Geochemical result of the analysis soil samples.
\\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
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Dr. Tabár is an author of “Teaching Atlas of Mammography”, published in 1983, co-authored with Dr. Peter B. Dean, which has been translated into German, Italian, Portugese and Spanish. The 3rd edition was published in 2001 and issued in six languages. Other publications include: “Breast Cancer - The Art & Science of Early Detection With Mammography” (2005), co-authored with Dr. Tibor Tot and Dr. Peter B. Dean, “Breast Cancer - The Art & Science of Early Detection With Mammography. Crushed stone-like calcifications: the most frequent malignant type” (2008), co-authored with Dr. Tibor Tot and Dr. Peter B. Dean, “Breast Cancer - The Art & Science of Early Detection With Mammography. Casting type calcifications: sign of a subtype with deceptive features” (2007), also co-authored with Dr. Tibor Tot and Dr. Peter B. Dean, and the “Practical Breast Pathology” (2002) also co-authored with Dr. Tibor Tot and Dr. Peter B. 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",isbn:"978-1-80356-627-6",printIsbn:"978-1-80356-626-9",pdfIsbn:"978-1-80356-628-3",doi:null,price:0,priceEur:0,priceUsd:0,slug:null,numberOfPages:0,isOpenForSubmission:!1,isSalesforceBook:!1,isNomenclature:!1,hash:"0dc35bb64f54083f24d0a7043fc52c69",bookSignature:"Ph.D. Alaeddin Abukabda and Dr. Christopher Fonner",publishedDate:null,coverURL:"https://cdn.intechopen.com/books/images_new/11657.jpg",keywords:"Diabetes Mellitus, Hypertension, Rarefaction, Oxidative Stress, Nitric Oxide, Endothelium, Vascular Reactivity, Microcirculation, Circulation, Vasomotion, Blood Pressure, Blood Flow",numberOfDownloads:null,numberOfWosCitations:0,numberOfCrossrefCitations:null,numberOfDimensionsCitations:null,numberOfTotalCitations:null,isAvailableForWebshopOrdering:!0,dateEndFirstStepPublish:"March 17th 2022",dateEndSecondStepPublish:"May 25th 2022",dateEndThirdStepPublish:"July 24th 2022",dateEndFourthStepPublish:"October 12th 2022",dateEndFifthStepPublish:"December 11th 2022",dateConfirmationOfParticipation:null,remainingDaysToSecondStep:"3 months",secondStepPassed:!0,areRegistrationsClosed:!0,currentStepOfPublishingProcess:4,editedByType:null,kuFlag:!1,biosketch:"A scientist who has been involved in the submission and writing of several National Institutes of Health (NIH) and National Science Foundation (NSF) grants. Dr. Abukabda is a member of many societies including the American Physiological Society and the American Association for the Advancement of Science.",coeditorOneBiosketch:"Dr. Christopher Fonner is an assistant professor of physiology at the Lake Erie College of Osteopathic Medicine. He served as an advisor to several student organizations, including the Tri-Beta Biological Honors Society and the Health Professions Institute, among others.",coeditorTwoBiosketch:null,coeditorThreeBiosketch:null,coeditorFourBiosketch:null,coeditorFiveBiosketch:null,editors:[{id:"307873",title:"Ph.D.",name:"Alaeddin",middleName:null,surname:"Abukabda",slug:"alaeddin-abukabda",fullName:"Alaeddin Abukabda",profilePictureURL:"https://mts.intechopen.com/storage/users/307873/images/system/307873.png",biography:"Dr. Abukabda graduated from Al Fateh Dental College, Libya, in 2007. He obtained a master`s degree in Molecular Biology from Clarion University, Pennsylvania, in 2011. He later obtained a Ph.D. in Cellular Physiology from West Virginia University in 2018 and a Certification in Biostatistics from the West Virginia University School of Public Health. In 2018, Dr. Abukabda worked as a postdoctoral research associate at the Vascular Medicine Institute at the University of Pittsburgh. He has been involved in the submission and writing of several National Institutes of Health (NIH) and National Science Foundation (NSF) grants and intramural seed grants. Dr. Abukabda has published and presented many papers in immunology, toxicology, and cardiovascular physiology. He has also served as a reviewer for many journals in his field of expertise.",institutionString:"Lake Erie College of Osteopathic Medicine",position:null,outsideEditionCount:0,totalCites:0,totalAuthoredChapters:"0",totalChapterViews:"0",totalEditedBooks:"1",institution:{name:"Lake Erie College of Osteopathic Medicine",institutionURL:null,country:{name:"United States of America"}}}],coeditorOne:{id:"447766",title:"Dr.",name:"Christopher",middleName:null,surname:"Fonner",slug:"christopher-fonner",fullName:"Christopher Fonner",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0033Y00003JajyeQAB/Profile_Picture_1638443107477",biography:"Dr. Christopher Fonner, Ph.D.\r\nAssistant Professor of Physiology\r\nAssistant Director of PBL\r\n\r\nLake Erie College of Osteopathic Medicine (LECOM)\r\n\r\n1858 West Grandview Boulevard\r\nErie, PA 16509\r\n814-866-8460\r\ncfonner@lecom.edu\r\nPodcast: thebiobusters.podbean.com\r\n\r\nEDUCATION\r\nDuquesne University, Pittsburgh, Pennsylvania\r\nDoctor of Philosophy, Biological Sciences, August 2015\r\nDissertation: The Effects of Stressors & Stress Hormones on Behavior, Physiology, & Disease\r\nSusceptibility in Terrestrial Salamanders\r\nMentor: Dr. Sarah K. Woodley\r\nGannon University, Erie, Pennsylvania\r\nBachelor of Science, Biology, May 2009\r\nUndergraduate Research Project: Effects of Plant Hormones on Spore Germination\r\nMentor: Dr. Michael Ganger\r\n\r\nTEACHING EXPERIENCE\r\n2019 – Current: Assistant Professor of Physiology, LECOM, Erie, PA\r\n DAE 1013 – PhD Physiology, Spring 2020, Spring 2021\r\n IPE 1001 – Inter-Professional Education, Spring 2020, Spring 2021\r\n MMS 1006 – MMS Cell Biology, Fall 2020, Fall 2021\r\n MMS 1016 – MMS Physiology, Fall 2019, Fall 2020, Fall 2021\r\n NAT 1003 - Basic Neuroscience, Spring 2020, Spring 2021\r\n PBL 1001 – PBL Modules, Spring 2020, Spring 2021, Fall 2021\r\n PHY 1010 – Core Physiology, Fall 2019, Fall 2020, Fall 2021\r\n SYS 1003 – Renal System, Fall 2020, Fall 2021\r\n2015 – 2019: Assistant Professor, Thiel College, Greenville, PA\r\n Introduction to Exercise Science, Thiel College, Fall 2018\r\n Human Anatomy Lecture & Lab, Thiel College, Fall 2018, Fall 2017, Fall 2016, Fall\r\n2015\r\n Human Physiology Lecture & Lab, Thiel College, Spring 2019, Spring 2018, Spring 2016\r\n\r\n2\r\n\r\n Health Professions Institute Trends in Health Care, Thiel College, Spring 2019, Spring\r\n2018\r\n Science and Movie Magic, Thiel College, Fall 2018\r\n Animal Physiology Lecture & Lab, Spring 2017\r\n Physiological Basis of Exercise & Physical Fitness Lecture & Lab, Spring 2019, Spring\r\n2017\r\n Developmental Biology Lecture & Lab, Thiel College, Spring 2018, Spring 2016\r\n Junior Research Seminar, Thiel College, Spring 2019, Spring 2017, Spring 2016\r\n Foundations of Biology Lecture & Lab, Thiel College, Fall 2018, Fall 2017, Fall 2016,\r\nFall 2015\r\n Senior Seminar in Biology, Thiel College, Fall 2017, Fall 2016, Fall 2015\r\n Advanced Study in Biology, Thiel College, 2016-2018, Fall & Spring\r\n Independent Study in Biology, Thiel College, 2016-2018, Fall & Spring; Spring 2019\r\nTeaching Assistant\r\n Anatomy and Physiology Lab, Duquesne University, Fall 2013, 2014\r\n Mammalian Physiology, Duquesne University, Fall 2010\r\n General Biology Laboratory, Duquesne University, Fall 2009, 2012, Spring 2010, 2011\r\n Physiology & Molecular Techniques for PT Lab, Duquesne University, Fall 2011\r\n Cell & Systems Physiology Lab, Duquesne University, Spring 2012, 2013, 2014, 2015\r\nResearch Experience\r\nPrincipal Investigator\r\nDates: 2015-2019\r\nInstitution: Thiel College, Greenville, PA\r\nProject Titles:\r\n Examination of the effects of sex, stress, and disease on the fungal pathogen\r\nBatrachochytrium dendrobatidis and antimicrobial activity in terrestrial salamanders\r\n Investigations into the stress hormone levels and physiological symptoms of stress in\r\nundergraduates enrolled in higher level biology courses\r\n The use of Avida Ed software for evolution simulations in an undergraduate biology\r\nlaboratory\r\n The effects of stress on student efficiency in upper-level biology courses at Thiel College\r\nGraduate Student\r\nDates: August 2009-June2015\r\nInstitution: Duquesne University, Pittsburgh, PA\r\nProject title:\r\n The effects of stressors and stress hormones on behavior, physiology, and disease\r\nsusceptibility in terrestrial salamanders.\r\n\r\nGuest Lectures\r\n\r\n3\r\n\r\n Weird Science!: How Studies with Amphibian Disease Biology Can Stimulate\r\nUndergraduate Research Interests. Invited Research Presentation, Slippery Rock\r\nUniversity, Fall 2017\r\n Stressed Out!: Tales from GNC-Funded Research on Amphibian Stress & Disease.\r\nInvited Research Presentation for the Thiel Forum, Thiel College, Spring 2017\r\n\r\nSERVICE\r\nLECOM\r\n2021-Present Assistant PBL Director\r\n2019-Present Assistant Director of the Affiliate Student Success Program\r\n2021 Coordinator of Affiliate Student Enhancement Course\r\n2021-Present EXCEL Team Member\r\n2021-Present MMS Cell Biology Course Director\r\n2021-Present Dermatology System Course Director\r\n2021 Student Doctor of the Year Committee\r\n2021-Present Student Government Association Advisor\r\n2021-Present Student National Medical Association, Advisor\r\n2021 Curriculum Review Coordinator, Endocrine System\r\n2021 Curriculum Review Team, Pathology\r\n2020 Research Day Judge\r\n2019, 2020 Student Researcher of the Year, Judge\r\n2020 Curriculum Review Team, Musculoskeletal System\r\n2019-Present Academic Advisor for LDP, MMS, & PBL Students\r\n2019-Present Medical Student Application Interview Member\r\nThiel College\r\n2018-2019 Department Chair, Biology Department, Thiel College\r\n2018 Co-Chair, Exercise Science Assistant Professor Search Committee, Thiel College\r\n2018 Member, Speech Language Pathology Master’s Program Director Search\r\n\r\nCommittee, Thiel College\r\n\r\n2018 Moderator, Exercise Science Alumni Panel, Thiel College\r\n2018-2019 Adviser, Communication Sciences and Disorders Advisory Board, Thiel College\r\n2018-2019 Adviser, Chess Club, Thiel College\r\n2018 Judge, K’NEX Science Competition, Greenville High School\r\n2017-2019 Adviser, Development of Exercise Science Program, Thiel College\r\n2017-Present Coordinator, Thiel Science Week Outreach Initiative, Thiel College\r\n2017-Present Adviser, Pre-Physical Therapy Program, Thiel College\r\n2017-Present Adviser, Tri-Beta Biological Honors Society, Thiel College\r\n2017-Present Instructor, GRE Preparatory Course, Greenville Neuromodulation Center, Thiel\r\n\r\nCollege\r\n\r\n2016-Present Adviser, Pre-Veterinary Medicine Program, Thiel College\r\n\r\n4\r\n\r\n2016-Present Lab Manager, Foundations of Biology Lab Course, Thiel College\r\n2015-Present Adviser, Dietrich Honors Institute, Thiel College\r\n2015-Present Reviewer for Canadian Journal of Zoology, Herpetologica and Southeastern\r\n\r\nNaturalist Journals\r\n\r\n2016-Present Member, Campus Lifestyle Committee, Thiel College\r\n2016-Present Member, Institutional Animal Care & Utilization Committee (IACUC), Thiel\r\n\r\nCollege\r\n\r\n2016-Present Advisor, Health Professions Institute (HPI), Thiel College\r\n2016 Lecturer/Volunteer, Career Day, Gastonville Elementary Center\r\nREFEREED PUBLICATIONS\r\nAbi Abdallah, D.S., Fonner, C.W., Lax, N.C., Babeji, M.R., & Pale, F.A. 2020. Evaluating the\r\nuse of Avida-ED digital organisms to teach evolution & natural selection. The American Biology\r\nTeacher 82(2).\r\nFonner, C.W., Patel, S., Boord, S., Venesky, M.D., & Sarah K. Woodley. 2017. Effects of\r\ncorticosterone on infection and disease in salamanders exposed to the amphibian fungal\r\npathogen, Batrachochytrium dendrobatidis. Diseases of Aquatic Organisms 123(2), 159-171.\r\nFonner, Christopher W. & Sarah K. Woodley. 2015. Testing the predation stress hypothesis:\r\nbehavioural and hormonal responses to predator cues in Allegheny Mountain dusky salamanders.\r\nBehaviour 152(6), 797-819.\r\n\r\nFUNDING SUPPORT (Thiel College)\r\nThe Carl Hoffman Science Fund Grant (2015). ($10,000)\r\nGreenville Neuromodulation Center (GNC) Research Institute Grant. Examining the Presence\r\nand Prevalence of Batrachochytrium dendrobatidis Around Thiel College & Investigation into\r\nthe Effects of Acidic Conditions on Fungal Pathogen Susceptibility to Batrachochytrium\r\ndendrobatidis. ($14,780)\r\nGreenville Neuromodulation Center (GNC) Research Institute Grant. Examining the Effects of\r\nSex/Mating, Testosterone, and Inhibitory Skin Bacteria on Susceptibility to Lethal Fungal\r\nPathogens in Red-Backed Salamanders. ($10,178)\r\nGreenville Neuromodulation Center (GNC) Research Institute Grant. Examining the effects of\r\ntestosterone on susceptibility to a lethal fungal pathogen in red-backed salamanders. ($19,458)\r\n\r\n5\r\nPROFESSIONAL PRESENTATIONS\r\nAbi Abdallah, D.S., Fonner, C.W., Lax, N.C., Babeji, M.R., & Pale, F.A. 2020. Evaluating the\r\nuse of Avida-ED digital organisms to teach evolution & natural selection. Poster presented at the\r\nNational Association of Biology Teachers conference, November 11-14, 2021.\r\nClaire Stoudemire, Mark Terrell, Sarah McCarthy, Raj Gulati, Chris Fonner, & Randy Kulesza.\r\nThe Effect of Clinical Anatomy Integration on Medical Student Academic Performance and\r\nLearning Approach. Oral talk presented at the LECOM Research Day, LECOM, October 29,\r\n2021.\r\nAmy Ritchie (Advised by C.W. Fonner). Effects of a fungal pathogen on mating behaviors &\r\ndisease transmission in terrestrial salamanders. Poster presentation presented at the\r\nUndergraduate Research at the Capitol Symposium, Harrisburg, PA, April 17, 2018.\r\nAmy Ritchie (Advised by C.W. Fonner). Effects of a fungal pathogen on mating behaviors &\r\ndisease transmission in terrestrial salamanders. Oral talk presented at the Western Pennsylvania\r\nUndergraduate Biology Symposium, Thiel College, April 14, 2018.\r\nSimpson, S., & Brook Simpson (Advised by C.W. Fonner). The effects of acid exposure on\r\nincidence of a fungal pathogen in red-backed salamanders. Poster presentation presented at the\r\nWestern Pennsylvania Undergraduate Biology Symposium, Thiel College, April 14, 2018.\r\nAlana Callahan (Advised by C.W. Fonner). The Effects of sex on disease susceptibility in the\r\nred-backed salamander. Poster presentation presented at the Undergraduate Research at the\r\nCapitol Symposium, Harrisburg, PA, April 25, 2017.\r\nAlana Callahan (Advised by C.W. Fonner). The Effects of sex on disease susceptibility in the\r\nred-backed salamander. Oral talk presented at the Western Pennsylvania Undergraduate Biology\r\nSymposium, Washington and Jefferson College, April 8, 2017.\r\nForringer, D., & Bradley Wisnoski (Advised by C.W. Fonner). Examining the effects of chronic\r\nhandling on infection and disease susceptibility of red-backed salamanders. Poster presentation\r\npresented at the Western Pennsylvania Undergraduate Biology Symposium, Washington and\r\nJefferson College, April 8, 2017.\r\nWhiteman, J., & Erin DiFalco (Advised by C.W. Fonner). Differences in skin bacterium\r\nincidence in the red-backed salamander, Plethodon cinereus. Poster presentation presented at the\r\nWestern Pennsylvania Undergraduate Biology Symposium, Washington and Jefferson College,\r\nApril 8, 2017.\r\nCallahan, A., & Amber Martin (Advised by C.W. Fonner). The effects of sex on disease\r\nsusceptibility in the red-backed salamander. Oral talk presented at the GNC Research Plenary\r\nSessions, Thiel College, September 9, 2016.",institutionString:"Lake Erie College of Osteopathic Medicine",position:null,outsideEditionCount:0,totalCites:0,totalAuthoredChapters:"0",totalChapterViews:"0",totalEditedBooks:"0",institution:{name:"Lake Erie College of Osteopathic Medicine",institutionURL:null,country:{name:"United States of America"}}},coeditorTwo:null,coeditorThree:null,coeditorFour:null,coeditorFive:null,topics:[{id:"16",title:"Medicine",slug:"medicine"}],chapters:null,productType:{id:"1",title:"Edited Volume",chapterContentType:"chapter",authoredCaption:"Edited by"},personalPublishingAssistant:{id:"429343",firstName:"Martina",lastName:"Ivancic",middleName:null,title:"Ms.",imageUrl:"https://mts.intechopen.com/storage/users/429343/images/19998_n.jpg",email:"martina@intechopen.com",biography:"As an Author Service Manager, my responsibilities include monitoring and facilitating all publishing activities for authors and editors. 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The distribution of pathfinder elements in these media especially stream sediment and soil is governed by weathering and hydromorphic conditions of the area under investigation in addition to the mobility of such elements. Despite their dispersion, trace and rare earth elements still retain their bedrock characteristics. These elements are adsorbed unto surfaces of weathered products and possess the ability to remain on the surfaces of these weathered particles for long periods unless they are mobilized by decomposition processes such as redox conditions [4]. Bowen [5] believes that the residence time of these elements in temperate soils is not the same. For example, the residence time of Pb is between 740 and 5900 years, Zn has a residence time of 70–510 years, 13–1100 years is the residence time for Cd, and 310–1500 years is the residence time for Cu, while the residence time in tropical soils is 40 years due to the shorter rate of leaching. Soil geochemical surveys have proven to be highly effective with long and impressive history of discovering blind deposits [6].
