\\n\\n
Released this past November, the list is based on data collected from the Web of Science and highlights some of the world’s most influential scientific minds by naming the researchers whose publications over the previous decade have included a high number of Highly Cited Papers placing them among the top 1% most-cited.
\\n\\nWe wish to congratulate all of the researchers named and especially our authors on this amazing accomplishment! We are happy and proud to share in their success!
Note: Edited in March 2021
\\n"}]',published:!0,mainMedia:{caption:"Highly Cited",originalUrl:"/media/original/117"}},components:[{type:"htmlEditorComponent",content:'IntechOpen is proud to announce that 191 of our authors have made the Clarivate™ Highly Cited Researchers List for 2020, ranking them among the top 1% most-cited.
\n\nThroughout the years, the list has named a total of 261 IntechOpen authors as Highly Cited. Of those researchers, 69 have been featured on the list multiple times.
\n\n\n\nReleased this past November, the list is based on data collected from the Web of Science and highlights some of the world’s most influential scientific minds by naming the researchers whose publications over the previous decade have included a high number of Highly Cited Papers placing them among the top 1% most-cited.
\n\nWe wish to congratulate all of the researchers named and especially our authors on this amazing accomplishment! We are happy and proud to share in their success!
Note: Edited in March 2021
\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:"7038",leadTitle:null,fullTitle:"Vitamin D Deficiency",title:"Vitamin D Deficiency",subtitle:null,reviewType:"peer-reviewed",abstract:'Vitamin D is the topic for many discussions in the scientific community. Nowadays, a different interpretation of this secosteroid hormone is needed. Today the term "vitamin" may be considered outdated. This compound may be correctly be called a vitamin only when it is administered to humans or animals that suffer from its deficiency. This book attempts to clarify the role of Vitamin D deficiency in many pathological processes in the whole organism. Chapters in this book cover such issues as the earliest clinical and preclinical investigations of the consequences of Vitamin D deficiency for cognitive, cardiovascular, metabolic, immune, and renal disorders.',isbn:"978-1-83880-776-4",printIsbn:"978-1-83880-775-7",pdfIsbn:"978-1-83880-777-1",doi:"10.5772/intechopen.73799",price:119,priceEur:129,priceUsd:155,slug:"vitamin-d-deficiency",numberOfPages:282,isOpenForSubmission:!1,isInWos:null,isInBkci:!1,hash:"ba24f0913341357b0779ff9529c4bbfc",bookSignature:"Julia Fedotova",publishedDate:"February 26th 2020",coverURL:"https://cdn.intechopen.com/books/images_new/7038.jpg",numberOfDownloads:13083,numberOfWosCitations:4,numberOfCrossrefCitations:14,numberOfCrossrefCitationsByBook:0,numberOfDimensionsCitations:24,numberOfDimensionsCitationsByBook:0,hasAltmetrics:1,numberOfTotalCitations:42,isAvailableForWebshopOrdering:!0,dateEndFirstStepPublish:"May 16th 2019",dateEndSecondStepPublish:"August 26th 2019",dateEndThirdStepPublish:"October 25th 2019",dateEndFourthStepPublish:"November 18th 2019",dateEndFifthStepPublish:"January 17th 2020",currentStepOfPublishingProcess:5,indexedIn:"1,2,3,4,5,6",editedByType:"Edited by",kuFlag:!1,featuredMarkup:null,editors:[{id:"269070",title:"Prof.",name:"Julia",middleName:null,surname:"Fedotova",slug:"julia-fedotova",fullName:"Julia Fedotova",profilePictureURL:"https://mts.intechopen.com/storage/users/269070/images/system/269070.jfif",biography:"Julia O. Fedotova, MD, PhD habil., Doc. Biol. Sci was born in St. Petersburg (Russia), in 1973. She graduated and received her Diploma of Pharmacist, from Pharmaceutical Faculty, St. Petersburg State Chemical-Pharmaceutical Academy in 1996. She received her\nPh.D. in Experimental and Clinical Pharmacology and\nPhysiology of Humans and Animals in 1999. She attended the Medical\nSchool, Department of Pharmacology, University of Catania in\n2002, and the Institute of Physiology, Medical School, University of Pecs. She graduated from the special doctoral course in neuropharmacology at the Department\nof Neuropharmacology in the Institute for Experimental Medicine of the Russian\nAcademy of Medical Sciences and she received her Doctor of Biological Sciences degree\n(Ph.D. habil.) in 2008. She is currently a professor at the ITMO University and the\nleading researcher at the I.P. Pavlov Institute of Physiology. She has more than 200 publications (mostly in Russian), 2 patents, and 4 journal articles in collaboration, as well as 6 chapters in journals.\nShe is head of the project “The studying of Vitamin D3 role in the development of\naffective-related disorders in women in the climacteric period, the search of ways for\npharmacorrection”, from the prestigious Russian Scientific Foundation.",institutionString:"ITMO University",position:null,outsideEditionCount:0,totalCites:0,totalAuthoredChapters:"1",totalChapterViews:"0",totalEditedBooks:"1",institution:{name:"ITMO University",institutionURL:null,country:{name:"Russia"}}}],equalEditorOne:null,equalEditorTwo:null,equalEditorThree:null,coeditorOne:null,coeditorTwo:null,coeditorThree:null,coeditorFour:null,coeditorFive:null,topics:[{id:"379",title:"Vitaminology",slug:"alimentology-vitaminology"}],chapters:[{id:"68649",title:"Vitamin D and Its Deficiency in Saudi Arabia",doi:"10.5772/intechopen.88745",slug:"vitamin-d-and-its-deficiency-in-saudi-arabia",totalDownloads:1074,totalCrossrefCites:1,totalDimensionsCites:1,hasAltmetrics:1,abstract:"Vitamin D is a hot topic that has attracted attention over the past 10 years, especially since a large proportion of people suffer from this nutrient deficiency. Vitamin D deficiency is estimated to be about 1 billion people all over the world and 50% in Asia and the Middle East. Saudi Arabia has also demonstrated a high prevalence of vitamin D deficiency among healthy Saudi individuals. This chapter provides, in detail, a clear and understandable identification of vitamin D, its function, source, synthesis, metabolism, status, and deficiency. The chapter also focuses on studying vitamin D deficiency in Saudi Arabia based on PubMed’s initial research criteria.",signatures:"Fawzi F. Bokhari and Mai Albaik",downloadPdfUrl:"/chapter/pdf-download/68649",previewPdfUrl:"/chapter/pdf-preview/68649",authors:[null],corrections:null},{id:"69039",title:"Vitamin D Deficiency in Children",doi:"10.5772/intechopen.89208",slug:"vitamin-d-deficiency-in-children",totalDownloads:843,totalCrossrefCites:1,totalDimensionsCites:1,hasAltmetrics:0,abstract:"In addition to its contribution to bone metabolism, vitamin D seems to fulfill a broad spectrum of biological functions which justifies the interest in monitoring its body content. The aim of this study is to analyze the prevalence of hypovitaminosis D and associated factors in schoolchildren and adolescents living in a region of northern Spain. A cross-sectional clinical and analytical study (calcium, phosphorus, calcidiol, and parathyroid hormone) was accomplished in a group of 602 Caucasian individuals (aged 3.1–15.4 years). Gender, age, body mass index, residence, and season of the year were recorded, and their association with vitamin D deficiency was analyzed by multiple regression. Vitamin D status was defined according to the US Endocrine Society criteria. The prevalence of hypovitaminosis D was 60.4% (insufficiency: 44.6%; deficiency: 15.8%). The female sex, adolescence, season of blood sample collection (autumn, winter, and spring), an urban residence, and severe obesity showed an association with an increased risk of hypovitaminosis D.",signatures:"Teodoro Durá-Travé, Fidel Gallinas-Victoriano, María Urretavizcaya-Martinez, Lotfi Ahmed-Mohamed, María Malumbres-Chacón and Paula Moreno-González",downloadPdfUrl:"/chapter/pdf-download/69039",previewPdfUrl:"/chapter/pdf-preview/69039",authors:[{id:"53819",title:"Prof.",name:"Teodoro",surname:"Durá-Travé",slug:"teodoro-dura-trave",fullName:"Teodoro Durá-Travé"}],corrections:null},{id:"70755",title:"Maternal Vitamin D Status among Different Ethnic Groups and Its Potential Contribution to Adverse Pregnancy and Child Outcomes",doi:"10.5772/intechopen.90766",slug:"maternal-vitamin-d-status-among-different-ethnic-groups-and-its-potential-contribution-to-adverse-pr",totalDownloads:830,totalCrossrefCites:1,totalDimensionsCites:2,hasAltmetrics:0,abstract:"Maternal vitamin D deficiency in pregnancy is a widespread public health concern. Race and ethnicity as biological and cultural factors, respectively, can affect vitamin D status through differences in skin color, sunlight exposure, and dietary intake. Low maternal vitamin D status in pregnancy may affect both mother and fetus adversely. Vitamin D deficiency and insufficiency are linked to a wide variety of adverse pregnancy outcomes such as gestational diabetes, preeclampsia, and preterm delivery. Furthermore, maternal vitamin D deficiency has been linked to several adverse health outcomes in infants and children. The examples include, but not limited to, impaired growth, skeletal problems, and autoimmune diseases such as type 1 diabetes and asthma. This chapter reviews the vitamin D status during pregnancy across different ethnic groups, looking into the adverse pregnancy and child outcomes, followed by a discussion on the association between maternal and child vitamin D status and successful interventions. Strong evidence exists about the association between vitamin D and some health outcomes during pregnancy, while more studies are needed to confirm the other claim. The existing body of evidence justifies the need for well-designed policies and systematic interventions to ensure optimal vitamin D status of pregnant women and their offsprings across different ethnic and racial groups.",signatures:"Pardis Keshavarz, Parisa Jandaghi, Mojtaba Shafiee, Naorin Islam and Hassan Vatanparast",downloadPdfUrl:"/chapter/pdf-download/70755",previewPdfUrl:"/chapter/pdf-preview/70755",authors:[null],corrections:null},{id:"69654",title:"Nutritional Considerations of Vitamin D Deficiency and Strategies of Food Fortification",doi:"10.5772/intechopen.89612",slug:"nutritional-considerations-of-vitamin-d-deficiency-and-strategies-of-food-fortification",totalDownloads:799,totalCrossrefCites:1,totalDimensionsCites:1,hasAltmetrics:0,abstract:"Vitamins and minerals are crucial for human health. Any deficiency can lead to major diseases; however, the most prevalent one is the vitamin D deficiency. Due to its high risk in the Middle East and Lebanon, besides its major effects, solutions to decrease this deficiency are taken nowadays. Vitamin D food fortification is the most popular solution taken now. Liposomes showed highest efficiency in vitamin D fortification. However, a study must be done in order to deduce the amounts needed in the targeted population. Therefore, before fortification starts, FDA regulations must be reviewed. Several foods succeeded in fortification with vitamin D and increasing its levels such as milk and cheddar cheese. Stability and flavors showed good results over fortification, while according to the odor, water sources showed more aroma depth than oil sources. The AOAC methods for vitamin D amount in fortified foods must be applied. Dietary 25(OH)D3 was 7.14-fold more effective at raising serum 25(OH)D than dietary vitamin D3.",signatures:"Sami El Khatib and Malak Abou Shahine",downloadPdfUrl:"/chapter/pdf-download/69654",previewPdfUrl:"/chapter/pdf-preview/69654",authors:[null],corrections:null},{id:"70173",title:"An Evidence-Based Review of Efficacy and Safety of Dietary, Natural Supplements and Sunlight in Vitamin D Deficiency",doi:"10.5772/intechopen.89598",slug:"an-evidence-based-review-of-efficacy-and-safety-of-dietary-natural-supplements-and-sunlight-in-vitam",totalDownloads:922,totalCrossrefCites:0,totalDimensionsCites:0,hasAltmetrics:0,abstract:"There have been recent concerns about the propensity of calcium and vitamin D supplementation to cause cancer. In osteoporotic patients, this has led to increasing recommendations advocating the replacement of calcium supplementation with dietary or other means. Around the world, the problem of vitamin D deficiency remains, being a large contributor of rickets and osteomalacia in the developing world and osteoporosis in post-menopausal women and people dependent on long-term corticosteroid treatment. We review the alternatives of vitamin D supplementation through dietary, other natural supplements as well as sunlight therapy, in an evidence-based manner. We will also review the safety aspect of each modality.",signatures:"Jenson Mak",downloadPdfUrl:"/chapter/pdf-download/70173",previewPdfUrl:"/chapter/pdf-preview/70173",authors:[{id:"60765",title:"Dr.",name:"Jenson",surname:"Mak",slug:"jenson-mak",fullName:"Jenson Mak"}],corrections:null},{id:"70606",title:"Association of Vitamin D Deficiency and Mood Disorders: A Systematic Review",doi:"10.5772/intechopen.90617",slug:"association-of-vitamin-d-deficiency-and-mood-disorders-a-systematic-review",totalDownloads:1025,totalCrossrefCites:2,totalDimensionsCites:4,hasAltmetrics:1,abstract:"The cells of our body comprise calcitriol (1,25(OH) vitamin D2), the active form of vitamin D, an integral biological substance that has an impact on a large number of biological processes. While high prevalence of vitamin D deficiency is detected in population worldwide, the reports from sun-soaked countries like India are also alarming to note that the deficiency of vitamin D as high as 70 to 90% is observed leading to several chronic diseases in the majority of people. Deficiency of vitamin D is observed not only because of low levels of vitamin D in the diet, less exposure to sunlight, reduced cutaneous vitamin D synthesis, but also due to consumption of particular medicines, undue alcohol intake, and tobacco smoking. Vitamin D is known to affect estradiol, dopamine, and pro-inflammatory cytokine levels, besides being involved in the regulation of mechanisms pertaining to hormones like glucocorticoids. When vitamin D binds to vitamin D receptors (VDR) present in the central nervous system, it is noted to be responsible for the regulation of brain neuronal functions. Low 25-hydroxy vitamin D levels are found to have a higher incidence of various mood disorders. This review focusses on vitamin D receptors, VDR gene mutations, and pathophysiology causing vitamin D deficiency disorders.",signatures:"Jigna Shah and Sakshi Gurbani",downloadPdfUrl:"/chapter/pdf-download/70606",previewPdfUrl:"/chapter/pdf-preview/70606",authors:[null],corrections:null},{id:"69069",title:"The Effects of Vitamin D Deficiency on Neurodegenerative Diseases",doi:"10.5772/intechopen.89160",slug:"the-effects-of-vitamin-d-deficiency-on-neurodegenerative-diseases",totalDownloads:982,totalCrossrefCites:2,totalDimensionsCites:7,hasAltmetrics:1,abstract:"Approximately 90% of the elderly population in the western countries has at least a mild to moderate vitamin D hypovitaminosis. Besides the well-known function of vitamin D in calcium homeostasis, it has been recently found that several enzymes and receptors involved in its homeostasis are expressed in the nervous system and brain suggesting also an important role in the brain homeostasis. Interestingly, epidemiological and clinical studies found reduced vitamin D level associated with an increased risk of several neurodegenerative disorders. In this chapter, we focus on a potential link between vitamin D and Alzheimer’s disease, Parkinson’s disease, multiple sclerosis, prion disease, and motor neuron disease. Epidemiological studies were summarized, an overview of the known potential underlying pathomolecular mechanisms are given, and results from clinical studies dealing with vitamin D supplementation were presented. As an outlook, recent literature suggesting an impact of vitamin D on autism spectrum disease, depression, and schizophrenia are briefly discussed. In conclusion, the identification of an abundant vitamin D metabolism in the brain and the tight link between the increasing number of several neurological and mental disorders emphasize the need of further research making a clear recommendation of the intake and supplementation of vitamin D in a growing elderly population.",signatures:"Anna A. Lauer, Daniel Janitschke, Tobias Hartmann, Heike S. Grimm and Marcus O.W. Grimm",downloadPdfUrl:"/chapter/pdf-download/69069",previewPdfUrl:"/chapter/pdf-preview/69069",authors:[null],corrections:null},{id:"69594",title:"Vitamin D3 Modulates NF-kB/p65, 17β-Estradiol, and Vitamin D Receptors Expression at Estrogen Deficiency",doi:"10.5772/intechopen.89357",slug:"vitamin-d-sub-3-sub-modulates-nf-kb-p65-17-estradiol-and-vitamin-d-receptors-expression-at-estrogen-",totalDownloads:850,totalCrossrefCites:0,totalDimensionsCites:0,hasAltmetrics:0,abstract:"The aim of the present study was to focus on the effects of Vitamin D3 (VD3) supplementation (5.0 mg/kg, s.c.) on the NF-kB/p65, 17β-estradiol (17β-E2)/VD3 receptors expression in the hippocampus in the long-term ovariectomized (OVX) rats treated with low dose of 17β-E2 (0.5 μg/rat, s.c.) submitted for the chronic unpredictable mild stress (CUMS) for 28 days. Sucrose preference (SPT), forced swimming (FST), and open-field (OFT) tests were conducted to estimate the anhedonia-/depression-like states. NF-kB/p65, 17β-E2/VD3 receptors levels in the hippocampus were evaluated by ELISA and Western blot assays. The findings demonstrated that VD3 at high dose (5.0 mg/kg, s.c.) in a combination with low dose of 17β-E2 decreased anhedonia in the SPT and depression-like behavior in the FST of the long-term OVX rats submitted to CUMS. VD3 (5.0 mg/kg) resulted in significant decreased levels of hippocampal NF-kB/p65 protein expression, as well as to the normalization