Sorghum genotypes used for stem compositional analysis.
\\n\\n
These books synthesize perspectives of renowned scientists from the world’s most prestigious institutions - from Fukushima Renewable Energy Institute in Japan to Stanford University in the United States, including Columbia University (US), University of Sidney (AU), University of Miami (USA), Cardiff University (UK), and many others.
\\n\\nThis collaboration embodied the true essence of Open Access by simplifying the approach to OA publishing for Academic editors and authors who contributed their research and allowed the new research to be made available free and open to anyone anywhere in the world.
\\n\\nTo celebrate the 50 books published, we have gathered them at one location - just one click away, so that you can easily browse the subjects of your interest, download the content directly, share it or read online.
\\n\\n\\n\\n\\n"}]',published:!0,mainMedia:null},components:[{type:"htmlEditorComponent",content:'
IntechOpen and Knowledge Unlatched formed a partnership to support researchers working in engineering sciences by enabling an easier approach to publishing Open Access content. Using the Knowledge Unlatched crowdfunding model to raise the publishing costs through libraries around the world, Open Access Publishing Fee (OAPF) was not required from the authors.
\n\nInitially, the partnership supported engineering research, but it soon grew to include physical and life sciences, attracting more researchers to the advantages of Open Access publishing.
\n\n\n\nThese books synthesize perspectives of renowned scientists from the world’s most prestigious institutions - from Fukushima Renewable Energy Institute in Japan to Stanford University in the United States, including Columbia University (US), University of Sidney (AU), University of Miami (USA), Cardiff University (UK), and many others.
\n\nThis collaboration embodied the true essence of Open Access by simplifying the approach to OA publishing for Academic editors and authors who contributed their research and allowed the new research to be made available free and open to anyone anywhere in the world.
\n\nTo celebrate the 50 books published, we have gathered them at one location - just one click away, so that you can easily browse the subjects of your interest, download the content directly, share it or read online.
\n\n\n\n\n'}],latestNews:[{slug:"intechopen-supports-asapbio-s-new-initiative-publish-your-reviews-20220729",title:"IntechOpen Supports ASAPbio’s New Initiative Publish Your Reviews"},{slug:"webinar-introduction-to-open-science-wednesday-18-may-1-pm-cest-20220518",title:"Webinar: Introduction to Open Science | Wednesday 18 May, 1 PM CEST"},{slug:"step-in-the-right-direction-intechopen-launches-a-portfolio-of-open-science-journals-20220414",title:"Step in the Right Direction: IntechOpen Launches a Portfolio of Open Science Journals"},{slug:"let-s-meet-at-london-book-fair-5-7-april-2022-olympia-london-20220321",title:"Let’s meet at London Book Fair, 5-7 April 2022, Olympia London"},{slug:"50-books-published-as-part-of-intechopen-and-knowledge-unlatched-ku-collaboration-20220316",title:"50 Books published as part of IntechOpen and Knowledge Unlatched (KU) Collaboration"},{slug:"intechopen-joins-the-united-nations-sustainable-development-goals-publishers-compact-20221702",title:"IntechOpen joins the United Nations Sustainable Development Goals Publishers Compact"},{slug:"intechopen-signs-exclusive-representation-agreement-with-lsr-libros-servicios-y-representaciones-s-a-de-c-v-20211123",title:"IntechOpen Signs Exclusive Representation Agreement with LSR Libros Servicios y Representaciones S.A. de C.V"},{slug:"intechopen-expands-partnership-with-research4life-20211110",title:"IntechOpen Expands Partnership with Research4Life"}]},book:{item:{type:"book",id:"456",leadTitle:null,fullTitle:"Advanced Biometric Technologies",title:"Advanced Biometric