Akilolu [7] reports the gossan manganite occurrences in Buya and Derena area, northwestern Nigeria. He groups these ores into three which are Buya, Derena north and Derena south clusters. In his paper, he argues that the Buya gossans are purer than other clusters. Bamigboye et al. [8] report goethite mineralization in addition to the manganite mineralizations reported by Akilolu [7] in Kaoje, northwestern Nigeria. Furthermore, an exposure of brown laminated manganite ore, south of Barkin-Ruwa, was also reported to earlier reported manganite clusters in these areas. This exposure is relatively unique in terms of its brown colouration as against the black colour of those in Buya and Derena clusters. The report of Akilolu [7] and Bamigboye et al. [8] did, however, not give account of the distribution of trace and rare earth elements in the soil in Kaoje and its environs, neither is vivid account given on the possibility of discovering concealed bodies of these ores or others within Kaoje and its environs. Other work related to this include the work of Adekoya [9], Mucke [10], Okorie et al. [11, 12] and Fillie [13, 14], among others. This work is therefore aimed at identifying the mineralized zones in Kaoje and its environs using geochemical signatures in soils around Kaoje and its environs, northwestern Nigeria. The study area is bounded by Long. 3°55′ and 4°10′E and Lat. 11°00′ and 11°15′N covering an approximate area of 676 km2.
The geology of the area can grossly be divided into the basement complex rock and sedimentary rocks. The basement complex rocks are mainly banded gneiss, migmatite, granite gneiss, quartz-mica schist and granite (Figure 1).
Geological map of Kaoje and its environs with insect of map of Nigeria and Africa.
The banded gneiss occurs as elongated rock body within the schist and is seen about 2 km south-west of Buya and midway between Idowa and Derena. The banded gneisses are rich in quartz with pervasive jointing, filled by quartz and quartzofeldspathic vein in most cases. Migmatite trends in SE-NW direction mainly. The granite gneisses have a sharp contact with the mica schist. Mineralogically, quartz, biotite and sodic feldspar predominate, but crystals of tourmaline are seen in some localities. The quartz-mica schist is extensively weathered and covers about one-fifth of the area studied. It occurs as a low-lying exposure and stream-cut exposure. Some of the schists occur as xenolith with a large pegmatitic body close to Barkin-Ruwa, along Barkin-Ruwa-Buya road.
The granitic bodies occur towards the southern part of the study area. The granitic rocks occur as boulders and cobbles of rocks and are closely associated with weathered schist in the southernmost part of the area. The pegmatitic rocks in this area are seen associated with the schist and migmatite mainly. Some of the pegmatites are also seen at the contact between the schist and the sedimentary rock in the northwestern area. Mineralogically, the pegmatites are made up of quartz, biotite, k-feldspar tourmaline (in the southeastern part) and chalcedony (in the northwestern part).
Sedimentary rocks in this area occupy about 60% of the area. This rock includes the Biongbe, Morongba and Koremi hills. These hills are essentially clastic sedimentary rocks that include the sandstone and silty sandstone. In the northeastern part of Kaoje, sedimentary rocks occur as remnant of gully eroded sedimentary rocks. These rocks are finely laminated with characteristic ichnofossil. Other characteristic of these rocks are their semi-consolidated nature that is typical of Taloka Formation in the Sokoto Basin. The rocks in this area include silty sandstones that are finely laminated, while some are massive. Other sedimentary rock types seen associated with the sandstone are goethite, kaolinitic mudstone, finely laminated siltstones and kaolinitic purple claystone. All these are exposed along Kaoje-Idowa road and towards the edge of the area studied in the northeastern part.
The iron ore occur as vein, boulders and sedimentary capping in the northeast and southeast mainly. It shows conspicuous alternating bands of iron and chert-rich layers in most of the location, while few are massive iron ore with little or no cherty contents. Bamigboye et al. [8] describe these irons to be of hydrothermal origin but now remobilized. Manganite gossans occur as boudins in an almost NE-SW direction from Buya through Derena to the eastern part of Barkin-Ruwa. These ores occur as black laminated exposures mainly around the Buya-Derena axis and as brown folded brown laminated body south of Barkin-Ruwa. Mn is associated with quartz veins. From the work of Bamigboye et al. [8], the iron ores are made up of feroxhyte, gibbsite, goethite, maghemite, magnetite and haematite essentially with subordinate manganite, while the manganites are composed of manganite, gibbsite, magnetite, bayerite, akaganeite and nordstrandite among others.
The methods adopted in this work are grossly divided into two. These are fieldwork and laboratory work. The fieldwork was carried out between 2011 and 2012. During this period, rock and soil samples were taken. The soil samples were taken from a grid of 1 km × 1 km from a depth range of 30–50 cm corresponding to the B-horizon as recommended by Vareikiene and Lehtonen [15]. Thirty soil samples were prepared and subjected to geochemical analysis at ACME Analytical laboratory, Vancouver, Canada. In the laboratory, 0.5 g of the soil samples were digested with a modified aqua regia solution of equal parts concentrated HCl, HNO3 and DI H2O for 1 h in a heating block. The resulting solution was thereafter analysed by ICP-ES and ICP-MS for trace and rare earth elemental concentration. The selected elements that were considered related to iron and manganite mineralization from the geochemical data was correlated. Others were subjected to principal component statistical analysis (PCSA) using the SPSS software, while isograde plotting of the data was done using Surfer 12.
The result of the geochemical analysis where the concentration of 53 elements was determined is shown in Table 1. From the result, sample 83a and 86 had the highest concentration of most of the elements, while sample 64 and 222 had the lowest concentration of most of the elements. S had a constant value of <0.02 except in sample 83a where the value is 0.02%. This same sample had 0.05 ppm concentration of W as against <0.05 in the remaining samples. This is equally similar to the slight higher concentration of 0.02 ppm concentration of Se as against <0.1 in other samples.
Sample no. | Cd (ppm) | Sb (ppm) | Bi (ppm) | V (ppm) | Ca (%) | P (%) | La (ppm) | Cr (ppm) | Mg (%) | Ba (ppm) | Ti (%) | B (ppm) | Al (%) | Na (%) | K (%) | W (ppm) | Sc (ppm) | Tl (ppm) | S (%) | Hg (ppb) |
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
10 | <0.01 | 0.04 | 0.06 | 17 | 0.02 | 0.006 | 9.4 | 9.0 | 0.02 | 18.7 | 0.009 | <20 | 0.43 | <0.001 | 0.03 | <0.05 | 2.3 | 0.05 | <0.02 | 11 |
18 | 0.02 | 0.05 | 0.05 | 22 | 0.15 | 0.009 | 15.8 | 15.1 | 0.03 | 42.4 | 0.019 | <20 | 0.41 | <0.001 | 0.03 | <0.05 | 2.4 | 0.04 | <0.02 | 30 |
33 | <0.01 | 0.04 | 0.05 | 14 | 0.02 | 0.004 | 8.9 | 11.3 | 0.02 | 14.5 | 0.021 | <20 | 0.23 | <0.001 | 0.01 | <0.05 | 1.6 | 0.03 | <0.02 | 6 |
44 | <0.01 | <0.02 | 0.11 | 20 | 0.03 | 0.006 | 12.4 | 12.5 | 0.07 | 40.3 | 0.018 | <20 | 0.45 | 0.002 | 0.08 | <0.05 | 2.1 | 0.11 | <0.02 | 9 |
60 | <0.01 | 0.06 | 0.07 | 45 | 0.08 | 0.011 | 13.4 | 20.8 | 0.03 | 50.8 | 0.008 | <20 | 0.49 | <0.001 | 0.03 | <0.05 | 2.3 | 0.07 | <0.02 | 14 |
64 | <0.01 | <0.02 | 0.02 | 10 | 0.03 | 0.004 | 7.1 | 6.0 | 0.02 | 42.4 | 0.004 | <20 | 0.14 | <0.001 | 0.02 | <0.05 | 1.0 | 0.03 | <0.02 | 8 |
73 | <0.01 | 0.02 | 0.04 | 13 | 0.03 | 0.005 | 7.3 | 8.1 | 0.02 | 33.4 | 0.008 | <20 | 0.25 | <0.001 | 0.02 | <0.05 | 1.3 | 0.04 | <0.02 | 7 |
76 | 0.01 | 0.03 | 0.05 | 33 | 0.01 | 0.010 | 10.9 | 21.3 | 0.02 | 15.1 | 0.014 | <20 | 0.69 | <0.001 | 0.01 | <0.05 | 5.2 | 0.04 | <0.02 | 14 |
78 | <0.01 | 0.03 | 0.05 | 21 | 0.06 | 0.008 | 16.1 | 14.2 | 0.02 | 19.1 | 0.012 | <20 | 0.47 | <0.001 | 0.02 | <0.05 | 2.7 | 0.03 | <0.02 | 19 |