of hippocampal 17β-E2/VD3 receptors levels in long-term OVX rats treated with 17β-E2 exposed to CUMS. In conclusion, VD3 (5.0 mg/kg, s.c.) in a combination with low dose of 17β-E2 had a synergic antianhedonic- and antidepressant-like effects in the adult female rats following long-term ovariectomy submitted to CUMS.",signatures:"Alexandra Koshkina, Olga Volkova and Julia Fedotova",downloadPdfUrl:"/chapter/pdf-download/69594",previewPdfUrl:"/chapter/pdf-preview/69594",authors:[null],corrections:null},{id:"70127",title:"Vitamin D and Obesity",doi:"10.5772/intechopen.90181",slug:"vitamin-d-and-obesity",totalDownloads:972,totalCrossrefCites:1,totalDimensionsCites:1,hasAltmetrics:1,abstract:"Obesity is a very common issue worldwide, and it is one of the risk factors for mortality. Several studies were done to identify the causes of this issue and to investigate factors that can affect this condition. Vitamin D is claimed to have an impact not only for maintaining bone health but also for having an association between its deficiency and obesity as some studies found that the concentrations of this vitamin are low in obese individuals. The suggested mechanisms and a discussion of the latest findings as well as the possibility of integrating supplementation in the treatment of obesity are covered in this book chapter. It was concluded that vitamin D deficiency is prevalent in many parts of the world and the supplements are an affordable option, but further studies are required to address different confounding factors that will result in clear data interpretation and will contribute to the future planning of health policies and guidelines used by healthcare professionals.",signatures:"Sabrina Ait Gacem and Moyad Jamal Shahwan",downloadPdfUrl:"/chapter/pdf-download/70127",previewPdfUrl:"/chapter/pdf-preview/70127",authors:[null],corrections:null},{id:"69402",title:"Vitamin D Deficiency and Diabetes Mellitus",doi:"10.5772/intechopen.89543",slug:"vitamin-d-deficiency-and-diabetes-mellitus",totalDownloads:1608,totalCrossrefCites:2,totalDimensionsCites:3,hasAltmetrics:1,abstract:"Vitamin D (VD) is a molecule that can be synthesized directly in the humans’ body or enter the organism with food in the form of inactive precursors. To exert its biological action, VD undergoes two-stage hydroxylation (at the 25th and 1st position) catalyzed by cytochromes P450, the presence of which has already been shown in almost all tissues of the human body. The product of hydroxylation is hormone-active form of vitamin D–1,25(OH)2D. 1,25(OH)2D binds to specific vitamin D receptor (VDR) and regulates the expression of genes involved in bone remodeling (classical function) and genes that control immune response, hormone secretion, cell proliferation, and differentiation (nonclassical functions). VD deficiency is prevalent around the globe and may be one of the key factors for diabetes development. The direct association between vitamin D deficiency and type 1 (T1D) and type 2 (T2D) diabetes has been proven. Detection of VDR in pancreas and adipose tissue, skeletal muscles, and immune cells allowed implying the antidiabetic role of vitamin D by enhancing insulin synthesis and exocytosis, increasing the expression of the insulin receptor, and modulating immune cells’ functions. This chapter summarizes data about relationship between VD insufficiency/deficiency and development of T1D and T2D, and their complications.",signatures:"Ihor Shymanskyi, Olha Lisakovska, Anna Mazanova and Mykola Veliky",downloadPdfUrl:"/chapter/pdf-download/69402",previewPdfUrl:"/chapter/pdf-preview/69402",authors:[null],corrections:null},{id:"70095",title:"Vitamin D and Cardiovascular Disease: The Final Chapter?",doi:"10.5772/intechopen.90106",slug:"vitamin-d-and-cardiovascular-disease-the-final-chapter-",totalDownloads:768,totalCrossrefCites:0,totalDimensionsCites:1,hasAltmetrics:0,abstract:"Vitamin D deficiency is globally prevalent and has been associated with the pathogenesis and complications of cardiovascular disease (CVD) and its risk factors. Defining these relationships has been challenging, and the clinical applications of vitamin D screening and supplementation for CVD risk prevention and modification have only recently become clearer. Most of the available evidence includes large observational studies and smaller randomized trials that scarcely evaluate CV outcomes as primary endpoints. Additionally, these studies include methodological inconsistencies, making it difficult to ascertain the benefits of vitamin D supplementation. However, more recently, randomized trials have been conducted which utilize CVD outcomes as primary endpoints, while assessing the effects of high dose vitamin D supplementation on CV health. Despite observational evidence as well as a conventional consensus that vitamin D supplementation improves CV health, these studies suggest that vitamin D supplementation likely has no benefit in this regard, at least in the follow-up period and populations evaluated.",signatures:"Jeremy I. Purow and Seth I. Sokol",downloadPdfUrl:"/chapter/pdf-download/70095",previewPdfUrl:"/chapter/pdf-preview/70095",authors:[null],corrections:null},{id:"69633",title:"Vitamin D and Autoimmune Diseases",doi:"10.5772/intechopen.89707",slug:"vitamin-d-and-autoimmune-diseases",totalDownloads:1306,totalCrossrefCites:2,totalDimensionsCites:2,hasAltmetrics:1,abstract:"Vitamin D has many and profound effects on the immune system. Vitamin D deficiency is known to be related to the development of autoimmune diseases. In particular, vitamin D deficiency is related to the development and the severity of rheumatoid arthritis (RA). RA develops in patients with vitamin D deficiency, and the activity of the disease is related to vitamin D deficiency. Vitamin D deficiency is also related to the development of systemic lupus erythematosus (SLE). SLE develops in patients with vitamin D deficiency, and the activity of the disease is also greater in patients with vitamin D deficiency. Vitamin D deficiency is also related to the development and the severity of multiple sclerosis. Vitamin D should be administered to patients with multiple sclerosis, and this seems to mitigate the symptoms of the disease and to prevent disease progression. Vitamin D deficiency is also observed in patients with inflammatory bowel disease and may be related to disease severity. Low vitamin D levels have also been observed in patients with autoimmune Hashimoto’s thyroiditis. Low vitamin D levels have been observed in patients with systemic sclerosis, especially in the diffuse form of the disease. Optimal vitamin D levels appear to be required for normal immune function and for the prevention and treatment of autoimmune diseases.",signatures:"Ifigenia Kostoglou-Athanassiou, Lambros Athanassiou and Panagiotis Athanassiou",downloadPdfUrl:"/chapter/pdf-download/69633",previewPdfUrl:"/chapter/pdf-preview/69633",authors:[null],corrections:null},{id:"69574",title:"Vitamin D Deficiency in Renal Disease",doi:"10.5772/intechopen.88928",slug:"vitamin-d-deficiency-in-renal-disease",totalDownloads:1104,totalCrossrefCites:1,totalDimensionsCites:1,hasAltmetrics:0,abstract:"Vitamin D deficiency is highly prevalent in patients with renal disease. The abnormal vitamin D (VD) metabolism in chronic kidney disease (CKD) is a key factor for developing CKD-related mineral bone disease (CKD-MBD), which directly influences the survival of the CKD patients. The importance of VD is perhaps of greater value due to its pleiotropic effects that span beyond calcium-phosphorus metabolism (cancer protection, diabetes prevention, and renal protection). The aim of our chapter is to depict the clinical implications of VD deficiency in the setting of CKD, including VD pleiotropy in renal disease, and to propose the most adequate treatment suggested in the literature.",signatures:"Jean Jeanov Filipov and Emil Paskalev Dimitrov",downloadPdfUrl:"/chapter/pdf-download/69574",previewPdfUrl:"/chapter/pdf-preview/69574",authors:[{id:"181956",title:"Dr.",name:"Jean",surname:"Jeanov Filipov",slug:"jean-jeanov-filipov",fullName:"Jean Jeanov Filipov"},{id:"185237",title:"Prof.",name:"Emil",surname:"Paskalev Dimitrov",slug:"emil-paskalev-dimitrov",fullName:"Emil Paskalev Dimitrov"}],corrections:null}],productType:{id:"1",title:"Edited Volume",chapterContentType:"chapter",authoredCaption:"Edited by"},subseries:null,tags:null},relatedBooks:[{type:"book",id:"5940",title:"Vitamin C",subtitle:null,isOpenForSubmission:!1,hash:"e23e79359167bb9d4a53edd78c7b5038",slug:"vitamin-c",bookSignature:"Amal H. Hamza",coverURL:"https://cdn.intechopen.com/books/images_new/5940.jpg",editedByType:"Edited by",editors:[{id:"188326",title:"Associate Prof.",name:"Amal",surname:"Hamza",slug:"amal-hamza",fullName:"Amal Hamza"}],equalEditorOne:null,equalEditorTwo:null,equalEditorThree:null,productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}},{type:"book",id:"5169",title:"Vitamin K2",subtitle:"Vital for Health and Wellbeing",isOpenForSubmission:!1,hash:"b2f9f024939ddc4f5da2a8afa3fcd9c9",slug:"vitamin-k2-vital-for-health-and-wellbeing",bookSignature:"Jan Oxholm Gordeladze",coverURL:"https://cdn.intechopen.com/books/images_new/5169.jpg",editedByType:"Edited by",editors:[{id:"36345",title:"Prof.",name:"Jan",surname:"Gordeladze",slug:"jan-gordeladze",fullName:"Jan Gordeladze"}],equalEditorOne:null,equalEditorTwo:null,equalEditorThree:null,productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}},{type:"book",id:"7263",title:"Vitamin E in Health and 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In the case map is created by someone else than a professional cartographer the process of making maps suffers by considerable degree of subjectivity. Despite the several-hundred-years effort of objectification of map making process, cartographers sometimes have difficulties to imagine the way how the user will use the map, especially the way of map perception, reading, analysis and interpretation [1]. Cartographers often lack the reasoning for the decision-making in balancing the map design and layout, designing a map symbology, choosing the cartographic method of visualization or level of generalization [2]. For these reasons it is necessary to carry out a research on user perception of maps.
According to Golledge and Stimson [3] the perception is function of a cognition (thinking), which can be understood as a way of encoding, storing and integrating information into existing knowledge. In order to study reading and using maps the perception is very important, because it helps to structure the area depicted on the map.
Several approaches of the research on user perception and evaluation of the applicability and effectiveness of maps exist. The eye-tracking is one of the rarely used. Based on results of eye movements analyses, many questions, that were not yet been discussed in cartography adequately, can be answered. For example, how users obtain information from the map, what is the strategy of map reading, how often users look to the map legend, how easily can be map symbols interpreted, etc. Analyses of maps usability can help in optimizing the map symbology, composition or design, so the new maps can be created in order to respect the specific user\'s requirements.
The main sensory channel for cognitive processes is vision [4]; therefore the research on map visual perception is necessary
The term usability is defined as “the effectiveness, efficiency, and satisfaction with which specified users achieve specified goals in particular environments” [5]. Satisfaction quantifies subjective users’ impressions dealing with such indicators as operability and learnability of a given task. Efficiency and effectiveness metrics are objective performance measures of speed and accuracy. [6]
Nielsen [7] defines usability as a quality attribute that assesses how are user interfaces easy to use. Usability can reveal qualities of the product as well as lack of its functionality, which usually arises during the design phase of a product. [8] The assessed product can be an image, web page, text or a map. To be able to derive qualitative or quantitative measures of the user experience (usability), a number of evaluation methods is possible to use. Li et al. [9] mentions these methods of usability evaluation:
focus group studies,
interview,
direct observation,
think-aloud protocol,
retrospective think-aloud protocol,
screen capture,
eye-tracking.
Each method has its advantages and disadvantages. Frequently a combination of methods is used in the research. For example, see [10, 11, 12].
The method of focus group studies and interview are based on direct contact with the user. They are based on a targeted questioning and recording of discussions and responses of individuals or groups.
The method of direct observation leads to the detection of subject’s behaviour in its natural environment without any interference by the observer. For observation various technical utilities, especially recorders, cameras and camcorders, are used. Direct observation sometimes leads to problems in professional ethics, especially when observed people are not acquainted with the fact that they are the subject of observation.
A frequently used method is "Think-Aloud". Its principle lies in the verbalization of the process performed by the user during solving a specific problem. Participating test subjects verbally describe the process of solving specific tasks and also their feelings [13]. This method is very quick and inexpensive, nevertheless, participant is not aware of all cognitive processes, and not all processes can be simply expressed in words. This method is very subjective in the term of observed subjects, who describe their experiences, and also in the term of the evaluation of their response. Detail usage of this method is discussed by Somersen [14]. Similar to the "Think-Aloud" method is a retrospective variant, when the subject describes a workflow after the task is completed.
The screen capture method of usability study was in the field of cartography and GIS used for example in Haklay et al. [15]. They assessed the usability of GIS software using screenshots that users had posted. On these images the windows of application were captured in the middle of the workday and composition of opened toolbars was analysed.
The last mentioned method, which is in the focus of this chapter, uses a device to monitor eye movements. Eye-tracking method can be considered to be objective, because it is not influenced by the opinion of the monitored person [16].
Eye-tracking technology is based on the principles of tracking movements of human eye while perceiving the visual scene. The measurement device used for measuring eye movements is commonly known as eye-tracker. [17]
When users are searching for the information in unknown environment (text articles, web pages, maps etc.), typically two types of processes occur: a perceptual one (the user should locate/notice the target) and a cognitive one (the user cognitively computes the visual input and understands the function of the target). Eye movement analysis provides valuable quantitative and qualitative information on both stages of visual search. [16]
Qualitative information describes the way in which user explores the stimuli. They can reveal areas of maximum interest, disruptive elements and strategy of searching for a specific element. Quantitative information describe the time spent by observing a particular phenomenon, speed of identifying information and several derived gaze data metrics.
In general, there are two types of eye movement monitoring techniques: those that measure the position of the eye relative to the head, and those that measure the orientation of the eye in space, or the “point of regard”. [18]
According to Duchowski [6], methods of eye movement tracking can be categorized into three main groups:
electrooculography (EOG),
scleral contact lens/search coil
remote eye-tracking.
EOG is a method which was popular about 40 years ago. Its principle lies in measuring of skin’s electric potential differences of electrodes placed around the eye. By recording quite small differences in the skin potential around the eye, the position of the eye can be tracked. [19]
The method of scleral contact lens or search coil uses an attachment to the eye, such as a special contact lens with an embedded mirror or magnetic field sensor, and the movement of the attachment is measured with the assumption that it does not slip significantly as the eye rotates. Both mentioned methods measure eye position relative to the head and they are not generally suitable for point of regard measurements.
Currently the most exploited eye movement measurement method is remote eye-tracking, also called the Pupil and Corneal Reflexion method. It relies on the measurement of visible features of eye, e. g. pupil, iris-sclera boundary and corneal reflection of a closely situated direct light source (often infra-red). The reflected light is recorded by a video camera or specially designed optical sensor. The information is then analyzed to extract eye rotation from changes in corneal reflections. The resulting corneal reflexion is also known as “glint” or the 1st Purkinje reflexion (P1) [20].
There are at least four Purkinje images (figure 1). The first Purkinje image (P1) is the reflection from the outer surface of the cornea. The second one (P2) is the reflection from the inner surface of the cornea. The third one (P3) is the reflection from the anterior surface of the lens and the last one (P4) is the reflection from the posterior surface of the lens. [21]
Eye position and gaze direction are estimated using information from an image sensors picking up reflection patterns on the cornea and other information points. By image analysis and mathematics a gaze point on a reference plane can be calculated.
