam . He is qualified in CSIR-NET. APSET, ASRB-NET and GATE competitive examinations in life Sciences. He authored 2 books and published 22 research papers in national and international journals. He participated and presented at 30 Seminar/Symposia organized in India.",institutionString:"Andhra University",position:null,outsideEditionCount:0,totalCites:0,totalAuthoredChapters:"0",totalChapterViews:"0",totalEditedBooks:"0",institution:null},coeditorFive:null,topics:[{id:"47",title:"Cell Biology",slug:"biochemistry-genetics-and-molecular-biology-cell-biology"}],chapters:[{id:"71913",title:"Introductory Chapter: Free Radical Biology in Metal Toxicities—Role of Antioxidants",doi:"10.5772/intechopen.92164",slug:"introductory-chapter-free-radical-biology-in-metal-toxicities-role-of-antioxidants",totalDownloads:775,totalCrossrefCites:0,totalDimensionsCites:0,hasAltmetrics:1,abstract:null,signatures:"Swastika Das, Shrilaxmi Bagali, Sayandeep K. Das, Aravind V. Patil, Ishwar B. Bagoji, Kusal K. Das and Mallanagouda S. Biradar",downloadPdfUrl:"/chapter/pdf-download/71913",previewPdfUrl:"/chapter/pdf-preview/71913",authors:[{id:"187859",title:"Prof.",name:"Kusal",surname:"Das",slug:"kusal-das",fullName:"Kusal Das"},{id:"289796",title:"Dr.",name:"Swastika",surname:"Das",slug:"swastika-das",fullName:"Swastika Das"},{id:"243660",title:"Dr.",name:"Mallanagouda Shivanagouda",surname:"Biradar",slug:"mallanagouda-shivanagouda-biradar",fullName:"Mallanagouda Shivanagouda Biradar"},{id:"263841",title:"Dr.",name:"Shrilaxmi",surname:"Bagali",slug:"shrilaxmi-bagali",fullName:"Shrilaxmi Bagali"},{id:"294258",title:"Dr.",name:"Ishwar",surname:"Bagoji",slug:"ishwar-bagoji",fullName:"Ishwar Bagoji"}],corrections:null},{id:"69153",title:"Physiological Functions of Mitochondrial Reactive Oxygen Species",doi:"10.5772/intechopen.88386",slug:"physiological-functions-of-mitochondrial-reactive-oxygen-species",totalDownloads:1103,totalCrossrefCites:5,totalDimensionsCites:7,hasAltmetrics:0,abstract:"Mitochondria are the major energy producers within a cell in the form of adenosine triphosphate by oxidative phosphorylation. Normal mitochondrial metabolism inevitably generates reactive oxygen species (ROS), which have been considered to solely cause cellular damage. Increase of oxidative stress has been linked to various pathologies. Thus, mitochondrial ROS (mROS) were basically proposed as byproducts of oxidative metabolism, which undergo normalized by antioxidant enzymes. However, the mROS have extensively been esteemed to function as signalling molecules to regulate a wide variety of physiology. These phenomena are indeed dependent on mitochondrial redox status, which is dynamically altered under different physiological and pathological conditions. The oxidative stress is incurred by which the redox status is inclined to exceeded oxidation or reduction. Here, we attempt to integrate the recent advances in our understanding of the physiological functions of mROS.",signatures:"Tae Gyu Choi and Sung Soo Kim",downloadPdfUrl:"/chapter/pdf-download/69153",previewPdfUrl:"/chapter/pdf-preview/69153",authors:[{id:"290169",title:"Prof.",name:"Sung Soo",surname:"Kim",slug:"sung-soo-kim",fullName:"Sung Soo Kim"},{id:"291276",title:"Ph.D.",name:"Tae Gyu",surname:"Choi",slug:"tae-gyu-choi",fullName:"Tae Gyu Choi"}],corrections:null},{id:"67543",title:"Role of Oxidative Stress in the Cardiovascular Complications of Kawasaki Disease",doi:"10.5772/intechopen.86781",slug:"role-of-oxidative-stress-in-the-cardiovascular-complications-of-kawasaki-disease",totalDownloads:534,totalCrossrefCites:0,totalDimensionsCites:0,hasAltmetrics:0,abstract:"Kawasaki disease (KD) is a rare and often undiagnosed disease, at least in the western countries. Although its etiology remains unidentified, epidemiological features point to the role of infection and genetic predisposition. KD is characterized by an inflammatory acute febrile vasculitis. Coronary artery involvement is the most important complication of KD and may cause significant coronary stenosis resulting in ischemic heart disease. It has been demonstrated that the major risks in KD progression are the endothelial dysfunction and that systemic oxidative stress together with premature aging of red blood cells and alteration of platelet homeostasis, could play a critical role in the cardiovascular complications associated with KD. This chapter will focus on the role of oxidative stress in endothelial damage and on circulating blood cells of KD patients.",signatures:"Rosa Vona, Donatella Pietraforte, Lucrezia Gambardella, Alessandra Marchesi, Isabella Tarissi de Jacobis, Alberto Villani, Domenico Del Principe and Elisabetta Straface",downloadPdfUrl:"/chapter/pdf-download/67543",previewPdfUrl:"/chapter/pdf-preview/67543",authors:[{id:"262499",title:"Dr.",name:"Elisabetta",surname:"Straface",slug:"elisabetta-straface",fullName:"Elisabetta Straface"}],corrections:null},{id:"69969",title:"Radiation-Generated ROS Induce Apoptosis via Mitochondrial",doi:"10.5772/intechopen.86747",slug:"radiation-generated-ros-induce-apoptosis-via-mitochondrial",totalDownloads:761,totalCrossrefCites:1,totalDimensionsCites:2,hasAltmetrics:0,abstract:"Ionizing radiation (IR) causes an increase in intracellular calcium, alters contractility, and triggers apoptosis via the activation of PKCα and -ε in irradiated smooth muscle cells. The present study investigated the role of the mitochondria in these processes and characterized the proteins involved in IR-induced apoptosis. Intestinal smooth muscle cells were exposed to 10–50 Gy from a γ-source. ROS and H2O2 levels were measured with colourimetry and a DCFH-DA probe, and protein expression was analyzed by immunoblotting and immunofluorescence. The IR-induced generation of ROS was inhibited by glutathione, and apoptosis was mediated by the mitochondria via BAX, cytochrome c, and caspase 3. IR increased the expression of the cyclins A, B2, and E, and led to unbalanced cellular growth in an absorption dose-dependent manner. However, radiation did not induce alterations in the mitochondrial ultrastructure or in KΨmito. In contrast, IR increased the nuclear expression of BAG-1, TNFα, PKCα, and -ε and cyclins A and E. In conclusion, IR triggers the activation of antiapoptotic proteins and enhances the risk of a second type of cancer in patients undergoing radiotherapy. In addition to increasing the radioresistance of cells, antiapoptotic proteins can also stimulate uncontrolled cell proliferation that culminates in mutagenesis.",signatures:"Sandra Claro, Alice Teixeira Ferreira and Maria Etsuko Miyamoto Oshiro",downloadPdfUrl:"/chapter/pdf-download/69969",previewPdfUrl:"/chapter/pdf-preview/69969",authors:[{id:"297126",title:"Ph.D.",name:"Sandra",surname:"Claro",slug:"sandra-claro",fullName:"Sandra Claro"},{id:"297127",title:"Prof.",name:"Alice",surname:"Ferreira",slug:"alice-ferreira",fullName:"Alice Ferreira"},{id:"301803",title:"Prof.",name:"Maria Etsuko",surname:"Myamoto Oshiro",slug:"maria-etsuko-myamoto-oshiro",fullName:"Maria Etsuko Myamoto Oshiro"}],corrections:null},{id:"69663",title:"Effects of Oxidative Stress on Spermatozoa and Male Infertility",doi:"10.5772/intechopen.86585",slug:"effects-of-oxidative-stress-on-spermatozoa-and-male-infertility",totalDownloads:963,totalCrossrefCites:1,totalDimensionsCites:2,hasAltmetrics:0,abstract:"Oxidative stress occurs when the production of potentially destructive reactive oxygen species (ROS) exceeds the body’s own natural antioxidant defences, resulting in cellular damage. Spermatozoa oxidative stress is intimately linked to several reproductive pathologies including the failure of spermatozoa cryopreservation and spermatozoa-egg recognition and fertilization. In this light, this review focuses on (i) the effects of oxidative stress on spermatozoa and application of antioxidants; (ii) production of ROS during cryopreservation; and (iii) oxidative stress in male infertility. This literature describes both a physiological and a pathological role of ROS in fertility. A delicate balance between ROS necessary for physiological activity and antioxidants to protect from cellular oxidative injury is essential for fertility.",signatures:"Yi Fang and Rongzhen Zhong",downloadPdfUrl:"/chapter/pdf-download/69663",previewPdfUrl:"/chapter/pdf-preview/69663",authors:[{id:"292239",title:"Dr.",name:"Yi",surname:"Fang",slug:"yi-fang",fullName:"Yi Fang"},{id:"292240",title:"Dr.",name:"Rongzhen",surname:"Zhong",slug:"rongzhen-zhong",fullName:"Rongzhen Zhong"}],corrections:null},{id:"68141",title:"Nonenzymatic Exogenous and Endogenous Antioxidants",doi:"10.5772/intechopen.87778",slug:"nonenzymatic-exogenous-and-endogenous-antioxidants",totalDownloads:1973,totalCrossrefCites:17,totalDimensionsCites:32,hasAltmetrics:0,abstract:"Nonenzymatic exogenous and endogenous antioxidants play an important role in human health and act as preservatives for cosmetics, pharmaceuticals, and food products. This chapter will discuss the chemical structure and mechanism of action of the most important nonenzymatic small exogenous and endogenous organic molecules that act as antioxidants. The chapter will focus on the structural features, functional groups, properties, biosynthetic origin, and mechanism of action of such antioxidants. It also covers damages that free radicals create and the mechanisms by which they are neutralized by the various antioxidants. The scope of this chapter will be limited to nonenzymatic exogenous and endogenous antioxidants since enzymatic antioxidants have been discussed extensively in several reviews.",signatures:"Ziad Moussa, Zaher M.A. Judeh and Saleh A. Ahmed",downloadPdfUrl:"/chapter/pdf-download/68141",previewPdfUrl:"/chapter/pdf-preview/68141",authors:[{id:"300774",title:"Dr.",name:"Ziad",surname:"Moussa",slug:"ziad-moussa",fullName:"Ziad Moussa"},{id:"306324",title:"Dr.",name:"Zaher",surname:"M. A. Judeh",slug:"zaher-m.-a.-judeh",fullName:"Zaher M. A. Judeh"},{id:"306325",title:"Prof.",name:"Saleh",surname:"A. Ahmed",slug:"saleh-a.-ahmed",fullName:"Saleh A. Ahmed"}],corrections:null}],productType:{id:"1",title:"Edited Volume",chapterContentType:"chapter",authoredCaption:"Edited by"},subseries:{id:"11",series:{id:"10",title:"Physiology",issn:"2631-8261",editor:{id:"35854",title:"Prof.",name:"Tomasz",middleName:null,surname:"Brzozowski",slug:"tomasz-brzozowski",fullName:"Tomasz Brzozowski",profilePictureURL:"https://mts.intechopen.com/storage/users/35854/images/system/35854.jpg",biography:"Prof. Dr. Thomas Brzozowski works as a professor of Human Physiology and is currently Chairman at the Department of Physiology and is V-Dean of the Medical Faculty at Jagiellonian University Medical College, Cracow, Poland. His primary area of interest is physiology and pathophysiology of the gastrointestinal (GI) tract, with the major focus on the mechanism of GI mucosal defense, protection, and ulcer healing. He was a postdoctoral NIH fellow at the University of California and the Gastroenterology VA Medical Center, Irvine, Long Beach, CA, USA, and at the Gastroenterology Clinics Erlangen-Nuremberg and Munster in Germany. He has published 290 original articles in some of the most prestigious scientific journals and seven book chapters on the pathophysiology of the GI tract, gastroprotection, ulcer healing, drug therapy of peptic ulcers, hormonal regulation of the gut, and inflammatory bowel disease.",institutionString:null,position:null,outsideEditionCount:0,totalCites:0,totalAuthoredChapters:"2",totalChapterViews:"0",totalEditedBooks:"1",institution:{name:"Jagiellonian University",institutionURL:null,country:{name:"Poland"}}}}},tags:null},relatedBooks:[{type:"book",id:"7009",title:"Hypoxia and Anoxia",subtitle:null,isOpenForSubmission:!1,hash:"80148bd84e86e5fe1c7527637e8e3be8",slug:"hypoxia-and-anoxia",bookSignature:"Kusal K. 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These have been labelled variously as “ zeolitic”, “ loosely held”, “structural”, “crystal”, “tightly bound” and “external” [1-3]. These labels suggest both the differing apparent energies of H2O as well as their differing apparent structural roles. Three useful distinctions can be made about H2O in compounds:
H2O that varies in content as a continuous function of temperature and pressure
H2O that changes discontinuously at a unique temperature for a given pressure
H2O that is sorbed to external surfaces
The first type (continuously varying H2O) is characteristic of the zeolites and clay minerals and considers that most of the zeolites and clay minerals lose or gain H2O in response to small changes in temperature and pressure over an extended temperature, relative humidity or the nature of cations in exchanged sites.