83a | 0.02 | <0.02 | 0.15 | 19 | 0.74 | 0.020 | 24.4 | 10.7 | 0.24 | 135.9 | 0.068 | <20 | 1.55 | 0.003 | 0.42 | 0.05 | 2.0 | 0.33 | 0.02 | 17 |
86 | 0.01 | <0.02 | 0.22 | 59 | 0.13 | 0.011 | 24.2 | 44.8 | 0.50 | 144.3 | 0.096 | <20 | 1.98 | 0.003 | 0.51 | <0.05 | 6.9 | 0.29 | <0.02 | 11 |
112 | <0.01 | 0.05 | 0.05 | 26 | 0.05 | 0.008 | 14.8 | 17.5 | 0.02 | 26.5 | 0.023 | <20 | 0.38 | <0.001 | 0.02 | <0.05 | 3.2 | 0.04 | <0.02 | 23 |
122 | <0.01 | 0.07 | 0.11 | 73 | <0.01 | 0.010 | 21.0 | 24.7 | 0.01 | 9.1 | 0.024 | <20 | 1.07 | <0.001 | 0.02 | <0.05 | 7.8 | 0.07 | <0.02 | 23 |
128 | <0.01 | 0.04 | 0.05 | 45 | 0.07 | 0.011 | 14.1 | 21.2 | 0.02 | 45.0 | 0.015 | <20 | 0.55 | <0.001 | 0.03 | <0.05 | 3.4 | 0.03 | <0.02 | 15 |
135 | <0.01 | 0.05 | 0.09 | 39 | 0.02 | 0.008 | 15.4 | 19.1 | 0.03 | 14.6 | 0.022 | <20 | 0.74 | <0.001 | 0.03 | <0.05 | 5.4 | 0.06 | <0.02 | 15 |
151 | 0.01 | 0.04 | 0.06 | 25 | 0.14 | 0.009 | 17.4 | 11.2 | 0.04 | 86.3 | 0.009 | <20 | 0.42 | <0.001 | 0.05 | <0.05 | 2.4 | 0.06 | <0.02 | 28 |
187 | 0.02 | 0.04 | 0.03 | 18 | 0.05 | 0.006 | 12.5 | 14.3 | 0.02 | 30.8 | 0.019 | <20 | 0.25 | <0.001 | 0.02 | <0.05 | 2.1 | 0.03 | <0.02 | 34 |
190 | <0.01 | 0.04 | 0.05 | 23 | 0.03 | 0.007 | 12.2 | 17.0 | 0.02 | 18.7 | 0.027 | <20 | 0.44 | <0.001 | 0.02 | <0.05 | 3.0 | 0.04 | <0.02 | 28 |
194 | <0.01 | 0.05 | 0.08 | 43 | <0.01 | 0.011 | 11.0 | 19.6 | 0.01 | 7.4 | 0.013 | <20 | 0.87 | <0.001 | 0.02 | <0.05 | 5.3 | 0.05 | <0.02 | 16 |
199 | <0.01 | 0.05 | 0.06 | 24 | 0.11 | 0.011 | 17.8 | 18.8 | 0.03 | 17.4 | 0.024 | <20 | 0.46 | <0.001 | 0.04 | <0.05 | 3.0 | 0.05 | <0.02 | 29 |
214 | <0.01 | <0.02 | 0.06 | 17 | 0.26 | 0.007 | 20.0 | 9.5 | 0.11 | 154.3 | 0.009 | <20 | 0.53 | 0.001 | 0.08 | <0.05 | 3.1 | 0.10 | <0.02 | 22 |
217a | <0.01 | <0.02 | 0.04 | 14 | 0.09 | 0.006 | 14.4 | 10.1 | 0.04 | 40.0 | 0.005 | <20 | 0.38 | <0.001 | 0.03 | <0.05 | 1.7 | 0.05 | <0.02 | 21 |
219 | 0.02 | 0.05 | 0.07 | 40 | 0.15 | 0.010 | 21.6 | 13.9 | 0.06 | 259.8 | 0.012 | <20 | 0.46 | 0.003 | 0.03 | <0.05 | 2.9 | 0.16 | <0.02 | 13 |
222 | <0.01 | <0.02 | 0.02 | 6 | 0.04 | 0.003 | 8.5 | 5.8 | 0.02 | 28.8 | 0.005 | <20 | 0.17 | 0.002 | 0.02 | <0.05 | 1.5 | 0.03 | <0.02 | 8 |
225 | <0.01 | <0.02 | 0.08 | 24 | 0.11 | 0.007 | 17.3 | 15.2 | 0.08 | 59.2 | 0.004 | <20 | 0.76 | <0.001 | 0.07 | <0.05 | 3.7 | 0.13 | <0.02 | 13 |
244 | <0.01 | 0.05 | 0.07 | 36 | 0.04 | 0.011 | 14.9 | 14.9 | 0.03 | 27.4 | 0.025 | <20 | 0.56 | 0.001 | 0.03 | <0.05 | 3.5 | 0.06 | <0.02 | 20 |
258 | 0.02 | 0.03 | 0.06 | 18 | 0.11 | 0.010 | 24.5 | 10.8 | 0.07 | 190.6 | 0.008 | <20 | 0.43 | 0.001 | 0.06 | <0.05 | 2.6 | 0.06 | <0.02 | 27 |
261 | 0.02 | 0.04 | 0.07 | 29 | 0.09 | 0.009 | 22.9 | 11.6 | 0.04 | 68.9 | 0.010 | <20 | 0.47 | <0.001 | 0.04 | <0.05 | 2.9 | 0.06 | <0.02 | 25 |
266 | 0.02 | 0.05 | 0.07 | 30 | 0.08 | 0.013 | 30.6 | 15.6 | 0.04 | 43.8 | 0.021 | <20 | 0.48 | <0.001 | 0.04 | <0.05 | 3.7 | 0.07 | <0.02 | 29 |
286 | 0.01 | 0.04 | 0.09 | 42 | 0.06 | 0.009 | 18.3 | 12.6 | 0.03 | 43.9 | 0.011 | <20 | 0.82 | <0.001 | 0.04 | <0.05 | 4.7 | 0.08 | <0.02 | 21 |
Sample no. | Se (ppm) | Te (ppm) | Ga (ppm) | Cs (ppm) | Ge (ppm) | Hf (ppm) | Nb (ppm) | Rb (ppm) | Sn (ppm) | Ta (ppm) | Zr (ppm) | Y (ppm) | Ce (ppm) | In (ppm) | In (ppm) | Re (ppb) | Be (ppm) | Li (ppm) | Pd (ppb) | Pt(ppb) |
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
10 | <0.1 | <0.02 | 2.6 | 0.48 | <0.1 | <0.02 | 0.15 | 8.7 | 0.5 | <0.05 | 1.4 | 8.11 | 33.8 | 0.03 | 0.03 | <1 | 0.3 | 1.2 | <10 | <2 |
18 | <0.1 | <0.02 | 3.1 | 0.36 | <0.1 | 0.09 | 0.65 | 7.4 | 0.7 | <0.05 | 3.2 | 9.57 | 33.1 | 0.02 | 0.02 | <1 | 0.2 | 1.2 | <10 | <2 |
33 | <0.1 | <0.02 | 2.1 | 0.28 | <0.1 | 0.07 | 0.37 | 4.7 | 0.6 | <0.05 | 2.8 | 5.35 | 21.8 | <0.02 | <0.02 | <1 | 0.1 | 0.7 | <10 | <2 |
44 | <0.1 | <0.02 | 2.7 | 1.16 | <0.1 | <0.02 | 0.18 | 17.9 | 0.5 | <0.05 | 0.9 | 5.62 | 25.8 | 0.02 | 0.02 | <1 | 0.4 | 3.4 | <10 | <2 |
60 | <0.1 | <0.02 | 3.1 | 0.39 | <0.1 | 0.04 | 0.26 | 8.9 | 0.5 | <0.05 | 2.3 | 8.98 | 33.2 | <0.02 | <0.02 | <1 | 0.5 | 1.1 | <10 | <2 |
64 | <0.1 | <0.02 | 0.8 | 0.22 | <0.1 | <0.02 | 0.10 | 3.9 | 0.2 | <0.05 | 0.6 | 3.85 | 12.7 | <0.02 | <0.02 | <1 | 0.1 | 0.6 | <10 | <2 |
73 | <0.1 | <0.02 | 1.7 | 0.26 | <0.1 | <0.02 | 0.17 | 5.1 | 0.3 | <0.05 | 1.1 | 4.63 | 21.8 | <0.02 | <0.02 | <1 | 0.3 | 0.6 | <10 | <2 |
76 | <0.1 | <0.02 | 5.5 | 0.44 | <0.1 | 0.17 | 0.35 | 2.8 | 0.9 | <0.05 | 8.7 | 9.11 | 35.2 | 0.04 | 0.04 | <1 | 0.2 | 1.0 | <10 | <2 |
78 | <0.1 | <0.02 | 3.0 | 0.42 | <0.1 | 0.03 | 0.33 | 5.4 | 0.6 | <0.05 | 1.9 | 10.48 | 55.0 | <0.02 | <0.02 | <1 | 0.2 | 1.1 | <10 | <2 |
83a | 0.2 | <0.02 | 7.2 | 3.66 | <0.1 | 0.11 | 2.63 | 57.1 | 1.1 | <0.05 | 3.8 | 4.52 | 49.0 | <0.02 | <0.02 | <1 | 1.4 | 28.8 | <10 | <2 |
86 | <0.1 | 0.05 | 7.5 | 4.66 | <0.1 | 0.03 | 0.49 | 55.1 | 1.0 | <0.05 | 1.7 | 10.84 | 60.8 | 0.03 | 0.03 | <1 | 1.1 | 32.2 | <10 | <2 |
112 | <0.1 | <0.02 | 3.5 | 0.41 | <0.1 | 0.04 | 0.50 | 7.1 | 0.8 | <0.05 | 3.3 | 9.72 | 41.0 | 0.03 | 0.03 | <1 | 0.3 | 0.9 | <10 | <2 |
122 | <0.1 | <0.02 | 9.5 | 0.81 | <0.1 | 0.36 | 0.35 | 5.5 | 1.6 | <0.05 | 19.6 | 10.67 | 79.6 | 0.05 | 0.05 | <1 | 0.2 | 1.4 | 14 | <2 |
128 | <0.1 | <0.02 | 4.5 | 0.41 | <0.1 | 0.05 | 0.45 | 6.0 | 0.9 | <0.05 | 2.4 | 11.38 | 38.4 | <0.02 | <0.02 | <1 | 0.3 | 1.1 | <10 | <2 |
135 | <0.1 | <0.02 | 7.0 | 0.75 | <0.1 | 0.22 | 0.25 | 10.8 | 1.3 | <0.05 | 11.2 | 9.41 | 85.1 | 0.04 | 0.04 | <1 | 0.3 | 1.7 | <10 | <2 |
151 | <0.1 | <0.02 | 2.3 | 0.39 | <0.1 | 0.06 | 0.26 | 9.9 | 0.4 | <0.05 | 2.4 | 13.53 | 47.9 | 0.02 | 0.02 | <1 | 0.4 | 1.2 | <10 | <2 |
187 | <0.1 | <0.02 | 2.0 | 0.29 | <0.1 | 0.05 | 0.40 | 5.4 | 0.7 | <0.05 | 2.9 | 9.95 | 26.0 | <0.02 | <0.02 | <1 | 0.2 | 0.7 | <10 | <2 |
190 | <0.1 | <0.02 | 3.9 | 0.42 | <0.1 | 0.04 | 0.39 | 6.5 | 0.8 | <0.05 | 3.9 | 8.94 | 40.4 | 0.03 | 0.03 | <1 | 0.2 | 1.2 | <10 | <2 |
194 | <0.1 | <0.02 | 6.8 | 0.55 | <0.1 | 0.19 | 0.43 | 5.0 | 1.4 | <0.05 | 10.5 | 5.06 | 48.3 | 0.04 | 0.04 | <1 | 0.2 | 1.5 | <10 | <2 |
199 | <0.1 | <0.02 | 4.1 | 0.41 | <0.1 | 0.08 | 0.54 | 7.9 | 1.0 | <0.05 | 3.4 | 10.10 | 45.8 | <0.02 | <0.02 | <1 | 0.3 | 1.1 | <10 | <2 |
214 | <0.1 | <0.02 | 2.3 | 0.46 | <0.1 | 0.04 | 0.25 | 14.1 | 0.7 | <0.05 | 2.1 | 15.96 | 43.3 | <0.02 | <0.02 | <1 | 1.0 | 3.1 | <10 | <2 |
217a | <0.1 | 0.02 | 1.6 | 0.32 | <0.1 | <0.02 | 0.13 | 8.0 | 0.3 | <0.05 | 1.1 | 8.44 | 31.5 | <0.02 | <0.02 | <1 | 0.3 | 1.1 | <10 | <2 |
219 | <0.1 | <0.02 | 3.1 | 0.50 | <0.1 | 0.07 | 0.40 | 8.2 | 0.6 | <0.05 | 3.6 | 17.46 | 78.6 | 0.02 | 0.02 | <1 | 0.6 | 1.2 | <10 | <2 |
222 | <0.1 | <0.02 | 0.9 | 0.26 | <0.1 | <0.02 | 0.09 | 4.0 | 0.2 | <0.05 | 0.4 | 4.74 | 17.6 | <0.02 | <0.02 | <1 | 0.4 | 0.6 | <10 | <2 |
225 | <0.1 | <0.02 | 4.1 | 0.82 | <0.1 | 0.04 | 0.18 | 14.3 | 0.6 | <0.05 | 2.0 | 9.58 | 39.4 | <0.02 | <0.02 | <1 | 0.7 | 3.1 | <10 | <2 |
244 | <0.1 | 0.03 | 4.5 | 0.56 | <0.1 | 0.07 | 0.48 | 9.8 | 1.1 | <0.05 | 4.4 | 10.24 | 54.8 | <0.02 | <0.02 | <1 | 0.4 | 1.5 | <10 | <2 |
258 | <0.1 | <0.02 | 1.9 | 0.44 | <0.1 | 0.03 | 0.26 | 11.2 | 0.4 | <0.05 | 1.1 | 24.93 | 48.4 | <0.02 | <0.02 | <1 | 0.7 | 1.3 | <10 | <2 |
261 | <0.1 | <0.02 | 3.5 | 0.57 | <0.1 | 0.06 | 0.25 | 8.9 | 0.8 | <0.05 | 3.3 | 14.57 | 83.8 | <0.02 | <0.02 | <1 | 0.4 | 1.4 | <10 | <2 |
266 | <0.1 | <0.02 | 3.7 | 0.66 | <0.1 | 0.04 | 0.53 | 12.4 | 1.2 | <0.05 | 3.1 | 22.52 | 58.9 | <0.02 | <0.02 | <1 | 0.4 | 1.8 | <10 | <2 |
286 | <0.1 | <0.02 | 6.0 | 0.82 | <0.1 | 0.15 | 0.35 | 10.8 | 1.0 | <0.05 | 7.6 | 15.61 | 45.8 | 0.04 | 0.04 | <1 | 0.4 | 2.1 | <10 | <2 |
Geochemical result of the analysis soil samples.
The good correlation coefficient of Mn with Ni and Mg and the weak correlation especially between Mn and Cu are related to Mn-rich end member (Table 2). Similarly, good correlation coefficients between Fe and Ti and P coupled with the correlation between Co and Ti and the weak-to-low correlation between Ti and Ca, Ca and P, Ca and Co, and Ca and Fe are all related to Fe-rich end member. Likewise, the strong correlation between Al and K (r = 0.845) is related to aluminosilicate minerals, while the fairly good correlation coefficients between Mg and Mn and Cr and Ca are related to mantle-derived ultramafic materials.