Technologies",subtitle:null,reviewType:"peer-reviewed",abstract:'The methods for human identity authentication based on biometrics - the physiological and behavioural characteristics of a person have been evolving continuously and seen significant improvement in performance and robustness over the last few years. However, most of the systems reported perform well in controlled operating scenarios, and their performance deteriorates significantly under real world operating conditions, and far from satisfactory in terms of robustness and accuracy, vulnerability to fraud and forgery, and use of acceptable and appropriate authentication protocols. To address some challenges, and the requirements of new and emerging applications, and for seamless diffusion of biometrics in society, there is a need for development of novel paradigms and protocols, and improved algorithms and authentication techniques. This book volume on "Advanced Biometric Technologies" is dedicated to the work being pursued by researchers around the world in this area, and includes some of the recent findings and their applications to address the challenges and emerging requirements for biometric based identity authentication systems. The book consists of 18 Chapters and is divided into four sections namely novel approaches, advanced algorithms, emerging applications and the multimodal fusion. The book was reviewed by editors Dr. Girija Chetty and Dr. Jucheng Yang We deeply appreciate the efforts of our guest editors: Dr. Norman Poh, Dr. Loris Nanni, Dr. Jianjiang Feng, Dr. Dongsun Park and Dr. Sook Yoon, as well as a number of anonymous reviewers.',isbn:null,printIsbn:"978-953-307-487-0",pdfIsbn:"978-953-51-5564-5",doi:"10.5772/969",price:139,priceEur:155,priceUsd:179,slug:"advanced-biometric-technologies",numberOfPages:396,isOpenForSubmission:!1,isInWos:null,isInBkci:!1,hash:null,bookSignature:"Girija Chetty and Jucheng Yang",publishedDate:"August 9th 2011",coverURL:"https://cdn.intechopen.com/books/images_new/456.jpg",numberOfDownloads:60929,numberOfWosCitations:66,numberOfCrossrefCitations:39,numberOfCrossrefCitationsByBook:0,numberOfDimensionsCitations:75,numberOfDimensionsCitationsByBook:0,hasAltmetrics:1,numberOfTotalCitations:180,isAvailableForWebshopOrdering:!0,dateEndFirstStepPublish:"October 18th 2010",dateEndSecondStepPublish:"November 15th 2010",dateEndThirdStepPublish:"March 22nd 2011",dateEndFourthStepPublish:"April 21st 2011",dateEndFifthStepPublish:"June 20th 2011",currentStepOfPublishingProcess:5,indexedIn:"1,2,3,4,5,6,7",editedByType:"Edited by",kuFlag:!1,featuredMarkup:null,editors:[{id:"30495",title:"Dr.",name:"Girija",middleName:null,surname:"Chetty",slug:"girija-chetty",fullName:"Girija Chetty",profilePictureURL:"https://mts.intechopen.com/storage/users/30495/images/5398_n.jpg",biography:"Girija Chetty, PhD is an Assistant Professor and Head of Software Engineering discipline in Faculty of Information Sciences and Engineering in University of Canberra, Australia. She received her Bachelors and Masters(Research) degrees in Electrical Engineering and Computer Science \nfrom India, and Doctorate in Information Sciences and Engineering from Australia. She has several years of research, teaching and industry experience from India and Australia, and has led several research, development and consulting projects in the related areas. She has published over 80 research papers in peer-reviewed International Journals and Conferences, and serves on editorial and review panels for several Journals and Conferences, including Biometrics, Multimedia Intelligence and Security, and Pattern Recognition and Computer Vision. Her research interests \ninclude biometrics, image and video coding, pattern recognition, computer vision and artificial intelligence.",institutionString:null,position:null,outsideEditionCount:0,totalCites:0,totalAuthoredChapters:"1",totalChapterViews:"0",totalEditedBooks:"1",institution:{name:"University of