Four Purkinje images - the reflection (L) on different parts of the eye: P1 from the outer surface of the cornea, P2 from the inner surface of the cornea, P3 from the anterior surface of the lens, P4 from the posterior surface of the lens. [
Human eyes can only perceive a limited fraction of the visual world at one point in time. Both eyes together provide a roughly elliptical view of the world which is approximately 200 of visual angle wide and 130 high. [23]
However not all parts of this view are perceived with equal acuity because the retina of the eye has a varying structure and composition. The fovea, part of the retina, is responsible for sharp central vision (also called foveal vision), which is necessary during reading, watching television or movies, driving, and any activity where visual detail is of primary importance. The really high-resolution area covers only about 2 of the visual field. The fovea is surrounded by the parafovea belt and the perifovea outer region [24]. The vision supported by this part of the eye is so called peripheral vision, which in comparison with foveal vision seem to be blurred [25].
Eye movement is not smooth. The eye moves in spurts and rests between each movement. During a fixation, eyes are relatively steadily looking at one spot in the visual scene. In order to achieve the most accurate visual impression of a visual scene, eyes move rapidly in mostly ballistic jumps (i.e., saccades) from one spot to another. Among those rather large saccadic eye movements that an attentive person can easily observe from his or her own experience, there are three other, much shorter eye movements, i.e. tremor, drift, and microsaccades. Their purpose is to avoid saturation effects of the visual receptors on the retina which would lead to fading perception. However, people are unaware of those tiny movements and they can be hardly detected by state-of-the-art unobtrusive eye-trackers. [23]
The analysis of fixations and saccades requires some form of identification that results from the processing of raw eye-movement data. Fixation and saccades identification is an inherently statistical description of observed eye movement behaviours.
It is important to define the exact detection algorithm for eye movement analysis, because different parameterizations of an algorithm might lead to different results [26]. Plenty of algorithms exist, but mostly used are I-VT and I-DT. In the case of the I-VT (Velocity-threshold fixation identification) algorithm, the eye-velocity value is compared to the threshold. If the sampled velocity is smaller than the threshold, the corresponding eye-position is marked as a part of a saccade, otherwise the eye-position sample is assigned to be a part of a fixation. The I-DT (Dispersion-Threshold Identification) algorithm takes into account the close spatial proximity of the eye position points in the eye movement trace. [27]
Based on statistical analysis of fixations, saccades, their mutual relationship and other characteristics, it is possible to identify certain attributes of respondent behaviour.
For example, long average fixation durations can be interpreted in two different ways as either: (1) the user has difficulties extracting information; or (2) the user is more engaged with interpreting a representation [28]. Hence, distinguishing between the two is case specific.
Saccade/Fixation ratio describes the ratio between search activity (represented by the number of the saccades) and processing activity (represented by the number of the fixations). A small saccade/fixation ratio indicates that the user is spending more “cognitive resources” on the task and less cognitive resources on gathering important background information [16].
A large number of saccades indicate a low degree of search efficiency or poor interface layout. User roams from place to place finding no satisfactory answer. Saccadic amplitude together with ScanPath duration and ScanPath length can refer to a strategy of user cognition style, or quality of examined layout [23].
According to fundamentals of examined problem it is necessary to use a proper eye-tracker. Individual devices differ from one another by precision given by the spatial resolution and accuracy of the point of view. An important parameter is the time resolution, which is expressed in hertz (Hz). Department of Geoinformatics, Palacký University in Olomouc owns static SMI RED 250 Eye-tracker (figure 2) with sample frequency of 120 Hz, so data are recorded approximately every 8 ms.
Device parameters (resolution, mobility) must respect the purpose of the application for which the device is used. Research on sportsmen or driver concentration, or arrangement of goods on the shelves requires a mobile device mounted on the head of the subject (the headset). Evaluation of stimuli on the computer screen or television will rather use the static device.
Laboratory setup with static remote SMI RED 250 eye-tracker at Department of Geoinformatics, Palacký University in Olomouc.
Anatomy of the human eye is known for hundreds of years, but scientific interest in the processes of visual perception began only during the 19th century [29]. After the Second World War, one of the first measures of gaze direction was done in 1947. The research was focused on the behaviour of military pilots during aircraft landing. It was carried out by analyzing the video with more than 500 000 film frames [30].
With the improvements of the eye-tracking technologies, eye-tracking tools gain their impacts on the usability field and nowadays they are accepted as a tool to improve computer interfaces [11]. Currently eye-tracking is utilizable in many areas of human activity - psychology, medicine, marketing, commercial, etc.
One of the research goals of contemporary cartography is the investigation of perception processing of maps, not only from the commercial point of view, but also in planning, crisis management and rescue operations.
On the one hand, map is very important carrier of information that readers need to assimilate as quickly as possible and undistorted, so cartographers labour for its highest possible accuracy. On the other hand map design and its visual appearance are determinants of user popularity.
In both cases, the key to success is to answer a number of highly debated issues - for example how readers follow the information in the map, in which order and how fast they read the information, which compositional elements they read earliest, how many times they look back to the map legend, which map elements are easy and which difficult to handle, what affects the legibility of the map, etc. These findings can facilitate to evaluate the quality of the map composition, symbology and map content, and thus define the methodology for creating maps that will correspond with requirements of users.
With respect to the investigatory device, maps evaluation using eye-tracking technology is available both for analog maps and the digital cartographic outputs.
One of the first publications focused on the application of eye-tracking methods in cartography is Eye Movement Studies in Cartography and Related Fields [29], in which the author summarizes the results of various studies in the late 80’s of the 20th century. It deals with the general knowledge of tracking of the human eye, studies on evaluation of specific graphic outputs, emphasizing the impossibility to generalize the findings in the behalf of dissimilar studies. He described several universal conclusions and highlighted the importance of distinguishing between user groups according to their age and education.
It is possible to separate the evaluation of information content of maps from the map design. However complex evaluation is more logical, because the information value of maps (e. g. content) can be increased or degraded by technical or artistic design.
An example of a complex evaluation of maps was presented by Alacam and Dalci [11], who compared four map portals (Google Maps, Yahoo Maps, Live Search Maps and MapQuest). Results of eye-tracking experiment revealed considerable variance in the strategy of solving particular quest in different map portals environment. Basic assumption of this study was that the lower the average duration of fixation, the more intuitive the environment. It was found, that users average fixation duration at the Google Map stimuli is statistically significantly lower, than in the case of other evaluated portals.
Coltekin et al. [31] in their research deal with the evaluation of user interface of cartographic software. Test subjects were ask to create a complex map in two different map applications. The study was designed as a between-subject experiment and eye movement analysis was coupled with traditional usability metrics to identify possible design issues. Initial analyses included statistical tests for satisfaction, effectiveness (accuracy of response), and efficiency (response speed).
In a different study the same authors [32] deal with a generic evaluation approach combining theory and data-driven methods based on sequence similarity analysis. The approach systematically studies users’ visual interaction strategies when using highly interactive map interfaces. The result was that the participants generally follow a sequence that agrees with the hypothetical sequence representing user’s strategies.
Another application of eye-tracking in cartography appears in the study of Opach and Nossum [33] where authors have explored the suitability of eye-tracking on two different semistatic and traditional cartographic animations of temperature and weather. Contrary to the author’s previous web based experiment, analysis of the eye-tracking data revealed that the viewing behaviour were surprisingly similar. Three of the metrics used (fixation counts, observation length and time to first fixation) indicated very similar viewing strategies and behaviour during viewing different kind of cartography animations.
Fuhrman, Tamir and Komogortsev [34] have dealt with an assumption that three-dimensional topographic maps provide more effective route planning, navigation, orientation, and way-finding results than traditional two-dimensional representations. The eye-tracking metrics analysis indicates with a high statistical level of confidence that three-dimensional holographic maps enable more efficient route planning.
Popelka and Brychtova [35] used eye-tracking together with questionnaire investigation for evaluation user’s attitudes toward interactive methods of virtual geovisualisation of changes in the city built-up area. Five approaches of visualization were assessed - textual description of changes, comparison of historical and recent pictures or photos, overlaying historical maps over the orthophoto, enhanced visualization of historical map in large scale using the third dimension and photorealistic 3D models of the same area in different ages.
Technologies and methods of eye-tracking have not yet been fully utilized in cartography, even though the possibilities are wide. Cartographic research in the field of eye-tracking currently focuses explicitly on improving the user quality of maps. Future potential expansion of eye-tracking technology can be seen in the activity of the International Cartographic Association, especially the Commission on Use and User Issues [36] and the newly established Commission on Cognitive Issues in Geographic Information Visualization [37].
Results of eye-tracking measurements are presented as a text file containing a timestamp and a number of specifications describing coordinates of the point of regard, the pupil size, the angle of the eye position etc. First of all, it is necessary to classify the data, with a specified algorithm, as fixations and saccades (see chapter Eye movements and algorithms of their detection). Then, the data are even visualized in a suitable way, or can be statistically analysed.
There are several basic methods of the eye-tracking data visualization. Holmqvist et al. [20] present the main techniques of gaze data visualization as follows: ScanPath (GazePlot), Attention (Heat) maps and the AOI (Area of Interest) Analysis.
Following chapters will present different possibilities of visualization and eye-tracking measurements on concrete examples from cartography. In this way, methods of eye-tracking will be shown. All examples are based on source data, which are results of several authentic experiments on cartography rules evaluation.
All presented case studies were performed using the SMI RED 250 remote device with the sampling frequency of 120 Hz. Eye position was measured every 8ms.
Respondents were chosen from university students of Geoinformatics and Cartography and also from other studying fields which are not related to cartography.
ScanPath is defined as a route of oculomotor events through space within a certain time-span [20]. Thanks to ScanPath, it is possible to display raw data as well as calculated fixations and saccades. Circles of different sizes represent fixations (their radius corresponds with their length) and lines which connect the circles represent saccades [38].
When a larger amount of data is displayed, this method becomes restraining. Overlapping parts of individual fixations cause that it is not possible to identify their number visually. Figure 3 shows an example of a ScanPath. Respondents were asked to find the highest peak on one of the maps. The aim of this experiment was to compare two types of visualization - perspective 3D display and a classical orthogonal map supplemented with the shading. Raw data are displayed on the left of the picture, fixations and saccades on the right. From both pictures, it is evident that this particular respondent preferred the three-dimensional visualization. His answer is displayed by a red dot which represents the mouse-click.
ScanPath showing raw data (left) and fixation and saccades (right)
There is a great need for robust and general method for ScanPath comparison existing in many fields of eye-tracking research [39]. Privitera and Stark [40] introduced ScanPath comparison based on string editing. Fixations are replaced with characters standing for the AOI’s they hit and the ScanPath is represented as character string. It is one of the first methods comparing not only the loci of fixations, but also their order. The principle of this method is the transformation of two-dimensional data (X, Y coordinates of fixations) to one-dimensional data (character string). Each ScanPath is recorded as a string of letters where each letter corresponds to the area of a current fixation location.
Two or more character strings are then compared and their similarity is measured. Defined by an optimization algorithm, string editing assigns a unit value to three different character operations: deletion, insertion, and substitution. Characters are then manipulated in order to transform one string into another and character manipulation values are tabulated [41]. String edit algorithm determines the number of operations needed to transform one sequence to another - the operations being insertions, deletions and substitutions. The calculated metric will be a measure of how different two sequences are. This method uses the Levenshtein algorithm to produce a string-edit distance between each sequence [42]. Example of the Levenshtein distance measure is in the figure 4. Character string comparison methods are widely used in bioinformatics to align DNA and protein sequences.
Result of the Levenshtein distance measure between group of eleven geoinformatics while observing a map. Gridded AOI with grid of 5*5 cells was used
Depending on specific tasks, it is important to distinguish between gridded AOI and semantic AOI approaches. When using the Gridded AOI, stimulus is split into areas of equal size (rectangles) with no relation to semantics. The second approach, Semantic AOI uses the Area of Interest which corresponds to specific areas in stimuli. In cartography, Semantic AOI is generally more advantageous because it corresponds to map composition elements like title, legend, etc.
Attention maps, also called HeatMaps, are used for visualization of quantitative characteristics of the user’s gaze. Thanks to attention maps, it is possible to identify to which area user pay attention and which are rather neglected. In eye-tracking, HeatMaps enable the creation of a brief summary of areas which are in the spotlight and so they are needed to be analyzed more thoroughly. Except of the function of visualization, they might be used as a background for AOI creation. When plotting AOI around a small object, fixations of some of the respondents could be noted outside the created AOI because of inaccurate measurement or calibration deflection. By means of HeatMaps, it is possible to get an overview of possible measurement inaccuracies and so to adapt the Area of Interest.
HeatMaps produced by SMI software BeGaze are created in two steps. The software first scales each pixel in proportion to the durations of all fixations landing on it. Typically, this results in a very sparse “Fixation Hit Map”, since only a small proportion of the pixels have been “hit”. In next step, the hit map is convolved with a Gaussian kernel with certain width. A wider kernel gives a smoother, less pointy appearance to the attention map [20].
HeatMap created from fixations of seven respondents
Areas of Interest (AOI) are regions in the stimulus which the researcher is interested in. The most important AOI metric is the dwell time defined as one visit in AOI, from entry to the exit. The dwell has its own duration, the starting point, the ending point, dispersion etc. In several ways, it is similar to a fixation, but it is of much larger entity, both in space and time [20]. It is also possible to follow the order in which the respondent looked at particular areas or the transition, the movement from one AOI to another etc.
In cartography the Areas of Interest analysis can be used advantageously. AOI analyses are based on evaluation of concrete parts of a map (legend, scale, title, specific phenomena in the map, etc.). When evaluating influence of a composition on the map reading, the application of AOI is very useful. By indicating and evaluating particular compositional elements as AOI, several characteristics can be find out - e.g. for how long the respondent was observing the given area, in which order he visited them etc.
The results can be visualized with use of the Sequence Chart, which displays observed areas in different colours on a timeline. Figure 6 shows results of an experiment, whose objective was to reveal differences in reading of a simple map by a group of students of cartography and cartography amateurs. Three different map compositions are displayed in figure 6. Maps (presented in the first row of figure 6) were projected in 5s intervals during which the respondents have to observe maps without answering any question. The second raw in the Figure 6 shows a sequence chart for a group of students of Geoinformatics and cartography, who have attended several cartography courses. The last row represents data given by cartographic amateurs, students of psychology, zoology etc.
Each stimulus was preceded by a short cross used to locate beginning of all trajectories at the same place (in the middle of the picture). That is why the AOI representing the map field is always pictured in first 500 ms. After this time; most geoinformatics students automatically read the title of the map, or rather noted fixations representing it in AOI. Cartographic amateurs did not do so. It is evident especially in the first column, where the stimulus was the “ideal” map composition [43]. In following columns, the composition was not in accordance with cartographic rules. Despite this fact, students of geoinformatics were trying to find the title of the map.
Sequence chart visualization. Sample data of the Esri were used for the creation of stimulus maps
The Sequence Chart is illustrative and easy to interpret, but it is necessary to evaluate the data by statistical approach.
The objective of the statistical hypotheses testing is to evaluate the data gained from experiments and the suitability of the purpose given before the testing. Statistical hypothesis is a certain purpose about the distribution of accidental quantities of a basic file.
In statistics, the result is called statistically significant when it is unlikely to have occurred by chance alone, according to a pre-determined threshold probability, the significance level. Critical tests of this kind may be called tests of significance. When such tests are available, we can say whether the second sample is/ is not significantly different from the first one [44].
From a more detailed evaluation of different types of basic eye movements (fixations and saccades), or gaze data metrics such as dwell time, it is possible to deduce a series of numeral metrics suitable for other statistical testing.
Different composition perception with two different groups of map users (experienced cartographers and non-cartographers) was verified by the testing of measured results by a two sample t-test, which is a method of mathematical statistics making possible to verify the null hypothesis that the means of two normally distributed populations are equal.
Differences of the mean dwell time of two groups of users were tested on particular Areas of Interest of the map list - title of the map, the map, the legend, the imprint and secondary maps. A zero hypothesis H0 was tested: mean values of particular choices are the same. Concrete results are illustrated in table 1.
t | df | p-value | alpha | mean of carto [ms] | mean of non-carto [ms] | statement | |
Main map | -2,2189 | 33,374 | 0,0334 | 0,05 | 2375,58 | 3080,11 | Rejecting H0 |
Map heading | 3,7546 | 51,501 | 0,0004 | 0,05 | 631,27 | 230,78 | Rejecting H0 |
Additive map 2 | 0,0963 | 36,715 | 0,9238 | 0,05 | 387,84 | 376,47 | Fail to reject H0 |
Additive map 1 | -0,1874 | 40,321 | 0,8523 | 0,05 | 260,59 | 284,08 | Fail to reject H0 |
Masthead | 1,1999 | 36,275 | 0,2380 | 0,05 | 127,27 | 57,57 | Fail to reject H0 |
Map legend | 0,2211 | 45,702 | 0,8260 | 0,05 | 99,50 | 84,33 | Fail to reject H0 |
By comparing the mean dwell time in particular AOI it is evident that both groups spent most time on the main map field. Extremely long time was noticed at students of cartography in AOI covering the map title. The same AOI was on the 4th position with non-cartographers.