Mo | Pb | Zn | Ni | Co | Mn | Fe | As | Th | Sr | Cd | Bi | V | Ca | P | Cr | Mg | Al | K | Sc | Cs | Nb | Rb | Sn | Zr | Ce | In | Be | Li | Pd | |
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
Mo | 1 | |||||||||||||||||||||||||||||
Pb | 0.610 | 1 | ||||||||||||||||||||||||||||
Zn | 0.499 | 0.332 | 1 | |||||||||||||||||||||||||||
Ni | 0.674 | 0.412 | 0.767 | 1 | ||||||||||||||||||||||||||
Co | 0.523 | 0.602 | 0.525 | 0.752 | 1 | |||||||||||||||||||||||||
Mn | 0.374 | 0.593 | 0.439 | 0.615 | 0.924 | 1 | ||||||||||||||||||||||||
Fe | 0.930 | 0.667 | 0.482 | 0.521 | 0.388 | 0.267 | 1 | |||||||||||||||||||||||
As | 0.827 | 0.506 | 0.693 | 0.605 | 0.352 | 0.240 | 0.854 | 1 | ||||||||||||||||||||||
Th | 0.634 | 0.564 | 0.091 | 0.090 | 0.043 | −0.050 | 0.755 | 0.537 | 1 | |||||||||||||||||||||
Sr | 0.031 | 0.284 | 0.758 | 0.310 | 0.256 | 0.317 | 0.100 | 0.341 | −0.106 | 1 | ||||||||||||||||||||
Cd | −0.094 | 0.427 | 0.202 | 0.052 | 0.311 | 0.407 | −0.013 | −0.034 | −0.095 | 0.469 | 1 | |||||||||||||||||||
Bi | 0.764 | 0.497 | 0.834 | 0.874 | 0.627 | 0.435 | 0.693 | 0.769 | 0.379 | 0.400 | 0.030 | 1 | ||||||||||||||||||
V | 0.911 | 0.666 | 0.244 | 0.455 | 0.378 | 0.248 | 0.926 | 0.718 | 0.739 | −0.127 | −0.113 | 0.581 | 1 | |||||||||||||||||
Ca | 0.037 | 0.222 | 0.768 | 0.277 | 0.198 | 0.238 | 0.115 | 0.378 | −0.074 | 0.987 | 0.425 | 0.403 | −0.132 | 1 | ||||||||||||||||
P | 0.502 | 0.576 | 0.676 | 0.373 | 0.354 | 0.321 | 0.603 | 0.664 | 0.382 | 0.653 | 0.398 | 0.558 | 0.454 | 0.659 | 1 | |||||||||||||||
Cr | 0.866 | 0.395 | 0.430 | 0.751 | 0.510 | 0.365 | 0.753 | 0.669 | 0.426 | −0.093 | −0.161 | 0.684 | 0.777 | −0.098 | 0.369 | 1 | ||||||||||||||
Mg | 0.516 | 0.287 | 0.856 | 0.950 | 0.671 | 0.537 | 0.381 | 0.557 | −0.066 | 0.502 | 0.086 | 0.840 | 0.258 | 0.480 | 0.380 | 0.598 | 1 | |||||||||||||
Al | 0.774 | 0.478 | 0.849 | 0.814 | 0.482 | 0.290 | 0.763 | 0.828 | 0.449 | 0.452 | 0.001 | 0.930 | 0.616 | 0.470 | 0.643 | 0.711 | 0.808 | 1 | ||||||||||||
K | 0.493 | 0.253 | 0.951 | 0.866 | 0.575 | 0.437 | 0.399 | 0.633 | −0.033 | 0.653 | 0.146 | 0.849 | 0.211 | 0.655 | 0.526 | 0.499 | 0.957 | 0.845 | 1 | |||||||||||
Sc | 0.808 | 0.534 | 0.270 | 0.487 | 0.272 | 0.120 | 0.856 | 0.605 | 0.799 | −0.164 | −0.186 | 0.592 | 0.864 | −0.164 | 0.348 | 0.766 | 0.309 | 0.680 | 0.242 | 1 | ||||||||||
Cs | 0.597 | 0.301 | 0.937 | 0.880 | 0.593 | 0.414 | 0.511 | 0.695 | 0.097 | 0.565 | 0.109 | 0.913 | 0.329 | 0.578 | 0.540 | 0.576 | 0.938 | 0.901 | 0.982 | 0.366 | 1 | |||||||||
Nb | 0.213 | 0.215 | 0.755 | 0.243 | 0.173 | 0.163 | 0.312 | 0.532 | 0.121 | 0.839 | 0.412 | 0.438 | 0.024 | 0.881 | 0.776 | 0.057 | 0.392 | 0.532 | 0.616 | −0.014 | 0.596 | 1 | ||||||||
Rb | 0.449 | 0.271 | 0.964 | 0.805 | 0.565 | 0.427 | 0.377 | 0.613 | −0.002 | 0.718 | 0.194 | 0.855 | 0.180 | 0.726 | 0.584 | 0.417 | 0.911 | 0.829 | 0.982 | 0.202 | 0.968 | 0.684 | 1 | |||||||
Sn | 0.676 | 0.505 | 0.324 | 0.264 | 0.189 | 0.090 | 0.810 | 0.643 | 0.860 | 0.055 | 0.046 | 0.496 | 0.719 | 0.090 | 0.602 | 0.554 | 0.134 | 0.587 | 0.194 | 0.798 | 0.310 | 0.362 | 0.221 | 1 | ||||||
Zr | 0.577 | 0.413 | 0.012 | −0.033 | −0.137 | −0.201 | 0.744 | 0.472 | 0.913 | −0.191 | −0.124 | 0.239 | 0.695 | −0.151 | 0.261 | 0.351 | −0.172 | 0.358 | −0.128 | 0.776 | 0.003 | 0.069 | −0.123 | 0.786 | 1 | |||||
Ce | 0.582 | 0.821 | 0.264 | 0.328 | 0.462 | 0.412 | 0.640 | 0.376 | 0.654 | 0.136 | 0.277 | 0.461 | 0.633 | 0.109 | 0.484 | 0.391 | 0.187 | 0.447 | 0.167 | 0.627 | 0.245 | 0.134 | 0.198 | 0.637 | 0.537 | 1 | ||||
In | 0.571 | 0.242 | 0.021 | 0.103 | −0.091 | −0.244 | 0.644 | 0.355 | 0.793 | −0.314 | −0.326 | 0.296 | 0.630 | −0.284 | 0.097 | 0.433 | −0.036 | 0.415 | −0.034 | 0.802 | 0.101 | −0.067 | −0.059 | 0.647 | 0.864 | 0.368 | 1 | |||
Be | 0.218 | 0.377 | 0.819 | 0.623 | 0.475 | 0.419 | 0.219 | 0.418 | −0.068 | 0.831 | 0.263 | 0.657 | 0.076 | 0.794 | 0.548 | 0.189 | 0.770 | 0.652 | 0.810 | 0.092 | 0.746 | 0.576 | 0.849 | 0.072 | −0.211 | 0.224 | −0.207 | 1 | ||
Li | 0.512 | 0.247 | 0.956 | 0.838 | 0.550 | 0.402 | 0.433 | 0.660 | 0.005 | 0.651 | 0.141 | 0.844 | 0.227 | 0.665 | 0.548 | 0.502 | 0.934 | 0.861 | 0.994 | 0.259 | 0.985 | 0.661 | 0.977 | 0.239 | −0.076 | 0.170 | 0.013 | 0.781 | 1 | |
Pd | 0.515 | 0.330 | 0.013 | 0.002 | −0.120 | −0.144 | 0.618 | 0.483 | 0.588 | −0.147 | −0.102 | 0.195 | 0.565 | −0.118 | 0.076 | 0.245 | −0.094 | 0.240 | −0.072 | 0.542 | 0.014 | −0.024 | −0.089 | 0.448 | 0.738 | 0.348 | 0.548 | −0.137 | −0.049 | 1 |
Result of correlation analysis of selected elements.
The result of the PCA shows a total of six factor groups (Table 3 and Figure 2). These are factors 1–6. Factor 1 with Mg, Ni, Cs, K, Te, Li, Ti, Rb, Bi, Al, Zn, Cu, Tl, U, Cr, Co, Na and Be accounts for a total of 43.59% before rotation and 31.86% after rotation. This is factor 2 with Zr, Hf, Th, Ga, In, Sc, Sn, Fe, V, Pd, Mo, Sb and As, and Ce accounts for 20.701% before rotation and 23.09% after rotation. Factor 3 has Se, Nb, Ca, Sr and P. This factor group accounts for 9.95% before rotation and 14.697% after rotation. Factor 4 with Ba, Pb, Y, Mn, La and Cd gave an account of 8.518% before rotation and 10.078% after rotation, while factor 5 with the following elements: Hg, Ag and Au account for 3.412% before rotation and 2.758% after rotation. Factor 6 does not have the highest loading of any element. Despite this, it still accounts for 2.658% before rotation and 3.106% after rotation.
Component | ||||||
---|---|---|---|---|---|---|
1 | 2 | 3 | 4 | 5 | 6 | |
Mg | 0.959 | |||||
Ni | 0.956 | |||||
Cs | 0.921 | 0.343 | ||||
K | 0.909 | 0.393 | ||||
Te | 0.900 | |||||
Li | 0.893 | 0.430 | ||||
Ti | 0.881 | |||||
Rb | 0.854 | 0.488 | ||||
Bi | 0.850 | 0.376 | ||||
Al | 0.812 | 0.481 | ||||
Zn | 0.795 | 0.563 | ||||
Cu | 0.770 | 0.354 | 0.319 | 0.315 | ||
Tl | 0.769 | 0.511 | ||||
U | 0.734 | 0.351 | 0.379 | |||
Cr | 0.711 | 0.476 | ||||
Co | 0.662 | 0.576 | 0.349 | |||
Na | 0.632 | 0.358 | 0.358 | −0.335 | ||
Be | 0.628 | 0.520 | 0.380 | |||
Zr | 0.969 | |||||
Hf | 0.948 | |||||
Th | 0.943 | |||||
Ga | 0.420 | 0.864 | ||||
In | 0.845 | |||||
Sc | 0.388 | 0.841 | ||||
Sn | 0.827 | |||||
Fe | 0.428 | 0.826 | ||||
V | 0.347 | 0.818 | ||||
Pd | 0.735 | |||||
Mo | 0.602 | 0.706 | ||||
Sb | −0.320 | 0.618 | 0.305 | 0.564 | ||
As | 0.584 | 0.608 | 0.313 | |||
Ce | 0.603 | 0.542 | ||||
Se | 0.942 | |||||
Nb | 0.307 | 0.914 | ||||
Ca | 0.311 | 0.903 | ||||
Sr | 0.318 | 0.862 | ||||
P | 0.350 | 0.367 | 0.629 | 0.361 | ||
Ba | 0.300 | 0.843 | ||||
Pb | 0.518 | 0.754 | ||||
Y | 0.737 | 0.569 | ||||
Mn | 0.483 | 0.663 | 0.443 | |||
La | 0.342 | 0.620 | 0.511 | |||
Cd | 0.455 | 0.521 | 0.381 | |||
Hg | 0.838 | |||||
Ag | −0.575 | |||||
Au | −0.500 |
Rotated component matrix.
3D component plot for soil factor analysis in rotated space.
Factor 1 of the principal component analysis of the soil was related to the weathering of the hydrothermal sulphide ore and silicate-rich banded iron formation [16, 17], while factor 2 was the product of weathered chert-rich magnetite and ores that are rich in terrigenous materials. The inclusion of elements, like Sn and Mo, indicates weathering of granitic rocks like pegmatite that had protore of some sulphide minerals [18]. The presence of Pd, Ce and Sb in this factor group attested to the presence of these minerals [16].
Factor 3 was related to the rocks and minerals such as phosphate REE-Nb deposits in an evaporite environment, while factor 4 was interpreted as the product of weathered manganese ore. Factor 5 was related to the weathered precious metals that were originally formed from hydrothermal sulphide ore [18]. Factor 6 had the second loading value of Mn, Sb and Co. This factor though not having the highest loading factor of any of the elements showed the weathering of Co-bearing manganese ore [19] and incompleteness or leakages in the system. These leakages typified by factor 6 were pronounced by the mobility of some of the elements. Factors 1–5 were strongly related to mineralization. The presence of the country rock in the factor groups as accounted for by the principal component analysis decreases from factor 1 to factor 5. Factor 6 does not have the highest loading of any element but had the second highest loading of Mn, Sb and Co. This factor group was interpreted to imply the presence of minor or protore of Co-bearing manganite and also accounts for very strong leakages in the system during weathering of the rocks and ores in the area.
The depressions in the isograde plots were interpreted to be the zones of negative anomaly, while the positive anomalous zones were the peaks in the plots. The brown-coloured area defines the regional threshold, while the pinkish sky blue-coloured zones on the plots were interpreted as the local aureole. Deep blue zones were interpreted as the anomalous regions. The values of these zones were estimated from the corresponding values in the colour scale that is beside each plot.
From the plots, Ag had three positive anomalies that are defined by long. 4.13°E and lat. 11.125°N, long. 4.0°E and lat. 11.075°N and long. 3.35°E and 11.1°N, while its negative anomalies were defined by long. 4.09°E and lat. 11.07°N, long 4.05°E and lat. 11.07°N and long. 4.075°E and long. 11.09°N. Its regional threshold was ≤55 ppm, while the local aureole and anomaly had 70 ppm and >90 ppm, respectively. The positive anomalies of Au were defined by long. 11.225°E and lat. 4.0°N, while its negative anomaly was defined by long. 4.05°E and lat. 11.1°N. Its regional aureole had ≤4ppb, while its local aureole is 5.5 ppb. Its anomalous area had a concentration value of ≥6.5 ppb. Ba had its positive anomaly on the spot defined by long. 3.975°E and lat. 11.13°N. Its regional threshold had a concentration value of ≤150 ppm, while its local threshold and anomalous values were 230 ppm and ≥240 ppm, respectively.
Al had its positive anomaly defined by long. 4.05°E and lat. 11.09°N, while the negative anomaly was defined by long. 3.92°E and lat. 11.09°N. Its regional aureole, local aureole and anomalous value were ≤1.2 ppm, 1.5 ppm and >1.6 ppm, respectively. As (Figure 3) had its positive anomalous zone defined by long. 4.05°E and lat. 11.1°N and long. 4.15°E and lat. 11.12°N. Its negative anomalies were defined by long. 4.075°E and lat. 11.075°N and long. 4.0°E and lat. 11.1°N. As had regional aureole, local aureole and anomaly with concentration values of ≤0.8 ppm, 1.0 ppm and ≥1.2 ppm, respectively.
3D isograde plot of As.
The positive anomalous zone of Be was defined by long. 4.06°E and lat. 11.12°N (Figure 4). Its negative anomaly was defined by long. 4.1°E and lat. 11.11°N. The concentration of Ba described as regional threshold is ≤0.8 ppm and its local and anomalous concentrations were 1.2 ppm and ≥1.3 ppm, respectively. The positive anomaly of Bi is on long. 4.04°E and lat. 11.075°N, while long. 3.93°E and lat. 11.1°N define the negative anomaly (Figure 5). The regional threshold, local threshold and anomaly values were ≤0.13 ppm, 0.18 ppm and ≥0.21 ppm, respectively. Ca has its positive anomaly defined by long. 4.04°E and lat. 11.075°N, while its negative anomaly is defined by long. 4.05°E and lat. 11.06°N. The regional threshold value of Ca is ≤0.45 ppm while its local aureole and anomalous values were 0.6 ppm and ≥0.65 ppm. Cd positive anomaly was on the spot defined by long. 4.075°E and lat. 11.1°N. Its regional threshold, local threshold and anomalous values were ≤0.013 ppm, 0.017 and ≥0.019 ppm, respectively.
3D isograde plot of Be.
3D isograde plot of Bi.
The positive anomaly of Co was defined by long. 4.04°E and lat. 11.05°N (Figure 6). Its negative anomaly was defined by long. 3.97°E and lat. 11.16°N, while its regional threshold, local aureole and anomalous values were ≤10 ppm, 14 ppm and ≥15 ppm, respectively. Cs has no negative anomaly but its positive anomalous point is defined by long. 4.04°E and lat. 11.06°N (Figure 7). Its regional threshold value was ≤2.8 ppm, while its local threshold and anomalous values were 4 ppm and ≤4.2 ppm, respectively. The positive anomaly of K was on the spot defined by long. 4.04°E and lat. 11.07°N. Its regional threshold value was ≤0.3 ppm, while its local aureole and anomaly had values 0.44 ppm and ≥0.48 ppm, respectively. Li had its positive anomaly defined by long. 4.04°E and lat. 11.07°N. Its regional threshold, local aureole and anomalous values were ≤8 ppm, 26 ppm and ≥30 ppm, respectively. Mg also had its positive anomaly defined by lat. 11.07°N but long. 4.035°E, while its negative anomaly was defined by long. 4.06°E and lat.11.025°N. Its regional threshold value, local aureole and anomaly had a concentration value of ≤0.012 ppm, 0.42 ppm and ≥0.48 ppm respectively. Mn had two positive anomalies that were defined by long. 3.36°E and lat. 11.12°N and long. 4.04°E and lat. 11.06°N (Figure 8). Its negative anomaly was defined by long. 4.07°E and lat. 11.05°E. Its regional threshold value, local aureole and anomalous values were ≤550 ppm, 800 ppm and ≥850 ppm, respectively.
3D isograde plot of Co.
3D isograde plot of Cs.
3D isograde plot of Mn.
The positive anomaly of Nb was on the spot defined by long. 4.04°E and lat.11.075°N (Figure 9). Its negative anomaly was defined by long. 4.05°E and lat. 11.075°N. Its regional threshold value was ≤0.6 ppm, while the local aureole was 2.2 ppm. Its anomaly had a value of ≥2.5 ppm. Ni had its positive anomaly on long. 4.03°E and lat. 11.075°N (Figure 10). Its regional threshold value and local and anomalous values were ≤6 ppm, 22 ppm and ≥25 ppm, respectively. P had its positive and negative anomalies defined by long. 4.04°E and lat. 11.1°N and long. 4.1°E and lat. 11.125°N, respectively. Its regional threshold, local aureole and anomalous values were ≤0.005 ppm, 0.017 ppm and ≥0.019 ppm, respectively. Rb has long. 4.05°E and lat. 11.1°N defining its positive anomaly. Its regional threshold, local aureole and anomalous values are ≤13 ppm, 47 ppm and ≥55 ppm, respectively. The positive anomaly of Sr was defined by long. 4.03°E and lat. 11.075°N, while its negative anomaly was defined by long. 4.07°E and lat. 11.05°N. Its regional threshold, local aureole and anomalous values were ≤12 ppm, 44 ppm and ≥48 ppm, respectively. Zn had its positive anomaly on the spot defined by long. 4.05°E and lat. 11.1°N (Figure 11). Its regional threshold, local aureole and anomalous values were ≤12 ppm, 42 ppm and ≥48 ppm, respectively. Ce had three positive anomalies defined by long. 3.97°E and lat. 11.15°N, long. 4.075°E and lat. 11.05°N and long. 4.16°E and lat. 11.1°N (Figure 12). Its regional threshold and local aureole had a concentration value of ≤55 ppm and 75 ppm, respectively, while the anomalous concentration is ≥80 ppm. Similarly, Cr had its positive anomaly defined by the same longitude and latitude that defined that of Co, but its negative anomaly was defined by long. 4.05°E and lat. 11.075°N (Figure 13). Its regional threshold value, local aureole and anomalous value were ≤28 ppm, 36 ppm and ≥40 ppm, respectively.