The second type of H2O is similar in nature to that found in hydrates of salts and considers that dehydration occurs over narrow temperature intervals in some compounds. Some zeolites, like analcime and laumontite, do not exchange water at room temperature. This type can be called “hydrate” H2O and has a specific position in the crystal structure. Hydroxides are excluded from this chapter because the H2O molecule is not identified but is only virtually present as a hydroxyl OH.
The third type of H2O is externally sorbed to the crystal and may be referred to as external. This type is present in quantities much smaller than the H2O present within the structure of any zeolite grain size. In the clay minerals, whose specific surfaces are greater than those of zeolites, the water located in inter-particle spaces, in inter-aggregate spaces and at the surface of uncharged clays minerals indicates that a special status of H2O may be different in the regimes of adsorption or of capillary condensation, and this is not considered in this chapter.
In evaluating the thermodynamic quantities, it is important to define the standard state chosen for a given constituent. In the present study, the standard state for water is chosen as pure water at a temperature of 25°C with a vapour pressure of Po, and for the minerals, the dry compound is at a temperature of 25°C with a vapour pressure of P=0.
The reaction of hydration may be expressed by the following reaction:
If we consider any standard thermodynamic entity of hydration
where
The standard thermodynamic parameters of the hydration water can be calculated if the thermodynamic entities of formation (enthalpy
where H2O(hyd) represents the hydration water. The thermodynamics of the intra-crystalline reaction can be written as follows:
By assuming that the standard thermodynamic entities of the intra-crystalline reaction are equal to zero,
The aim of this chapter is to determine how the thermodynamic entity
Different methods of measurements of thermodynamic entities of hydration are presented in this section:
Hydrofluoric acid solution calorimetry. The calorimetric measurements of the heat of dissolution of anhydrous and hydrated compounds provide the enthalpy of formation to form elements. The enthalpies of hydration are obtained by measuring the difference in the enthalpy of the solution in HF acid at approximately 70°C, of a hydrated and a dehydrated zeolite [4-6] or at 25°C in a HF - HNO3 solution for clay minerals [7].
Transposed-temperature drop calorimetry. The enthalpy of hydration data are obtained by measurements of the heat evolved from a sample dropped at room temperature into a calorimeter maintained at 700–800°C [8], [9-12]. One of the difficulties associated with this measurement includes the enthalpy effects because of the irreversible structural changes at 700–800°C.
Adiabatic low temperature calorimetry. This is performed on the anhydrous and hydrated compounds to determine the third law of entropy for the zeolites [4-6] and clay minerals [7, 13].
Heat of adsorption combined with adsorption-desorption isotherms. This method provides measurements of integral enthalpies of hydration as a function of the degree of hydration. Some of the difficult parameters to control include the amount of H2O adsorbed by the sample (requires knowledge of the amount of H2O in the sample while immersed in water), the accurate measurement of the initial state of dehydration and the potential for irreversible change in the zeolite structure during dehydration such that the sample does not re-adsorb its full capacity of H2O during immersion [14]. For clays, the measurements of heat of adsorption were performed on eight homoionic SWy-1 montmorillonites[15-17] [18] [19] [20] and on vermiculites[21]. One advantage of the method is that it is a direct measurement of the enthalpy of hydration.
Phase equilibriums. The enthalpy of hydration can be determined from the phase equilibrium measurements of the isoteric method, which are plotted as Ln P (or Ln K) versus 1/T at a constant hydration state. The slopes of these lines give the enthalpy of hydration for zeolites [22], [23] and for montmorillonites[24-26].
Gas-adsorption calorimetry. The enthalpies of hydration data are obtained by exposing a bed of zeolite to differing vapour pressures within a calorimeter [27]. One of the difficulties of this method is the kinetic limitations on attainment of equilibrium (slow kinetics requires a very sensitive and stable calorimeter). An advantage of the method is the capacity to measure partial molar enthalpies of hydration directly.
Adsorption-desorption isotherms measured at different temperatures. With the Clausius-Clapeyron relationships, the ability to extract the integral and partial thermodynamic entities of hydration from isotherms at any two temperatures was developed by [28, 29] and applied on montmorillonite in [30] and [31]
Thermochemistry and Raman spectroscopy. A combined study of thermochemistry and raman spectroscopy has been tested on zeolites [32] and clays [33][34].
The thermodynamic data of liquid water and ice are displayed in Table 1. The formation properties of the hydration water may vary depending on the nature of the physical-chemical properties of the anhydrous compound [35]. In any case, when the minerals exist as hydrated phases, the presence of water molecules stabilises them. Thermodynamically, this corresponds to ΔG0hyd< 0 kJ mol-1 or ΔG0f,(H2OHyd) < -237.14 kJ mol-1, the value for bulk water at 250C and 1 bar [36]. Additionally, the maximum entropy is for bulk water and implies that S0(H2OHyd) < 69.95 J K-1 mol-1 [36]. The minimum entropy may be assessed by considering the entropy of Ih ice, as refined by Tardy et al. [37] (44.77 J K-1 mol-1). To give a minimum value for ΔG0f(H2OHyd) is more complicated. Ice cannot be of use, for example, because it is not stable at room temperature, and on the contrary, ΔG0f(Ice Ih) >ΔG0f (bulk water), with –236.59 kJ mol-1. For the enthalpy term ΔH0f(H2OHyd), because ΔG0hyd< 0 kJ.mol-1 and S0(H2OHyd) < S0(bulk H2O) for hydrated minerals, then ΔH0hyd must be negative or ΔH0f(H2OHyd) <ΔH0f(bulk H2O) with -285.83 kJ mol-1 [36]. For the heat capacity of hydration water, very few measurements have been actually performed so far.
Families | Ref. | ΔH°f | ΔG°f | S° | Cp | V |
(kJ mol-1) | (kJ mol-1) | (J K-1 mol-1) | (J K-1 mol-1) | cm3 mol-1 | ||
Liquid water | 1 | -285.84±0.04 | -237.18±0.05 | 69.923±0.03 | 75.576 | 18.064 |
Ice | 2,3 | -292.75±0.1 | -236.59±0.1 | 44.771±0.05 | 42.008 | 19.228 |
Table 1.Average thermodynamic entities (ΔH°f, ΔG°f, S°, Cp and V) of liquid water and ice.
Among the numerous methods of prediction of thermodynamics entities of compounds (salts, and minerals), only twelve are retained and exhibit different values of the thermodynamic entities of ice-like water obtained from the statistical results from the anhydrous and hydrated compounds (Table 2).
Families | Ref. | Nb. | ΔH°f | ΔG°f | S° | Cp | V |
comp | (kJ/mole) | (kJ/mole) | (J/K/mole) | (J/K/mole) | cm3/mole | ||
Sulphates & sulphites | 1 | 41 | -301.4±7.7 | -244.4±7.9 | 41.5±6.0 | 39±5.2 | 14.5±1.2 |
Chlorates & Chlorides | 1 | 34 | -308.3±8.6 | -251.8±8.5 | 43.7±5.9 | 42±2.7 | 14.1±2.3 |
Zeolites | 2 | 15 | 59.1 | ||||
Hydrates | 3 | 342 | -298.6±20.5 | -242.4 | 40.9 | 42.8 | 14.75 |
Silicates | 4 | ? | 39.3±4.2 | 13.7±0.5 | |||
Silicates | 5 | 3 | 54.123 | ||||
Hydrates | 6 | ? | -297.06 | ||||
RE chlorides | 7 | 8 | -297 | 46.4 | |||
Binary comp. of Na | 8 | 42 | -297±8.3 | ||||
Silicates | 9 | 7 | 43.5 | 14 | |||
Silicates | 10 | 7 | -306.99±12.8 | 44.1±2.0 | 14.6±0.09 | ||
Silicates | 11 | 6 | -292.37±4.6 | -239.91±5.7 | |||
Borates | 12 | 23 | -290.42 | -237.28 | 54.86 | ||
U bearing minerals | 13 | 14 | -295.58 | -241.1 |
Average thermodynamic entities (ΔH°f, ΔG°f, S°, Cp and V) of hydration water obtained in different prediction models.
All of these models of predictions are built on a simple additive scheme and require knowledge of the thermodynamic entity of the anhydrous compound, the number of water molecules and the thermodynamic entity of formation of “ice-like” water or of hydration water obtained by statistical regressions. For each thermodynamic entity (enthalpy, free energy, entropy, heat capacity and molar volume), the values are significantly different within the nature of the compounds or minerals. For each prediction model, the nature of family, number of compounds and statistical errors are provided to check the extent and the validity of the model. There appear to be few models of prediction of free energies of hydration, which is the most useful parameter in geochemical modelling. The best way to reach this target is to combine the enthalpy and entropy of hydration. Despite the great diversity of the enthalpy of formation of the hydration water and its great error within different families of compounds, some recent and accurate models of prediction of the enthalpy of hydration are important to introduce for compounds such as salts, zeolites and clays minerals.
To improve the accuracy of prediction, the next section develops several models of prediction based on different kinds of minerals displaying recent measurements of the thermodynamic entities of the hydration water closely related either to the environmental conditions and or to the nature and chemical formulas of the anhydrous compounds.
the enthalpy of hydration of the reaction (6) becomes
where n is the number of molecules of crystalline water contained in the hydrate under consideration and
This parameter is analogous to the enthalpy of dissolution of an anhydrous salt per equivalent (characterised by the product of charges of the cation and anion). The relationships of the enthalpy of hydration of a salt to the number of the molecules of water and to the nature of the salt is:
where
The enthalpy of the formation of ice used in Eq. (7) [50-52] comes from Robie&Waldbaum[53] and is equal to -279.8 kJ mol-1. As this value is very different from those given in table 1, the values of coefficients (
The values of
An example is given by considering the data of all of the sodium salts displayed in Figure 1A and shows the great variation of the enthalpy of hydration having the same number as the crystalline water. The different straight lines are obtained from Eq. (10) with values of
Cations | β | Nb. of data | % error1 | Std dev. | |
(kJ/mol H2O) | |||||
Li+ | -0.277 | -0.341 | 19 | 0.34 | ± 3.58 |
Na+ | -0.294 | 1.759 | 61 | 0.29 | ± 3.44 |
K+ | -0.115 | -9.168 | 15 | 0.66 | ± 10.70 |
Rb+ | -0.360 | -6.769 | 6 | 0.29 | ± 3.38 |
Cs+ | -0.577 | 18.954 | 4 | 0.48 | ± 6.35 |
Be+2 | -0.485 | -3.068 | 7 | 0.25 | ± 3.48 |
Mg+2 | -0.312 | -10.708 | 21 | 0.43 | ± 5.39 |
Ca+2 | -0.270 | -3.892 | 25 | 0.44 | ± 4.64 |
Sr+2 | -0.349 | -1.894 | 20 | 0.32 | ± 5.93 |
Ba+2 | -0.327 | -4.637 | 19 | 0.80 | ± 5.31 |
Zn2+ | -0.211 | -16.461 | 12 | 0.44 | ± 6.57 |
Cd2+ | -0.322 | 2.266 | 8 | 0.33 | ± 4.29 |
Cu+2 | -0.433 | -1.791 | 11 | 0.65 | ± 4.22 |
Ni2+ | -0.176 | -18.056 | 10 | 0.46 | ± 2.81 |
Co2+ | -0.260 | -2.296 | 11 | 0.36 | ± 3.60 |
Fe2+ | -0.136 | -17.806 | 6 | 0.18 | ± 1.58 |
Mn2+ | -0.238 | -5.144 | 15 | 0.25 | ± 6.14 |
Cr+2 | -0.478 | 31.459 | 3 | 0.28 | ± 1.77 |
UO2+2 | -0.247 | -7.945 | 18 | 0.35 | ± 4.80 |
Values of
A – Hydration enthalpy of sodium salts versus the parameter
From the selected average enthalpies of hydration of the different zeolites with their chemical formulas (145 data points), a regression equation for the enthalpy of hydration per mole of water is proposed [54]:
where coefficients a and b are
Coefficients of Eqs. (11) (12) and (13), such as the ratio Al/Si, Al/(Al+Si), FDanh.,
The framework density (FD) [55, 56] represents the number of tetrahedral atoms per 1000 Å3 and are obtained as:
The electronegativity of site Az+, defined by ΔHO=(site A), represents the weighed average of ΔHO=Mz+(aq) of nc different cations in the exchanged site A:
The number of oxygens balancing site Mz+ (in extra-framework sites) is then:
The parameter ΔHO= Mz+ (aq) characterises the electronegativity for a given cationMz+ and is defined as the difference between the enthalpy of formation of the corresponding oxides
where z is the charge of the cationMz+ and x is the number of oxygen atoms combined with one atom of M in the oxide (x = z/2), such that the difference in Eq. (17) refers to one oxygen atom. A set of internally consistent values was presented by Vieillard& Mathieu [54] and is given in Table 4.