The t-test result disproved the zero-hypothesis saying that the values of the mean dwell time were the same with AOI map heading and the main map field. The visit rate of the main map field was significantly higher with non-cartographers. On the contrary, the map title visit rate was higher with cartographers. There was no difference of the dwell time statistically proved with other observed AOI.
Data sets created as a result of the eye-tracking are often very large, which limits their visualization possibilities by means of methods mentioned above. When displaying larger data sets with the ScanPath visualization, overlapping parts are created and the follow-up interpretation of results is not possible. The cause of this problem is displaying of three-dimensional data (X, Y, time) into two-dimensional space (X, Y).
With relatively smaller data sets, it is possible to use colours to differentiate fixations according to their order. During the visualization, transparency can be used to identify overlapping fixations.
Another possible solution is to neglect the time. Two dimensional data (X, Y) can be then displayed by means of HeatMap method which displays only the number of fixations, without their order. However, the loss of the information can make the analysis of results impossible in many cases.
Thanks to Space-Time-Cube (STC) which is the most important element of the Hägerstrand time-space model, the data can be effectively visualized without neglecting any of the data files [45].
In its basic appearance, the cube has on its base a representation of the geography (X, Y), while the cube’s height represents time (Z) [46]. As it is evident from figure 7, if the location of the observed object or phenomenon does not change in time, the line is always perpendicular to the base of the cube. The steeper the line between two vertices, the slower the change in the position of observed object/phenomenon. Today there are softwares that automatically creates a Space-Time-Cube from the data in the database. It is also important that it is possible to interactively rotate the cube and select the best perspective for data analysis.
By means of Space-Time-Cube, it is possible to portray any space-time data. These might be for example data recorded by a GPS device, statistic data containing information about location and time, or data detected with eye-tracking.
In this case, coordinates X and Y describe the distribution of fixations in space, and time is described by the axis Z. Thanks to Space-Time-Cube it is possible to reveal different behaviour of particular users. On the other hand, ScanPath cannot identify in which direction the user moved when reading the picture. Up to now, application of Space-Time-Cube with analysis of eye-tracking data was examined only by [9, 47, 48].
Space-Time-Cube visualization is presented in this chapter on testing the user’s perception of the map legend. Respondents were given the task to mark flax growing areas on the map. The aim of the test was to find out the proportion of respondents (%), which use the map legend to fulfil the task. Trajectories of eye movements of two respondents are displayed in figure 8. It is evident that during the first two second of solving the task, the respondents followed almost the same gaze trajectories. One of the first fixations of both respondents are localised in the legend. Then, the respondents tried to answer the given question and started to explore the map.
Time-space data displayed by means of Space-Time-Cube.
Use of Space-Time-Cube visualization for investigation of ScanPaths from two respondents
Up to now, technologies and methods of eye-tracking in cartography were not fully utilized despite their great possibilities in cartography. A cartographical research in the field of eye-tracking recently focuses on the improvement of the user quality of a map, particularly on the map composition improvement. However, there is a question how to define the user quality of a map or a “good” map composition. In the main, the user has to be able to interpret the content of the map correctly and accurately. A correct but a too long interpretation of a map cannot be considered as a sign of high user quality of the map. A method of the map content interpretation or the way of internal recording and later recalling of the information are related to its structure of cognitive and mental maps [49, 50, 51]. That is why the improvement of the user quality of a map is considered necessary if we want to perceive into cognitive processes going on during work with maps. In this field, eye-tracking can enable the user to do a research of cognitive maps. Nevertheless, it is necessary to respect the fact that maps have its own special dimension which cannot be neglected during the research because it is essentially connected with the user’s map-content interpretation.
Thanks to easier (but not easy) access to high-performance eye-trackers, we can expect, in a short time period, more numerous and deeper researches on different aspects of map reading. In the field of map creation, there exist certain short and long-term rules. Many of them are respected without any international convention, for example a blue colour used for waters [52].
High initial investments on high quality equipment and a non-existence of a single methodology for preparing and evaluation of tests limit the implementation of the described technology in cartography research. It is also necessary to cooperate with a professional psychologist.
Cartographic research with eye-tracking methods will considerably contribute to argumentation of a high number of empirically based rules and instructions for map creation and the map language will be internationalized. By implication, it will enable geographers to present better results of their researches and studies.
AcknowledgementThe chapter has been completed within the project CZ.1.07/2.4.00/31.0010 Supporting the creation of a national network of new generation of Cartography – NeoCartoLink which is co-financed from European Social Fund and State financial resources of the Czech Republic and the project The small format photography in the study of the effect of heterogeneity on the surface of habitats of the Palacky University (Integral Grant Agency, project no. PrF_2012_007).”
Magnetic resonance imaging (MRI) is a multimodal technique that can noninvasively reflect the structure and function of the human brain. Structural MRI (sMRI), including longitudinal (spin-lattice) relaxation time T1-weighted and transverse (spin-spin) relaxation time T2-weighted imaging, has been applied to investigate the structural features of the brain. Based on the different relaxation times of different tissue, T1-weighted and T2-weighted images can be used to reflect the volume of grey matter, white matter, as well as lesions caused by infarction or hemorrhage. Diffusion MRI (dMRI), such as diffusion-weighted imaging (DWI) and diffusion tensor imaging (DTI), can be used to measure water diffusion along different directions and tract neural fiber counts and orientation. Functional MRI (fMRI) reflects neural activity during a period of time by measuring the relative amount of deoxygenated hemoglobin and oxygenated hemoglobin in the blood flow, which is also called the blood-oxygen-level-dependent (BOLD) signal. The fMRI is becoming popular in clinical situations to investigate the functional alterations following disease or treatment.
The fMRI experiment can be categorized into task fMRI and resting-state fMRI (rs-fMRI). For task fMRI, subjects need to perform a specific task, such as finger tapping or receive external stimulation like heat or sound during the scanning session. Resting-state fMRI, on the other hand, is collected when the subject lies still in the scanner, without doing any movement or thinking anything particular, and keeping awake at all time. Researchers focus on the spontaneous neural activity reflected by the BOLD signal under resting conditions. The correlation of signals related to spatially distinct regions is commonly defined as functional connectivity (FC) [1].
In the recent two decades, several methods have been developed to analyze functional connectivity in the resting state, including seed-based analysis, independent component analysis (ICA) [2], and resting-state network (RSN) method [3, 4]. The network method characterizes brain spontaneous activity as a graph, where nodes are defined as brain regions and edges are represented as connectivity between regions. There are different ways to calculate the connectivity, including static and dynamic functional connectivity and directed connectivity. Furthermore, features proposed in network science can be adopted to characterize the brain network topology, such as graph theory attributes [5].
Resting-state fMRI has been applied to clinical research and applications [6, 7]. In clinical situations, a common research paradigm is performing group comparison and searching for inter-group significant different features. Researchers are interested in whether a group of patients is significantly different from a group of healthy controls, or whether the same group of patients shows significant recovery after treatment. The identified significant different features may be the potential biomarker to aid in diagnosis as well as treatment. More importantly, the location of the significant different feature is of great interest, since each brain region has its unique function. As a result, this requires comparing groups of brain networks and other extracted network features. In clinical research, there are two key techniques of brain network analysis, the method of network construction and significant difference analysis of groups of brain networks.
In the following sections, we first describe how to construct brain networks from resting-state fMRI data, including different node definitions and a range of connectivity measurements. Then, we present common group analysis methods of brain networks. The clinical application of brain network analysis is also reported. We also propose several future directions in brain network research and end the chapter with a conclusion.
Unlike structural and diffusion MRI, the fMRI scanning captures the BOLD signal in a period of time that typically lasts for several minutes. The collected data are a time series, and the “sampling period” is called repetition time (TR). That is, whole-brain data are collected every TR seconds. Before constructing brain networks, the data need to be preprocessed to clean out non-neural artifacts, including physiological signals like breath and heartbeat, head movements, and scanner noise. Then the nodes of the network are defined and connectivity between each pair of nodes is calculated. The whole data processing pipeline is shown in Figure 1.
Resting-state fMRI data process pipeline.
The preprocessing of fMRI data is necessary since there are non-neural noises in the signal. There are openly available toolboxes to carry out preprocessing, such as Statistical Parametric Mapping (SPM), FMRIB Software Library (FSL), and Data Processing Assistant for Resting-State fMRI (DPARSF)[8]. Common preprocessing procedures begin by removing the first 10 time points to let the subject be familiar with the scanning environment. Since the scanning of fMRI data within a repetition period (2s) is done in a slice-by-slice manner, the exact collection time of the first slice and the last slice has a time difference. To correct this difference, a procedure called slice timing correction needs to be performed. Then the head motion is corrected so that each voxel corresponds to the same brain location in the scanning series.
For group analysis, the data of different subjects need to be co-registered or normalized to the Montreal Neurological Institute (MNI) standard space. The data then undergoes smoothing using a Gaussian filter with a specified full-width-half-maximum (FWHM) value. After that, the linear trend in the signal is removed and nuisance covariates, such as white matter, cerebral spinal fluid (CSF), and global signal, are regressed out. At last, the data are filtered to keep signals within 0.01-0.08 Hz, since signals within this frequency range are reported to reflect spontaneous neural activities.
Although numerous preprocessing steps have been developed, there is still no consensus on the standard fMRI data preprocessing pipeline. The controversy is centered on the nuisance covariates regression, especially global signal regression (GSR)[9] and white matter signal regression [10]. Other researchers tried to optimize the preprocessing across multiple outcome measures [11], for low-frequency fluctuation analysis [12] and specific patients, such as stroke patients [13]. We have also investigated how the choices of preprocessing parameters and steps influence statistical analysis results [14]. The preprocessing of fMRI data remains to be a complex but important research topic.
The most basic node definition is the voxel in a 3D fMRI image. Each voxel within the brain can be treated as a node and the constructed voxel-based network covers the whole brain. However, since the spatial resolution of fMRI is relatively high (2mm–4mm), the number of voxels is rather large (around the magnitude of 100,000) and the constructed network requires huge computation power for further analysis. Researchers have proposed specialized methods, such as the Parallel Graph-theoretical Analysis (PAGANI) toolkit to accelerate the processing of voxel-based whole-brain networks [15].
On the other hand, the nodes of the brain network can be defined as regions in the brain. The preprocessed data of voxels within a region are averaged spatially as the signal related to this node. The region can be specified manually by drawing regions of interest (ROI). Independent component analysis (ICA) can also reveal the component region but requires specifying parameters, such as the number of components. Both methods require human intervention and depend heavily on expert knowledge.
We proposed a fuzzy node definition method in Ref. [16] for tumor-brain, named “Spatial-Neighborhood and Functional-Correlation (SNFC)” based on fuzzy connectedness. It is a self-adapting method where the network was divided into functional connection and spatial adjacency. In the SNFC method, fuzzy connectedness between two voxels acts as a measurement to decide if they belong to the same node. Each voxel in the brain could be mapped into two feature spaces—structure feature space
If
The nodes can also be defined using regions in the brain atlas to avoid the subjective error caused by human intervention and enable automatic processing for large cohorts of data. The most known brain atlas is the Brodmann atlas, created by the German anatomist Korbinian Brodmann based on cytoarchitecture [17]. Another popular brain parcellation is the Automated Anatomical Labeling (AAL) atlas [18]. The AAL atlas focuses on brain structure and the finer partition of certain cortices was proposed in AAL2 [19] and AAL3 [20]. Apart from structure, the brain atlas derived from diffusion and functional data is getting more attention. The Brainnetome Atlas was proposed based on DTI data with fine-grained parcellation [21]. Researchers also developed functional atlas, such as the Atlas of Intrinsic Connectivity of Homotopic Areas (AICHA) that considered the homolog of regions in both hemispheres [22]. The above-defined network is called a region-based whole-brain network. We can also construct networks within a region. In this scenario, the voxels are defined as nodes, and the network only consists of voxels within a region. The constructed network is called a voxel-based local network, representing the topology within certain regions. We proposed a multilevel brain network joint analysis method on voxel-based whole-brain networks, voxel-based local networks as well as region-based whole-brain networks (Figure 2) [23].
Construction of multilevel functional brain networks.
Node definition has a fundamental influence on the topology of the brain network. Different atlas parcels the cerebrum and cerebellum based on different information, and it plays a key role in linking physiological regions to abstract brain network nodes. However, similar to the preprocessing of fMRI data, there is no gold standard for the node definition. Several researches have been carried out to investigate the effect of node definition on network analysis [24], resting-state networks [25], and the topology of both functional networks [26] and structural networks [27]. It is still an open question and needs more thorough research.
Edges in brain networks are represented by the connectivity between nodes. One of the most common connectivity measures is functional connectivity (FC). In 1995, Biswal et al firstly reported the correlation of intrinsic low-frequency BOLD signal fluctuation under resting-state and since then, multiple efforts have been devoted to FC analysis [1, 3]. Functional connectivity is commonly defined as the Pearson correlation between the BOLD signal of spatially distant regions. In recent years, researchers realized that FC ignores the dynamics of neural activity and developed dynamic functional connectivity (DFC) or Chronnectome [28, 29, 30]. The research on DFC is becoming popular and has attracted lots of attention.
Technically speaking, FC or static functional connectivity (SFC) is calculated using the whole time series, whereas DFC utilizes a sliding time window and the correlation of signals within the window is calculated. The window then moves from the beginning of the BOLD signal to the end, with a pre-defined step size. As a result, the connectivity shows dynamic fluctuations as the window slides, and each scanning session is associated with a series of brain networks, or a dynamic brain network. In contrast, there is only one static network related to the scanning session. The network is usually represented by a graph adjacency matrix, which is a square symmetric matrix and the
There are two major parameters regarding DFC calculation—the window length and the sliding step size. With a longer window length, the dynamics of neural activity might be averaged out while a shorter window length can capture transient signal changes. The step size controls the temporal resolution of DFC. Normally it is specified as several TRs. We investigated the optimal window width by using the small-world property as criteria [31]. Node degree distribution has exponential truncated power-law in the small-world network, and the normal human brain network shows a strong small-world property. The reasonable window width range was verified on both SNFC-based and voxel-based whole-brain networks. Results show that the smallest window width is 200 seconds and 260 seconds for normal subjects and brain tumor patients, respectively. Leonardi et al also studied the theory between window length and filter cut-off frequency during preprocessing [32]. Apart from the two window parameters, the shape of the sliding window is another concern. The rectangular window is the simplest solution, but other choices such as tapered window exist. Mokhtari et al also proposed a modulated rectangular (mRect) window to reduce spectral modulations [33].
We also proposed a dynamic network analysis method for enlarging the training samples required by an unsupervised learning classification algorithm [34], such as a classical backpropagation neural network classifier containing a hidden layer. It reached the optimal accuracy of 100% for classifying glioma patients and normal subjects.
Despite controversies, DFC has been used to investigate diseases, such as schizophrenia [35], post-traumatic stress disorder (PTSD) [36], Parkinson’s Disease [37], and autism [38]. It has also been applied to lifespan studies [39] and cognitive research [40]. From either a methodological or application view, the research on DFC is still insufficient.
As the definition implies, both SFC and DFC contain no directional information. Effective connectivity (EC) can measure the directional influence of one region toward another area by calculating the causal relationships between time series. Commonly adopted EC estimation methods are structural equation modeling (SEM) [41], dynamic causal modeling (DCM) [42], and Granger causality analysis (GCA) [43, 44]. The computation cost becomes unacceptable for SEM and DCM as the number of nodes increases [43]. Several amendments have been proposed to reduce the computation requirement of DCM recently [45, 46], but the model complexity is still challenging for clinical applications. We proposed a method based on convergent cross-mapping (CCM) that can reflect the interactions between regions in a dynamic, nonlinear, and deterministic way, which is not covered by GCA [47]. The method overview, together with the extended network-based statistic, is shown in Figure 3.
CCM-based directed connectivity estimation and extended network-based statistic method.