3D isograde plot of Nb.
3D isograde plot of Ni.
3D isograde plot of Zn.
3D isograde plot of Ce.
3D isograde plot of Cr.
Fe had its highest concentration value on the spot defined by long. 4.16°E and lat. 11.1°N (Figure 14). Its regional threshold value was ≤2.4%, while its local aureole and anomalous values were 3.2% and ≥3.4%, respectively. The positive anomalies of Ga and Hf were defined by the same longitude and latitude that defined the anomalous point of Fe. The regional threshold, local aureole and anomalous value of Ga are ≤6 ppm, 8 ppm and ≥8.5 ppm, respectively, but the regional threshold value, local aureole and anomalous value of Hf were ≤0.22 ppm, 0.3 ppm and ≥0.32 ppm, respectively.
3D isograde plot of Fe.
The positive anomaly of Hg was defined by long. 4.16°E and lat. 11.25°N, while its negative anomaly was defined by long. 4.1°E and lat. 11.1°N. Its regional threshold value was ≤22 ppm, while its local aureole and anomalous values were 26 ppm and ≥30 ppm, respectively. Like Fe, Ga and Hf, the positive anomaly of In was defined by long. 4.16°E and lat. 11.11°N (Figure 15). Its regional threshold value, local aureole and anomaly had values ≤0.03 ppm, 0.044 and ≥0.046 ppm, respectively. The positive anomaly of Mo was on the spot defined by long. 4.05°E and lat. 11.07°N (Figure 16). Its regional threshold had ≤0.25 ppm concentration, while its local aureole and anomalous value were 0.5 ppm and ≥0.9 ppm, respectively.
3D isograde plot of In.
3D isograde plot of Mo.
The positive anomaly of Pb is defined by long. 3.35°E and lat. 11.125°N. Its regional threshold, local threshold and anomalous values were ≤5 ppm, 17 ppm and ≥19 ppm, respectively. Pd anomaly was on the spot defined by long. 4.16°E and lat. 11.1°N (Figure 17). Its regional threshold value, local aureole and anomalous concentrations are ≤3 ppm, 12.5 ppm and ≥13.5 ppm. Sb, Sc and Sn (Figure 18) all have their positive anomalies defined by long. 4.16°E and lat. 11.1°N. The negative anomaly of Sc was defined by long. 3.95°E and lat. 11.1°N, while its regional threshold value, local aureole and anomalous values were ≤2 ppm, 6.5 ppm and ≥7.5 ppm, respectively. The regional threshold value, local aureole and anomalous values for Sb were ≤0.015 ppm, 0.06 ppm and ≥0.065 ppm. The negative anomaly of Sn was defined by long. 4.05°E and lat. 11.075°N. Its regional threshold value, local threshold and anomalous values were ≤0.4 ppm, 1.3 ppm and ≥1.5 ppm, respectively.
3D isograde plot of Pd.
3D isograde plot of Sn.
The anomalous value of Th is on the spot defined by long. 4.16°E and lat. 11.09°N (Figure 19). Its regional threshold value was ≤3 ppm, while its local aureole and anomalous values are 12 ppm and ≥13.5 ppm, respectively. Long. 4.05°E and lat. 11.05°N define Ti positive anomaly. Its regional threshold, local aureole and anomalous values were ≤0.025 ppm, 0.08 ppm and ≥0.095 ppm, respectively. Tl positive anomaly was defined by long. 4.04°E and lat. 11.1°N. Its regional threshold value, local aureole and anomalous value were ≤0.08 ppm, 0.28 ppm and ≥0.32 ppm, respectively. U had its positive and negative anomalies defined by long. 4.05°E and lat. 11.05°N and long. 4.1°E and lat. 11.1°N. Its regional threshold value, local aureole and anomaly were ≤0.6 ppm, 2.1 ppm and ≥2.4 ppm, respectively.
3D isograde plot of Th.
Long. 4.16°E and lat. 11.1°N defined the positive anomaly of V (Figure 20), while its regional threshold, local aureole and anomalous values were ≤18 ppm, 60 ppm and ≥70 ppm, respectively. Y had its positive and negative anomaly defined by long. 3.92°E and lat. 11.17°N and long. 4.03°E and lat. 11.075°N. Its regional threshold, local aureole and anomalous values are ≤6 ppm, 22 ppm and ≥24 ppm, respectively. Long. 4.16°E and lat. 11.11°N defined the Zr positive anomaly (Figure 21). Its regional threshold, local aureole and anomalous values were ≤5 ppm, 17 ppm and ≥19 ppm, respectively. La had its positive anomaly defined by long. 3.98°E and lat. 11.15°N. Its regional threshold, local aureole and anomalous values were ≤18 ppm, 26 ppm and ≥28 ppm, respectively. Na had its own positive anomalies defined by long. 3.96°E and lat. 11.12°N and long. 4.05°E and lat. 11.1°N, while its regional threshold value is ≤0.0008 ppm. Its local and anomalous values were 0.0026 ppm and ≥0.0028 ppm. Te had its positive anomaly defined by long. 4.06°E and lat. 11.05°N. Its regional threshold value, local aureole and anomalous value were ≤0.012 ppm, 0.044 ppm and ≥0.048 ppm, respectively.
3D isograde plot of V.
3D isograde plot of Zr.
Factor 1 of the soil factor analysis is predominated by the lithophile, chalcophile and siderophile elements. The distribution in this group is similar to the corresponding factor 1 in the ore factor analysis. In this factor group, most of the elements have mobilities which vary from low mobility to immobile [20]. Some of them, for example, Cu and Zn have varying mobilities between high to very low depending on the condition as against most of the elements that are immobile in the varying conditions. The association though related to weathered hydrothermal sulphide ore and sulphide-rich BIF is also aided by the mobility of the elements in fluctuating environmental conditions. The fluctuation in the condition is inferred from the inconsequential position occupied by the three types of elements that form the factor group. This scene is also repeated in factor 2 of the soil factor analysis. Most of the elements in this group are mainly transition metals. Their varying oxidation states coupled with the varying component of the materials that are coming together down the slope as the material is transported could account for the association in this group. At the beginning of this phase, the environmental condition favoured the lithophile element then followed by the condition that favoured the chalcophile. Midway into the phase, the condition became inconsistent before the condition that favoured the siderophile prevailed and capped by the chalcophile.
Factor 3 is typically of the lithophile elements with trapped single chalcophile element. The mobility of the chalcophile is similar to the mobility of the lithophile, thereby making it easy to be transported down the slope through the weathering path despite the differences in their chemical affinities and chemical properties. Factor 4 is also formed under relatively unstable environmental conditions that fluctuated between the condition that favoured the siderophile, chalcophile and lithophile elements. The conditions that favoured the lithophile existed over a relatively long period especially towards the end of the phase and thereafter changed to the condition that favoured the chalcophile elements and then capped by the condition favouring siderophile. Factor 5 with Hg, Ag and Au is related to the weathered precious metals that were originally formed from hydrothermal sulphide ore [16]. Factor 6 with no highest loading of any element but has Co, Sb and Mn with fair loading implies the presence of minute Co-bearing manganese ore in the area.
Ag has three positive anomalies. These are in the eastern and southwestern parts of the study area. The local aureoles are aligned in NW-SE and NE-SW towards the southern part of Kaoje and its environs. Closely associated with these aureoles are negative anomalies that trend parallel to the positive anomalies. Al has its anomaly at long. 4.05°E and lat. 11.09°N. There are other positive anomalies in the NW (long. 3.95°E and lat. 11.2°N) and at the eastern end (long. 3.92°E and lat. 11.2°N). The negative anomaly of Al is well-defined at the western part of the mapped area (long. 3.92°E, lat. 11.09°N). These anomalies trend in NW-SE. Another spot of negative anomaly is to the right of the positive anomaly that extends from the southern part of the area towards the central part. As has its positive anomaly in almost the same place with Al. Though there are three peaks described as anomaly having the highest values, two of these peaks are twinned towards the centre of the area, while the third one is at the eastern end of the study area. The negative anomaly that is closely associated with the twinned anomalies towards the centre is also similarly positioned like the negative anomaly in Al. At the western end of this twinned peaks are two of each positive and negative anomalies. While the positives trend in NE-SW, the negative anomalies trend perpendicular to them in NW-SE direction.
Au has relative different distribution patterns from Ag, Al and As. Its negative anomaly is positioned where the three elements (Ag, Al and As) have their positive anomalies. This relationship in the position of the negative anomaly of Au indicates its depletion in the minerals formed or path-found by the three elements. Other peaks of anomaly of Au are in the SE corner and eastern and western parts of the area. These peaks like the negative anomalies are aligned in almost east-west direction with the exception of the peak in the northern part. The three positive anomaly peaks in Ba trend essentially in NW-SE with its highest concentration point defined by lat. 11.13°N and long. 3.975°E. This point of highest concentration of Ba corresponds to local aureole of elements like As, Al, Ag and Au. There is no negative anomaly except sharp decrease to the background value within the area of study. These slopes flank the peaks and also separate the peaks from each other.
Like As, Be has its anomaly in the southern part extending towards the central part of the study area. There are positive anomalies that are similarly positioned in the western half of the area except that while the positive anomalies in this half trend in NE-SW for As, those in Be trend in NW-SE. In like manner, the negative anomalies in Be trend in NE-SW, but those in As trend in NW-SE. Be also has a twin peak of anomaly like As, but one of it is not well-defined. Their distribution pattern is not identical but has similar position of their anomalies. Bi has a distribution pattern that is closely similar to that of As in terms of their positive and negative anomalies. Its anomalous point is defined by lat. 11.075°N and long. 4.04°E. These peaks slope towards the north. There are few negative anomalies that are evenly distributed in the four quadrants of the area studied. Ca has a point of positive anomaly towards the centre of the area. This area is defined by long. 4.05°E and lat. 11.1°N. The negative anomaly is poorly defined in the NE and SE parts of Kaoje and its environs.
Cd has ridge of anomaly that trend in NW-SE. The other anomaly is almost perpendicular to the broad NW-SE trending anomaly. Ce has its aureole in the western and SE part essentially. The extreme NE and SW part are relatively depleted in Ce. The Ce anomaly defines an arc curving back at the southern part. Cr has its anomaly at lat. 4.05°E and long. 11.075°N. Its negative anomalies trend in almost E-W direction. It shares some point of anomaly with elements like As and Bi. With the exception of slightly elevated concentration at the western part of the area (lat. 3.965°E and long. 11.120°N) essentially, the distribution of Co is almost identical with that of Cr. They (Cr and Co) have their anomaly in the same spot, while the distribution pattern of Cs and K is identical and similar with that of Ca. Their anomaly point is defined by lat. 4.05°E and long. 11.06°E. This anomaly trends in N-S direction. The anomaly of Ca does not cover larger area; the anomaly of Cs, K, Li and Mg covers relatively larger area compared with that of Ca, Bi and Cr. Their distribution pattern is also identical sharing the same point of anomalous concentration. There are passive zones of depletion which fall generally under regional threshold. Fe has its highest concentration in the eastern part of the study area and an anomaly that is described as local aureole in the southern part of the study area. These two peaks of anomalies are also observed in the isograde plot of As. With little variations, its distribution pattern is closely related to the distribution pattern of Cr and As.
Ga and Hf have different distribution patterns, but their zones of anomaly are similarly positioned in the eastern part of the area. This part is similarly shared by Fe, As and Cr essentially. While the negative anomaly in Ga trends in NW-SE direction essentially, the negative anomaly in Hf is randomly oriented. Hg has its peaks trending in NW-SE and at the extreme NE. This aureole is closely associated with negative anomaly that trends also in NW-SE. The anomaly at the extreme NE end is similarly positioned like the one in Cd, while the aligned NW-SE aureoles are similar to those in Cd. In is enriched in the eastern half of the study area. There is an aureole in the NW part, while the remaining area is relatively depleted in In. this depleted zone coincide with the boundary between the sedimentary rocks and the basement rock exposures. It zones of highest concentration are in the extreme eastern part where Fe, Cd, etc. also have theirs. No negative anomaly is seen as the values of depression are relatively higher than the values in the extreme NW and SW part of the area.
The distribution pattern of La is similar to that of Hg. Its point of highest aureole is defined by lat. 11.15°N and long. 3.98°E. The aureoles in La form a poorly defined curve shape that trends mainly in NW-SE direction. The extreme SE part is also slightly enriched in La but not as high as the central to NW part of the study area; the depleted zones flank the aureoles. Mn plot is identical with that of Co; it shares the same spot of anomalous concentration with Co and one of Cr anomalous concentration area. The aureole trends in NW-SE and decreases from the SW half towards the extreme NE part. Though not identical, other elements like Cs, K, Li, Mg, Ca, Bi, Cr, etc. have their anomalous point in either point of the anomalous concentration of Mn and Co. Like Mn, Mo has its highest point of concentration in the southern part of the area. There is also a relatively high concentration in the eastern part where Fe has one of its aureoles. Other slightly enriched zone of Mo is the western part. The positive aureole of Mo trends almost perpendicular to the positive aureole of Mn. With the exception of two well-defined peaks of aureoles, other patterns of distribution of these elements are alike.
Na has two peaks of positive anomaly. These peaks are located in the western and central parts of the area study. The western aureole is related to the western aureole of Mn though the Mn aureole is not as broad as that of Na but is more steep sided than that of Na. The area study is slightly more enriched in Na except the extreme four corners of the area. Nb has similar distribution pattern with Ca. The study area is slightly more enriched in Nb relative to Ca, although they both have their positive aureole defined by the same latitude and longitude. The SW part of the area is more depleted in Nb, while the central part is enriched and trends perfectly in NW-SE direction. At the SE end of the positive anomaly, there is a zone of negative anomaly. This zone of Nb negative anomaly coincides with the zone of the most pronounced Au negative anomaly. Other elements with their positive anomaly or one of their positive anomalies defined by lat. 11.075°N and long. 4.05°E or closely related to that of Nb include Ca, Mg, K, Cs, Li, Be and As. Ni has its distribution pattern identical with that of Mg but the western part of the area is slightly depleted in Ni. The southern part of the study area is more enriched in Ni relative to the rest of the area. The aureole has >23 ppm concentration, while its local aureole has a concentration value of 21 ppm. Besides the fact that Li, Cs and K have primitive peaks closely associated with their aureoles, their distribution patterns and the distribution pattern of Ni are alike when their zones of anomaly are compared together. Ni also has its positive anomaly similarly positioned like the aureole of elements like Co, Bi and Al even though their distribution pattern is different. The positive aureole of Ni coincides with one of the positive aureoles in As while it is within the enriched zone of Be that trend NE-SW from the southern part. Au has its negative anomaly where Ni has its positive anomaly. This implies that Au depletion indicate the present of mineralization that is indicated by anomalous high concentration of Ni in this area.
Like Nb, P has its positive aureole defined by lat. 11.1°N and long. 4.05°E. The spot is shared or closely related to by the aureole of other elements like Li, Al, As, Be, Ca, Cs, K, etc. Its distribution pattern is similar to the distribution pattern of Mo, La, Hg, Ga, Fe and Ce essentially. Though with relatively lower concentration values and in rare cases slightly high concentration, the zones of positive enrichment and depletion of these elements are closely related. Cr has relatively high enrichment in all the areas where P also has its high enrichment but the zone of P depletion in the eastern part is not seen in Cr isograde plot. Pb has its highest concentration (>19 ppm) in the western part of the area defined by long. 3.35°E and lat. 11.125°N. Like P, La, Fe, Ce, etc., its distribution pattern forms a poorly defined U-shape. The zone of its highest positive anomaly has negative anomalies closely associated with it in the SW and NE parts. Other peaks of positive anomalies are in the southern and extreme eastern parts of the area. Its zone of highest concentration is related to the zone of highest concentration of elements like La, Ce, Cd and Ba. The peaks of positive anomaly in the western and southern parts relate very well with the two peaks of positive anomaly in Mn, while the peaks of positive anomaly of Pb in the southern and eastern parts are closely associated with the peaks of highest Fe concentration. Fe also has slightly elevated value in the western part where Pb has its highest concentration value. Other elements have their positive anomalies in one or more zone of Pb enrichment even though their distribution patterns are not the same.