The total intracrystalline pore volume, WP, was introduced by Barrer [57] for determining the volume of liquid water that can be recovered thorough the outgassing of the fully hydrated zeolite. Assuming that the unit cell volume of zeolitic water is the same as that of liquid water (
where Vu.c. hyd. represents the unit cell volume of a hydrated zeolite containingnH2O water molecules. Assuming that the number of water molecules nH2O varies from 0 to nH2O max, the unit cell volume of a zeolite can be directly related to the number of water molecules. Although such variations in the unit -cell volume do occur, let us assume a linear variation in the unit-cell volume as a function of the number of water molecules:
where Vu.c. anh. represents the unit-cell volume of the anhydrous zeolite. Parameter k weights the variation in the unit-cell volume between an anhydrous zeolite and a fully hydrated zeolite per one water molecule. This parameter can be calculated from the available unit-cell volumes of anhydrous and fully hydrated zeolites. Thus, knowledge of the number of water molecules and the unit-cell volume of anhydrous and hydrated zeolites is required for the calculation of the water porosity:
Ions | ΔHO=Mz+(aq) | Ions | ΔHO=Mz+(aq) |
(kJ mol-1) | (kJ mol-1) | ||
Li+(aq) | -40.90 | Ca+2(aq) | -92.1 |
Na+(aq) | 65.80 | Mg+2(aq) | -134.6 |
K+(aq) | 141.00 | Fe+2(aq) | -181.58 |
Rb+(aq) | 163.24 | Mn+2(aq) | -164.4 |
Cs+(aq) | 170.0 | Zn+2(aq) | -197.07 |
Ba+2(aq) | -15.6 | La+3(aq) | -124.8 |
Sr+2(aq) | -40.4 | H+(aq) | -285.83 |
Parameter ΔHO=Mz+ (aq) of selected cations[54].
By eliminating 9 erroneous data points [54], the regression coefficient for 136 data is R2= 0.880, with a standard error of ± 3.46 kJ mol-1 for all data, regardless of the nature of the experimental data. Figure 2 displays the predicted enthalpy of hydration of zeolitic water calculated from Eqs. (11) (12) and (13) versus the experimental enthalpy of hydration coming from the different technical measurements. Regression coefficients and standard errors are different within the two main groups: R2= 0.88 and std. err. = ± 3.41 kJ mol-1 for TTDC data (67 data points), R2= 0.658 and std err. = ± 2.66 kJ mol-1 for the “IC” data (57 data points).
When Al/Si and Al/(Al+Si) = 0, the hypothetical integral enthalpy of water in zeolites obtained by the extrapolation of Eq. (11) is 0, which corresponds to the enthalpy of hydration of water in cordierite (2.2 ± 1.6 kJ mol-1 from Carey [58]). Unlike zeolites, the water in cordierite is not coordinated by cations, so the molecular environment of H2O in cordierite is similar to that of H2O in water.
Predicted enthalpy of the hydration of zeolitic water calculated from
A detailed computation of the enthalpy of hydration is given as an example for three natural clinoptilolites (-Ca, -Na and –K)with the following chemical formula given by [22]:
Clinoptilolite-Na: (Ca0.12Mg0.29K0.75Na5.21)(Al6.78Fe0.06Si29.2)O72.05-21.3H2O
Clinoptilolite-K: (Ca0.13Mg0.25K5.84Na0.27)(Al6.85Fe0.1Si29)O71..9-18.5H2O
Clinoptilolite-Ca: (Ca2.34Mg0.57K0.9Na0.18)(Al6.7Fe0.017Si29)O71..8-21.9H2O
The values of the ratio Al/Si yield a constant value of 0.235. The electronegativity of the exchangeable site Az+ for clinoptilolite-Na is, for example, the average electronegativity of four cations (Na+, K+, Ca2+ and Mg2+ (table 4)) as follows:
i.e.,
The unit-cell volume of the anhydrous clinoptilolite–K (V u.c.) is 2019.51 Å3[59]. This means that there are 35.95 tetrahedral atoms (6.95+0.1+29) in 2019.51 Å3; which indicates that FDanh.= 17.8 tetrahedral atoms in 1000Å3. The unit-cell volume of the hydrated clinoptilolite-K (at saturation or fully hydrated) with 18.5 moles of zeolitic waters is 2089.50 Å3[54], which is slightly greater than the anhydrous form and allows the setting of the relationship of water porosity versus the number of hydration water moles:
From these previous examples, the parameters requested for the prediction of the enthalpy of hydration are displayed in table 5 for the three clinoptilolites (-Na, -K and –Ca).
Zeolite minerals | V u.c.anh. | Vu.c. hydr. | k | ΔHO= | FD. | WP | Al/Si |
(Å3) | (Å3) | Site A | Anh. | ||||
kJmol-1 | |||||||
Clinoptilolite -Na | 2000.00 1 | 2140.00 1 | 6.35 | 51.39 | 18.02 | 0.31 | 0.23 |
Clinoptilolite-K | 2019.51 2 | 2089.50 2 | 3.78 | 109.16 | 17.80 | 0.26 | 0.24 |
Clinoptilolite -Ca | 2019.51 2 | 2089.50 2 | 3.20 | -64.60 | 17.78 | 0.31 | 0.23 |
From the values given in table 5, the enthalpy of hydration of the zeolitic water,
The model of the computation of the enthalpy of hydration of the hydration water represents a very useful tool and contributes to the knowledge of enthalpies of formation of hydrated zeolites from anhydrous ones [61].
A useful method for avoiding complications at the outset of a thermodynamic analysis is to emphasise the H2O rather than the zeolite structure. Using such an approach, the equilibriums can be consideredas the equilibrium between the H2O in the fluid-vapour phase and the H2O in the zeolite. According to the definition of equilibrium, the chemical potential of H2O in the vapour phase must equal thechemical potential of the H2O component in the zeolite. Any series of measurements of the amount ofH2O in zeolite at a known fugacity (or partial pressure of H2O under ideal gas conditions) providesthe basis for the thermodynamic description of the system. The most elegant approach to develop athermodynamic formulation is to know the partial molar enthalpy of hydration,
Zeolite minerals | |||
predicted(kJ mol-1 H2O) | measured(kJmol-1 H2O) | References | |
Clinoptilolite.-Na | -22.20 -22.20 | -30.17 | [22] |
Clinoptilolite -K | -20.24 | -23.97 | [22] |
Clinoptilolite-Ca | -29.03 | -32.87 | [22] |
Predicted and experimental enthalpy of hydration,
The bulk enthalpy of hydration or the integral enthalpy of hydration can be used as the product of the enthalpy of hydration of the water times the number of zeolitic water:
As the integral hydration enthalpy
The fractional water content can be obtained if the maximum number of zeolitic waters is known at the saturation state and is equal to:
From values of table 5, the partial molar enthalpy of clinoptilolites K, Na and Ca can be calculated versus the fractional water content and plotted in Figure 3 with the experimental partial molar enthalpies measured from immersion calorimetry [62] and from thermogravimetry [22]. The modelled values of the partial molar enthalpy for the three clinoptilolites appear to be closer to the data from the immersion calorimetry than from thermogravimetry. The second important point is the fact that the calculated and experimental partial molar enthalpy of hydration has a similar behaviour.
The partial molar enthalpy of hydration per mole of H2O increases smoothly from low water content to high θ and indicates that the H2O in clinoptilolites occupies a continuum of energetic states. This is not the case for chabazite-Ca [23], which exhibits three energetically distinct types of H2O.
This shows that, within different zeolites with the same exchangeable cation, the partial molar enthalpy as a function of the hydration degree may display different functions. This is the reason why the fundamental relationship verifying the enthalpy of hydration by means of the chemical composition and the accurate knowledge of the unit-cell parameters of anhydrous and hydrated zeolites needs to be improved with new data of hydration enthalpy of the partially hydrated zeolites on the one hand and a better fit of the effective water porosity as a function of the hydration degree on the other hand. Then, the thermodynamic description of the hydration-dehydration process can be modelled as a function of pressure and temperature with the contribution of predicted enthalpies of hydration and entropies of hydration.
Partial molar enthalpy of hydration of K-, Na- and Ca- clinoptilolites derived from a model in [
Unlike zeolites, smectites are clearly not inert phases, as the particles size increases with the relative humidity [15]. Adsorbed water is distributed throughout the interlayer space, the outer surfaces of particles and the open pores space in the sample. [15-17] provided measured values of the surface covering waters for both the hydration and dehydration reactions of a set of eight homo-ionic SWy-1 montmorillonites saturated by alkali and alkaline-earth cations from their BET specific surface area (Table 1) and their basal spacing variations with relative humidity. To quantify the effective amount of water involved in the hydration reaction, the amount of poral H2O must be quantified and subtracted from the total amount of H2O taken up by the clay sample. The number of external surface water molecules (expressed in mmol/g dry clay) can be expressed as a function of relative humidity [63]. There are numerous papers about the adsorption-desorption isotherms performed on various clays minerals, but few are devoted to the acquisition of enthalpy of hydration-dehydration on SWy-1 [15-17, 64] [18, 19, 30] [20] [34] [24, 26, 65] [25] and on vermiculites [21].
All recent predictive models of the hydration of smectites are based on an approach that uses the solid solution initiated by Ransom &Helgeson[66]. The hydration of a smectite is considered through the following reaction between hydrated and dehydrated end-members:
where nm represents the maximal number of moles of water that can be included in the smectite on the basis of a half-cell (i.e., O10(OH)2). One considers the interlayer water H2O(i) (where subscript i stands for interlayer) as a variable weighing the hydration ratio. The amount of interlayer water in a smectite is proportional to the mole fraction of hydrated end-member: x*H2O= nm*xhs=(1-nm)*xas;to the mole fraction of the hydrous end-member, xhs or to the anhydrous end-members xas. Ransom &Helgeson[66] considered the system hydrated smectite – anhydrous smectite + bulk water as a strictly regular binary solid solution by considering the free energy only. Thus, the excess free energy of mixing can be expressed as follows:
where WG is an excess mixing constant. The integral Gibbs free energy of hydration is:
in which
Vidal et al. [68-69] have assumed that a smectite could be considered strictly regular solid solutions between four end-members with 0.7 H2O, 2 H2O, 4 H2O, and 7 H2O. Those compositions correspond to four different hydrated states (with 0, 1, 2, and 3 water sheets, respectively).For any strictly regular solid solution, the integral enthalpy of hydration is expressed as the following:
with
The hydration enthalpy is retrievedfrom data of [24] for montmorillonite –Na and –K and derived from differential heats of adsorption obtained from the measurements of the heat of immersion [18, 20] for Na-, Ca- and Mg- montmorillonite. Thus, an integral enthalpy of hydration
Units (kJ mol-1) | H2O | Cs | Rb | K | Na | Ba | Sr | Ca | Mg |
4.5 | -289.93 | -290.23 | -290.45 | -291.25 | -294.14 | -294.57 | -294.86 | -295.71 | |
0-0.7 | -295.50 | -299.71 | -301.43 | -302.86 | |||||
WH2 | 0. | 0. | 0. | 0. | |||||
0-2 | -293.58 | -295.90 | -298.60 | -300.05 | |||||
WH2 | -10. | -10. | -10. | -10. | |||||
0-4 | -291.96 | -293.83 | -296.25 | -297.62 | |||||
WH 2 | -10. | -10. | -10. | -10. | |||||
0-7 | -291.05 | -292.33 | -293.86 | -294.69 | |||||
WH2 | -10. | -10. | -10. | -10. | |||||
5.5 | -287.47 | -288.01 | -288.16 | -290.01 | -292.10 | -292.65 | -294.72 | -296.56 | |
16.0 | 19.0 | 15.0 | 8.0 | -60.0 | -55.0 | -60.0 | -49.0 | ||
-90.0 | -95.0 | -68.0 | -33.0 | -75.0 | -90.0 | -100.0 | -129.0 |
Standard thermodynamic enthalpy
The integral hydration enthalpy is obtained by the following relationships:
in which
The curve 1 in Figure 4A (yellow dotted line) comes from model of Ransom &Helgeson [66], is linear and is obtained from the following equation of integral enthalpy of hydration:
where the coefficient -24.39 is computed from
A – Integral enthalpy of hydration versus the number of interlayer cation; B – Standard enthalpy of formation of interlayer water versus the nature of the interlayer cation.