CCM was originally developed to detect causality in complex ecosystems [48]. It acts as a complement to GCA as CCM assumes the system to be deterministic and dynamical, while GCA works for a stochastic system and requires separability. In GCA, if removing X decreases the predictability of Y, it can be deduced that X causes Y, and in a brain network scenario, there is a directed connection from X to Y. On the other hand, in deterministic dynamic systems where CCM was developed, we can measure how well Y can estimate X to determine the causal relationship from X to Y, which then determines the directed connectivity strength from X to Y. The procedure of estimating X using Y is called cross-mapping. CCM is also applicable under situations where separability is not guaranteed. GCA, on the other hand, may produce erroneous results [49]. As for the brain, it is a dynamic system whose functional organization is poorly understood [50]. Utilizing CCM to estimate directed connectivity between regions could facilitate the investigation of brain activity as well as enable novel clinical applications.
After brain network construction, for each scanning of each subject, the preprocessed fMRI data were converted to a brain network represented by a graph adjacency matrix. The next question is how to find the difference between groups of brain networks. Here we summarize two popular methods to further analyze brain networks.
The most basic method is analyzing functional connectivity directly. Specifically, suppose we are comparing two groups of networks. Each connectivity value is extracted from every network, forming two sets of values. Statistical hypothesis testing can be adopted to decide whether this connection shows a significant difference as well as which group is higher. After performing a comparison on every connection in the network, the group difference network consisting of significant different connections is obtained. All edges with a significant difference were stored in a network for further discussion. We can also select several regions based on prior knowledge, such as the sensorimotor area or visual area, to further filter the set of significant different connections.
Another method is calculating graph theory attributes. Graph theory characterizes the topology of the network by nodal and global attributes. Common node level graph theory attributes are betweenness centrality, clustering coefficient, local efficiency, modularity, and weighted degree, while the network level graph theory attributes include global efficiency and characteristic path length. Small-worldness is also a common index used in brain network analysis. For multilevel brain networks, we define intra-region features as the attributes calculated at voxel-based local networks, and the attributes calculated at region-based whole-brain networks are called inter-region features. We can calculate the global feature of the voxel-based local network (intra-region features), and the nodal feature of the region-based whole-brain network (inter-region features). As a result, for each graph attribute, we obtain a feature vector whose length equals the number of nodes in the network, representing the whole-brain network feature.
After obtaining feature vectors of graph theory attributes, we can perform a statistical comparison on each region similar to FC analysis. The feature at each region is extracted, forming two sets of values; and statistical testing is used to find significant regions or significant different features. Moreover, the clinical relevance of the features can be evaluated by assessing the correlation of features and clinical scores, which produces features with significant correlation. The intersection of significant different and significant correlated features is selected for further discussion and following analysis.
We also investigated methods to analyze dynamic graph theory attributes [51]. For dynamic brain networks, at each sliding window location, the obtained brain network is static, and graph theory attributes can be calculated. As the window slides, graph theory attributes at each window location are estimated, forming the dynamic graph theory attributes of the dynamic network. To combine static and dynamic attributes together with clinical scores, we proposed an analysis framework [51]. The strength and stability of dynamic graph attributes were calculated. We found significant different and correlated features for both static and dynamic networks, as well as their intersection. The resulting features were further analyzed using receiver-operating curves (ROC) to test their ability in classification.
A controversy regarding the above analysis method is the multiple comparison problem. For each single statistical comparison with a 0.05 significance level, there is a 0.05 chance of obtaining a false positive. However, when performing multiple statistical comparisons at the same time, the chance of getting at least one false positive would become higher as the number of comparisons increases. To tackle this problem, correction methods, such as Bonferroni correction and false discovery rate (FDR) correction, were proposed. The basic idea behind these correction methods is to decrease the single comparison significance level according to the number of comparisons. However, since the amount of comparison is related to the number of nodes in the network, and certain features show high within group variance, directly applying correction might result in no significant result. We argue that statistical comparison can be seen as a feature selection procedure. The significant or selected features are then fed into the next module, such as a classifier. During feature selection, we should keep as much useful information as possible. The uncorrected significant features are preliminary scanning results and taking the intersection of significant different and correlated features further select clinically relevant information. Searching for intersected significant features might be an alternative method to multiple comparison correction.
For brain networks, to overcome the multiple comparison issue, network-based statistics (NBS) was proposed, enabling direct comparison of groups of brain networks [52]. NBS assumes that the effect or the group difference forms a certain structure instead of distributed single connections. The edge-wise comparison is performed first and the links are thresholded according to the test statistics or p-values obtained from the edge-wise comparison, producing a binarized difference network. It then searches for structures or connected components in the binarized difference network. The size of the component, defined as the number of edges or nodes, is used to determine if the component is significant by a permutation test, where group labels of samples are randomly shuffled and the same procedure is performed to search for the maximum component size. The permutation is repeated 5000 times and the empirical distribution of the component size is obtained. An empirical p-value can be assigned to the original connected component by calculating the ratio of the number of permutations, where the maximal size is larger than the original size, to the total permutation number.
Compared with edge-wise comparison and direct edge-wise correction, NBS provides higher statistical power at the cost of coarser spatial resolution in detecting differences [52]. In other words, NBS can only declare the connected component as a whole to be significant. It draws no conclusion on the significance of each single connection within the component. However, the original NBS only works for symmetric adjacency matrices, which corresponds to functional connectivity.
Based on directed connectivity, we proposed the extended-NBS (e-NBS) to search for altered connected components in groups of directed networks [47]. The method overview is shown in Figure 3. We search for strongly connected components (SCC) and weakly connected components (WCC) with and without direction information. A classical depth-first search algorithm was adopted when searching for SCCs and WCCs. The edge-wise p-value was utilized to filter for candidate connections and construct a difference network. Since there is no consensus on how to choose the pre-defined p-value threshold, we changed it within a certain range to test method performance. Specifically, an edge is kept if the p-value is less than the pre-define p-value threshold. For edge-wise comparison, we also tried to use two-sample t-test and the non-parametric Mann-Whitney test. The e-NBS method, together with the CCM-based directed connection estimation method, was verified using a dataset of spinal cord injury patients and healthy controls.
Moreover, we note that given the framework of e-NBS, one can define connected components that suit research needs. For example, in a study of motor function alteration following spinal cord injury, researchers are interested in connections related to sensorimotor areas and visual regions. The connected component can be defined as significant different connections related to these regions of interest. Furthermore, we can define two-step connected components that comprise connections directly related to the ROIs in the binarized difference network, and connections related to regions (first level nodes) that connect with ROIs (Figure 4). Either way, the permutation test in e-NBS makes it possible to draw conclusion on the significance of the defined component.
Two-step connected component. The first level node is directly connected to the ROI in the binarized difference network, while the second level node is connected with the first-level node.
The resting-state fMRI has been applied to clinical research and applications, mainly investigating pathophysiological mechanisms and searching for sensitive biomarkers for early diagnosis [6, 7]. The prognosis predictability of rs-fMRI is intriguing as well [53, 54, 55]. In glioma research, resting-state fMRI has also shown potential in diagnosis and treatment planning. Here we introduce three examples of applications and related works.
It has been shown that changes in both brain function and structure occur following central nervous lesions, such as spinal cord injury [56] and cerebral stroke [57]. According to the theory of neuroplasticity, the brain function continues to change during rehabilitation, and it is the theoretical and physiological basis for individualized neurorehabilitation as well as assistive rehabilitation technologies, such as transcranial direct current stimulation (tDCS) [58, 59, 60] and brain-computer interfaces (BCI) [61, 62]. We performed a study on spinal cord injury patients and investigated the alteration of grey matter volume extracted from structural MRI and functional connectivity related to the sensorimotor area, combining clinical assessments [63]. We found that that the alteration of anatomical structure features and the brain network connectivity in the sensorimotor area were non-concomitant following spinal cord injury, and the functional connectivity within the sensorimotor area had a significant correlation with clinical sensory scores, indicating the potential of FC as a prediction biomarker.
Another issue related to neurorehabilitation is the automated objective evaluation of rehabilitation progress. Traditionally, patient recovery is assessed by clinical measurements, which can only reflect behavioral improvements and might include subjective bias. We proposed a distance-based rehabilitation evaluation method that takes resting-state fMRI data of patients and healthy controls as input (Figure 5) [64]. We hypothesize that the sample point distribution of patients and healthy controls in the feature space is dichotomous. A support vector machine (SVM) classifier was first trained using significantly different functional connectivity of healthy controls and the first scanning session of patients. The distance of the patient sample points to the separating hyperplane was calculated and used to evaluate patient recovery. If the patient recovered, the sample point of the patient would move toward healthy controls and the distance would decrease. The method was verified using both group level and individual longitudinal data, and the distance evaluation was consistent with clinical measurements.
Method overview of the distance-based rehabilitation evaluation framework.
On the other hand, a stroke could lead to certain movement disabilities. Motor-related brain function alteration after stroke and during recovery is of great interest. Brain-Computer Interface (BCI) systems are helpful in motor recovery, possibly by stimulating neuroplasticity following brain activity [65]. The brain network reorganization of stroke patients after BCI training is of great significance. We conducted an experiment to investigate the functional changes after BCI training and their relations to clinical scores [66]. Functional connectivity was calculated using data collected before and after training and we searched for significant increased FC in groups with and without BCI training. The correlation between FC and clinical scores was also calculated. We found increased FC between certain cerebral and subcortical regions and the inter-hemisphere FC was positively correlated with motor scores.
Multiple system atrophy (MSA) is a neurodegenerative disease typically characterized by parkinsonism, cerebellar ataxia syndrome, and autonomic nervous dysfunction [67]. It is further divided into two subtypes, MSA with predominant parkinsonism (MSA-P) and MSA with predominant cerebellar ataxia (MSA-C) [67]. Previous studies mainly investigated the structural abnormalities related to MSA patients and compared subtypes of MSA with Parkinson’s Disease (PD) as well as healthy controls [68, 69, 70, 71]. The functional alteration induced by MSA is also studied by calculating regional homogeneity (ReHo) [72], the amplitude of low-frequency fluctuations (ALFF) [73], as well as functional and effective connectivity [74, 75].
The dynamic functional features of MSA-C patients not thoroughly investigated before. We conducted an experiment on MSA-C patients and proposed a method to combine static and dynamic functional connectivity features, as well as clinical scores (Figure 6) [51]. The static and dynamic brain networks were constructed using methods described in section 2.3 and static and dynamic graph theory attributes were calculated. Statistical comparisons and correlation analysis were carried out and significant different and correlated features were found. The significant regions mainly covered the cerebellum and certain cerebral areas, which is consistent with prior knowledge. The dynamic features showed the highest area under the curve (AUC) value during receiver-operating characteristic (ROC) analysis, indicating the potential of dynamic features in disease diagnosis.
The coalition analysis of rs-fMRI data combining static, dynamic functional connectivity as well as clinical information.
Apart from structural and functional analysis, multimodal research on MSA is getting more attention. We also tried to combine structural, diffusion, tractography, and functional features extracted from T1, DTI, and fMRI to search for sensitive biomarkers for MSA-C patient diagnosis (Figure 7) [76]. The T1 data were processed to produce grey matter and white matter probability maps. We performed tractography on DTI data and counted the number of tracts crossing each brain region. The fraction anisotropy (FA) and mean diffusivity (MD) maps were also obtained. For rs-fMRI, we calculated functional connectivity and constructed brain networks. The extended network-based statistics for the undirected network were adopted to search for significant different connected components between the two groups. By using the AAL atlas, feature maps extracted from different modalities were converted to feature vectors and networks. After that, significant analysis was performed with false discovery rate correction and we identified significant different features, mainly distributed in cerebellar and certain cerebral regions. The correlation of these features with clinical scores was also tested. We also searched for sensitive biomarkers in disease diagnosis by applying a nested leave-one-out cross-validation framework and evaluated classification performance using the significant features of each region with a support vector machine (SVM) classifier, as shown in Figure 7. The identified biomarkers were mainly cerebellar regions. Different modalities contain complementary information. Merging multimodal data and clinical variables together can further reveal the neurological alteration related to the disease as well as increase the accuracy, robustness, and generalization of the disease diagnosis algorithm.
The multimodal MRI feature fusion framework and the nested leave-one-out cross-validation procedure. GMV: grey matter volume; WMV: white matter volume; FA: fractional anisotropy; MD: mean diffusivity; NBS: network-based statistics; LOOCV: leave-one-out cross-validation.
Glioma stems from the canceration of neurogliocyte and is the most common tumor in the human brain [77]. It has an intensive impact on the structure of the brain and further on the corresponding physiological functions. Different locations of the glioma will result in different functional alterations and prognosis outcomes. For a high-level glioma, it is highly likely to relapse even after being excised in a surgery [78]. As a result, it is necessary to analyze the brain function changes according to the location and volume of glioma for both diagnosis and treatment. We proposed a framework of multilevel functional network analysis to find the functional network characteristics of glioma patients [79]. The multilevel network consists of a hemisphere functional network, glioma voxel local network, and glioma region local network, as illustrated in Figure 8. The hemisphere functional network was constructed based on regions from a single hemisphere in the AAL atlas excluding cerebellar parcellation (Figure 9). The glioma voxel local network is constructed at the voxel level in the region of glioma that is extracted by a tumor segmentation method. And glioma region local network is also constructed at the voxel level, but within each atlas region containing the glioma. A ratio, defined as the number of voxels in an AAL area that belongs to the segmented glioma region over the total voxel number of the area, is used as the threshold for selecting areas containing the glioma in the AAL atlas.
A framework of multilevel functional network analysis for finding the functional network characteristics of glioma patients.
The process of the construction of the hemisphere functional networks is based on the AAL atlas of a glioma patient. The green dots stand for the nodes of the functional network. The yellow line segments represent the weighted edges whose thickness reflects the weight. The colored area shows the tumor region and different colors reflect the possibility of whether a voxel belongs to the tumor.
Network features, including connectivity strength, characteristic path length, average nodal betweenness centrality, and average nodal clustering coefficient, were calculated for all networks. The network connectivity strength was defined as the average z-scores of all edges. Network characteristic path length equals the average of shortest paths between each pair of nodes in the network. Nodal attributes, including betweenness centrality and clustering coefficients, are calculated at each node within the network and averaged as network features. For hemisphere functional networks, both static and dynamic functional connectivity were investigated. Since the period of the BOLD signal induced by the hemodynamic response of neuronal activity is about 20s [80], during the reconstruction of dynamic networks, a sliding window with a length of 50s and a step size of 10s was selected. Each glioma patient received functional scanning lasting for 460s. As a result, the sliding time window extracted 46 sub-signals with a length of 50s and constructed dynamic brain networks with 46-time slices.
In this study, 38 patients with tumors in one side of the brain were enrolled. We constructed 38 positive and 38 negative hemisphere functional networks. Among these patients, 15 subjects had glioma area segmentation. Moreover, 15 healthy subjects were collected as the control group. The local network analysis was performed on 15 patients with segmentation and 15 healthy controls. We used the two-sample t-test to evaluate the significant difference of each feature between hemisphere functional networks constructed on the healthy side and the glioma side. The glioma voxel local networks and glioma region local networks were constructed at the same location of glioma segmentation in data collected from healthy controls as well. Statistical comparison was performed to compare network features of glioma voxel local networks and glioma region local networks from patients and healthy controls. There were 41 glioma region local networks constructed from 15 patients, and for comparison, 41 local networks were estimated from healthy controls.
We also investigated the classification performance using hemisphere functional networks. Given that the sample size is small (38 networks with glioma and 38 networks with healthy tissue), linear support vector machine (SVM) was chosen as the classifier. Static and dynamic network features were extracted and aligned into a feature vector of dimensions 4 and 184 (
Results revealed by the multilevel functional network analysis method showed that the existence of glioma changed certain features of the normal functional networks. Our work finds that glioma weakened the connection strength of the global and local functional networks. Moreover, it decreased the clustering degree of the nodes in both local functional networks, indicating that glioma may destruct the non-randomness and the small-world property of brain networks.
Previous studies have already investigated how glioma alters functional connectivity [80, 81, 82, 83]. We find that glioma attenuates the connectivity of functional networks, which is in accordance with previous studies. Moreover, we also involved network features other than connectivity. Our study emphasized the characteristic features, such as betweenness centrality, clustering coefficient, and characteristic path length, which were not covered by previous research.
Despite progress in recent years, there are lots of work to be done in developing new methods for constructing and analyzing brain networks, as well as performing group and individualized analysis. In this section, we propose some possible directions in the field of brain network research.