Canberra",institutionURL:null,country:{name:"Australia"}}}],equalEditorOne:null,equalEditorTwo:null,equalEditorThree:null,coeditorOne:{id:"36689",title:"Dr.",name:"Jucheng",middleName:null,surname:"Yang",slug:"jucheng-yang",fullName:"Jucheng Yang",profilePictureURL:"https://mts.intechopen.com/storage/users/36689/images/1760_n.jpg",biography:"Jucheng Yang is a special professor of Haihe Scholar in College of Computer Science and Information Engineering, Tianjin University of Science and Technology, Tianjin, China. He is a special professor of Tianjin City, too. He received his B.S. degree from South-Central University for Nationalities, China, and M.S. and Ph.D. degree from Chonbuk National University, Republic of Korea. He did his post-doc at the Advanced Graduate Education Center of Jeonbuk for Electronics and Information Technology-BK21 (AGECJEIT-BK21), Republic of Korea. He was a professor in Jiangxi University of Finance and Economics, China and was a visiting fellow in the University of New South Wales, Australia. He has published over 50 papers in related international journals and conferences. He has served as editors or reviews of international journals such as IEEE Transactions on Information Forensics & Security, Sensors, Science China, Information Technology Journal and so on, and as reviewers or PC members of many conferences such as ICNC\\'06-FSKD\\'06, IMPRESS’09, FIRM-EPECC’11. He is the publicity chair of ICMeCG’10-11. He has applied 9 Chinese patents and was awarded 2 Chinese patents of biometrics. 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He is also working on the gene-editing tools using CRISPR (Clustered Regularly Interspaced Short Palindromic Repeats) technology and the development of Blood-Brain Barrier penetrating Polymers as a delivery vehicle for CRISPR molecules.",institutionString:"Dehradun Institute of Technology University",position:null,outsideEditionCount:0,totalCites:0,totalAuthoredChapters:"0",totalChapterViews:"0",totalEditedBooks:"0",institution:{name:"Dehradun Institute of Technology University",institutionURL:null,country:{name:"India"}}}],coeditorOne:{id:"182874",title:"Prof.",name:"Sushil Kumar",middleName:null,surname:"Singh",slug:"sushil-kumar-singh",fullName:"Sushil Kumar Singh",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bSAm4QAG/Profile_Picture_2022-04-07T11:17:21.JPG",biography:"Principal Investigator, Development of bioactive molecules as therapeutic agent for Alzheimer’s disease and screening their toxicity; IIT (BHU), Varanasi.\r\nPrincipal Investigator, Design and synthesis is of Matrix Metallo Proteinase (MMP -2 & 9) inhibitors as therapeutic agents for Alzheimer’s disease; DBT, New Delhi.\r\nCo- Principal Investigator, Cestocidal activity of glands and hairs of fruits of Mallotus phillippinensis (Kampillaka Plant); ICMR, New Delhi.\r\nPrincipal Investigator, Ethno-medicinal plants as a source of new therapeutic agents against psoriasis; National medicinal Plant Board, AYUSH, New Delhi.\r\nPrincipal Investigator, Isolation of marker compounds from Withania somnifera; Natreon Inc., Kolkata.\r\nPrincipal Investigator, Isolation of marker Compounds from natural Sources; Drug Research and Development Center, Kolkata.\r\nOne of the Investigators of the Centre, Establishment of facilities for identification, chemical characterization, standardization and quality control of medicinal plants found in tribal area in central India; DST, New Delhi.",institutionString:"Banaras Hindu University",position:null,outsideEditionCount:0,totalCites:0,totalAuthoredChapters:"0",totalChapterViews:"0",totalEditedBooks:"0",institution:{name:"Banaras Hindu University",institutionURL:null,country:{name:"India"}}},coeditorTwo:{id:"465935",title:"Dr.",name:"Ankit",middleName:null,surname:"Ganeshpurkar",slug:"ankit-ganeshpurkar",fullName:"Ankit Ganeshpurkar",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0033Y00003RKF6EQAX/Profile_Picture_2022-04-07T11:30:06.jpg",biography:null,institutionString:"Bharati