The curve 3 (black line) in Figure 4A comes from the model of Vieillard et al. [63] and is represented by the following equation:
It appears that integral enthalpy of hydration modelled by Vieillard et al. [63] (black line) based on experimental measurements of heat of adsorption from [15-17] encompasses nearly all experimental data. As the standard entropy of hydration is assumed constant in [66] and [68] models, the integral hydration enthalpies provided by these two previous models are nearly linear. Those obtained by [68] exhibit three sections of curves corresponding to the three states of hydration (1, 2 and 3 water layers).
In Figure 4B, a relationship between the standard state enthalpy of interlayer water with the nature of the interlayer cation located in the SWy-1 montmorillonite with a constant layer charge of 0.38, characterised by its electronegativity (ΔHO=Mz+ (aq), Table 4) is proposed [63] and given as follows:
Lowering the electronegativity of cation in the interlayer sites stabilises the enthalpy of formation of the interlayer water. It should be kept in mind that Eq. (39) has been settled for the same support,
where
J/K/mole | J/K/mole | J/K/mole | J/K/mole | |
Cs+ | 64.6 | 163.5 | -348.0 | -78. |
Rb+ | 63.8 | 142.0 | -355.0 | -84. |
K+ | 63.7 | 104.0 | -267.5 | -93. |
Na+ | 59.8 | 49.1 | -94.0 | -130. |
Ba2+ | 55.7 | -116.0 | -211.5 | -224. |
Sr2+ | 54.3 | -117.8 | -244.5 | -261. |
Ca2+ | 51.5 | -93.5 | -270.5 | -271. |
Mg2+ | 45.4 | -42.8 | -380.0 | -350. |
Standard thermodynamic enthalpy
Figure 5A displays the comparison of the integral entropy of hydration of a smectite- Na computed from the three models [67] [68] and [63] developed previously with different experimental values.
As indicated in the enthalpy section, integral hydration entropies modelled by [66] (yellow dotted line, N°1) and [68] (green dotted line, N°2a, 2b and 2c corresponding to 1st, 2nd and 3rd layer) are linear and merge together. In the model proposed byVieillard et al. [63], three calculated integral entropies of SWy1-Na –water system were plotted in Figure 5Aand correspond to the adsorption (red line), the desorption (blue line) and the theoretical equilibrium water – Swy1-Na (black line, N° 3), whose equation is given:
The comparison of hydration-dehydration curves calculated by [63] with those provided by Fu et al. [34] show an opposite interpretation. The data from [34] show that integral entropies during adsorption are less negative than those during desorption. Data from our model show the opposite. This difference is explained by the fact that from experimental works of [34], adsorption follows desorption, while with our data, desorption follows adsorption. Thus, a maximum entropy difference between hydration and dehydration functions can be depicted and is equal to 18 J/K/mole. These observations show the importance of movement of exchangeable cations from ditrigonal cavities and the rotation of tetrahedrals in the tetrahedral sheets when dry collapsed layers are progressively exposed to water vapour.
A – Integral entropy of hydration versus the number of interlayer cation; B – Standard entropy of formation of interlayer water versus the nature of the interlayer cation.
A correlation between the entropy of interlayer cation
Negative values of the hydration entropy of the hydrated ion lower the hydration entropy of the interlayer water.
Heat capacity function (298.15- 500 K) | ||
Eq. A | [41] | |
Eq. B | [74] | |
Eq. C | [45] | |
Eq. D | [72] |
Heat capacity functions for zeolites minerals
Heat capacities of the hydration in zeolites have been performed by Neuhoff& Wang [75] on three zeolites (analcime, natrolite and wairakite) and exhibit marked variations in the heat capacity of hydration with temperature. Four zeolites (mordenite, wairakite and two different values from different sources for analcime and natrolite) for which the heat capacity of zeolitic water can be obtained by a difference between the heat capacities measured on both the anhydrous and the hydrated phases [72] are representedin Figure 6A. Also displayed are the heat capacity values of water in all its states (ice, liquid and vapour) for comparison [35]. The heat capacity values of zeolitic water obtained by minimisation techniques (Eq. D of table 9, turquish line) matches with the heat capacity function equations of [74] and [45].
Heat capacity of zeolitic water versus temperature: A – Heat capacities of zeolitic water in zeolites, in different prediction models and of water in its various states (l for liquid, c for ice and g for vapour); B – Experimental heat capacities of zeolitic waters in natural zeolites and predicted heat capacities from
Eq. D of table 9 provides a statistical error of 4.51%, 2.35% and 4.18% for hydrated zeolites at 298.15 K, 400 K and 500 K, respectively. To improve the accuracy of the prediction of the heat capacity of hydrated zeolites, one considers the normalised hydration volume, which is the difference of unit-cell volume (Vu.c.) between the hydrated and dehydrated forms for any zeolite per zeolitic water molecule [72]:
The heat capacities of hydration water given in Figure 6B have been calculated for the four hydrated zeolites (mordenite, analcime, wairakite and natrolite) from the unit-cell volumes of their dehydrated and hydrated forms[72]. It can be observed that the heat capacities of hydration water calculated in this way are much better than those obtained by Eq. D of table 9 (indicated in Fig. 6B as a turquishfull line). With this improvement, the errors made on hydrated zeolites decrease to 3.5%, 2.35% and 3.89% at 298.15 K, 400 K and 500 K, respectively.
This heat capacity equation has also been used by [68] and by [63] in the behaviour of thermodynamic entities versus temperature.
The relationships among the free energy change, enthalpy of reaction and entropy for an isothermal process is:
where ΔG stands for free energy change, ΔH for enthalpy of reaction, ΔS for the change in entropy and T for the absolute temperature. This relationship holds true for both the integral entities that are represented by
The predicted values contribute to the variations of solubility products and the cation selectivity constants among the series of salts. An example is given in [78] for two series of hydrated salts of MgCl2 and SrCl2.
For zeolites and clays, the adsorbent (a single smectite or zeolite phase) is supposed to be inert so that the derived enthalpy and entropy functions formally represent the energy variations between the adsorbed and the bulk water.
The integral free energy of hydration
where R = 8.314 J.mol-1K-1 is the ideal gas constant, n is the amount of adsorbed water, P is the partial water vapour pressure, and P0 is the saturated water vapour pressure at temperature T (P/P0 = Relative Humidity/100). This value can be determined by plotting R*T*Ln(P/Po)versus the water content n (adsorbed or desorbed) and determining the area under the curve from 0 to nw. When nw approaches 0, R*T*Ln(P/Po) approaches infinity, making integration somewhat difficult.
A - Adsorption-desorption isotherms; B - Integral free energy of hydration versus the number of moles of interlayer water; C - Integral free energy of hydration versus the relative humidity; D - Free energy of formation of the interlayer water versus the relative humidity.
In each figure, the data of the free energy of hydration (Eq. 50) from the experimental isotherms [15, 16] (blue square for adsorption and red square for desorption) and the free energy of hydration are computed and are reported for comparison of three different works: the Vieillard et al. model [63] (blue, red and black lines for adsorption, desorption and theoretical equilibrium, respectively), the Ransom &Helgesonmodel [66] (dotted yellow line), and the Vidal &Dubacq model [68] (dotted green line). For the adsorption and desorption reactions, the modelled isotherm calculated by the Vieillard et al.model[63] (blue and red lines, respectively) agrees well with the experimental data acquired by [15, 16] in high relative humidity.
At low relative humidity, the uncertainty appears very important between the experimental desorption data and the desorption curve from the model in [63] (3 kJ/mol for integral free energy, Fig C) due to the analytical limits and mathematical constraints.
The theoretical equilibrium (black line) suggests that the hydration of a Na-SWy-1 begins at only R.H.= 0.15 (Figure 7A), which correlates well with the experimental adsorption but not with the desorption. The integral Gibbs free energy of hydration (figure 7B and 7C) and the Gibbs free energy of the interlayer water (Figure 7D) of the theoretical equilibrium between the water and Na-Smectite (black line) are plotted and correspond to the average values of calculated adsorption-desorption isotherms. The theoretical curve of equilibrium between the water and Na-smectite provided by Ransom &Helgeson [66] displays a small number of moles of the interlayer water close to saturation, while those of Vidal &Dubacq[68] reproduce this stepwise behaviour fairly well because it assumes three solid solutions with 3 end-members (0.7 H2O, 2 H2O, 4.5 H2O). However, it does not match the behaviour of water adsorption versus relative humidity, which is not a step function. The advantage of this approach is that it allows reproducing the observed stepwise evolution of the smectite volume and water content with varying T and relative humidity. At low relative humidity, as the hydration of a Na-SWy-1 begins at only R.H.= 0.15, the computations from [68] and [66] (green and yellow dotted lines) do not match the observed isotherms because there is a strong hydration in the RH= 0.0- 0.18 range. During the interval of R.H.=0.0-0.2, the adsorption of water molecules occurs predominantly on the external surface of tactoids (basal external faces and edges of tactoids). This explains why we observe a very negative integral free energy in the low relative humidity domain for these two models (green dotted line and in a less extent, yellow dotted lines). The necessity to take into account only the hydration water, sensu-stricto, is justified. This procedure has been incompletely performed by Ransom &Helgeson [66] with the external surface of a kaolinite to estimate the amount of surface covering water, while Vidal &Dubacq [68] made no correction on the gravimetric waters. At high relative humidity, Vidal &Dubacq [68] proposed a third step of hydration, with the number of water molecules increasing up to 7 moles per O10(OH)2. All of the experimental isotherms performed by [15, 16] exhibit an increase in the water contents beyond RH = 0.9, identified as osmotic water. The osmotic swelling of the sodium montmorillonite corresponds to an iso-enthalpic effect, with the heat of adsorption being constant. The theoretical equilibrium between water and Na-SWy-1 (black line) matches the experimental dehydration near saturation.
The cationic exchange and hydration reactions are intimately related, and the cationic exchange reactions not only modify the interlayer composition but also imply changes in the interlayer water content. These changes can be quite significant and can be evaluated using the Vieillard et al. model [63], which provides a theoretical number of moles of interlayer water and integral thermodynamic properties (H, S and G) for the SWy-1 montmorillonites. Thus, the cationic exchange reactions may depend on an external parameter, such as the relative humidity.
This chapter demonstrated some useful relationships in the prediction of thermodynamic entities. Some important areas are still lacking and deserve further study.
Among the anhydrous and hydrated salts, the relationships between the entropy and molar volume may exist and will improve the prediction of the entropy of hydration. The function of the average heat capacities for the hydration water is lacking and will help in characterising the behaviour of the crystalline water versus temperature.
In the zeolite field, the relationships among the molar volume, water content and relative humidity may exist within zeolites families with a reversibility in the hydration-dehydration processes. These relationships will contribute to a better understanding of the behaviour of partial molar enthalpy versus the degree of saturation or versus the relative humidity.
In the clay Minerals, three following recommendations are needed: 1) to dissociate the hydration water from the gravimetric water; 2) to measure the heat of hydration among the dioctahedral and trioctahedral clays; and 3) to find a relationship between the hysteresis and the entropy of the hydration-dehydration by the molecular modellings. With these three aims, the knowledge of mechanisms of the hydration within clay minerals will advance our understanding of cationic exchange in soils under various physical and chemical constraints.
Financial support from the French National Radioactive Waste Management Agency (ANDRA), from the French Geological Survey(BRGM) and from the national council for scientific Research (CNRS) is gratefully acknowledged. Special thanks to Ph. Blanc, H. Gailhanou and Cl. Fialips for their effective and decisive contribution to this document.
Uropathogenic
Adhesins are adhesive organelles, notably fimbriae, that promote bacterial colonization. Some adhesins also promote bacterial invasion of the host cell. Adhesins are thought to be the most important virulence-associated molecules which function in UPEC pathogenicity. The adhesins can also directly trigger host and bacterial cell signaling pathways. They can also facilitate the delivery of other bacterial products to the host tissues [17]. Prominent bacterial cell surface virulence factors, which play significant roles in UPEC pathogenicity include type 1 fimbriae [11]; Class I, Class II, and Class III of P-fimbriae [18, 19, 20]; Dr. family of adhesins for binding to the decay-accelerating factor (DAF) [21]; Curli fimbriae which functions as binding factor and biofilm producer [22]; and S-fimbriae [14, 23, 24]. Type 1 fimbriae have the most significant effects in UTIs as they enhance bacterial survival and growth, enhance inflammatory reaction at the mucosa, bacterial invasion, and control biofilm production [7]. P-fimbriae have the second most prominent role in UPEC-associated pathogenesis of human ascending UTIs and pyelonephritis. They promote UPEC adherence to the matrix of the mucosa and tissues and trigger cytokine production [25, 26, 27, 28, 29, 30].