Network science has been used to analyze brain networks and advanced methods need to be developed to characterize the topological features of brain networks. The algebraic topological data analysis (TDA) method provides a new way to analyze the interactions between a set of nodes instead of bilateral connections. TDA could act as a complement to graph theoretical analysis in describing the topology characteristic of brain networks. More advanced network theory concepts, such as algebraic topology, have also been introduced to the analysis of brain networks [5]. Moreover, artificial neural networks and deep learning methods have been shown to be powerful in analyzing graph data. On the one hand, before network construction, models, such as Recurrent Neural Network (RNN) and Transformer, that were originally proposed to process sequential data, such as natural language and voice, can be applied to analyze the BOLD time series, both with and without preprocessing. Since the network perspective mainly models the inter-relationships between signals of spatially distinct regions, applying deep learning models directly to the time series could possibly extract information complementary to statistical dependency, as described by functional connectivity. On the other hand, after constructing brain networks using functional connectivity, directed connectivity, or DTI fiber tracking, Graph Neural Network (GNN) or Graph Convolutional Network (GCN) could be utilized to merge these multimodal networks and combine both edge-wise features (connections) and nodal features, such as graph theory attributes. GNN was proposed to directly analyze graphs that can model relationships between nodes and perform inference on node, edge, or graph level. Applying GNN to brain networks, especially multilevel static and dynamic brain networks, could possibly extract useful features and enable multimodal information fusion.
On the application side, multiple group comparison methods have been developed. However, for clinical application, individualized diagnosis and treatment are crucial. How to transform conclusions derived from group research into individual situations is a challenging question. We define “healthy templates” as a set of methods to delineate characteristics of a healthy population. The healthy templates describe the distribution of features of healthy people and need to be built for each feature extracted from different modalities. In its most basic form, the healthy template can be a value range given a specific feature. Subjects whose feature value falls within this value range would be considered to be normal, similar to the interpretation of a blood test result. Open-source datasets are valuable resources in the construction of healthy templates. However, the site effect of MRI data is a crucial issue and multi-site data harmonization techniques need to be adopted when combining data from different scanning locations. Several methods have been proposed for harmonization but their utility remains to be tested [84, 85]. With low variance healthy templates, individualized precise treatment planning and prognosis prediction would become possible.
The human brain is modeled as a functionally inter-connected network. Resting-state functional magnetic resonance imaging enables observing brain spontaneous activity
This work was supported by a grant from the Tsinghua University Initiative Scientific Research Program (No. 20131089382) and the National Natural Science Foundation of China (No. 61171002, 60372023). We would like to thank Zexuan Hao and Ziliang Zhang from the Department of Electronic Engineering, Beijing National Research Center for Information Science and Technology (BNRist), Tsinghua University for useful advice during the experiment and manuscript development.
The authors declare no conflict of interest.
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His studies in robotics lead him not only to a PhD degree but also inspired him to co-found and build the International Journal of Advanced Robotic Systems - world's first Open Access journal in the field of robotics.",institutionString:null,institution:{name:"TU Wien",country:{name:"Austria"}}},{id:"441",title:"Ph.D.",name:"Jaekyu",middleName:null,surname:"Park",slug:"jaekyu-park",fullName:"Jaekyu Park",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/441/images/1881_n.jpg",biography:null,institutionString:null,institution:{name:"LG Corporation (South Korea)",country:{name:"Korea, South"}}},{id:"465",title:"Dr.",name:"Christian",middleName:null,surname:"Martens",slug:"christian-martens",fullName:"Christian Martens",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"Rheinmetall (Germany)",country:{name:"Germany"}}},{id:"479",title:"Dr.",name:"Valentina",middleName:null,surname:"Colla",slug:"valentina-colla",fullName:"Valentina Colla",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/479/images/358_n.jpg",biography:null,institutionString:null,institution:{name:"Sant'Anna School of Advanced Studies",country:{name:"Italy"}}},{id:"494",title:"PhD",name:"Loris",middleName:null,surname:"Nanni",slug:"loris-nanni",fullName:"Loris Nanni",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/494/images/system/494.jpg",biography:"Loris Nanni received his Master Degree cum laude on June-2002 from the University of Bologna, and the April 26th 2006 he received his Ph.D. in Computer Engineering at DEIS, University of Bologna. On September, 29th 2006 he has won a post PhD fellowship from the university of Bologna (from October 2006 to October 2008), at the competitive examination he was ranked first in the industrial engineering area. He extensively served as referee for several international journals. He is author/coauthor of more than 100 research papers. He has been involved in some projects supported by MURST and European Community. His research interests include pattern recognition, bioinformatics, and biometric systems (fingerprint classification and recognition, signature verification, face recognition).",institutionString:null,institution:null},{id:"496",title:"Dr.",name:"Carlos",middleName:null,surname:"Leon",slug:"carlos-leon",fullName:"Carlos Leon",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"University of Seville",country:{name:"Spain"}}},{id:"512",title:"Dr.",name:"Dayang",middleName:null,surname:"Jawawi",slug:"dayang-jawawi",fullName:"Dayang Jawawi",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"University of Technology Malaysia",country:{name:"Malaysia"}}},{id:"528",title:"Dr.",name:"Kresimir",middleName:null,surname:"Delac",slug:"kresimir-delac",fullName:"Kresimir Delac",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/528/images/system/528.jpg",biography:"K. Delac received his B.Sc.E.E. degree in 2003 and is currentlypursuing a Ph.D. degree at the University of Zagreb, Faculty of Electrical Engineering andComputing. His current research interests are digital image analysis, pattern recognition andbiometrics.",institutionString:null,institution:{name:"University of Zagreb",country:{name:"Croatia"}}},{id:"557",title:"Dr.",name:"Andon",middleName:"Venelinov",surname:"Topalov",slug:"andon-topalov",fullName:"Andon Topalov",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/557/images/1927_n.jpg",biography:"Dr. Andon V. Topalov received the MSc degree in Control Engineering from the Faculty of Information Systems, Technologies, and Automation at Moscow State University of Civil Engineering (MGGU) in 1979. He then received his PhD degree in Control Engineering from the Department of Automation and Remote Control at Moscow State Mining University (MGSU), Moscow, in 1984. From 1985 to 1986, he was a Research Fellow in the Research Institute for Electronic Equipment, ZZU AD, Plovdiv, Bulgaria. In 1986, he joined the Department of Control Systems, Technical University of Sofia at the Plovdiv campus, where he is presently a Full Professor. He has held long-term visiting Professor/Scholar positions at various institutions in South Korea, Turkey, Mexico, Greece, Belgium, UK, and Germany. And he has coauthored one book and authored or coauthored more than 80 research papers in conference proceedings and journals. His current research interests are in the fields of intelligent control and robotics.",institutionString:null,institution:{name:"Technical University of Sofia",country:{name:"Bulgaria"}}},{id:"585",title:"Prof.",name:"Munir",middleName:null,surname:"Merdan",slug:"munir-merdan",fullName:"Munir Merdan",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/585/images/system/585.jpg",biography:"Munir Merdan received the M.Sc. degree in mechanical engineering from the Technical University of Sarajevo, Bosnia and Herzegovina, in 2001, and the Ph.D. degree in electrical engineering from the Vienna University of Technology, Vienna, Austria, in 2009.Since 2005, he has been at the Automation and Control Institute, Vienna University of Technology, where he is currently a Senior Researcher. 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Aalborg University has Two Satellite Campuses, one in Copenhagen (Aalborg University Copenhagen) and the other in Esbjerg (Aalborg University Esbjerg).\n· He is a member of prestigious IEEE (Institute of Electrical and Electronics Engineers), and IAENG (International Association of Engineers) organizations. \n· He is the chief Editor of the Journal of Software Engineering.\n· He is the member of the Editorial Board of International Journal of Computer Science and Software Technology (IJCSST) and International Journal of Computer Engineering and Information Technology. \n· He is also the Editor of Communication in Computer and Information Science CCIS-20 by Springer.\n· Reviewer For Many Conferences\nHe is the lead person in making collaboration agreements between Aalborg University and many universities of Pakistan, for which the MOU’s (Memorandum of Understanding) have been signed.\nProfessor Akbar is working in Academia since 1990, he started his career as a Lab demonstrator/TA at the University of Sussex. 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It is an oldest, most efficient, and easiest method to apply any surface without modifying the intrinsic properties of materials. Moreover, the initial phase of fire always occurs on the surface by ignition, and hence, it is important to concentrate on the surface protection of a material. Being an organic nature of conventional surface coating will burn easily and generate smoke and toxic fumes, which may not be suitable for application where fire protection or fire prevention is required. Reaction-to-fire and/or resistance-to-fire are to be considered for assessing both flammable and non-flammable material by using fire retardant and fire resistant or fire protective coatings. The degree of fire retardation mainly depends on the coating thickness, substrates, and efficiency of formulations. This chapter explains briefly the fire retardation of wood by using fire retardant coatings.",book:{id:"5827",slug:"new-technologies-in-protective-coatings",title:"New Technologies in Protective Coatings",fullTitle:"New Technologies in Protective Coatings"},signatures:"Thirumal Mariappan",authors:[{id:"198114",title:"Dr.",name:"Thirumal",middleName:null,surname:"Mariappan",slug:"thirumal-mariappan",fullName:"Thirumal Mariappan"}]},{id:"75967",title:"Recent Advances in Ceramic Materials for Dentistry",slug:"recent-advances-in-ceramic-materials-for-dentistry",totalDownloads:815,totalCrossrefCites:0,totalDimensionsCites:0,abstract:"Dental ceramics constitute a heterogeneous group of materials with desirable optical and mechanical proprieties combined with chemical stability. They are inorganic non-metallic materials used in several applications. These materials are biocompatible to tissue, highly esthetic, with satisfying resistance to tensile and shear stress. Over the past years, several developments in new ceramic materials in dental restoration were achieved, including processing techniques and high mechanical properties. Thus, concepts on the structure and strengthening mechanisms of dental ceramic materials are also discussed. The dental practitioner requires best knowledge concerning indications, limitations, and correct use of started materials. The purpose of this book chapter is to overview advances in new ceramic materials and processes, which are used in dentistry. The properties of these materials are also discussed.",book:{id:"9894",slug:"advanced-ceramic-materials",title:"Advanced Ceramic Materials",fullTitle:"Advanced Ceramic Materials"},signatures:"Mohsen Mhadhbi, Faïçal Khlissa and Chaker Bouzidi",authors:[{id:"228366",title:"Dr.",name:"Mohsen",middleName:null,surname:"Mhadhbi",slug:"mohsen-mhadhbi",fullName:"Mohsen Mhadhbi"},{id:"324375",title:"Dr.",name:"Faïçal",middleName:null,surname:"Khlissa",slug:"faical-khlissa",fullName:"Faïçal Khlissa"},{id:"324535",title:"Dr.",name:"Chaker",middleName:null,surname:"Bouzidi",slug:"chaker-bouzidi",fullName:"Chaker Bouzidi"}]},{id:"66615",title:"Survey of Bauxite Resources, Alumina Industry and the Prospects of the Production of Geopolymer Composites from the Resulting by-product",slug:"survey-of-bauxite-resources-alumina-industry-and-the-prospects-of-the-production-of-geopolymer-compo",totalDownloads:1233,totalCrossrefCites:2,totalDimensionsCites:2,abstract:"Guinea is endowed with huge mineral resources. Several geological surveys have identified bauxite, iron, gold, diamond, and several metal ores. Because of the diversity and the magnitude of its resources, the country is referred to as a geological scandal. Nowadays the aluminum industry is still at the quarrying stage of bauxite, the main raw material that is converted into alumina and further to aluminum. Approximately 35–40% of the processed bauxite ore goes into the waste as alkaline red mud RM slurry which consists of 15–40% solids. RM and other industrial wastes material such as fly ash FA, rice husk ash RHA, that poses environmental hazards can be mixed to make them apt for usage in engineering applications. Geopolymers GP represent a new class of materials consisting of Al2O3▬SiO2-based material suitable for several engineering application. The present chapter presents the bauxitic potential of Guinea, the subsequent developing alumina industry. It reviews the application of RM for the production of geopolymer materials in the perspective of the valorization of the huge bauxite potential of Guinea.",book:{id:"8612",slug:"geopolymers-and-other-geosynthetics",title:"Geopolymers and Other Geosynthetics",fullTitle:"Geopolymers and Other Geosynthetics"},signatures:"Sékou Traoré, A. Diarra, O. Kourouma and D.L. Traoré",authors:[{id:"266484",title:"Prof.",name:"Sekou",middleName:null,surname:"Traore",slug:"sekou-traore",fullName:"Sekou Traore"},{id:"272379",title:"Dr.",name:"Doussou L.",middleName:null,surname:"Traoré",slug:"doussou-l.-traore",fullName:"Doussou L. Traoré"}]},{id:"59550",title:"Introductory Chapter: A Brief Introduction to Porous Ceramic",slug:"introductory-chapter-a-brief-introduction-to-porous-ceramic",totalDownloads:1871,totalCrossrefCites:7,totalDimensionsCites:16,abstract:null,book:{id:"6084",slug:"recent-advances-in-porous-ceramics",title:"Recent Advances in Porous Ceramics",fullTitle:"Recent Advances in Porous Ceramics"},signatures:"Uday M. Basheer Al-Naib",authors:[{id:"182041",title:null,name:"Uday",middleName:"M.",surname:"Basheer",slug:"uday-basheer",fullName:"Uday Basheer"}]}],onlineFirstChaptersFilter:{topicId:"155",limit:6,offset:0},onlineFirstChaptersCollection:[],onlineFirstChaptersTotal:0},preDownload:{success:null,errors:{}},subscriptionForm:{success:null,errors:{}},aboutIntechopen:{},privacyPolicy:{},peerReviewing:{},howOpenAccessPublishingWithIntechopenWorks:{},sponsorshipBooks:{sponsorshipBooks:[],offset:8,limit:8,total:0},allSeries:{pteSeriesList:[{id:"14",title:"Artificial Intelligence",numberOfPublishedBooks:11,numberOfPublishedChapters:91,numberOfOpenTopics:6,numberOfUpcomingTopics:0,issn:"2633-1403",doi:"10.5772/intechopen.79920",isOpenForSubmission:!0},{id:"7",title:"Biomedical Engineering",numberOfPublishedBooks:12,numberOfPublishedChapters:108,numberOfOpenTopics:3,numberOfUpcomingTopics:0,issn:"2631-5343",doi:"10.5772/intechopen.71985",isOpenForSubmission:!0}],lsSeriesList:[{id:"11",title:"Biochemistry",numberOfPublishedBooks:33,numberOfPublishedChapters:333,numberOfOpenTopics:4,numberOfUpcomingTopics:0,issn:"2632-0983",doi:"10.5772/intechopen.72877",isOpenForSubmission:!0},{id:"25",title:"Environmental Sciences",numberOfPublishedBooks:1,numberOfPublishedChapters:19,numberOfOpenTopics:4,numberOfUpcomingTopics:0,issn:"2754-6713",doi:"10.5772/intechopen.100362",isOpenForSubmission:!0},{id:"10",title:"Physiology",numberOfPublishedBooks:14,numberOfPublishedChapters:145,numberOfOpenTopics:4,numberOfUpcomingTopics:0,issn:"2631-8261",doi:"10.5772/intechopen.72796",isOpenForSubmission:!0}],hsSeriesList:[{id:"3",title:"Dentistry",numberOfPublishedBooks:11,numberOfPublishedChapters:144,numberOfOpenTopics:2,numberOfUpcomingTopics:0,issn:"2631-6218",doi:"10.5772/intechopen.71199",isOpenForSubmission:!0},{id:"6",title:"Infectious Diseases",numberOfPublishedBooks:13,numberOfPublishedChapters:125,numberOfOpenTopics:4,numberOfUpcomingTopics:0,issn:"2631-6188",doi:"10.5772/intechopen.71852",isOpenForSubmission:!0},{id:"13",title:"Veterinary Medicine and Science",numberOfPublishedBooks:11,numberOfPublishedChapters:113,numberOfOpenTopics:3,numberOfUpcomingTopics:0,issn:"2632-0517",doi:"10.5772/intechopen.73681",isOpenForSubmission:!0}],sshSeriesList:[{id:"22",title:"Business, Management and Economics",numberOfPublishedBooks:1,numberOfPublishedChapters:23,numberOfOpenTopics:3,numberOfUpcomingTopics:0,issn:"2753-894X",doi:"10.5772/intechopen.100359",isOpenForSubmission:!0},{id:"23",title:"Education and Human Development",numberOfPublishedBooks:0,numberOfPublishedChapters:12,numberOfOpenTopics:1,numberOfUpcomingTopics:1,issn:null,doi:"10.5772/intechopen.100360",isOpenForSubmission:!0},{id:"24",title:"Sustainable Development",numberOfPublishedBooks:1,numberOfPublishedChapters:19,numberOfOpenTopics:5,numberOfUpcomingTopics:0,issn:"2753-6580",doi:"10.5772/intechopen.100361",isOpenForSubmission:!0}],testimonialsList:[{id:"13",text:"The collaboration with and support of the technical staff of IntechOpen is fantastic. 