Vidyapeeth Deemed University",position:null,outsideEditionCount:0,totalCites:0,totalAuthoredChapters:"0",totalChapterViews:"0",totalEditedBooks:"0",institution:{name:"Bharati Vidyapeeth Deemed University",institutionURL:null,country:{name:"India"}}},coeditorThree:null,coeditorFour:null,coeditorFive:null,topics:[{id:"18",title:"Neuroscience",slug:"life-sciences-neuroscience"}],chapters:[{id:"82876",title:"Oxygen Tissue Levels as an Effectively Modifiable Factor in Alzheimer’s Disease Improvement",slug:"oxygen-tissue-levels-as-an-effectively-modifiable-factor-in-alzheimer-s-disease-improvement",totalDownloads:10,totalCrossrefCites:0,authors:[{id:"280131",title:"Ph.D.",name:"Arturo",surname:"Solis Herrera",slug:"arturo-solis-herrera",fullName:"Arturo Solis Herrera"}]}],productType:{id:"1",title:"Edited Volume",chapterContentType:"chapter",authoredCaption:"Edited by"},personalPublishingAssistant:{id:"453623",firstName:"Silvia",lastName:"Sabo",middleName:null,title:"Mrs.",imageUrl:"https://mts.intechopen.com/storage/users/453623/images/20396_n.jpg",email:"silvia@intechopen.com",biography:null}},relatedBooks:[{type:"book",id:"6628",title:"Circadian Rhythm",subtitle:"Cellular and Molecular Mechanisms",isOpenForSubmission:!1,hash:"628bbcbfaf54a56710498540efe51b87",slug:"circadian-rhythm-cellular-and-molecular-mechanisms",bookSignature:"Mohamed Ahmed El-Esawi",coverURL:"https://cdn.intechopen.com/books/images_new/6628.jpg",editedByType:"Edited by",editors:[{id:"191770",title:"Dr.",name:"Mohamed A.",surname:"El-Esawi",slug:"mohamed-a.-el-esawi",fullName:"Mohamed A. 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In order to provide a safer environment to our future generations, we need to use energy wisely and economically and look for alternative fuel sources like biofuels, derived from crops and their waste products [1].
\nBiofuels are considered zero net emitters as they use atmospheric carbon dioxide for their growth and afterward release the same when burnt in the vehicles. The biofuels are generally classified as “conventional” (the first generation) and “advanced” biofuels (the second-, third-, and fourth-generation biofuels). Biodiesel and bioethanol are categorized as first-generation biofuels. These are produced from food crops rich in higher fermentable carbohydrate level. The second-generation biofuels are most commonly extracted from switchgrass, jatropha, miscanthus, and the residues of food crops. Often, industrial wastes are also used for the production of second-generation biofuel. The biofuels extracted from algae are classed as third generation. Major crops used for the production of biofuel are sugarcane, corn, wheat, sorghum, sugar beet, and cassava [2].
\nThe choice of the most efficient biofuel depends upon its life cycle analysis, climatic, and economic factors. Moreover, its transportation cost to refinery, price of biofuel, and greenhouse gases also matter. Plant-based feedstocks for biofuels include crops like corn, sugarcane, soybean, poplar, sorghum, switch grass, etc. The cost-effective biofuel production depends upon the exploitation of high-yielding energy crops. Designing climate-smart energy crop with optimized composition to suit the growers, consumers, and industry needs is the backbone of cost-competitive biofuel industry. C4 grasses provide a perfect fit to this definition owing to higher photosynthetic rate, productivity, and broader genetic base of germplasm. Sorghum is a short duration crop of about 3–4 months and produces higher biomass yield with less inputs. These characteristics make sorghum a popular biofuel feedstock [3]. Sorghum has different end-use types including biomass, forage, sweet, and grain sorghums. Energy sorghum including biomass and sweet type varieties is the most efficient and climate-smart feedstock being able to grow with less inputs on marginal lands under harsh climatic conditions and having ability to utilize more sunlight [4, 5, 6].