UPEC secrete several virulence toxins which are responsible for the damage of the host cells and host inflammatory response. α-hemolysin (HlyA) is the most virulent toxin produced by UPEC. The effects of HlyA in UTIs are dependent on its dosage produced by UPEC. At high concentration, HlyA destroys the erythrocytes and allow UPEC to break through the mucosal barriers, damage immune system, and depletes iron stores of the host [31, 32, 33, 34]. At low concentration, HlyA induces cell death in the bladder using proinflammatorycaspase-1/caspase-4. This causes kidney damage and scarring; oscillations of Ca2+; ascension and colonization of ureters and kidney parenchyma in the renal tubule epithelia resulting in the disruption of normal flow of urine [35, 36, 37, 38]. The stimulation of
Urinary tract has limited iron. However, UPEC are able to produce small iron chelator molecules, known as siderophores, to scavenge ferric iron (Fe3+) in the host. The most prominent ones are yersiniabactin, salmochelin, and aerobactin [48, 49]. The yersiniabactin and its receptor, FyuA, are encoded in a PAI [50, 51]. It has also been reported that for efficient biofilm formation by UPEC, FyuA is required [52]. UPEC also secretes another important hydroxamate siderophore called aerobactin. This is produced from the condensation of two lysine and a citrate molecules. During UPEC invasion, the bacterium secretes salmochelin. Its outer membrane siderophore receptor (IroN) transports different catechol siderophores, including N-(2,3-dihydroxybenzoy)-L-serine and enterochelin also called enterobactin [53]. Enterobactin has less solubility and stability than aerobactin [54, 55, 56] but has higher iron affinity than aerobactin in aqueous [55, 57]. UPEC also uses enterobactin for Fe3+ scavenging in the urinary tract [9]. However, enterobactin can be inactivated by the host proteins such as serum albumin and siderocalin thereby preventing its uptake [58]. UPEC overcomes this instability by modifying the enterobactin to salmochelin by glucosylation through the enzymatic action of glucosyltransferase and prevents it from being recognized by the host proteins [9]. Also, UPEC has another iron acquisition system called haemin uptake system consisting of Ton-B dependent receptor (ChuA) and heavy metal associated (
UPEC-associated fitness and virulence. Adapted from the work by Servin [
Lipopolysaccharide (LPS) is a major part of the cell wall which has highly conserved lipid A-core and repeating O-antigen subunits which vary in different strains of
Capsule is made up of polysaccharides and it covers and protects UPEC from various harsh environmental conditions [66]. The capsule helps UPEC to resist phagocytosis and bactericidal effects of complements in the host. It also confers antimicrobial resistance and antiserum activity to UPEC [54, 61]. Capsules like K1 and K5 interfere with the proper response of the humoral immunity of the infected host [66]. The K1 polysaccharide plays a significant role in intracellular bacterial community (IBC) development and the pathogenesis of several UTI stages [54, 67].
Toll receptor (TIR)/interleukin1 (IL-1) receptor domain-containing protein (TcpC) is a novel class of virulence factors that destabilize TIR signaling for UPEC to survive during UTIs [68]. Interaction of TcpC with myeloid differentiation primary response 88 (MyD88) found in the host ends the downstream signaling pathways mediated by TLRs [69].
UPEC produces outer membrane protease T (OmpT) that catalyzes plasminogen activation to plasmin [70]. OmpT helps UPEC to persist in the urinary tract when protamine and other cation peptides cleave with antibiotic activity [71, 72]. UPEC also decreases cytokines production by blocking nuclear factor kappa-light-chain-enhancer of activated B cells (NF-ĸB) [68]. In Table 1, prominent UPEC virulence factors, their role and genetic markers are presented.
Virulence factor | Role | Genetic markers/gene name | References |
---|---|---|---|
Afimbrial adhesions | Binding factor | [23, 24, 54] | |
Cytotoxic necrotizing factor 1 | Toxin | [38, 39] | |
Curlifimbriae | Binding factor | [22] | |
Dr family of adhesions | Binding factor | [21] | |
Haemin | Iron uptake and biofilm formation | [59, 60, 61] | |
Type 1 fimbriae | Binding factor | [8] | |
Ferric yersiniabactin uptake receptor | Iron uptake and biofilm formation | [62] | |
α-hemolysin | Lyses red blood cells | [33] | |
Salmochelin | Siderophore receptor | [51] | |
Aerobactin | Iron chelation and uptake | [50] | |
Outer membrane protease T | Outer membrane protease production to degrade protamine peptides | [73, 74] | |
Uropathogen specific protein | Movement of UPEC from the urinary tract to the bloodstream | [42] | |
Class I, Class II, and Class III P-fimbriae | For binding to the uroepithelial cells | [18, 20, 21] | |
Serine-protease autotransporter toxin | Vacuolation and tissue damage | [73, 74] | |
S-fimbrial family | Binding factor | [8, 23, 24] |
Virulence factors of uropathogenic
Apart from possessing virulence factors, for the medical importance of
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After finishing his P. hD degree in 1992, he served in the Industry as a Scientific Officer and continued his academic career as a visiting scholar for a number of educational institutions. In 1996 he joined National University of Science & Technology Pakistan (NUST) as an Associate Professor; NUST is one of the top few universities in Pakistan. In 1999 he joined an International Company Lineo Inc, Canada as Manager Compiler Group, where he headed the group for developing Compiler Tool Chain and Porting of Operating Systems for the BLACKfin processor. The processor development was a joint venture by Intel and Analog Devices. In 2002 Lineo Inc., was taken over by another company, so he joined Aalborg University Denmark as an Assistant Professor.\nProfessor Akbar has truly a multi-disciplined career and he continued his legacy and making progress in many areas of his interests both in teaching and research. 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thermoregulation and being a resource for stem cells. Hair is a derivative of the epidermis and consists of two distinct parts: the follicle and the hair shaft. The follicle is the essential unit for the generation of hair. The hair shaft consists of a cortex and cuticle cells, and a medulla for some types of hairs. Hair follicle has a continuous growth and rest sequence named hair cycle. The duration of growth and rest cycles is coordinated by many endocrine, vascular and neural stimuli and depends not only on localization of the hair but also on various factors, like age and nutritional habits. Distinctive anatomy and physiology of hair follicle are presented in this chapter. Extensive knowledge on anatomical and physiological aspects of hair can contribute to understand and heal different hair disorders.",book:{id:"5461",slug:"hair-and-scalp-disorders",title:"Hair and Scalp Disorders",fullTitle:"Hair and Scalp Disorders"},signatures:"Bilgen Erdoğan",authors:[{id:"193661",title:"Dr.",name:"Bilgen",middleName:null,surname:"Erdoğan",slug:"bilgen-erdogan",fullName:"Bilgen Erdoğan"}]},{id:"42520",doi:"10.5772/55026",title:"Discovery and Delineation of Dermatan 4-O-Sulfotransferase-1 (D4ST1)-Deficient Ehlers-Danlos Syndrome",slug:"discovery-and-delineation-of-dermatan-4-o-sulfotransferase-1-d4st1-deficient-ehlers-danlos-syndrome",totalDownloads:2844,totalCrossrefCites:4,totalDimensionsCites:8,abstract:null,book:{id:"3038",slug:"current-genetics-in-dermatology",title:"Current Genetics in Dermatology",fullTitle:"Current Genetics in Dermatology"},signatures:"Tomoki Kosho",authors:[{id:"153541",title:"Dr.",name:"Tomoki",middleName:null,surname:"Kosho",slug:"tomoki-kosho",fullName:"Tomoki Kosho"}]},{id:"52801",doi:"10.5772/66156",title:"Psychosocial Aspects of Hair Loss",slug:"psychosocial-aspects-of-hair-loss",totalDownloads:2558,totalCrossrefCites:6,totalDimensionsCites:7,abstract:"Hair loss (alopecia) is a common dermatological condition that affects men and women of all ages. It can be due to a wide variety of causes including scarring and non-scarring diseases. Although alopecia is not a life-threatening condition, it has significant psychological impact on the quality of life. Mental disorders such as anxiety, depression, social phobia, posttraumatic stress disorder, and suicidal thoughts are increased among alopecia patients. On the other hand, alopecia frequency increases during the course of psychological disorders. In this chapter, psychosocial aspects of hair loss and the relationship between alopecia and psychological disorders are reviewed.",book:{id:"5461",slug:"hair-and-scalp-disorders",title:"Hair and Scalp Disorders",fullTitle:"Hair and Scalp Disorders"},signatures:"Hilal Gokalp",authors:[{id:"193580",title:"M.D.",name:"Hilal",middleName:null,surname:"Gokalp",slug:"hilal-gokalp",fullName:"Hilal Gokalp"}]},{id:"62733",doi:"10.5772/intechopen.79807",title:"Ethosomes: An Exciting and Promising Alcoholic Carrier System for Treating Androgenic Alopecia",slug:"ethosomes-an-exciting-and-promising-alcoholic-carrier-system-for-treating-androgenic-alopecia",totalDownloads:1091,totalCrossrefCites:1,totalDimensionsCites:5,abstract:"Androgenetic alopecia (male-pattern hair loss) is characterized by the deposition of dihydrotestosterone at the pilosebaceous unit of the scalp. Oral administration of drugs (like finasteride) which can reverse androgenic alopecia causes undesired effects to the body. Targeting these drugs directly to the pilosebaceous unit of the scalp will enhance the pharmacological response at the desired site by reducing undesired systemic side effects. This chapter discusses about ethosomes, a specially tailored ethanolic vesicular carriers which can efficiently deliver various drugs with different physicochemical properties to and through the skin. The unique characteristics of the ethosomal carriers, their composition, preparation methods, and the mechanism of permeation, safety, and practical experience (finasteride and herbal extracts) have been discussed in detail.",book:{id:"6961",slug:"alopecia",title:"Alopecia",fullTitle:"Alopecia"},signatures:"Veintramuthu Sankar, Santhanam Ramesh and Karthik Siram",authors:[{id:"254541",title:"Prof.",name:"Sankar",middleName:null,surname:"Veintramuthu",slug:"sankar-veintramuthu",fullName:"Sankar Veintramuthu"},{id:"260986",title:"Mr.",name:"Karthik",middleName:null,surname:"Siram",slug:"karthik-siram",fullName:"Karthik Siram"},{id:"260991",title:"Dr.",name:"Santhanam",middleName:null,surname:"Ramesh",slug:"santhanam-ramesh",fullName:"Santhanam Ramesh"}]},{id:"63066",doi:"10.5772/intechopen.79656",title:"Pharmacological Treatment of Alopecia",slug:"pharmacological-treatment-of-alopecia",totalDownloads:1462,totalCrossrefCites:1,totalDimensionsCites:3,abstract:"In this chapter, we will explore non-surgical treatments of alopecia. Unlike many other areas of medicine, pharmacological treatments for alopecia are relatively new. There are only two treatments which are approved by the Food and Drug Administration (FDA); the rest are drugs developed for other indications which have gained popular off-label use to promote hair growth. The reasons for this are many, including the designation of alopecia by the FDA as a cosmetic disease. This designation has restricted alopecia development programs to compounds with virtually no side effects. Unfortunately, it has also led to off-label use of far more dangerous compounds as alopecia treatments, without the benefit of controlled trials. There is a growing recognition that alopecia, particularly alopecia areata and chemotherapy-induced alopecia, are disorders which significantly alter the quality of life, similar to acne vulgaris and psoriasis, and merit treatment accordingly. There have also been several recent advances in our understanding of the hair cycle, revealing new targets for developing alopecia therapies. As a result, there is a more robust slate of programs for developing new pharmacological treatments for alopecia. In this chapter, we will review current pharmacological treatments for alopecia and selected treatments under development (i.e., those with significant preclinical or clinical data which have appeared in the published literature).",book:{id:"6961",slug:"alopecia",title:"Alopecia",fullTitle:"Alopecia"},signatures:"Robert Gensure",authors:[{id:"16515",title:"Dr.",name:"Robert",middleName:null,surname:"Gensure",slug:"robert-gensure",fullName:"Robert Gensure"}]}],mostDownloadedChaptersLast30Days:[{id:"53880",title:"Anatomy and Physiology of Hair",slug:"anatomy-and-physiology-of-hair",totalDownloads:7836,totalCrossrefCites:5,totalDimensionsCites:8,abstract:"Hair is one of the characteristic features of mammals and has various functions such as protection against external factors; producing sebum, apocrine sweat and pheromones; impact on social and sexual interactions; thermoregulation and being a resource for stem cells. 