Pd has its aureole in the western end of the study area. Its concentration decreases gradually towards the western end of the area. The zones of its highest concentration in the eastern part of the area coincide perfectly with one of the positive aureoles of Fe, Mo, In, Ga, Hf, etc. The Rb style of distribution is identical with the distribution pattern of Li, K and Cs. Its zone of highest concentration is wholly or partly shared besides the aforementioned elements by Al, As, Be, Bi, Ca, Cd, Co, Mg, Mn, Mo, Nb, Ni, P, etc. The peaks of its aureoles trend essentially in NE-SW direction. The negative anomalies are not well-defined but are closely associated with positive anomaly in the eastern part of the area.
Sb has its zones of highest concentration in the extreme eastern and western end of the area. Other zones of enrichment are closely associated with these two peaks defining a slightly different NE-SW trending direction. The distribution pattern is relatively unique, but its zone of highest concentration in the eastern end is related to the zones of highest concentration of Fe, Mo, In, Ga and Hf. The extreme NW and SW are the most depleted zones of Sb. Other areas have slightly elevated value relative to other elements.
With the exception of break in the ridge of positive anomaly of Sc in the western part of the area, the distribution pattern of Sc and Sn is identical. They both have a ridge of positive anomaly that rises in the NW going through the southern part and turning through the eastern part to end in the NE part of the area study. They have two peaks of positive aureoles. One of the aureoles is situated in the eastern part where elements like Fe, Mo, In, Ga and Hf have their or one of their positive anomalies. The second positive aureole of Sc is in the southern part of the area, while that of Sn shifts slightly to the SE part of the area. They have their negative anomalies trending essentially NW-SE in the western end and NE-SW in the eastern end. Sr has slight enrichment in the western part. These enrichments trend in NW-SE terminating in the central part. Its zone of highest concentration is in the centre. This centre where it has its highest concentration is defined by long. 4.05°E and lat. 11.075°N. Its zone of highest concentration is similarly shared by Rb, Al, As, Be, Bi, Ca, Cd, Co, Mg, Mn, Mo, Nb, Ni, P, etc. Its distribution pattern is identical with the distribution pattern of Ca.
The distribution pattern of Te is similar to the distribution pattern of Na. Its peak (positive anomaly) is in the central to SE part of the area. Its anomaly trends in NW-SE but generally decreases to the background value of ≤0.028 ppm. Th has its highest concentration in the eastern part. Other area with relatively high concentration of Th is in the SE and is closely associated with the zone of Th positive anomaly. The concentration of Th in the western half is also relatively high but not as high as the concentration in the eastern part. The western aureole trends in N-S direction with about three alternations in its concentration with about three alternations in its concentration. The extreme NW and SW corners of the area are relatively the most depleted zone for Th. The position of the positive anomaly of Th is the same with the position of positive anomaly of Fe, Sn, Sc, Sb, Pd, In, Hf and As. Mo and Ce has one of their positive anomaly in this eastern part, but the zone of highest concentration of Ag is just slightly off the zone of Th highest concentration to the west.
Ti, Tl and U have their positive anomalies defined by lat. 11.075°N and long. 4.04°E and lat. 11.08°N and long. 4.04°E and lat. 11.07°N and long. 4.04°E, respectively. Though with slight variation, these elements have their positive anomalies where elements like Sr, Rb, Ni, P, Nb, Li, K, Cs, Co, Cd, Ca, Bi, Be, As and Al have theirs or one of their positive anomalies. This zone is also though not exactly but similarly positioned like one of the Mn positive anomaly. Ti and Tl have their highest concentration within the central part of the area. Ti concentration is slightly high in the eastern and extreme NE part, but Tl has its own concentration decreasing gradually towards the extreme west, thereby making the western half slightly more enriched than the eastern half. Both Ti and Tl have sharp depression to the background value. These depressions are similarly oriented in poorly defined NWW-SEE in the western half of the area. Unlike Ti and Tl, U has its concentration in the central part which forms a ridge of positive anomaly extending from the central area to the NW of the area where it forms a twin peak. The peak to the east among these two peaks has slightly higher concentration than that in the western part. There are negative anomalies in the western half and eastern part of the area. The negative anomalies in the western half that are well-defined trend in NE-SW. The poorly defined negative anomaly trends with one of the well-defined in NW-SE. The U negative anomalies in the eastern half of the area trend mainly in NE-SW.
The distribution pattern of V is similar to the distribution pattern of Th, Sc, Sn, Pb, P, Mo, La, Hg, Ga, Fe, Cr and Ce. Its zone of highest concentration (>65 ppm) is in the extreme eastern part, while it is also enriched in the southern part. These two zones of highest concentration are similar to the zone of highest concentration of Fe, Sc and Mo. The enrichment in the western half is almost identical with that of Fe when the position of the zones of highest enrichment and depletion are compared. The central part of the area is the most depleted zone of V. Like some other elements, e.g. Hf, its distribution pattern has poorly defined U-shape. The zone of highest concentration of Y (>23 ppm) is in the NW part of the area. This area is flanked by negative anomaly in the SW and NE part. The zone of relative high concentration of the anomaly, usually ≥16 ppm, is restricted to the western half of the study area and trends in NW-SE direction. The extreme SW and SE corner is relatively depleted of Y (≤5 ppm), while other areas have elevated value that range between 5 and 16 ppm. The positive anomalous zone of Y is similarly enriched in Pb, La, Hg, Cd, Ce, Ba and Mn.
The distribution pattern of Zn is identical with the distribution pattern of Rb and almost identical with the distribution pattern of Li, K and Cs. Both Zn and Rb have two peaks at the crest of their anomalous zone in the central part of the study area. The peak in the northern part out of these two peaks is slightly more prominent than the one in the south. These two peaks are also present in the same position in the isograde plot of Tl despite the fact that its style of distribution is slightly different from that of Zn and Rb. Other similarities in the distribution pattern of Zn and Rb include the twin slightly enriched area in the NW part of the area and also the negative anomaly in their isograde plot. Other elements that have their positive anomaly where Zn has its own and with similar distribution pattern include Ti, Mg, Cs, etc. Cs and K have the two peaks, but their peak in the southern part is more prominent than the one in the northern part. The zone of Zn anomaly is shared by the anomaly of Al, As, Be, Bi, Ca, Cd, Co, Mn, Nb, P and Ni essentially. Zr highest concentration is ≥19 ppm. This concentration is in the eastern part of the area. With the exception of elevated value (≤9 ppm) in the NW part of the area, the enrichment of Zr is restricted to the eastern half of the area especially where Fe, Th and Pd have their highest concentration.
From integrated field observation, geochemical study, statistical analysis and isograde plottings, it was concluded that the area investigated is mineralized with goethite and manganite ores, while there are minor enrichments of tourmaline and silicate minerals like chalcedony. It was also concluded that the eastern and southern parts of the study area is mineralized with goethite, while the western and southern parts are mineralized with manganite. Furthermore, in exploring for iron-manganite mineralization in this area, manganite has as its pathfinder the following associations Zn + As + Be + Bi + Co + Nb + Ni + Cs ± P + Al + Ca + Cd + Rb + Li + K, while Zr + Th + Pd + Mo + V + Sn + Cr + Ce + In ± Sc + P + Pb associations are related to iron mineralization.
Thermal cracking is one of the biggest concerns regarding early-age concrete. Hydration of a large amount of cement results in higher peak temperatures as well as larger temperature differences between the concrete surface and the core. Such large temperature differentials can cause substantial tensile stresses that might increase the likelihood of early-age cracking in the concrete [1].
In order to control the temperature in early-age concrete structures, thus mitigating the risk of thermal cracking, temperature and stress analyses should be performed beforehand. Different methods have been used for predicting the temperatures and thermal stresses concrete structures at an early age. Among them, the Schmidt’s method is a simple approach but has been widely used for computing the temperatures for single nodes in the concrete [1]. The finite difference (FD) method was also employed in spreadsheet programs [2, 3] or in computer programs [4, 5] for calculating temperature–time histories in concrete elements. A two-dimensional model for thermal analysis based on the finite volume method (FVM) was introduced by Yikici and Chen [6]. The finite element (FE) method has been commonly utilized for both thermal and stress analyses of early-age concrete structures [7, 8, 9, 10, 11, 12, 13].
This chapter presents a two-dimensional FD scheme for thermal analysis of a concrete element. An FE analysis was then used to calculate the temperature-induced stresses in the concrete. The analysis results were compared with measurements of actual concrete elements. The combined approach can be a simple and useful tool for analyzing temperatures and thermal stresses in early-age concrete elements.
The heat evolution and temperature in a concrete element can be known by solving the governing differential equation as described in Eq. (1):
where
The finite difference formulation for any node in the system can be written as [14]:
where
During the actual construction stage of concrete structures, the concrete is usually covered by formwork and/or insulation materials. Heat generated from cement hydration is conducted through the formwork and/or insulation layer before being dissipated to the surroundings by surface convection (Figure 1).
FD mesh for heat conduction of concrete covered with insulation layer.
Considering a formwork/insulation layer covering the concrete, and assuming a unit square mesh for the concrete (Δ
FE plane triangular element.
where
Using Eq. (2), the FD equations for each of the four outer corner nodes of the insulation can be derived. For instance, the quarter size volume element of the insulation layer (
where
The insulation volume element at the surface node (2,N) adjacent to the top left outer corner node is subjected to convection at the top and conduction at the left, right, and bottom surfaces. An energy balance on this element gives:
where
Similarly, the insulation volume element of half size at a surface node is subjected to convection at the top and conduction at the left, right, and bottom surfaces. An energy balance on this element gives:
where
The “mixed” volume element at the concrete’s corner node (2,N-1) is subjected to conduction at the four sides. An energy balance on this element gives:
where
The “mixed” volume element at a concrete’s top surface node is also subjected to conduction at the four sides. An energy balance on this element gives:
where
It is noted that the stability criterion of the explicit method requires all primary coefficients to be positive or zero for all nodes:
The maximum time step used to solve the problem must satisfy Eq. (15) above.
If an insulation layer is not used, the new corner temperature
and the next time step temperature of a top surface node will be simplified to:
The maximum time step in this case is as follows:
The rate of heat liberated from cement hydration depends on the temperature of the concrete element itself. The heat rate can be experimentally determined using isothermal [10, 15], adiabatic [16, 17], or semi-adiabatic calorimetry [4]. The experimental adiabatic temperature rise (ATR) can be converted into a maturity-based heat rate as presented by Ballim and Graham [18], in which the total heat (
where
The “maturity heat rate” (
where
where
The activation energy (
where pFA = % fly ash in the cementing blend; pFA-CaO = % CaO in fly ash; pslag = % slag in the cementing blend; pSF = percentage of silica fume in the cementitious materials; Blaine = cement fineness (m2/kg); pi = percentage of
The actual heat rate, which will be used in a numerical model, can be reconstructed from the maturity heat rate using the following equation:
The maturity-based heat rate curve
There are several models to mathematically characterize the heat generation from the cement hydration. The 3-parameter exponential degree of hydration model show in Eq. (25) [21] has been widely used for predicting temperature development in concrete since it includes the temperature effect through the equivalent age:
where
The total cumulative heat
where
The hydration parameters (
Since a common concrete structure has one dimension larger than the other two, the middle cross section should be analyzed; hence, a FE plane strain problem is selected for the stress computation. A triangular element is chosen with nodes
where
in which
The stress vector in the element can be calculated as:
where
and the thermal strain is derived as [22]:
in which
where
The nodal forces due to thermal strain is computed as follows:
in which
Computational Procedure
FD thermal analysis:
Define geometry of the structure (including the nodal grid), initial material properties, initial temperature and boundary conditions, and time interval.
Compute the nodal degree of hydration and the rate of heat evolution.
Compute the new temperature at each node.
Iterate (2) & (3) and record the temperatures.
FE stress analysis:
Divide the nodal grid into triangular elements (the vertices coincide with the FD grid nodes).
At
Let
Compute element stiffness matrix, global stiffness matrix, and equivalent nodal forces; solve for nodal displacements and element stresses.
Let
Let
A bridge pier footing constructed in Orlando, Florida was monitored for temperature development within 7 days after casting (Figure 3). The concrete footing had dimensions of 6.71-m × 3.05-m × 1.75-m and was insulated with 25.4-mm thick polystyrene foam boards at its bottom, top, and sides during 7 days.
Bridge footing for monitoring in Orlando, Florida.
The cementitious materials of Mix #1 was experimentally measured for the heat of hydration using an isothermal calorimeter. The hydration parameters and calculated activation energy (
Mix | τ (h) | β | αu | Qc (J/m3) | Ea (J/mol) |
---|---|---|---|---|---|
#1 | 16.73 | 0.8764 | 8.314 | 1.26 × 108 | 35,451 |
#2 | 14.0 | 0.94 | 0.703 | 1.67 × 108 | 41,800 |
Hydration parameters and activation energy.
The concrete had a density of 2238 kg/m3, specific heat of 1045 J/kg-K, and thermal conductivity of 1.87 W/m-K. The footing was insulated with Styrofoam that has density, thermal conductivity, and specific heat of 16 kg/m3, 0.04 W/m-K, and 1200 J/kg-K, respectively [14]. The boundary conditions consist of the initial temperature and the external ambient temperature over time. The air convection coefficient at the insulation surfaces was assumed to be 13.9 W/m2-K [5, 23].
Two temperature sensors were installed at the center and at the center top surface of the footing to record temperatures within 7 days after placement. The measured temperatures at the center and top, and the ambient temperature are shown in Figure 4. A peak measured temperature of 74°C occurred in the middle 42 hours after concrete casting. Figure 5 shows the temperature distribution in the footing at 40 h calculated by the FD model. The predicted FD temperatures at the center and the top of the footing are also plotted in Figure 4. It is clear that the temperature histories computed using the FD model show very close agreement with those collected in the field.
Predicted and measured temperature profiles in the footing.
FD temperature contour in the footing at 40 h (°C).
A bridge concrete cap beam (pier cap) was analyzed for temperatures and thermal stresses due to the heat of cement hydration. The cross section of the pier cap was 1.6-m by 2.1-m. The concrete used in the cap beam is Mix #2 with the hydration parameters and activation energy listed in Table 1. The concrete coefficient of thermal expansion (CTE) of 8.5 × 10−6/°C, density of 2287 kg/m3, the specific heat of 1028 J/kg-K, and thermal conductivity of 1.87 W/m-K were assumed in the analysis.
Figure 6 shows the calculated temperature profiles at the core, corner and side of the section. The center temperature peaked at 70.7°C approximately 28 hours after casting. The temperature contours are also depicted in Figure 7.
Temperature profiles at different points in the cap beam.
Temperature distribution of the section at 30 h.
The thermal analysis was followed by a stress calculation using the FE model with the element mesh shown in Figure 8a. The 1st principal stress and stress component
FE mesh and stress distributions (MPa) in pier cap at 21 h.
The calculated stresses over time at different locations of the pier cap are plotted in Figure 9. Clearly, the maximum stress is
Calculated stresses in the pier cap.
To assess the model’s accuracy, the computed stress-time histories are compared with those obtained from the 3-D ABAQUS FE model developed by Lin and Chen [12]. It is worth noting that the ABAQUS model was validated using measurements on 2 concrete blocks. Figure 9b shows that the 2-D FE results reasonably match with those of the 3-D ABAQUS model.