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Initial biochemical studies have been exclusively analytic: dissecting, purifying, and examining individual components of a biological system; in the apt words of Efraim Racker (1913 –1991), “Don’t waste clean thinking on dirty enzymes.” Today, however, biochemistry is becoming more agglomerative and comprehensive, setting out to integrate and describe entirely particular biological systems. The ‘big data’ metabolomics can define the complement of small molecules, e.g., in a soil or biofilm sample; proteomics can distinguish all the comprising proteins, e.g., serum; metagenomics can identify all the genes in a complex environment, e.g., the bovine rumen. 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Dr. Blumenberg’s research is focused on the epidermis, expression of keratin genes, transcription profiling, keratinocyte differentiation, inflammatory diseases and cancers, and most recently the effects of the microbiome on the skin. He has published more than 100 peer-reviewed research articles and graduated numerous Ph.D. and postdoctoral students.",institutionString:null,institution:{name:"New York University Langone Medical Center",institutionURL:null,country:{name:"United States of America"}}},editorTwo:null,editorThree:null},subseries:{paginationCount:6,paginationItems:[{id:"22",title:"Applied Intelligence",coverUrl:"https://cdn.intechopen.com/series_topics/covers/22.jpg",isOpenForSubmission:!0,editor:{id:"27170",title:"Prof.",name:"Carlos",middleName:"M.",surname:"Travieso-Gonzalez",slug:"carlos-travieso-gonzalez",fullName:"Carlos Travieso-Gonzalez",profilePictureURL:"https://mts.intechopen.com/storage/users/27170/images/system/27170.jpeg",biography:"Carlos M. Travieso-González received his MSc degree in Telecommunication Engineering at Polytechnic University of Catalonia (UPC), Spain in 1997, and his Ph.D. degree in 2002 at the University of Las Palmas de Gran Canaria (ULPGC-Spain). He is a full professor of signal processing and pattern recognition and is head of the Signals and Communications Department at ULPGC, teaching from 2001 on subjects on signal processing and learning theory. His research lines are biometrics, biomedical signals and images, data mining, classification system, signal and image processing, machine learning, and environmental intelligence. He has researched in 52 international and Spanish research projects, some of them as head researcher. He is co-author of 4 books, co-editor of 27 proceedings books, guest editor for 8 JCR-ISI international journals, and up to 24 book chapters. He has over 450 papers published in international journals and conferences (81 of them indexed on JCR – ISI - Web of Science). He has published seven patents in the Spanish Patent and Trademark Office. He has been a supervisor on 8 Ph.D. theses (11 more are under supervision), and 130 master theses. He is the founder of The IEEE IWOBI conference series and the president of its Steering Committee, as well as the founder of both the InnoEducaTIC and APPIS conference series. He is an evaluator of project proposals for the European Union (H2020), Medical Research Council (MRC, UK), Spanish Government (ANECA, Spain), Research National Agency (ANR, France), DAAD (Germany), Argentinian Government, and the Colombian Institutions. He has been a reviewer in different indexed international journals (<70) and conferences (<250) since 2001. He has been a member of the IASTED Technical Committee on Image Processing from 2007 and a member of the IASTED Technical Committee on Artificial Intelligence and Expert Systems from 2011. \n\nHe has held the general chair position for the following: ACM-APPIS (2020, 2021), IEEE-IWOBI (2019, 2020 and 2020), A PPIS (2018, 2019), IEEE-IWOBI (2014, 2015, 2017, 2018), InnoEducaTIC (2014, 2017), IEEE-INES (2013), NoLISP (2011), JRBP (2012), and IEEE-ICCST (2005)\n\nHe is an associate editor of the Computational Intelligence and Neuroscience Journal (Hindawi – Q2 JCR-ISI). He was vice dean from 2004 to 2010 in the Higher Technical School of Telecommunication Engineers at ULPGC and the vice dean of Graduate and Postgraduate Studies from March 2013 to November 2017. He won the “Catedra Telefonica” Awards in Modality of Knowledge Transfer, 2017, 2018, and 2019 editions, and awards in Modality of COVID Research in 2020.\n\nPublic References:\nResearcher ID http://www.researcherid.com/rid/N-5967-2014\nORCID https://orcid.org/0000-0002-4621-2768 \nScopus Author ID https://www.scopus.com/authid/detail.uri?authorId=6602376272\nScholar Google https://scholar.google.es/citations?user=G1ks9nIAAAAJ&hl=en \nResearchGate https://www.researchgate.net/profile/Carlos_Travieso",institutionString:null,institution:{name:"University of Las Palmas de Gran Canaria",institutionURL:null,country:{name:"Spain"}}},editorTwo:null,editorThree:null},{id:"23",title:"Computational Neuroscience",coverUrl:"https://cdn.intechopen.com/series_topics/covers/23.jpg",isOpenForSubmission:!0,editor:{id:"14004",title:"Dr.",name:"Magnus",middleName:null,surname:"Johnsson",slug:"magnus-johnsson",fullName:"Magnus Johnsson",profilePictureURL:"https://mts.intechopen.com/storage/users/14004/images/system/14004.png",biography:"Dr Magnus Johnsson is a cross-disciplinary scientist, lecturer, scientific editor and AI/machine learning consultant from Sweden. \n\nHe is currently at Malmö University in Sweden, but also held positions at Lund University in Sweden and at Moscow Engineering Physics Institute. \nHe holds editorial positions at several international scientific journals and has served as a scientific editor for books and special journal issues. \nHis research interests are wide and include, but are not limited to, autonomous systems, computer modeling, artificial neural networks, artificial intelligence, cognitive neuroscience, cognitive robotics, cognitive architectures, cognitive aids and the philosophy of mind. \n\nDr. Johnsson has experience from working in the industry and he has a keen interest in the application of neural networks and artificial intelligence to fields like industry, finance, and medicine. \n\nWeb page: www.magnusjohnsson.se",institutionString:null,institution:{name:"Malmö University",institutionURL:null,country:{name:"Sweden"}}},editorTwo:null,editorThree:null},{id:"24",title:"Computer Vision",coverUrl:"https://cdn.intechopen.com/series_topics/covers/24.jpg",isOpenForSubmission:!0,editor:{id:"294154",title:"Prof.",name:"George",middleName:null,surname:"Papakostas",slug:"george-papakostas",fullName:"George Papakostas",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002hYaGbQAK/Profile_Picture_1624519712088",biography:"George A. Papakostas has received a diploma in Electrical and Computer Engineering in 1999 and the M.Sc. and Ph.D. degrees in Electrical and Computer Engineering in 2002 and 2007, respectively, from the Democritus University of Thrace (DUTH), Greece. Dr. Papakostas serves as a Tenured Full Professor at the Department of Computer Science, International Hellenic University, Greece. Dr. Papakostas has 10 years of experience in large-scale systems design as a senior software engineer and technical manager, and 20 years of research experience in the field of Artificial Intelligence. Currently, he is the Head of the “Visual Computing” division of HUman-MAchines INteraction Laboratory (HUMAIN-Lab) and the Director of the MPhil program “Advanced Technologies in Informatics and Computers” hosted by the Department of Computer Science, International Hellenic University. He has (co)authored more than 150 publications in indexed journals, international conferences and book chapters, 1 book (in Greek), 3 edited books, and 5 journal special issues. His publications have more than 2100 citations with h-index 27 (GoogleScholar). His research interests include computer/machine vision, machine learning, pattern recognition, computational intelligence. \nDr. Papakostas served as a reviewer in numerous journals, as a program\ncommittee member in international conferences and he is a member of the IAENG, MIR Labs, EUCogIII, INSTICC and the Technical Chamber of Greece (TEE).",institutionString:null,institution:{name:"International Hellenic University",institutionURL:null,country:{name:"Greece"}}},editorTwo:null,editorThree:null},{id:"25",title:"Evolutionary Computation",coverUrl:"https://cdn.intechopen.com/series_topics/covers/25.jpg",isOpenForSubmission:!0,editor:{id:"136112",title:"Dr.",name:"Sebastian",middleName:null,surname:"Ventura Soto",slug:"sebastian-ventura-soto",fullName:"Sebastian Ventura Soto",profilePictureURL:"https://mts.intechopen.com/storage/users/136112/images/system/136112.png",biography:"Sebastian Ventura is a Spanish researcher, a full professor with the Department of Computer Science and Numerical Analysis, University of Córdoba. Dr Ventura also holds the positions of Affiliated Professor at Virginia Commonwealth University (Richmond, USA) and Distinguished Adjunct Professor at King Abdulaziz University (Jeddah, Saudi Arabia). Additionally, he is deputy director of the Andalusian Research Institute in Data Science and Computational Intelligence (DaSCI) and heads the Knowledge Discovery and Intelligent Systems Research Laboratory. He has published more than ten books and over 300 articles in journals and scientific conferences. Currently, his work has received over 18,000 citations according to Google Scholar, including more than 2200 citations in 2020. In the last five years, he has published more than 60 papers in international journals indexed in the JCR (around 70% of them belonging to first quartile journals) and he has edited some Springer books “Supervised Descriptive Pattern Mining” (2018), “Multiple Instance Learning - Foundations and Algorithms” (2016), and “Pattern Mining with Evolutionary Algorithms” (2016). He has also been involved in more than 20 research projects supported by the Spanish and Andalusian governments and the European Union. He currently belongs to the editorial board of PeerJ Computer Science, Information Fusion and Engineering Applications of Artificial Intelligence journals, being also associate editor of Applied Computational Intelligence and Soft Computing and IEEE Transactions on Cybernetics. Finally, he is editor-in-chief of Progress in Artificial Intelligence. He is a Senior Member of the IEEE Computer, the IEEE Computational Intelligence, and the IEEE Systems, Man, and Cybernetics Societies, and the Association of Computing Machinery (ACM). Finally, his main research interests include data science, computational intelligence, and their applications.",institutionString:null,institution:{name:"University of Córdoba",institutionURL:null,country:{name:"Spain"}}},editorTwo:null,editorThree:null},{id:"26",title:"Machine Learning and Data Mining",coverUrl:"https://cdn.intechopen.com/series_topics/covers/26.jpg",isOpenForSubmission:!0,editor:{id:"24555",title:"Dr.",name:"Marco Antonio",middleName:null,surname:"Aceves Fernandez",slug:"marco-antonio-aceves-fernandez",fullName:"Marco Antonio Aceves Fernandez",profilePictureURL:"https://mts.intechopen.com/storage/users/24555/images/system/24555.jpg",biography:"Dr. Marco Antonio Aceves Fernandez obtained his B.Sc. (Eng.) in Telematics from the Universidad de Colima, Mexico. He obtained both his M.Sc. and Ph.D. from the University of Liverpool, England, in the field of Intelligent Systems. He is a full professor at the Universidad Autonoma de Queretaro, Mexico, and a member of the National System of Researchers (SNI) since 2009. Dr. Aceves Fernandez has published more than 80 research papers as well as a number of book chapters and congress papers. He has contributed in more than 20 funded research projects, both academic and industrial, in the area of artificial intelligence, ranging from environmental, biomedical, automotive, aviation, consumer, and robotics to other applications. He is also a honorary president at the National Association of Embedded Systems (AMESE), a senior member of the IEEE, and a board member of many institutions. 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He has an excellent track record in the herpesvirus field, and his group is engaged in clinical research in the field of Epstein-Barr virus diseases. He is the editor of the online Encyclopedia of Environment and he coordinates the Universal Health Coverage education program for the BioHealth Computing Schools of the European Institute of Science.",institutionString:null,institution:{name:"Grenoble Alpes University",country:{name:"France"}}},{id:"131400",title:"Prof.",name:"Alfonso J.",middleName:null,surname:"Rodriguez-Morales",slug:"alfonso-j.-rodriguez-morales",fullName:"Alfonso J. Rodriguez-Morales",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/131400/images/system/131400.png",biography:"Dr. Rodriguez-Morales is an expert in tropical and emerging diseases, particularly zoonotic and vector-borne diseases (especially arboviral diseases). 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In 2021 he has been awarded the “Raul Isturiz Award” Medal of the API. Also, in 2021, he was awarded with the “Jose Felix Patiño” Asclepius Staff Medal of the Colombian Medical College, due to his scientific contributions to COVID-19 during the pandemic. He is currently the Editor in Chief of the journal Travel Medicine and Infectious Diseases. His Scopus H index is 47 (Google Scholar H index, 68).",institutionString:"Institución Universitaria Visión de las Américas, Colombia",institution:null},{id:"332819",title:"Dr.",name:"Chukwudi Michael",middleName:"Michael",surname:"Egbuche",slug:"chukwudi-michael-egbuche",fullName:"Chukwudi Michael Egbuche",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/332819/images/14624_n.jpg",biography:"I an Dr. Chukwudi Michael Egbuche. 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The preliminary objectives of the study are to understand and develop the evidence-based tools and interventions for the control and prevention of malaria in different sites of the INDIA. Alongside, with the help of next-generation genomics study, the team has studied the antimalarial drug resistance in India. Further, he has extended his research in the development of Humanized mice for the study of liver-stage malaria and identification of molecular marker(s) for the Artemisinin resistance. At present, his research focuses on understanding the role of B cells in the activation of CD8+ T cells in malaria. 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She is currently an Adjunct Professor at Feevale University in Medicine and Biomedicine courses and a permanent professor of the Academic Master\\'s Degree in Virology. She has experience in the field of Microbiology, with an emphasis on Bacteriology, working mainly on the following topics: bacteriophages, bacterial resistance, clinical microbiology and food microbiology.",institutionString:null,institution:{name:"Universidade Feevale",country:{name:"Brazil"}}},{id:"229220",title:"Dr.",name:"Amjad",middleName:"Islam",surname:"Aqib",slug:"amjad-aqib",fullName:"Amjad Aqib",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/229220/images/system/229220.png",biography:"Dr. Amjad Islam Aqib obtained a DVM and MSc (Hons) from University of Agriculture Faisalabad (UAF), Pakistan, and a PhD from the University of Veterinary and Animal Sciences Lahore, Pakistan. 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His research interests include epidemiological patterns and molecular analysis of antimicrobial resistance and modulation and vaccine development against animal pathogens of public health concern.",institutionString:"Cholistan University of Veterinary and Animal Sciences",institution:{name:"University of Agriculture Faisalabad",country:{name:"Pakistan"}}},{id:"333753",title:"Dr.",name:"Rais",middleName:null,surname:"Ahmed",slug:"rais-ahmed",fullName:"Rais Ahmed",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/333753/images/20168_n.jpg",biography:null,institutionString:null,institution:{name:"University of Agriculture Faisalabad",country:{name:"Pakistan"}}},{id:"62900",title:"Prof.",name:"Fethi",middleName:null,surname:"Derbel",slug:"fethi-derbel",fullName:"Fethi Derbel",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/62900/images/system/62900.jpeg",biography:"Professor Fethi Derbel was born in 1960 in Tunisia. He received his medical degree from the Sousse Faculty of Medicine at Sousse, University of Sousse, Tunisia. He completed his surgical residency in General Surgery at the University Hospital Farhat Hached of Sousse and was a member of the Unit of Liver Transplantation in the University of Rennes, France. He then worked in the Department of Surgery at the Sahloul University Hospital in Sousse. Professor Derbel is presently working at the Clinique les Oliviers, Sousse, Tunisia. His hospital activities are mostly concerned with laparoscopic, colorectal, pancreatic, hepatobiliary, and gastric surgery. He is also very interested in hernia surgery and performs ventral hernia repairs and inguinal hernia repairs. He has been a member of the GREPA and Tunisian Hernia Society (THS). During his residency, he managed patients suffering from diabetic foot, and he was very interested in this pathology. For this reason, he decided to coordinate a book project dealing with the diabetic foot. Professor Derbel has published many articles in journals and collaborates intensively with IntechOpen Access Publisher as an editor.",institutionString:"Clinique les Oliviers",institution:null},{id:"300144",title:"Dr.",name:"Meriem",middleName:null,surname:"Braiki",slug:"meriem-braiki",fullName:"Meriem Braiki",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/300144/images/system/300144.jpg",biography:"Dr. Meriem Braiki is a specialist in pediatric surgeon from Tunisia. She was born in 1985. She received her medical degree from the University of Medicine at Sousse, Tunisia. She achieved her surgical residency training periods in Pediatric Surgery departments at University Hospitals in Monastir, Tunis and France.