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Extensive knowledge on anatomical and physiological aspects of hair can contribute to understand and heal different hair disorders.",book:{id:"5461",slug:"hair-and-scalp-disorders",title:"Hair and Scalp Disorders",fullTitle:"Hair and Scalp Disorders"},signatures:"Bilgen Erdoğan",authors:[{id:"193661",title:"Dr.",name:"Bilgen",middleName:null,surname:"Erdoğan",slug:"bilgen-erdogan",fullName:"Bilgen Erdoğan"}]},{id:"53947",title:"Infections, Infestations and Neoplasms of the Scalp",slug:"infections-infestations-and-neoplasms-of-the-scalp",totalDownloads:3547,totalCrossrefCites:0,totalDimensionsCites:0,abstract:"This chapter reviews common cutaneous infections, infestations, and neoplasms of the scalp. Infections of the scalp are subdivided into three major groups. The most seen are: (1) Bacterial: Folliculitis, folliculitis decalvans, tufted hair folliculitis and acne keloidalis nuchae. (2) Fungal: Tinea capitis, favus and kerion celsi. (3) Protozoal: Syphilitic alopecia. Pediculosis capitis is the most common worldwide infestation of the scalp. The neoplasms of the scalp are large group of different diseases due to arising different origin. In the following section, trichilemmal cyst, proliferating trichilemmal cyst, nevus sebaceous and cylindroma are discussed in detail.",book:{id:"5461",slug:"hair-and-scalp-disorders",title:"Hair and Scalp Disorders",fullTitle:"Hair and Scalp Disorders"},signatures:"Filiz Canpolat",authors:[{id:"191617",title:"Associate Prof.",name:"Filiz",middleName:null,surname:"Canpolat",slug:"filiz-canpolat",fullName:"Filiz Canpolat"}]},{id:"53525",title:"Trichoscopy and Trichogram",slug:"trichoscopy-and-trichogram",totalDownloads:2633,totalCrossrefCites:0,totalDimensionsCites:0,abstract:"Hair and scalp examination techniques can be classified into three categories: noninvasive methods (clinical history, general examination, photography, hair count, weighing shed hair, pull test, global hair counts, dermoscopy, electron microscopy, laser scanning microscopy, etc.); semi‐invasive methods (the trichogram, unit areatrichogram); and invasive methods (biopsies in cicatritial alopecia). Scalp dermoscopy or trichoscopy is one of thenoninvasive techniques for the evaluation of patients with hair loss that allows for magnified visualization of the hair and scalp skin. It may be performed with a manual dermoscope (10× magnification) or a videodermoscope (up to 1000× magnification). This method is simple, quick, and easy to perform, is well‐accepted by patients, and is useful for monitoring treatment, determining severity of the disease and follow‐up. It is a simple, minimally invasive and rapid technique for measuring hair follicle activity. Trichogram represents a semi‐invasive technique for the evaluation of patients with hair loss that allows the microscopic examination of hairs plucked from the scalp and provides information about the state of the proximal end of the hair shaft and the distal end. The trichogram is a useful complementary tool for clinical evaluation, diagnosis, and the monitoring of treatment response.",book:{id:"5461",slug:"hair-and-scalp-disorders",title:"Hair and Scalp Disorders",fullTitle:"Hair and Scalp Disorders"},signatures:"Melike Kibar",authors:[{id:"189899",title:"Dr.",name:"Melike",middleName:null,surname:"Kibar Ozturk",slug:"melike-kibar-ozturk",fullName:"Melike Kibar Ozturk"}]},{id:"42524",title:"Hereditary Palmoplantar Keratosis",slug:"hereditary-palmoplantar-keratosis",totalDownloads:4592,totalCrossrefCites:0,totalDimensionsCites:0,abstract:null,book:{id:"3038",slug:"current-genetics-in-dermatology",title:"Current Genetics in Dermatology",fullTitle:"Current Genetics in Dermatology"},signatures:"Tamihiro Kawakami",authors:[{id:"155091",title:"Associate Prof.",name:"Tamihiro",middleName:null,surname:"Kawakami",slug:"tamihiro-kawakami",fullName:"Tamihiro Kawakami"}]},{id:"63066",title:"Pharmacological Treatment of Alopecia",slug:"pharmacological-treatment-of-alopecia",totalDownloads:1460,totalCrossrefCites:1,totalDimensionsCites:3,abstract:"In this chapter, we will explore non-surgical treatments of alopecia. Unlike many other areas of medicine, pharmacological treatments for alopecia are relatively new. There are only two treatments which are approved by the Food and Drug Administration (FDA); the rest are drugs developed for other indications which have gained popular off-label use to promote hair growth. The reasons for this are many, including the designation of alopecia by the FDA as a cosmetic disease. This designation has restricted alopecia development programs to compounds with virtually no side effects. Unfortunately, it has also led to off-label use of far more dangerous compounds as alopecia treatments, without the benefit of controlled trials. There is a growing recognition that alopecia, particularly alopecia areata and chemotherapy-induced alopecia, are disorders which significantly alter the quality of life, similar to acne vulgaris and psoriasis, and merit treatment accordingly. There have also been several recent advances in our understanding of the hair cycle, revealing new targets for developing alopecia therapies. As a result, there is a more robust slate of programs for developing new pharmacological treatments for alopecia. 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Travieso-González received his MSc degree in Telecommunication Engineering at Polytechnic University of Catalonia (UPC), Spain in 1997, and his Ph.D. degree in 2002 at the University of Las Palmas de Gran Canaria (ULPGC-Spain). He is a full professor of signal processing and pattern recognition and is head of the Signals and Communications Department at ULPGC, teaching from 2001 on subjects on signal processing and learning theory. His research lines are biometrics, biomedical signals and images, data mining, classification system, signal and image processing, machine learning, and environmental intelligence. He has researched in 52 international and Spanish research projects, some of them as head researcher. He is co-author of 4 books, co-editor of 27 proceedings books, guest editor for 8 JCR-ISI international journals, and up to 24 book chapters. He has over 450 papers published in international journals and conferences (81 of them indexed on JCR – ISI - Web of Science). He has published seven patents in the Spanish Patent and Trademark Office. He has been a supervisor on 8 Ph.D. theses (11 more are under supervision), and 130 master theses. He is the founder of The IEEE IWOBI conference series and the president of its Steering Committee, as well as the founder of both the InnoEducaTIC and APPIS conference series. He is an evaluator of project proposals for the European Union (H2020), Medical Research Council (MRC, UK), Spanish Government (ANECA, Spain), Research National Agency (ANR, France), DAAD (Germany), Argentinian Government, and the Colombian Institutions. He has been a reviewer in different indexed international journals (<70) and conferences (<250) since 2001. He has been a member of the IASTED Technical Committee on Image Processing from 2007 and a member of the IASTED Technical Committee on Artificial Intelligence and Expert Systems from 2011. \n\nHe has held the general chair position for the following: ACM-APPIS (2020, 2021), IEEE-IWOBI (2019, 2020 and 2020), A PPIS (2018, 2019), IEEE-IWOBI (2014, 2015, 2017, 2018), InnoEducaTIC (2014, 2017), IEEE-INES (2013), NoLISP (2011), JRBP (2012), and IEEE-ICCST (2005)\n\nHe is an associate editor of the Computational Intelligence and Neuroscience Journal (Hindawi – Q2 JCR-ISI). He was vice dean from 2004 to 2010 in the Higher Technical School of Telecommunication Engineers at ULPGC and the vice dean of Graduate and Postgraduate Studies from March 2013 to November 2017. 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His research interests include computer/machine vision, machine learning, pattern recognition, computational intelligence. \nDr. Papakostas served as a reviewer in numerous journals, as a program\ncommittee member in international conferences and he is a member of the IAENG, MIR Labs, EUCogIII, INSTICC and the Technical Chamber of Greece (TEE).",institutionString:null,institution:{name:"International Hellenic University",institutionURL:null,country:{name:"Greece"}}},editorTwo:null,editorThree:null},{id:"25",title:"Evolutionary Computation",coverUrl:"https://cdn.intechopen.com/series_topics/covers/25.jpg",isOpenForSubmission:!0,annualVolume:11421,editor:{id:"136112",title:"Dr.",name:"Sebastian",middleName:null,surname:"Ventura Soto",slug:"sebastian-ventura-soto",fullName:"Sebastian Ventura Soto",profilePictureURL:"https://mts.intechopen.com/storage/users/136112/images/system/136112.png",biography:"Sebastian Ventura is a Spanish researcher, a full professor with the Department of Computer Science and Numerical Analysis, University of Córdoba. 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He has both an MS and Ph.D. in Biomedical Engineering. He was previously a research scientist at the University of California Los Angeles (UCLA) and visiting professor and researcher at the University of North Dakota. He is currently working in artificial intelligence and its applications in medical signal processing. In addition, he is using digital signal processing in medical imaging and speech processing. Dr. Asadpour has developed brain-computer interfacing algorithms and has published books, book chapters, and several journal and conference papers in this field and other areas of intelligent signal processing. He has also designed medical devices, including a laser Doppler monitoring system.",institutionString:"Kaiser Permanente Southern California",institution:null},{id:"169608",title:"Prof.",name:"Marian",middleName:null,surname:"Găiceanu",slug:"marian-gaiceanu",fullName:"Marian Găiceanu",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/169608/images/system/169608.png",biography:"Prof. Dr. Marian Gaiceanu graduated from the Naval and Electrical Engineering Faculty, Dunarea de Jos University of Galati, Romania, in 1997. He received a Ph.D. (Magna Cum Laude) in Electrical Engineering in 2002. Since 2017, Dr. Gaiceanu has been a Ph.D. supervisor for students in Electrical Engineering. He has been employed at Dunarea de Jos University of Galati since 1996, where he is currently a professor. Dr. Gaiceanu is a member of the National Council for Attesting Titles, Diplomas and Certificates, an expert of the Executive Agency for Higher Education, Research Funding, and a member of the Senate of the Dunarea de Jos University of Galati. He has been the head of the Integrated Energy Conversion Systems and Advanced Control of Complex Processes Research Center, Romania, since 2016. He has conducted several projects in power converter systems for electrical drives, power quality, PEM and SOFC fuel cell power converters for utilities, electric vehicles, and marine applications with the Department of Regulation and Control, SIEI S.pA. (2002–2004) and the Polytechnic University of Turin, Italy (2002–2004, 2006–2007). He is a member of the Institute of Electrical and Electronics Engineers (IEEE) and cofounder-member of the IEEE Power Electronics Romanian Chapter. He is a guest editor at Energies and an academic book editor for IntechOpen. He is also a member of the editorial boards of the Journal of Electrical Engineering, Electronics, Control and Computer Science and Sustainability. Dr. Gaiceanu has been General Chairman of the IEEE International Symposium on Electrical and Electronics Engineering in the last six editions.",institutionString:'"Dunarea de Jos" University of Galati',institution:{name:'"Dunarea de Jos" University of Galati',country:{name:"Romania"}}},{id:"4519",title:"Prof.",name:"Jaydip",middleName:null,surname:"Sen",slug:"jaydip-sen",fullName:"Jaydip Sen",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/4519/images/system/4519.jpeg",biography:"Jaydip Sen is associated with Praxis Business School, Kolkata, India, as a professor in the Department of Data Science. His research areas include security and privacy issues in computing and communication, intrusion detection systems, machine learning, deep learning, and artificial intelligence in the financial domain. He has more than 200 publications in reputed international journals, refereed conference proceedings, and 20 book chapters in books published by internationally renowned publishing houses, such as Springer, CRC press, IGI Global, etc. Currently, he is serving on the editorial board of the prestigious journal Frontiers in Communications and Networks and in the technical program committees of a number of high-ranked international conferences organized by the IEEE, USA, and the ACM, USA. He has been listed among the top 2% of scientists in the world for the last three consecutive years, 2019 to 2021 as per studies conducted by the Stanford University, USA.",institutionString:"Praxis Business School",institution:null},{id:"320071",title:"Dr.",name:"Sidra",middleName:null,surname:"Mehtab",slug:"sidra-mehtab",fullName:"Sidra Mehtab",position:null,profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0033Y00002v6KHoQAM/Profile_Picture_1584512086360",biography:"Sidra Mehtab has completed her BS with honors in Physics from Calcutta University, India in 2018. She has done MS in Data Science and Analytics from Maulana Abul Kalam Azad University of Technology (MAKAUT), Kolkata, India in 2020. Her research areas include Econometrics, Time Series Analysis, Machine Learning, Deep Learning, Artificial Intelligence, and Computer and Network Security with a particular focus on Cyber Security Analytics. Ms. Mehtab has published seven papers in international conferences and one of her papers has been accepted for publication in a reputable international journal. She has won the best paper awards in two prestigious international conferences – BAICONF 2019, and ICADCML 2021, organized in the Indian Institute of Management, Bangalore, India in December 2019, and SOA University, Bhubaneswar, India in January 2021. Besides, Ms. Mehtab has also published two book chapters in two books. Seven of her book chapters will be published in a volume shortly in 2021 by Cambridge Scholars’ Press, UK. Currently, she is working as the joint editor of two edited volumes on Time Series Analysis and Forecasting to be published in the first half of 2021 by an international house. Currently, she is working as a Data Scientist with an MNC in Delhi, India.",institutionString:"NSHM College of Management and Technology",institution:{name:"Association for Computing Machinery",country:{name:"United States of America"}}},{id:"226240",title:"Dr.",name:"Andri Irfan",middleName:null,surname:"Rifai",slug:"andri-irfan-rifai",fullName:"Andri Irfan Rifai",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/226240/images/7412_n.jpg",biography:"Andri IRFAN is a Senior Lecturer of Civil Engineering and Planning. He completed the PhD at the Universitas Indonesia & Universidade do Minho with Sandwich Program Scholarship from the Directorate General of Higher Education and LPDP scholarship. He has been teaching for more than 19 years and much active to applied his knowledge in the project construction in Indonesia. His research interest ranges from pavement management system to advanced data mining techniques for transportation engineering. He has published more than 50 papers in journals and 2 books.",institutionString:null,institution:{name:"Universitas Internasional Batam",country:{name:"Indonesia"}}},{id:"314576",title:"Dr.",name:"Ibai",middleName:null,surname:"Laña",slug:"ibai-lana",fullName:"Ibai Laña",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/314576/images/system/314576.jpg",biography:"Dr. Ibai Laña works at TECNALIA as a data analyst. He received his Ph.D. in Artificial Intelligence from the University of the Basque Country (UPV/EHU), Spain, in 2018. He is currently a senior researcher at TECNALIA. His research interests fall within the intersection of intelligent transportation systems, machine learning, traffic data analysis, and data science. He has dealt with urban traffic forecasting problems, applying machine learning models and evolutionary algorithms. He has experience in origin-destination matrix estimation or point of interest and trajectory detection. Working with large volumes of data has given him a good command of big data processing tools and NoSQL databases. He has also been a visiting scholar at the Knowledge Engineering and Discovery Research Institute, Auckland University of Technology.",institutionString:"TECNALIA Research & Innovation",institution:{name:"Tecnalia",country:{name:"Spain"}}},{id:"314575",title:"Dr.",name:"Jesus",middleName:null,surname:"L. Lobo",slug:"jesus-l.