\nIt has diverse germplasm owing to extensive breeding and natural selection [7]. Sorghum is a crop of subsistence worldwide, the fifth most important cereal crop and an important component of poultry industry [8]. It is very responsive to biotechniques ranging from simple in vitro culture to transgenics, cisgenics, and genome-editing technologies. However, the outcrossing of sorghum with its weedy relatives has prevented regulation of GM technology in this crop. All above-ground parts of sorghum, starch, sugar, or stem biomass are utilized for the first- and second-generation biofuel production [9]. Though sweet sorghum has been widely used as a biofuel source, biomass sorghum has also been recently recognized as a promising feedstock for cellulosic ethanol production. This sorghum type usually has stem higher than 5 m, more number of leaves, fibrous roots, greater potential for vegetative growth, and is suitable for mechanization [10]. Besides producing second-generation ethanol, biomass sorghum also releases energy during biomass combustion [11]. It is a good substitute to corn and sugarcane with additional benefit of less water consumption. It is an annual grass having higher dry matter yield like perennial crops but in less duration, thus facilitating cheaper crop rotation. Recent wide scale applications of omics approaches like phenomics, genomics, proteomics, and metabolomics are enhancing the efficiency of sorghum breeding processes. Being an important element of system biology approach, omics analysis dissects the association between genes and proteins within diverse phenotypes. Genome analysis further refines this integration. Sorghum yields fuel and chemicals form sugars and cell wall biopolymers. Sorghum is a widely grown summer forage of Pakistan, while its biofuel potential is yet to be explored in the country. Information on sorghum stem quality traits is vital for designing eco-friendly biofuel source. Present study intended to demonstrate the basis of morphological characterization of 24 USDA sorghum genotypes selected under Pakistan conditions. These genotypes were subjected to proximate analysis to measure stem quality traits like crude protein, ash contents, neutral detergent fiber, acid detergent fiber, hemicellulose, cellulose, and acid detergent lignin. Translational analysis indicated a unique band of 56.1 kDa in 12 out of 24 genotypes. This uncharacterized protein is supposed to be translated by Dw1 gene (Sobic.009G229800) comprising of 510 amino acids and controls the internodal length in sorghum. In this chapter, stem composition evaluation and proteomics-based recent research involving USDA sorghum germplasm is reported in order to screen promising energy-type sorghum.
\nSorghum biomass is influenced by genetic and environmental factors [12]. The identification of variation in phenotypic, genetic, structural, and physiological characters of energy sorghum is vital to its improvement. Sorghum biomass improvement model relies on integrating several genomic-assisted techniques with phenomics approaches. Common field-based selection of high biomass sorghum depends upon characterizing biomass-related morphological traits like days to flowering (days after sowing), plant height, fresh biomass yield, dry matter, and dry matter yield, plant height, stalk diameter, leaf number, leaf width, leaf length, leaf angle and leaf area index, etc. [13]. Several studies report on morphological diversity assessment of sorghum for biomass traits in the field environment [14, 15].
\nAccurate and comprehensive phenotypic data are the baseline to elucidate genetic mechanisms underlying complex quantitative biomass traits. Since biomass-related traits are measured via destructive sampling, recording morphological data during the entire growing period of energy sorghum is possible only once. Manual, nondestructive sampling for these traits over complete development of sorghum is impossible. As compared to relatively cheaper technologies of genomic selection, association mapping and GWAS, reliable phenotyping is laborious and expensive. About 20 years back when genotyping techniques were fast advancing, improving phenotyping approaches was completely ignored. Recently, there has been a growing interest in developing effective sorghum phenotyping methods. The work started with optimizing high-throughput phenotyping systems for model plants under controlled environments. Later on, field-based phenotyping platforms were devised for short stature crops [16]. In the last 5 years, different approaches have been excogitated with promising capabilities of recording sorghum phenology in field environments. Some of these include various UAS platforms [17, 18], field-based robotic phenotyping system [19], unmanned aerial system [20], ultrasonic sensors [21], the light detection and ranging (LiDAR) [22], the time of flight cameras [23], tomography imaging [24], Kinect v2 camera [21], RGB and NIR imaging [25], and Phenobot 1.0 [26]. The next-generation phenomics tools generate enormous amount of data that are being translated via machine- learning statistical approaches into trait descriptions, relevant to sorghum breeders [27].