The 3-D ABAQUS results reveal that the maximum stress is the component
In this study, FD and FE formulations were created for solving the transient heat transfer equation and thermal stresses in a concrete element. The results of this study show that the approach that combines the FD and FE methods can be a useful and effective tool for predicting temperature evolution and thermally induced stresses in early-age concrete members with simple geometries. The FD model can analyze thermal behavior of a concrete placement covered with formwork or an insulation layer, thus it can help engineers/contractors control concrete temperature during construction.
This work is financially supported by the Ministry of Transport of Vietnam. Special thanks are given to Prof. H. L. Chen and Mr. G. Leon at West Virginia University (WVU) for their contributions to this study.
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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. 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DL is implemented by deep neural network (DNN) which has multi-hidden layers. DNN is developed from traditional artificial neural network (ANN). However, in the training process of DL, it has certain inefficiency due to very long training time required. Meta-heuristic aims to find good or near-optimal solutions at a reasonable computational cost. In this article, meta-heuristic algorithms are reviewed, such as genetic algorithm (GA) and particle swarm optimization (PSO), for traditional neural network’s training and parameter optimization. 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It is easy to understand and implement. The existing studies show that it is prone to premature convergence and suggest the relaxation of having constant parameters. To boost the performance of the algorithm, different modifications are done by several researchers. In this chapter, we will review these modifications done on the standard firefly algorithm based on parameter modification, modified search strategy and change the solution space to make the search easy using different probability distributions. The modifications are done for continuous as well as non-continuous problems. Different studies including hybridization of firefly algorithm with other algorithms, extended firefly algorithm for multiobjective as well as multilevel optimization problems, for dynamic problems, constraint handling and convergence study will also be briefly reviewed. A simulation-based comparison will also be provided to analyse the performance of the standard as well as the modified versions of the algorithm.",book:{id:"5165",slug:"optimization-algorithms-methods-and-applications",title:"Optimization Algorithms",fullTitle:"Optimization Algorithms - Methods and Applications"},signatures:"Waqar A. Khan, Nawaf N. Hamadneh, Surafel L. Tilahun and Jean\nM. T. Ngnotchouye",authors:[{id:"180330",title:"Dr.",name:"Surafel",middleName:null,surname:"Tilahun",slug:"surafel-tilahun",fullName:"Surafel Tilahun"},{id:"180784",title:"Dr.",name:"Waqar Ahmed",middleName:null,surname:"Khan",slug:"waqar-ahmed-khan",fullName:"Waqar Ahmed Khan"},{id:"185148",title:"Dr.",name:"Nawaf",middleName:null,surname:"Hamadneh",slug:"nawaf-hamadneh",fullName:"Nawaf Hamadneh"},{id:"185149",title:"Dr.",name:"Jean M. T.",middleName:null,surname:"Ngnotchouye",slug:"jean-m.-t.-ngnotchouye",fullName:"Jean M. T. 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While quite a major portion of the techniques is only useful for academic purposes, there are some which are important in the solution of real problems arising from science and engineering. In this chapter, only very limited techniques for solving ordinary differential and partial differential equations are discussed, as it is impossible to cover all the available techniques even in a book form. The readers are then suggested to pursue further studies on this issue if necessary. After that, the readers are introduced to two major numerical methods commonly used by the engineers for the solution of real engineering problems.",book:{id:"5513",slug:"dynamical-systems-analytical-and-computational-techniques",title:"Dynamical Systems",fullTitle:"Dynamical Systems - Analytical and Computational Techniques"},signatures:"Cheng Yung Ming",authors:[{id:"191017",title:"Dr.",name:"Cheng",middleName:null,surname:"Y.M.",slug:"cheng-y.m.",fullName:"Cheng Y.M."}]},{id:"56538",title:"Stochastic Resonance and Related Topics",slug:"stochastic-resonance-and-related-topics",totalDownloads:1718,totalCrossrefCites:1,totalDimensionsCites:1,abstract:"The stochastic resonance (SR) is the phenomenon which can emerge in nonlinear dynamic systems. In general, it is related with a bistable nonlinear system of Duffing type under additive excitation combining deterministic periodic force and Gaussian white noise. It manifests as a stable quasiperiodic interwell hopping between both stable states with a small random perturbation. Classical definition and basic features of SR are regarded. The most important methods of investigation outlined are: analytical, semi-analytical, and numerical procedures of governing physical systems or relevant Fokker-Planck equation. Stochastic simulation is mentioned and experimental way of results verification is recommended. Some areas in Engineering Dynamics related with SR are presented together with a particular demonstration observed in the aeroelastic stability. Interaction of stationary and quasiperiodic parts of the response is discussed. Some nonconventional definitions are outlined concerning alternative operators and driving processes are highlighted. The chapter shows a large potential of specific basic, applied and industrial research in SR. This strategy enables to formulate new ideas for both development of nonconventional measures for vibration damping and employment of SR in branches, where it represents an operating mode of the system itself. Weaknesses and empty areas where the research effort of SR should be oriented are indicated.",book:{id:"6128",slug:"resonance",title:"Resonance",fullTitle:"Resonance"},signatures:"Jiří Náprstek and Cyril Fischer",authors:[{id:"207472",title:"Dr.",name:"Jiri",middleName:null,surname:"Naprstek",slug:"jiri-naprstek",fullName:"Jiri Naprstek"},{id:"213311",title:"Dr.",name:"Cyril",middleName:null,surname:"Fischer",slug:"cyril-fischer",fullName:"Cyril Fischer"}]},{id:"74032",title:"Wavelets for EEG Analysis",slug:"wavelets-for-eeg-analysis",totalDownloads:1263,totalCrossrefCites:3,totalDimensionsCites:3,abstract:"This chapter introduces the applications of wavelet for Electroencephalogram (EEG) signal analysis. First, the overview of EEG signal is discussed to the recording of raw EEG and widely used frequency bands in EEG studies. The chapter then progresses to discuss the common artefacts that contaminate EEG signal while recording. With a short overview of wavelet analysis techniques, namely; Continues Wavelet Transform (CWT), Discrete Wavelet Transform (DWT), and Wavelet Packet Decomposition (WPD), the chapter demonstrates the richness of CWT over conventional time-frequency analysis technique e.g. Short-Time Fourier Transform. Lastly, artefact removal algorithms based on Independent Component Analysis (ICA) and wavelet are discussed and a comparative analysis is demonstrated. The techniques covered in this chapter show that wavelet analysis is well-suited for EEG signals for describing time-localised event. Due to similar nature, wavelet analysis is also suitable for other biomedical signals such as Electrocardiogram and Electromyogram.",book:{id:"10065",slug:"wavelet-theory",title:"Wavelet Theory",fullTitle:"Wavelet Theory"},signatures:"Nikesh Bajaj",authors:[{id:"326400",title:"Dr.",name:"Nikesh",middleName:null,surname:"Bajaj",slug:"nikesh-bajaj",fullName:"Nikesh Bajaj"}]},{id:"70067",title:"Analytic Prognostic in the Linear Damage Case Applied to Buried Petrochemical Pipelines and the Complex Probability Paradigm",slug:"analytic-prognostic-in-the-linear-damage-case-applied-to-buried-petrochemical-pipelines-and-the-comp",totalDownloads:2873,totalCrossrefCites:3,totalDimensionsCites:3,abstract:"In 1933, Andrey Nikolaevich Kolmogorov established the system of five axioms that define the concept of mathematical probability. This system can be developed to include the set of imaginary numbers by adding a supplementary three original axioms. Therefore, any experiment can be performed in the set \n\nC\n\n of complex probabilities which is the summation of the set \n\nR\n\n of real probabilities and the set \n\nM\n\n of imaginary probabilities. The purpose here is to include additional imaginary dimensions to the experiment taking place in the “real” laboratory in \n\nR\n\n and hence to evaluate all the probabilities. Consequently, the probability in the entire set \n\nC\n=\nR\n+\nM\n\n is permanently equal to one no matter what the stochastic distribution of the input random variable in \n\nR\n\n is; therefore the outcome of the probabilistic experiment in \n\nC\n\n can be determined perfectly. This is due to the fact that the probability in \n\nC\n\n is calculated after subtracting from the degree of our knowledge the chaotic factor of the random experiment. Consequently, the purpose in this chapter is to join my complex probability paradigm to the analytic prognostic of buried petrochemical pipelines in the case of linear damage accumulation. Accordingly, after the calculation of the novel prognostic model parameters, we will be able to evaluate the degree of knowledge, the magnitude of the chaotic factor, the complex probability, the probabilities of the system failure and survival, and the probability of the remaining useful lifetime; after that a pressure time t has been applied to the pipeline, which are all functions of the system degradation subject to random and stochastic influences.",book:{id:"7751",slug:"fault-detection-diagnosis-and-prognosis",title:"Fault Detection, Diagnosis and Prognosis",fullTitle:"Fault Detection, Diagnosis and Prognosis"},signatures:"Abdo Abou Jaoude",authors:[{id:"248271",title:"Dr.",name:"Abdo",middleName:null,surname:"Abou Jaoudé",slug:"abdo-abou-jaoude",fullName:"Abdo Abou Jaoudé"}]}],onlineFirstChaptersFilter:{topicId:"163",limit:6,offset:0},onlineFirstChaptersCollection:[],onlineFirstChaptersTotal:0},preDownload:{success:null,errors:{}},subscriptionForm:{success:null,errors:{}},aboutIntechopen:{},privacyPolicy:{},peerReviewing:{},howOpenAccessPublishingWithIntechopenWorks:{},sponsorshipBooks:{sponsorshipBooks:[],offset:8,limit:8,total:0},allSeries:{pteSeriesList:[{id:"14",title:"Artificial Intelligence",numberOfPublishedBooks:9,numberOfPublishedChapters:90,numberOfOpenTopics:6,numberOfUpcomingTopics:0,issn:"2633-1403",doi:"10.5772/intechopen.79920",isOpenForSubmission:!0},{id:"7",title:"Biomedical Engineering",numberOfPublishedBooks:12,numberOfPublishedChapters:107,numberOfOpenTopics:3,numberOfUpcomingTopics:0,issn:"2631-5343",doi:"10.5772/intechopen.71985",isOpenForSubmission:!0}],lsSeriesList:[{id:"11",title:"Biochemistry",numberOfPublishedBooks:33,numberOfPublishedChapters:330,numberOfOpenTopics:4,numberOfUpcomingTopics:0,issn:"2632-0983",doi:"10.5772/intechopen.72877",isOpenForSubmission:!0},{id:"25",title:"Environmental Sciences",numberOfPublishedBooks:1,numberOfPublishedChapters:19,numberOfOpenTopics:4,numberOfUpcomingTopics:0,issn:"2754-6713",doi:"10.5772/intechopen.100362",isOpenForSubmission:!0},{id:"10",title:"Physiology",numberOfPublishedBooks:14,numberOfPublishedChapters:145,numberOfOpenTopics:4,numberOfUpcomingTopics:0,issn:"2631-8261",doi:"10.5772/intechopen.72796",isOpenForSubmission:!0}],hsSeriesList:[{id:"3",title:"Dentistry",numberOfPublishedBooks:9,numberOfPublishedChapters:140,numberOfOpenTopics:2,numberOfUpcomingTopics:0,issn:"2631-6218",doi:"10.5772/intechopen.71199",isOpenForSubmission:!0},{id:"6",title:"Infectious Diseases",numberOfPublishedBooks:13,numberOfPublishedChapters:123,numberOfOpenTopics:4,numberOfUpcomingTopics:0,issn:"2631-6188",doi:"10.5772/intechopen.71852",isOpenForSubmission:!0},{id:"13",title:"Veterinary Medicine and Science",numberOfPublishedBooks:11,numberOfPublishedChapters:112,numberOfOpenTopics:3,numberOfUpcomingTopics:0,issn:"2632-0517",doi:"10.5772/intechopen.73681",isOpenForSubmission:!0}],sshSeriesList:[{id:"22",title:"Business, Management and Economics",numberOfPublishedBooks:1,numberOfPublishedChapters:22,numberOfOpenTopics:3,numberOfUpcomingTopics:0,issn:"2753-894X",doi:"10.5772/intechopen.100359",isOpenForSubmission:!0},{id:"23",title:"Education and Human Development",numberOfPublishedBooks:0,numberOfPublishedChapters:11,numberOfOpenTopics:1,numberOfUpcomingTopics:1,issn:null,doi:"10.5772/intechopen.100360",isOpenForSubmission:!0},{id:"24",title:"Sustainable Development",numberOfPublishedBooks:1,numberOfPublishedChapters:19,numberOfOpenTopics:5,numberOfUpcomingTopics:0,issn:"2753-6580",doi:"10.5772/intechopen.100361",isOpenForSubmission:!0}],testimonialsList:[{id:"6",text:"It is great to work with the IntechOpen to produce a worthwhile collection of research that also becomes a great educational resource and guide for future research endeavors.",author:{id:"259298",name:"Edward",surname:"Narayan",institutionString:null,profilePictureURL:"https://mts.intechopen.com/storage/users/259298/images/system/259298.jpeg",slug:"edward-narayan",institution:{id:"3",name:"University of Queensland",country:{id:null,name:"Australia"}}}},{id:"13",text:"The collaboration with and support of the technical staff of IntechOpen is fantastic. The whole process of submitting an article and editing of the submitted article goes extremely smooth and fast, the number of reads and downloads of chapters is high, and the contributions are also frequently cited.",author:{id:"55578",name:"Antonio",surname:"Jurado-Navas",institutionString:null,profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bRisIQAS/Profile_Picture_1626166543950",slug:"antonio-jurado-navas",institution:{id:"720",name:"University of Malaga",country:{id:null,name:"Spain"}}}}]},series:{item:{id:"6",title:"Infectious Diseases",doi:"10.5772/intechopen.71852",issn:"2631-6188",scope:"This series will provide a comprehensive overview of recent research trends in various Infectious Diseases (as per the most recent Baltimore classification). Topics will include general overviews of infections, immunopathology, diagnosis, treatment, epidemiology, etiology, and current clinical recommendations for managing infectious diseases. Ongoing issues, recent advances, and future diagnostic approaches and therapeutic strategies will also be discussed. This book series will focus on various aspects and properties of infectious diseases whose deep understanding is essential for safeguarding the human race from losing resources and economies due to pathogens.",coverUrl:"https://cdn.intechopen.com/series/covers/6.jpg",latestPublicationDate:"August 12th, 2022",hasOnlineFirst:!0,numberOfPublishedBooks:13,editor:{id:"131400",title:"Prof.",name:"Alfonso J.",middleName:null,surname:"Rodriguez-Morales",slug:"alfonso-j.-rodriguez-morales",fullName:"Alfonso J. Rodriguez-Morales",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). He is the president of the Travel Medicine Committee of the Pan-American Infectious Diseases Association (API), as well as the president of the Colombian Association of Infectious Diseases (ACIN). He is a member of the Committee on Tropical Medicine, Zoonoses, and Travel Medicine of ACIN. He is a vice-president of the Latin American Society for Travel Medicine (SLAMVI) and a Member of the Council of the International Society for Infectious Diseases (ISID). Since 2014, he has been recognized as a Senior Researcher, at the Ministry of Science of Colombia. He is a professor at the Faculty of Medicine of the Fundacion Universitaria Autonoma de las Americas, in Pereira, Risaralda, Colombia. He is an External Professor, Master in Research on Tropical Medicine and International Health, Universitat de Barcelona, Spain. He is also a professor at the Master in Clinical Epidemiology and Biostatistics, Universidad Científica del Sur, Lima, Peru. In 2021 he has been awarded the “Raul Isturiz Award” Medal of the API. Also, in 2021, he was awarded with the “Jose Felix Patiño” Asclepius Staff Medal of the Colombian Medical College, due to his scientific contributions to COVID-19 during the pandemic. He is currently the Editor in Chief of the journal Travel Medicine and Infectious Diseases. His Scopus H index is 47 (Google Scholar H index, 68).",institutionString:"Institución Universitaria Visión de las Américas, Colombia",institution:null},editorTwo:null,editorThree:null},subseries:{paginationCount:4,paginationItems:[{id:"14",title:"Cell and Molecular Biology",coverUrl:"https://cdn.intechopen.com/series_topics/covers/14.jpg",isOpenForSubmission:!0,annualVolume:11410,editor:{id:"165627",title:"Dr.",name:"Rosa María",middleName:null,surname:"Martínez-Espinosa",slug:"rosa-maria-martinez-espinosa",fullName:"Rosa María Martínez-Espinosa",profilePictureURL:"https://mts.intechopen.com/storage/users/165627/images/system/165627.jpeg",biography:"Dr. Rosa María Martínez-Espinosa has been a Spanish Full Professor since 2020 (Biochemistry and Molecular Biology) and is currently Vice-President of International Relations and Cooperation development and leader of the research group 'Applied Biochemistry” (University of Alicante, Spain). Other positions she has held at the university include Vice-Dean of Master Programs, Vice-Dean of the Degree in Biology and Vice-Dean for Mobility and Enterprise and Engagement at the Faculty of Science (University of Alicante). She received her Bachelor in Biology in 1998 (University of Alicante) and her PhD in 2003 (Biochemistry, University of Alicante). She undertook post-doctoral research at the University of East Anglia (Norwich, U.K. 2004-2005; 2007-2008).