-lobo",fullName:"Jesus L. Lobo",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/314575/images/system/314575.png",biography:"Dr. Jesús López is currently based in Bilbao (Spain) working at TECNALIA as Artificial Intelligence Research Scientist. In most cases, a project idea or a new research line needs to be investigated to see if it is good enough to take into production or to focus on it. That is exactly what he does, diving into Machine Learning algorithms and technologies to help TECNALIA to decide whether something is great in theory or will actually impact on the product or processes of its projects. So, he is expert at framing experiments, developing hypotheses, and proving whether they’re true or not, in order to investigate fundamental problems with a longer time horizon. He is also able to design and develop PoCs and system prototypes in simulation. He has participated in several national and internacional R&D projects.\n\nAs another relevant part of his everyday research work, he usually publishes his findings in reputed scientific refereed journals and international conferences, occasionally acting as reviewer and Programme Commitee member. Concretely, since 2018 he has published 9 JCR (8 Q1) journal papers, 9 conference papers (e.g. ECML PKDD 2021), and he has co-edited a book. He is also active in popular science writing data science stories for reputed blogs (KDNuggets, TowardsDataScience, Naukas). Besides, he has recently embarked on mentoring programmes as mentor, and has also worked as data science trainer.",institutionString:"TECNALIA Research & Innovation",institution:{name:"Tecnalia",country:{name:"Spain"}}},{id:"103779",title:"Prof.",name:"Yalcin",middleName:null,surname:"Isler",slug:"yalcin-isler",fullName:"Yalcin Isler",position:null,profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bRyQ8QAK/Profile_Picture_1628834958734",biography:"Yalcin Isler (1971 - Burdur / Turkey) received the B.Sc. degree in the Department of Electrical and Electronics Engineering from Anadolu University, Eskisehir, Turkey, in 1993, the M.Sc. degree from the Department of Electronics and Communication Engineering, Suleyman Demirel University, Isparta, Turkey, in 1996, the Ph.D. degree from the Department of Electrical and Electronics Engineering, Dokuz Eylul University, Izmir, Turkey, in 2009, and the Competence of Associate Professorship from the Turkish Interuniversity Council in 2019.\n\nHe was Lecturer at Burdur Vocational School in Suleyman Demirel University (1993-2000, Burdur / Turkey), Software Engineer (2000-2002, Izmir / Turkey), Research Assistant in Bulent Ecevit University (2002-2003, Zonguldak / Turkey), Research Assistant in Dokuz Eylul University (2003-2010, Izmir / Turkey), Assistant Professor at the Department of Electrical and Electronics Engineering in Bulent Ecevit University (2010-2012, Zonguldak / Turkey), Assistant Professor at the Department of Biomedical Engineering in Izmir Katip Celebi University (2012-2019, Izmir / Turkey). He is an Associate Professor at the Department of Biomedical Engineering at Izmir Katip Celebi University, Izmir / Turkey, since 2019. In addition to academics, he has also founded Islerya Medical and Information Technologies Company, Izmir / Turkey, since 2017.\n\nHis main research interests cover biomedical signal processing, pattern recognition, medical device design, programming, and embedded systems. He has many scientific papers and participated in several projects in these study fields. He was an IEEE Student Member (2009-2011) and IEEE Member (2011-2014) and has been IEEE Senior Member since 2014.",institutionString:null,institution:{name:"Izmir Kâtip Çelebi University",country:{name:"Turkey"}}},{id:"339677",title:"Dr.",name:"Mrinmoy",middleName:null,surname:"Roy",slug:"mrinmoy-roy",fullName:"Mrinmoy Roy",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/339677/images/16768_n.jpg",biography:"An accomplished Sales & Marketing professional with 12 years of cross-functional experience in well-known organisations such as CIPLA, LUPIN, GLENMARK, ASTRAZENECA across different segment of Sales & Marketing, International Business, Institutional Business, Product Management, Strategic Marketing of HIV, Oncology, Derma, Respiratory, Anti-Diabetic, Nutraceutical & Stomatological Product Portfolio and Generic as well as Chronic Critical Care Portfolio. A First Class MBA in International Business & Strategic Marketing, B.Pharm, D.Pharm, Google Certified Digital Marketing Professional. Qualified PhD Candidate in Operations and Management with special focus on Artificial Intelligence and Machine Learning adoption, analysis and use in Healthcare, Hospital & Pharma Domain. Seasoned with diverse therapy area of Pharmaceutical Sales & Marketing ranging from generating revenue through generating prescriptions, launching new products, and making them big brands with continuous strategy execution at the Physician and Patients level. Moved from Sales to Marketing and Business Development for 3.5 years in South East Asian Market operating from Manila, Philippines. Came back to India and handled and developed Brands such as Gluconorm, Lupisulin, Supracal, Absolut Woman, Hemozink, Fabiflu (For COVID 19), and many more. In my previous assignment I used to develop and execute strategies on Sales & Marketing, Commercialization & Business Development for Institution and Corporate Hospital Business portfolio of Oncology Therapy Area for AstraZeneca Pharma India Ltd. Being a Research Scholar and Student of ‘Operations Research & Management: Artificial Intelligence’ I published several pioneer research papers and book chapters on the same in Internationally reputed journals and Books indexed in Scopus, Springer and Ei Compendex, Google Scholar etc. Currently, I am launching PGDM Pharmaceutical Management Program in IIHMR Bangalore and spearheading the course curriculum and structure of the same. I am interested in Collaboration for Healthcare Innovation, Pharma AI Innovation, Future trend in Marketing and Management with incubation on Healthcare, Healthcare IT startups, AI-ML Modelling and Healthcare Algorithm based training module development. I am also an affiliated member of the Institute of Management Consultant of India, looking forward to Healthcare, Healthcare IT and Innovation, Pharma and Hospital Management Consulting works.",institutionString:null,institution:{name:"Lovely Professional University",country:{name:"India"}}},{id:"310576",title:"Prof.",name:"Erick Giovani",middleName:null,surname:"Sperandio Nascimento",slug:"erick-giovani-sperandio-nascimento",fullName:"Erick Giovani Sperandio Nascimento",position:null,profilePictureURL:"https://intech-files.s3.amazonaws.com/0033Y00002pDKxDQAW/ProfilePicture%202022-06-20%2019%3A57%3A24.788",biography:"Prof. Erick Sperandio is the Lead Researcher and professor of Artificial Intelligence (AI) at SENAI CIMATEC, Bahia, Brazil, also working with Computational Modeling (CM) and HPC. He holds a PhD in Environmental Engineering in the area of Atmospheric Computational Modeling, a Master in Informatics in the field of Computational Intelligence and Graduated in Computer Science from UFES. He currently coordinates, leads and participates in R&D projects in the areas of AI, computational modeling and supercomputing applied to different areas such as Oil and Gas, Health, Advanced Manufacturing, Renewable Energies and Atmospheric Sciences, advising undergraduate, master's and doctoral students. He is the Lead Researcher at SENAI CIMATEC's Reference Center on Artificial Intelligence. In addition, he is a Certified Instructor and University Ambassador of the NVIDIA Deep Learning Institute (DLI) in the areas of Deep Learning, Computer Vision, Natural Language Processing and Recommender Systems, and Principal Investigator of the NVIDIA/CIMATEC AI Joint Lab, the first in Latin America within the NVIDIA AI Technology Center (NVAITC) worldwide program. He also works as a researcher at the Supercomputing Center for Industrial Innovation (CS2i) and at the SENAI Institute of Innovation for Automation (ISI Automação), both from SENAI CIMATEC. He is a member and vice-coordinator of the Basic Board of Scientific-Technological Advice and Evaluation, in the area of Innovation, of the Foundation for Research Support of the State of Bahia (FAPESB). He serves as Technology Transfer Coordinator and one of the Principal Investigators at the National Applied Research Center in Artificial Intelligence (CPA-IA) of SENAI CIMATEC, focusing on Industry, being one of the six CPA-IA in Brazil approved by MCTI / FAPESP / CGI.br. He also participates as one of the representatives of Brazil in the BRICS Innovation Collaboration Working Group on HPC, ICT and AI. He is the coordinator of the Work Group of the Axis 5 - Workforce and Training - of the Brazilian Strategy for Artificial Intelligence (EBIA), and member of the MCTI/EMBRAPII AI Innovation Network Training Committee. He is the coordinator, by SENAI CIMATEC, of the Artificial Intelligence Reference Network of the State of Bahia (REDE BAH.IA). He leads the working group of experts representing Brazil in the Global Partnership on Artificial Intelligence (GPAI), on the theme \"AI and the Pandemic Response\".",institutionString:"Manufacturing and Technology Integrated Campus – SENAI CIMATEC",institution:null},{id:"1063",title:"Prof.",name:"Constantin",middleName:null,surname:"Volosencu",slug:"constantin-volosencu",fullName:"Constantin Volosencu",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/1063/images/system/1063.png",biography:"Prof. Dr. Constantin Voloşencu graduated as an engineer from\nPolitehnica University of Timișoara, Romania, where he also\nobtained a doctorate degree. He is currently a full professor in\nthe Department of Automation and Applied Informatics at the\nsame university. Dr. Voloşencu is the author of ten books, seven\nbook chapters, and more than 160 papers published in journals\nand conference proceedings. He has also edited twelve books and\nhas twenty-seven patents to his name. He is a manager of research grants, editor in\nchief and member of international journal editorial boards, a former plenary speaker, a member of scientific committees, and chair at international conferences. His\nresearch is in the fields of control systems, control of electric drives, fuzzy control\nsystems, neural network applications, fault detection and diagnosis, sensor network\napplications, monitoring of distributed parameter systems, and power ultrasound\napplications. He has developed automation equipment for machine tools, spooling\nmachines, high-power ultrasound processes, and more.",institutionString:'"Politechnica" University Timişoara',institution:null},{id:"221364",title:"Dr.",name:"Eneko",middleName:null,surname:"Osaba",slug:"eneko-osaba",fullName:"Eneko Osaba",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/221364/images/system/221364.jpg",biography:"Dr. Eneko Osaba works at TECNALIA as a senior researcher. He obtained his Ph.D. in Artificial Intelligence in 2015. He has participated in more than twenty-five local and European research projects, and in the publication of more than 130 papers. He has performed several stays at universities in the United Kingdom, Italy, and Malta. Dr. Osaba has served as a program committee member in more than forty international conferences and participated in organizing activities in more than ten international conferences. He is a member of the editorial board of the International Journal of Artificial Intelligence, Data in Brief, and Journal of Advanced Transportation. He is also a guest editor for the Journal of Computational Science, Neurocomputing, Swarm, and Evolutionary Computation and IEEE ITS Magazine.",institutionString:"TECNALIA Research & Innovation",institution:{name:"Tecnalia",country:{name:"Spain"}}},{id:"275829",title:"Dr.",name:"Esther",middleName:null,surname:"Villar-Rodriguez",slug:"esther-villar-rodriguez",fullName:"Esther Villar-Rodriguez",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/275829/images/system/275829.jpg",biography:"Dr. Esther Villar obtained a Ph.D. in Information and Communication Technologies from the University of Alcalá, Spain, in 2015. She obtained a degree in Computer Science from the University of Deusto, Spain, in 2010, and an MSc in Computer Languages and Systems from the National University of Distance Education, Spain, in 2012. Her areas of interest and knowledge include natural language processing (NLP), detection of impersonation in social networks, semantic web, and machine learning. Dr. Esther Villar made several contributions at conferences and publishing in various journals in those fields. Currently, she is working within the OPTIMA (Optimization Modeling & Analytics) business of TECNALIA’s ICT Division as a data scientist in projects related