\nThe composition of biomass derived from forage, grain, and sweet sorghums has been well characterized [28]. The research on exploiting forage sorghum as biofuel was initiated in 1980s, which led to the development of photoperiod-sensitive-energy sorghum hybrids [29]. These are high biomass yielders [30]. Being relatively a recent introduction, the stem composition knowledge of energy sorghum is still limited. Up till now, a majority of research on sorghum biomass feedstock has focused more on improving yield than the quality components. So, there is a need to accurately conduct the biochemical analysis, since stem composition is the basic element influencing biofuel yield.
\nPlant cell walls are the main constituents of biomass that provide strength and limited plasticity to cell. The cell wall serves as a tough physical barrier, protecting interior of the cell against biotic and abiotic stresses. It is a multilayered structure composed of polysaccharides and proteins, which are important contributors of biofuel quality and energy conversion processes. The polysaccharides are cellulose (a polymer of glucose), pectic compounds (polymers of galacturonic acid), and hemicellulose (a polymer of a variety of sugars including xylose, arabinose, and mannose). Cellulose is the largest source of glucose for biofuels. Glucuronoarabinoxylan (GAX) hemicellulose complex is linked to lignin. Since lignin component of plant cell wall provides structure, it cannot be converted to carbohydrates and hence is recalcitrant to conversion protocols. Likewise, ash content also reduces biomass to biofuel conversion reaction. Certain constituents of cell wall are water soluble like sugars, proteins, amino acids, mixed-linkage glucans, and phenolic glycosides, whereas chlorophyll, lipids, and waxes are water-insoluble ingredients that need ethanol extraction.
\nDifferent studies have reported various approaches for compositional analysis of energy sorghum leaves and stem. In some sorghum genotypes, proportion of cellulose can vary between 27 and 52%, while the range of hemicellulose content is 17–23% and lignin content is 6.2–8.1% [31, 32]. Along with the biomass yield, low lignin, high cellulose, and hemicellulose contents are also the desirable selection attributes for energy sorghum genotypes [33]. Such sorghums exhibit wide variations in biomass composition [34]. Now a days, near-infrared spectroscopic (NIR) analysis is routinely used for high-throughput computation of biomass composition [28].
\nCellulosic bioethanol production requires three main steps: pretreatment, hydrolysis, and fermentation [35] (Figure 1). Pretreatment is performed to fractionate lignocellulose into different components via physical (boiling, steaming, and ultrasonication), chemical (acid, alkali, salts, etc.), physiochemical (ammonium fiber explosion or AFEX), and biological methods (bacteria and fungi). It increases porosity and surface area of the substrate. During hydrolysis, nonstructural carbohydrates are degraded in to sugars. Enzyme-based hydrolysis is preferred over acid hydrolysis being a mild and cost-effective process.
\nFlow chart of sorghum cellulosic ethanol production process.
The process of fermentation proceeds under liquid or solid state in the presence of bacteria or yeast [36]. In a recent study, 24 sorghum genotypes (Table 1) were subjected to stem compositional analysis [37]. These genotypes had previously been selected on the basis of morphological traits [38].
\nSr. # | \nGenotype # | \nSr. # | \nGenotype # | \n
---|---|---|---|
1. | \nPI-609239-01-SD | \n13. | \nPI-329875-03-SD | \n
2. | \nPI-620625-01-SD | \n14. | \nPI-330039-02-SD | \n
3. | \nPI-648173-01-SD | \n15. | \nPI-330022-01-SD | \n
4. | \nPI-648187-01-SD | \n16. | \nPI-456415-03-SD | \n
5. | \nPI-454464-03-SD | \n17. | \nPI-329488-02-SD | \n
6. | \nPI-570039-02-SD | \n18. | \nPI-155871-02-SD | \n
7. | \nPI-525981-01-SD | \n19. | \nPI-457393-02-SD | \n
8. | \nPI-329569-01-SD | \n20. | \nPI-329480-02-SD | \n
9. | \nPI-583832-02-SD | \n21. | \nPI-303658-02-SD | \n
10. | \nPI-329733-01-SD | \n22. | \nPI-303656-01-SD | \n
11. | \nPI-456441-03-SD | \n23. | \nNSL-54978 | \n
12. | \nPI-329471-02-SD | \n24. | \nPI-257595-01-SD | \n
Sorghum genotypes used for stem compositional analysis.