\nHer multidisciplinary research focuses on investigating archaea and their potential applications in biotechnology. She has an H-index of 21. She has authored one patent and has published more than 70 indexed papers and around 60 book chapters.\nShe has contributed to more than 150 national and international meetings during the last 15 years. Her research interests include archaea metabolism, enzymes purification and characterization, gene regulation, carotenoids and bioplastics production, antioxidant\ncompounds, waste water treatments, and brines bioremediation.\nRosa María’s other roles include editorial board member for several journals related\nto biochemistry, reviewer for more than 60 journals (biochemistry, molecular biology, biotechnology, chemistry and microbiology) and president of several organizing committees in international meetings related to the N-cycle or respiratory processes.",institutionString:null,institution:{name:"University of Alicante",institutionURL:null,country:{name:"Spain"}}},editorTwo:null,editorThree:null},{id:"15",title:"Chemical Biology",coverUrl:"https://cdn.intechopen.com/series_topics/covers/15.jpg",isOpenForSubmission:!0,annualVolume:11411,editor:{id:"441442",title:"Dr.",name:"Şükrü",middleName:null,surname:"Beydemir",slug:"sukru-beydemir",fullName:"Şükrü Beydemir",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0033Y00003GsUoIQAV/Profile_Picture_1634557147521",biography:"Dr. Şükrü Beydemir obtained a BSc in Chemistry in 1995 from Yüzüncü Yıl University, MSc in Biochemistry in 1998, and PhD in Biochemistry in 2002 from Atatürk University, Turkey. He performed post-doctoral studies at Max-Planck Institute, Germany, and University of Florence, Italy in addition to making several scientific visits abroad. He currently works as a Full Professor of Biochemistry in the Faculty of Pharmacy, Anadolu University, Turkey. Dr. Beydemir has published over a hundred scientific papers spanning protein biochemistry, enzymology and medicinal chemistry, reviews, book chapters and presented several conferences to scientists worldwide. He has received numerous publication awards from various international scientific councils. He serves in the Editorial Board of several international journals. Dr. Beydemir is also Rector of Bilecik Şeyh Edebali University, Turkey.",institutionString:null,institution:{name:"Anadolu University",institutionURL:null,country:{name:"Turkey"}}},editorTwo:{id:"13652",title:"Prof.",name:"Deniz",middleName:null,surname:"Ekinci",slug:"deniz-ekinci",fullName:"Deniz Ekinci",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002aYLT1QAO/Profile_Picture_1634557223079",biography:"Dr. Deniz Ekinci obtained a BSc in Chemistry in 2004, MSc in Biochemistry in 2006, and PhD in Biochemistry in 2009 from Atatürk University, Turkey. He studied at Stetson University, USA, in 2007-2008 and at the Max Planck Institute of Molecular Cell Biology and Genetics, Germany, in 2009-2010. Dr. Ekinci currently works as a Full Professor of Biochemistry in the Faculty of Agriculture and is the Head of the Enzyme and Microbial Biotechnology Division, Ondokuz Mayıs University, Turkey. He is a member of the Turkish Biochemical Society, American Chemical Society, and German Genetics society. Dr. Ekinci published around ninety scientific papers, reviews and book chapters, and presented several conferences to scientists. He has received numerous publication awards from several scientific councils. Dr. Ekinci serves as the Editor in Chief of four international books and is involved in the Editorial Board of several international journals.",institutionString:null,institution:{name:"Ondokuz Mayıs University",institutionURL:null,country:{name:"Turkey"}}},editorThree:null},{id:"17",title:"Metabolism",coverUrl:"https://cdn.intechopen.com/series_topics/covers/17.jpg",isOpenForSubmission:!0,annualVolume:11413,editor:{id:"138626",title:"Dr.",name:"Yannis",middleName:null,surname:"Karamanos",slug:"yannis-karamanos",fullName:"Yannis Karamanos",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002g6Jv2QAE/Profile_Picture_1629356660984",biography:"Yannis Karamanos, born in Greece in 1953, completed his pre-graduate studies at the Université Pierre et Marie Curie, Paris, then his Masters and Doctoral degree at the Université de Lille (1983). He was associate professor at the University of Limoges (1987) before becoming full professor of biochemistry at the Université d’Artois (1996). He worked on the structure-function relationships of glycoconjugates and his main project was the investigations on the biological roles of the de-N-glycosylation enzymes (Endo-N-acetyl-β-D-glucosaminidase and peptide-N4-(N-acetyl-β-glucosaminyl) asparagine amidase). From 2002 he contributes to the understanding of the Blood-brain barrier functioning using proteomics approaches. He has published more than 70 papers. His teaching areas are energy metabolism and regulation, integration and organ specialization and metabolic adaptation.",institutionString:null,institution:{name:"Artois University",institutionURL:null,country:{name:"France"}}},editorTwo:null,editorThree:null},{id:"18",title:"Proteomics",coverUrl:"https://cdn.intechopen.com/series_topics/covers/18.jpg",isOpenForSubmission:!0,annualVolume:11414,editor:{id:"200689",title:"Prof.",name:"Paolo",middleName:null,surname:"Iadarola",slug:"paolo-iadarola",fullName:"Paolo Iadarola",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bSCl8QAG/Profile_Picture_1623568118342",biography:"Paolo Iadarola graduated with a degree in Chemistry from the University of Pavia (Italy) in July 1972. He then worked as an Assistant Professor at the Faculty of Science of the same University until 1984. In 1985, Prof. Iadarola became Associate Professor at the Department of Biology and Biotechnologies of the University of Pavia and retired in October 2017. Since then, he has been working as an Adjunct Professor in the same Department at the University of Pavia. His research activity during the first years was primarily focused on the purification and structural characterization of enzymes from animal and plant sources. During this period, Prof. Iadarola familiarized himself with the conventional techniques used in column chromatography, spectrophotometry, manual Edman degradation, and electrophoresis). Since 1995, he has been working on: i) the determination in biological fluids (serum, urine, bronchoalveolar lavage, sputum) of proteolytic activities involved in the degradation processes of connective tissue matrix, and ii) on the identification of biological markers of lung diseases. In this context, he has developed and validated new methodologies (e.g., Capillary Electrophoresis coupled to Laser-Induced Fluorescence, CE-LIF) whose application enabled him to determine both the amounts of biochemical markers (Desmosines) in urine/serum of patients affected by Chronic Obstructive Pulmonary Disease (COPD) and the activity of proteolytic enzymes (Human Neutrophil Elastase, Cathepsin G, Pseudomonas aeruginosa elastase) in sputa of these patients. More recently, Prof. Iadarola was involved in developing techniques such as two-dimensional electrophoresis coupled to liquid chromatography/mass spectrometry (2DE-LC/MS) for the proteomic analysis of biological fluids aimed at the identification of potential biomarkers of different lung diseases. He is the author of about 150 publications (According to Scopus: H-Index: 23; Total citations: 1568- According to WOS: H-Index: 20; Total Citations: 1296) of peer-reviewed international journals. He is a Consultant Reviewer for several journals, including the Journal of Chromatography A, Journal of Chromatography B, Plos ONE, Proteomes, International Journal of Molecular Science, Biotech, Electrophoresis, and others. He is also Associate Editor of Biotech.",institutionString:null,institution:{name:"University of Pavia",institutionURL:null,country:{name:"Italy"}}},editorTwo:{id:"201414",title:"Dr.",name:"Simona",middleName:null,surname:"Viglio",slug:"simona-viglio",fullName:"Simona Viglio",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bRKDHQA4/Profile_Picture_1630402531487",biography:"Simona Viglio is an Associate Professor of Biochemistry at the Department of Molecular Medicine at the University of Pavia. She has been working since 1995 on the determination of proteolytic enzymes involved in the degradation process of connective tissue matrix and on the identification of biological markers of lung diseases. She gained considerable experience in developing and validating new methodologies whose applications allowed her to determine both the amount of biomarkers (Desmosine and Isodesmosine) in the urine of patients affected by COPD, and the activity of proteolytic enzymes (HNE, Cathepsin G, Pseudomonas aeruginosa elastase) in the sputa of these patients. Simona Viglio was also involved in research dealing with the supplementation of amino acids in patients with brain injury and chronic heart failure. She is presently engaged in the development of 2-DE and LC-MS techniques for the study of proteomics in biological fluids. The aim of this research is the identification of potential biomarkers of lung diseases. She is an author of about 90 publications (According to Scopus: H-Index: 23; According to WOS: H-Index: 20) on peer-reviewed journals, a member of the “Società Italiana di Biochimica e Biologia Molecolare,“ and a Consultant Reviewer for International Journal of Molecular Science, Journal of Chromatography A, COPD, Plos ONE and Nutritional Neuroscience.",institutionString:null,institution:{name:"University of Pavia",institutionURL:null,country:{name:"Italy"}}},editorThree:null}]},overviewPageOFChapters:{paginationCount:20,paginationItems:[{id:"83065",title:"Interventions and Practical Approaches to Reduce the Burden of Malaria on School-Aged Children",doi:"10.5772/intechopen.106469",signatures:"Andrew Macnab",slug:"interventions-and-practical-approaches-to-reduce-the-burden-of-malaria-on-school-aged-children",totalDownloads:2,totalCrossrefCites:null,totalDimensionsCites:0,authors:[{name:"Andrew",surname:"Macnab"}],book:{title:"Malaria - Recent Advances, and New Perspectives",coverURL:"https://cdn.intechopen.com/books/images_new/11576.jpg",subseries:{id:"5",title:"Parasitic Infectious Diseases"}}},{id:"82804",title:"Psychiatric Problems in HIV Care",doi:"10.5772/intechopen.106077",signatures:"Seggane Musisi and Noeline Nakasujja",slug:"psychiatric-problems-in-hiv-care",totalDownloads:1,totalCrossrefCites:0,totalDimensionsCites:0,authors:null,book:{title:"Future Opportunities and Tools for Emerging Challenges for HIV/AIDS Control",coverURL:"https://cdn.intechopen.com/books/images_new/11575.jpg",subseries:{id:"6",title:"Viral Infectious Diseases"}}},{id:"82827",title:"Epidemiology and Control of Schistosomiasis",doi:"10.5772/intechopen.105170",signatures:"Célestin Kyambikwa Bisangamo",slug:"epidemiology-and-control-of-schistosomiasis",totalDownloads:4,totalCrossrefCites:0,totalDimensionsCites:0,authors:null,book:{title:"New Horizons for Schistosomiasis Research",coverURL:"https://cdn.intechopen.com/books/images_new/10829.jpg",subseries:{id:"5",title:"Parasitic Infectious Diseases"}}},{id:"82817",title:"Perspective Chapter: Microfluidic Technologies for On-Site Detection and Quantification of Infectious Diseases - The Experience with SARS-CoV-2/COVID-19",doi:"10.5772/intechopen.105950",signatures:"Andres Escobar and Chang-qing Xu",slug:"perspective-chapter-microfluidic-technologies-for-on-site-detection-and-quantification-of-infectious",totalDownloads:3,totalCrossrefCites:0,totalDimensionsCites:0,authors:null,book:{title:"SARS-CoV-2 Variants - Two Years After",coverURL:"https://cdn.intechopen.com/books/images_new/11573.jpg",subseries:{id:"6",title:"Viral Infectious Diseases"}}}]},overviewPagePublishedBooks:{paginationCount:13,paginationItems:[{type:"book",id:"6667",title:"Influenza",subtitle:"Therapeutics and Challenges",coverURL:"https://cdn.intechopen.com/books/images_new/6667.jpg",slug:"influenza-therapeutics-and-challenges",publishedDate:"September 19th 2018",editedByType:"Edited by",bookSignature:"Shailendra K. Saxena",hash:"105e347b2d5dbbe6b593aceffa051efa",volumeInSeries:1,fullTitle:"Influenza - Therapeutics and Challenges",editors:[{id:"158026",title:"Prof.",name:"Shailendra K.",middleName:null,surname:"Saxena",slug:"shailendra-k.-saxena",fullName:"Shailendra K. Saxena",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",institutionURL:null,country:{name:"India"}}}]},{type:"book",id:"7064",title:"Current Perspectives in Human Papillomavirus",subtitle:null,coverURL:"https://cdn.intechopen.com/books/images_new/7064.jpg",slug:"current-perspectives-in-human-papillomavirus",publishedDate:"May 2nd 2019",editedByType:"Edited by",bookSignature:"Shailendra K. Saxena",hash:"d92a4085627bab25ddc7942fbf44cf05",volumeInSeries:2,fullTitle:"Current Perspectives in Human Papillomavirus",editors:[{id:"158026",title:"Prof.",name:"Shailendra K.",middleName:null,surname:"Saxena",slug:"shailendra-k.-saxena",fullName:"Shailendra K. Saxena",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",institutionURL:null,country:{name:"India"}}}]},{type:"book",id:"7123",title:"Current Topics in Neglected Tropical Diseases",subtitle:null,coverURL:"https://cdn.intechopen.com/books/images_new/7123.jpg",slug:"current-topics-in-neglected-tropical-diseases",publishedDate:"December 4th 2019",editedByType:"Edited by",bookSignature:"Alfonso J. 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Dr. Khalid\\'s research interests include leadership and negotiations, digital transformations, gamification, eLearning, blockchain, Big Data, and management of information technology. Dr. Bilal Khalid also serves as an academic editor at Education Research International and a reviewer for international journals.",institutionString:"KMITL Business School",institution:{name:"King Mongkut's Institute of Technology Ladkrabang",country:{name:"Thailand"}}},{id:"418514",title:"Dr.",name:"Muhammad",middleName:null,surname:"Mohiuddin",slug:"muhammad-mohiuddin",fullName:"Muhammad Mohiuddin",position:null,profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0033Y000038UqSfQAK/Profile_Picture_2022-05-13T10:39:03.jpg",biography:"Dr. Muhammad Mohiuddin is an Associate Professor of International Business at Laval University, Canada. He has taught at Thompson Rivers University, Canada; University of Paris-Est, France; Osnabruck University of Applied Science, Germany; and Shanghai Institute of Technology and Tianjin University of Technology, China. He has published research in Research Policy, Applied Economics, Review of Economic Philosophy, Strategic Change, International Journal of Logistics, Sustainability, Journal of Environmental Management, Journal of Global Information Management, Journal of Cleaner Production, M@N@GEMENT, and more. He is a member of CEDIMES Institut (France), Academy of International Business (AIB), Strategic Management Society (SMS), Academy of Management (AOM), Administrative Science Association of Canada (ASAC), and Canadian council of small business and entrepreneurship (CCSBE). He is currently the director of the Research Group on Contemporary Asia (GERAC) at Laval University. 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