to the prediction and optimization of management and industrial processes (resource planning, energy efficiency, etc).",institutionString:"TECNALIA Research & Innovation",institution:{name:"Tecnalia",country:{name:"Spain"}}},{id:"49813",title:"Dr.",name:"Javier",middleName:null,surname:"Del Ser",slug:"javier-del-ser",fullName:"Javier Del Ser",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/49813/images/system/49813.png",biography:"Prof. Dr. Javier Del Ser received his first PhD in Telecommunication Engineering (Cum Laude) from the University of Navarra, Spain, in 2006, and a second PhD in Computational Intelligence (Summa Cum Laude) from the University of Alcala, Spain, in 2013. He is currently a principal researcher in data analytics and optimisation at TECNALIA (Spain), a visiting fellow at the Basque Center for Applied Mathematics (BCAM) and a part-time lecturer at the University of the Basque Country (UPV/EHU). His research interests gravitate on the use of descriptive, prescriptive and predictive algorithms for data mining and optimization in a diverse range of application fields such as Energy, Transport, Telecommunications, Health and Industry, among others. In these fields he has published more than 240 articles, co-supervised 8 Ph.D. theses, edited 6 books, coauthored 7 patents and participated/led more than 40 research projects. He is a Senior Member of the IEEE, and a recipient of the Biscay Talent prize for his academic career.",institutionString:"Tecnalia Research & Innovation",institution:{name:"Tecnalia",country:{name:"Spain"}}},{id:"278948",title:"Dr.",name:"Carlos Pedro",middleName:null,surname:"Gonçalves",slug:"carlos-pedro-goncalves",fullName:"Carlos Pedro Gonçalves",position:null,profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bRcmyQAC/Profile_Picture_1564224512145",biography:'Carlos Pedro Gonçalves (PhD) is an Associate Professor at Lusophone University of Humanities and Technologies and a researcher on Complexity Sciences, Quantum Technologies, Artificial Intelligence, Strategic Studies, Studies in Intelligence and Security, FinTech and Financial Risk Modeling. He is also a progammer with programming experience in:\n\nA) Quantum Computing using Qiskit Python module and IBM Quantum Experience Platform, with software developed on the simulation of Quantum Artificial Neural Networks and Quantum Cybersecurity;\n\nB) Artificial Intelligence and Machine learning programming in Python;\n\nC) Artificial Intelligence, Multiagent Systems Modeling and System Dynamics Modeling in Netlogo, with models developed in the areas of Chaos Theory, Econophysics, Artificial Intelligence, Classical and Quantum Complex Systems Science, with the Econophysics models having been cited worldwide and incorporated in PhD programs by different Universities.\n\nReceived an Arctic Code Vault Contributor status by GitHub, due to having developed open source software preserved in the \\"Arctic Code Vault\\" for future generations (https://archiveprogram.github.com/arctic-vault/), with the Strategy Analyzer A.I. module for decision making support (based on his PhD thesis, used in his Classes on Decision Making and in Strategic Intelligence Consulting Activities) and QNeural Python Quantum Neural Network simulator also preserved in the \\"Arctic Code Vault\\", for access to these software modules see: https://github.com/cpgoncalves. He is also a peer reviewer with outsanding review status from Elsevier journals, including Physica A, Neurocomputing and Engineering Applications of Artificial Intelligence. 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Currently working as an Assistant Professor in the Department of Mathematics, Institute of Applied Science, Mangalayatan University, Aligarh. She taught so many courses of Mathematics of UG and PG level. Her research Area of Expertise is Functional Analysis & Sequence Spaces. She has been working on Ideal Convergence of double sequence. She has published 17 research papers in National and International Journals including Cogent Mathematics, Filomat, Journal of Intelligent and Fuzzy Systems, Advances in Difference Equations, Journal of Mathematical Analysis, Journal of Mathematical & Computer Science etc. She has also reviewed few research papers for the and international journals. 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He worked on the structure-function relationships of glycoconjugates and his main project was the investigations on the biological roles of the de-N-glycosylation enzymes (Endo-N-acetyl-β-D-glucosaminidase and peptide-N4-(N-acetyl-β-glucosaminyl) asparagine amidase). From 2002 he contributes to the understanding of the Blood-brain barrier functioning using proteomics approaches. He has published more than 70 papers. 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Recently, bioinspired systems have been successfully employing biomechanics to develop and improve assistive technology and rehabilitation devices. The research topic "Bioinspired Technology and Biomechanics" welcomes studies reporting recent advances in bioinspired technologies that contribute to individuals\' health, inclusion, and rehabilitation. Possible contributions can address (but are not limited to) the following research topics: Bioinspired design and control of exoskeletons, orthoses, and prostheses; Experimental evaluation of the effect of assistive devices (e.g., influence on gait, balance, and neuromuscular system); Bioinspired technologies for rehabilitation, including clinical studies reporting evaluations; Application of neuromuscular and biomechanical models to the development of bioinspired technology.',coverUrl:"https://cdn.intechopen.com/series_topics/covers/8.jpg",keywords:"Bioinspired Systems, Biomechanics, Assistive Technology, Rehabilitation"},{id:"9",title:"Biotechnology - Biosensors, Biomaterials and Tissue Engineering",scope:"The Biotechnology - Biosensors, Biomaterials and Tissue Engineering topic within the Biomedical Engineering Series aims to rapidly publish contributions on all aspects of biotechnology, biosensors, biomaterial and tissue engineering. We encourage the submission of manuscripts that provide novel and mechanistic insights that report significant advances in the fields. Topics can include but are not limited to: Biotechnology such as biotechnological products and process engineering; Biotechnologically relevant enzymes and proteins; Bioenergy and biofuels; Applied genetics and molecular biotechnology; Genomics, transcriptomics, proteomics; Applied microbial and cell physiology; Environmental biotechnology; Methods and protocols. Moreover, topics in biosensor technology, like sensors that incorporate enzymes, antibodies, nucleic acids, whole cells, tissues and organelles, and other biological or biologically inspired components will be considered, and topics exploring transducers, including those based on electrochemical and optical piezoelectric, thermal, magnetic, and micromechanical elements. Chapters exploring biomaterial approaches such as polymer synthesis and characterization, drug and gene vector design, biocompatibility, immunology and toxicology, and self-assembly at the nanoscale, are welcome. Finally, the tissue engineering subcategory will support topics such as the fundamentals of stem cells and progenitor cells and their proliferation, differentiation, bioreactors for three-dimensional culture and studies of phenotypic changes, stem and progenitor cells, both short and long term, ex vivo and in vivo implantation both in preclinical models and also in clinical trials.",coverUrl:"https://cdn.intechopen.com/series_topics/covers/9.jpg",keywords:"Biotechnology, Biosensors, Biomaterials, Tissue Engineering"}],annualVolumeBook:{},thematicCollection:[],selectedSeries:{title:"Biomedical Engineering",id:"7"},selectedSubseries:null},seriesLanding:{item:{id:"7",title:"Biomedical Engineering",doi:"10.5772/intechopen.71985",issn:"2631-5343",scope:"Biomedical Engineering is one of the fastest-growing interdisciplinary branches of science and industry. The combination of electronics and computer science with biology and medicine has improved patient diagnosis, reduced rehabilitation time, and helped to facilitate a better quality of life. Nowadays, all medical imaging devices, medical instruments, or new laboratory techniques result from the cooperation of specialists in various fields. The series of Biomedical Engineering books covers such areas of knowledge as chemistry, physics, electronics, medicine, and biology. 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Dr. Koprowski has authored more than a hundred research papers with dozens in impact factor (IF) journals and has authored or co-authored six books. Additionally, he is the author of several national and international patents in the field of biomedical devices and imaging. Since 2011, he has been a reviewer of grants and projects (including EU projects) in biomedical engineering.",institutionString:null,institution:{name:"University of Silesia",institutionURL:null,country:{name:"Poland"}}},subseries:[{id:"7",title:"Bioinformatics and Medical Informatics",keywords:"Biomedical Data, Drug Discovery, Clinical Diagnostics, Decoding Human Genome, AI in Personalized Medicine, Disease-prevention Strategies, Big Data Analysis in Medicine",scope:"Bioinformatics aims to help understand the functioning of the mechanisms of living organisms through the construction and use of quantitative tools. The applications of this research cover many related fields, such as biotechnology and medicine, where, for example, Bioinformatics contributes to faster drug design, DNA analysis in forensics, and DNA sequence analysis in the field of personalized medicine. Personalized medicine is a type of medical care in which treatment is customized individually for each patient. Personalized medicine enables more effective therapy, reduces the costs of therapy and clinical trials, and also minimizes the risk of side effects. Nevertheless, advances in personalized medicine would not have been possible without bioinformatics, which can analyze the human genome and other vast amounts of biomedical data, especially in genetics. The rapid growth of information technology enabled the development of new tools to decode human genomes, large-scale studies of genetic variations and medical informatics. The considerable development of technology, including the computing power of computers, is also conducive to the development of bioinformatics, including personalized medicine. In an era of rapidly growing data volumes and ever lower costs of generating, storing and computing data, personalized medicine holds great promises. Modern computational methods used as bioinformatics tools can integrate multi-scale, multi-modal and longitudinal patient data to create even more effective and safer therapy and disease prevention methods. 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Possible contributions can address (but are not limited to) the following research topics: Bioinspired design and control of exoskeletons, orthoses, and prostheses; Experimental evaluation of the effect of assistive devices (e.g., influence on gait, balance, and neuromuscular system); Bioinspired technologies for rehabilitation, including clinical studies reporting evaluations; Application of neuromuscular and biomechanical models to the development of bioinspired technology.',annualVolume:11404,isOpenForSubmission:!0,coverUrl:"https://cdn.intechopen.com/series_topics/covers/8.jpg",editor:{id:"144937",title:"Prof.",name:"Adriano",middleName:"De Oliveira",surname:"Andrade",fullName:"Adriano Andrade",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bRC8QQAW/Profile_Picture_1625219101815",institutionString:null,institution:{name:"Federal University of Uberlândia",institutionURL:null,country:{name:"Brazil"}}},editorTwo:null,editorThree:null,editorialBoard:[{id:"49517",title:"Prof.",name:"Hitoshi",middleName:null,surname:"Tsunashima",fullName:"Hitoshi Tsunashima",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002aYTP4QAO/Profile_Picture_1625819726528",institutionString:null,institution:{name:"Nihon University",institutionURL:null,country:{name:"Japan"}}},{id:"425354",title:"Dr.",name:"Marcus",middleName:"Fraga",surname:"Vieira",fullName:"Marcus Vieira",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0033Y00003BJSgIQAX/Profile_Picture_1627904687309",institutionString:null,institution:{name:"Universidade Federal de Goiás",institutionURL:null,country:{name:"Brazil"}}},{id:"196746",title:"Dr.",name:"Ramana",middleName:null,surname:"Vinjamuri",fullName:"Ramana Vinjamuri",profilePictureURL:"https://mts.intechopen.com/storage/users/196746/images/system/196746.jpeg",institutionString:"University of Maryland, Baltimore County",institution:{name:"University of Maryland, Baltimore County",institutionURL:null,country:{name:"United States of America"}}}]},{id:"9",title:"Biotechnology - Biosensors, Biomaterials and Tissue Engineering",keywords:"Biotechnology, Biosensors, Biomaterials, Tissue Engineering",scope:"The Biotechnology - Biosensors, Biomaterials and Tissue Engineering topic within the Biomedical Engineering Series aims to rapidly publish contributions on all aspects of biotechnology, biosensors, biomaterial and tissue engineering. We encourage the submission of manuscripts that provide novel and mechanistic insights that report significant advances in the fields. Topics can include but are not limited to: Biotechnology such as biotechnological products and process engineering; Biotechnologically relevant enzymes and proteins; Bioenergy and biofuels; Applied genetics and molecular biotechnology; Genomics, transcriptomics, proteomics; Applied microbial and cell physiology; Environmental biotechnology; Methods and protocols. Moreover, topics in biosensor technology, like sensors that incorporate enzymes, antibodies, nucleic acids, whole cells, tissues and organelles, and other biological or biologically inspired components will be considered, and topics exploring transducers, including those based on electrochemical and optical piezoelectric, thermal, magnetic, and micromechanical elements. 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