\r\nShe is currently working at the Pediatric surgery department, Sidi Bouzid Hospital, Tunisia. Her hospital activities are mostly concerned with laparoscopic, parietal, urological and digestive surgery. She has published several articles in diffrent journals.",institutionString:"Sidi Bouzid Regional Hospital",institution:null},{id:"229481",title:"Dr.",name:"Erika M.",middleName:"Martins",surname:"de Carvalho",slug:"erika-m.-de-carvalho",fullName:"Erika M. de Carvalho",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/229481/images/6397_n.jpg",biography:null,institutionString:null,institution:{name:"Oswaldo Cruz Foundation",country:{name:"Brazil"}}},{id:"186537",title:"Prof.",name:"Tonay",middleName:null,surname:"Inceboz",slug:"tonay-inceboz",fullName:"Tonay Inceboz",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/186537/images/system/186537.jfif",biography:"I was graduated from Ege University of Medical Faculty (Turkey) in 1988 and completed his Med. PhD degree in Medical Parasitology at the same university. I became an Associate Professor in 2008 and Professor in 2014. I am currently working as a Professor at the Department of Medical Parasitology at Dokuz Eylul University, Izmir, Turkey.\n\nI have given many lectures, presentations in different academic meetings. I have more than 60 articles in peer-reviewed journals, 18 book chapters, 1 book editorship.\n\nMy research interests are Echinococcus granulosus, Echinococcus multilocularis (diagnosis, life cycle, in vitro and in vivo cultivation), and Trichomonas vaginalis (diagnosis, PCR, and in vitro cultivation).",institutionString:"Dokuz Eylül University",institution:{name:"Dokuz Eylül University",country:{name:"Turkey"}}},{id:"71812",title:"Prof.",name:"Hanem Fathy",middleName:"Fathy",surname:"Khater",slug:"hanem-fathy-khater",fullName:"Hanem Fathy Khater",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/71812/images/1167_n.jpg",biography:"Prof. Khater is a Professor of Parasitology at Benha University, Egypt. She studied for her doctoral degree, at the Department of Entomology, College of Agriculture, Food and Natural Resources, University of Missouri, Columbia, USA. She has completed her Ph.D. degrees in Parasitology in Egypt, from where she got the award for “the best scientific Ph.D. dissertation”. She worked at the School of Biological Sciences, Bristol, England, the UK in controlling insects of medical and veterinary importance as a grant from Newton Mosharafa, the British Council. Her research is focused on searching of pesticides against mosquitoes, house flies, lice, green bottle fly, camel nasal botfly, soft and hard ticks, mites, and the diamondback moth as well as control of several parasites using safe and natural materials to avoid drug resistances and environmental contamination.",institutionString:null,institution:{name:"Banha University",country:{name:"Egypt"}}},{id:"99780",title:"Prof.",name:"Omolade",middleName:"Olayinka",surname:"Okwa",slug:"omolade-okwa",fullName:"Omolade Okwa",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/99780/images/system/99780.jpg",biography:"Omolade Olayinka Okwa is presently a Professor of Parasitology at Lagos State University, Nigeria. She has a PhD in Parasitology (1997), an MSc in Cellular Parasitology (1992), and a BSc (Hons) Zoology (1990) all from the University of Ibadan, Nigeria. She teaches parasitology at the undergraduate and postgraduate levels. She was a recipient of a Commonwealth fellowship supported by British Council tenable at the Centre for Entomology and Parasitology (CAEP), Keele University, United Kingdom between 2004 and 2005. She was awarded an Honorary Visiting Research Fellow at the same university from 2005 to 2007. \nShe has been an external examiner to the Department of Veterinary Microbiology and Parasitology, University of Ibadan, MSc programme between 2010 and 2012. She is a member of the Nigerian Society of Experimental Biology (NISEB), Parasitology and Public Health Society of Nigeria (PPSN), Science Association of Nigeria (SAN), Zoological Society of Nigeria (ZSN), and is Vice Chairperson of the Organisation of Women in Science (OWSG), LASU chapter. She served as Head of Department of Zoology and Environmental Biology, Lagos State University from 2007 to 2010 and 2014 to 2016. She is a reviewer for several local and international journals such as Unilag Journal of Science, Libyan Journal of Medicine, Journal of Medicine and Medical Sciences, and Annual Research and Review in Science. \nShe has authored 45 scientific research publications in local and international journals, 8 scientific reviews, 4 books, and 3 book chapters, which includes the books “Malaria Parasites” and “Malaria” which are IntechOpen access publications.",institutionString:"Lagos State University",institution:{name:"Lagos State University",country:{name:"Nigeria"}}},{id:"273100",title:"Dr.",name:"Vijay",middleName:null,surname:"Gayam",slug:"vijay-gayam",fullName:"Vijay Gayam",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/273100/images/system/273100.jpeg",biography:"Dr. Vijay Bhaskar Reddy Gayam is currently practicing as an internist at Interfaith Medical Center in Brooklyn, New York, USA. He is also a Clinical Assistant Professor at the SUNY Downstate University Hospital and Adjunct Professor of Medicine at the American University of Antigua. He is a holder of an M.B.B.S. degree bestowed to him by Osmania Medical College and received his M.D. at Interfaith Medical Center. His career goals thus far have heavily focused on direct patient care, medical education, and clinical research. He currently serves in two leadership capacities; Assistant Program Director of Medicine at Interfaith Medical Center and as a Councilor for the American\r\nFederation for Medical Research. As a true academician and researcher, he has more than 50 papers indexed in international peer-reviewed journals. He has also presented numerous papers in multiple national and international scientific conferences. His areas of research interest include general internal medicine, gastroenterology and hepatology. He serves as an editor, editorial board member and reviewer for multiple international journals. His research on Hepatitis C has been very successful and has led to multiple research awards, including the 'Equity in Prevention and Treatment Award” from the New York Department of Health Viral Hepatitis Symposium (2018) and the 'Presidential Poster Award” awarded to him by the American College of Gastroenterology (2018). He was also awarded 'Outstanding Clinician in General Medicine” by Venus International Foundation for his extensive research expertise and services, perform over and above the standard expected in the advancement of healthcare, patient safety and quality of care.",institutionString:"Interfaith Medical Center",institution:{name:"Interfaith Medical Center",country:{name:"United States of America"}}},{id:"93517",title:"Dr.",name:"Clement",middleName:"Adebajo",surname:"Meseko",slug:"clement-meseko",fullName:"Clement Meseko",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/93517/images/system/93517.jpg",biography:"Dr. Clement Meseko obtained DVM and PhD degree in Veterinary Medicine and Virology respectively. He has worked for over 20 years in both private and public sectors including the academia, contributing to knowledge and control of infectious disease. Through the application of epidemiological skill, classical and molecular virological skills, he investigates viruses of economic and public health importance for the mitigation of the negative impact on people, animal and the environment in the context of Onehealth. \r\nDr. Meseko’s field experience on animal and zoonotic diseases and pathogen dynamics at the human-animal interface over the years shaped his carrier in research and scientific inquiries. He has been part of the investigation of Highly Pathogenic Avian Influenza incursions in sub Saharan Africa and monitors swine Influenza (Pandemic influenza Virus) agro-ecology and potential for interspecies transmission. He has authored and reviewed a number of journal articles and book chapters.",institutionString:"National Veterinary Research Institute",institution:{name:"National Veterinary Research Institute",country:{name:"Nigeria"}}},{id:"158026",title:"Prof.",name:"Shailendra K.",middleName:null,surname:"Saxena",slug:"shailendra-k.-saxena",fullName:"Shailendra K. Saxena",position:null,profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bRET3QAO/Profile_Picture_2022-05-10T10:10:26.jpeg",biography:"Professor Dr. Shailendra K. Saxena is a vice dean and professor at King George's Medical University, Lucknow, India. His research interests involve understanding the molecular mechanisms of host defense during human viral infections and developing new predictive, preventive, and therapeutic strategies for them using Japanese encephalitis virus (JEV), HIV, and emerging viruses as a model via stem cell and cell culture technologies. His research work has been published in various high-impact factor journals (Science, PNAS, Nature Medicine) with a high number of citations. He has received many awards and honors in India and abroad including various Young Scientist Awards, BBSRC India Partnering Award, and Dr. JC Bose National Award of Department of Biotechnology, Min. of Science and Technology, Govt. of India. Dr. Saxena is a fellow of various international societies/academies including the Royal College of Pathologists, United Kingdom; Royal Society of Medicine, London; Royal Society of Biology, United Kingdom; Royal Society of Chemistry, London; and Academy of Translational Medicine Professionals, Austria. He was named a Global Leader in Science by The Scientist. He is also an international opinion leader/expert in vaccination for Japanese encephalitis by IPIC (UK).",institutionString:"King George's Medical University",institution:{name:"King George's Medical University",country:{name:"India"}}},{id:"94928",title:"Dr.",name:"Takuo",middleName:null,surname:"Mizukami",slug:"takuo-mizukami",fullName:"Takuo Mizukami",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/94928/images/6402_n.jpg",biography:null,institutionString:null,institution:{name:"National Institute of Infectious Diseases",country:{name:"Japan"}}},{id:"233433",title:"Dr.",name:"Yulia",middleName:null,surname:"Desheva",slug:"yulia-desheva",fullName:"Yulia Desheva",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/233433/images/system/233433.png",biography:"Dr. Yulia Desheva is a leading researcher at the Institute of Experimental Medicine, St. Petersburg, Russia. She is a professor in the Stomatology Faculty, St. Petersburg State University. She has expertise in the development and evaluation of a wide range of live mucosal vaccines against influenza and bacterial complications. Her research interests include immunity against influenza and COVID-19 and the development of immunization schemes for high-risk individuals.",institutionString:'Federal State Budgetary Scientific Institution "Institute of Experimental Medicine"',institution:null},{id:"238958",title:"Mr.",name:"Atamjit",middleName:null,surname:"Singh",slug:"atamjit-singh",fullName:"Atamjit Singh",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/238958/images/6575_n.jpg",biography:null,institutionString:null,institution:null},{id:"252058",title:"M.Sc.",name:"Juan",middleName:null,surname:"Sulca",slug:"juan-sulca",fullName:"Juan Sulca",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/252058/images/12834_n.jpg",biography:null,institutionString:null,institution:null},{id:"191392",title:"Dr.",name:"Marimuthu",middleName:null,surname:"Govindarajan",slug:"marimuthu-govindarajan",fullName:"Marimuthu Govindarajan",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/191392/images/5828_n.jpg",biography:"Dr. M. 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He serves as an editorial board member in various national and international scientific journals.",institutionString:null,institution:null},{id:"274660",title:"Dr.",name:"Damodar",middleName:null,surname:"Paudel",slug:"damodar-paudel",fullName:"Damodar Paudel",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/274660/images/8176_n.jpg",biography:"I am DrDamodar Paudel,currently working as consultant Physician in Nepal police Hospital.",institutionString:null,institution:null},{id:"241562",title:"Dr.",name:"Melvin",middleName:null,surname:"Sanicas",slug:"melvin-sanicas",fullName:"Melvin Sanicas",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/241562/images/6699_n.jpg",biography:null,institutionString:null,institution:null},{id:"117248",title:"Dr.",name:"Andrew",middleName:null,surname:"Macnab",slug:"andrew-macnab",fullName:"Andrew Macnab",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"University of British Columbia",country:{name:"Canada"}}},{id:"322007",title:"Dr.",name:"Maria Elizbeth",middleName:null,surname:"Alvarez-Sánchez",slug:"maria-elizbeth-alvarez-sanchez",fullName:"Maria Elizbeth Alvarez-Sánchez",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"Universidad Autónoma de la Ciudad de México",country:{name:"Mexico"}}},{id:"337443",title:"Dr.",name:"Juan",middleName:null,surname:"A. 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A dynamic career research platform which is based on the thematic areas of comparative vertebrate physiology, stress endocrinology, reproductive endocrinology, animal health and welfare, and conservation biology. \nEdward has supervised 40 research students and published over 60 peer reviewed research.",institutionString:null,institution:{name:"University of Queensland",institutionURL:null,country:{name:"Australia"}}},editorTwo:null,editorThree:null,series:{id:"13",title:"Veterinary Medicine and Science",doi:"10.5772/intechopen.73681",issn:"2632-0517"},editorialBoard:[{id:"258334",title:"Dr.",name:"Carlos Eduardo",middleName:null,surname:"Fonseca-Alves",slug:"carlos-eduardo-fonseca-alves",fullName:"Carlos Eduardo Fonseca-Alves",profilePictureURL:"https://mts.intechopen.com/storage/users/258334/images/system/258334.jpg",institutionString:null,institution:{name:"Universidade Paulista",institutionURL:null,country:{name:"Brazil"}}},{id:"191123",title:"Dr.",name:"Juan José",middleName:null,surname:"Valdez-Alarcón",slug:"juan-jose-valdez-alarcon",fullName:"Juan José Valdez-Alarcón",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bSBfcQAG/Profile_Picture_1631354558068",institutionString:"Universidad Michoacana de San Nicolás de Hidalgo",institution:{name:"Universidad Michoacana de San Nicolás de Hidalgo",institutionURL:null,country:{name:"Mexico"}}},{id:"161556",title:"Dr.",name:"Maria Dos Anjos",middleName:null,surname:"Pires",slug:"maria-dos-anjos-pires",fullName:"Maria Dos Anjos Pires",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bS8q2QAC/Profile_Picture_1633432838418",institutionString:null,institution:{name:"University of Trás-os-Montes and Alto Douro",institutionURL:null,country:{name:"Portugal"}}},{id:"209839",title:"Dr.",name:"Marina",middleName:null,surname:"Spinu",slug:"marina-spinu",fullName:"Marina Spinu",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bRLXpQAO/Profile_Picture_1630044895475",institutionString:null,institution:{name:"University of Agricultural Sciences and Veterinary Medicine of Cluj-Napoca",institutionURL:null,country:{name:"Romania"}}},{id:"92185",title:"Dr.",name:"Sara",middleName:null,surname:"Savic",slug:"sara-savic",fullName:"Sara Savic",profilePictureURL:"https://mts.intechopen.com/storage/users/92185/images/system/92185.jfif",institutionString:'Scientific Veterinary Institute "Novi Sad"',institution:{name:'Scientific Veterinary Institute "Novi Sad"',institutionURL:null,country:{name:"Serbia"}}}]},onlineFirstChapters:{paginationCount:18,paginationItems:[{id:"83115",title:"Fungi and Oomycetes–Allies in Eliminating Environmental Pathogens",doi:"10.5772/intechopen.106498",signatures:"Iasmina Luca",slug:"fungi-and-oomycetes-allies-in-eliminating-environmental-pathogens",totalDownloads:0,totalCrossrefCites:0,totalDimensionsCites:0,authors:null,book:{title:"Animal Welfare - New Insights",coverURL:"https://cdn.intechopen.com/books/images_new/11579.jpg",subseries:{id:"19",title:"Animal Science"}}},{id:"82991",title:"Diseases of the Canine Prostate Gland",doi:"10.5772/intechopen.105835",signatures:"Sabine Schäfer-Somi",slug:"diseases-of-the-canine-prostate-gland",totalDownloads:8,totalCrossrefCites:0,totalDimensionsCites:0,authors:null,book:{title:"Recent Advances in Canine Medicine",coverURL:"https://cdn.intechopen.com/books/images_new/11580.jpg",subseries:{id:"19",title:"Animal Science"}}},{id:"82773",title:"Canine Transmissible Venereal Tumor: An Infectious Neoplasia in Dogs",doi:"10.5772/intechopen.106150",signatures:"Chanokchon Setthawongsin, Somporn Techangamsuwan and Anudep Rungsipipat",slug:"canine-transmissible-venereal-tumor-an-infectious-neoplasia-in-dogs",totalDownloads:17,totalCrossrefCites:0,totalDimensionsCites:0,authors:null,book:{title:"Recent Advances in Canine Medicine",coverURL:"https://cdn.intechopen.com/books/images_new/11580.jpg",subseries:{id:"19",title:"Animal Science"}}},{id:"82797",title:"Anatomical Guide to the Paranasal Sinuses of Domestic Animals",doi:"10.5772/intechopen.106157",signatures:"Mohamed A.M. 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