The dried stem samples of these genotypes were grinded and used for measuring crude protein (%), ash contents (%), neutral detergent fiber (NDF %), acid detergent fiber (ADF %), hemicellulose (%), cellulose (%), and acid detergent lignin (ADL %), using the respective formulae:
\nStatistical analysis indicated highly significant variations among all sorghum genotypes for crude protein, ash contents, NDF, ADF, ADL, hemicellulose, and cellulose contents (Table 2).
\nEigen vectors | \nPC1 | \nPC2 | \nPC3 | \n
---|---|---|---|
AC | \n0.437 | \n−0.218 | \n0.373 | \n
ADL | \n0.476 | \n0.384 | \n0.134 | \n
ADF | \n0.012 | \n0.501 | \n−0.191 | \n
C | \n0.455 | \n0.468 | \n0.097 | \n
CP | \n0.000 | \n−0.188 | \n0.777 | \n
HC | \n0.374 | \n−0.481 | \n−0.293 | \n
NDF | \n0.485 | \n−0.261 | \n−0.328 | \n
Eigen value | \n2.623 | \n1.916 | \n1.267 | \n
Variability % | \n37.476 | \n27.371 | \n18.096 | \n
Cumulative % | \n37.476 | \n64.847 | \n82.943 | \n
Principle component analysis (PCA) related to biomass traits in sorghum.
PC, principle component; SD, standard deviation; CV, coefficient of variation; AC, ash contents; ADL, acid detergent lignin; ADF, acid detergent fiber; C, cellulose; CP, crude protein; HC, hemicellulose; NDF, neutral detergent fiber.
PCA analysis of different biochemical traits indicated three principle components (PC1, PC2, and PC3) having Eigen values greater than 1 (Table 3). The cumulative variability of three PCs was 82.94% for the studied genotypes. The total variability in traits shared by three PCs was 37.48, 27.37, and 18.096%, respectively. Different biomass-related traits added more than 34% of variation factor in PC1 such as: ash contents (43.7%), ADL (47.6%), cellulose (45.5%), hemicelluloses (37.4%), and NDF (48.5%). PC1 showed weak and positive correlation with crude protein (0.000%) and ADF (0.012%). The PC2 contributed for 27.37% of total variability. PC2 showed positive and strong correlation with the traits such as ADL (38.4%), ADF (50.1%), and cellulose (46.8%). Weak and negative correlation was observed for ash contents (21.8%), crude protein (18.8%), hemicellulose (48.1%), and NDF (26.1%). Crude protein and ash contents showed 77.7 and 37.3% of the factor variations in PC3, respectively.
\nVariables | \nMinimum | \nMaximum | \nMean | \nSD | \nCV (%) | \n
---|---|---|---|---|---|
CP | \n4.927 | \n10.927 | \n7.808 | \n1.414 | \n1.37 | \n
AC | \n5.217 | \n19.470 | \n12.418 | \n3.877 | \n2.39 | \n
NDF | \n54.633 | \n81.500 | \n63.947 | \n6.411 | \n2.29 | \n
ADF | \n26.167 | \n54.500 | \n34.410 | \n6.994 | \n4.34 | \n
ADL | \n1.500 | \n8.000 | \n3.160 | \n1.316 | \n14.17 | \n
HC | \n22.087 | \n44.150 | \n31.419 | \n5.981 | \n1.64 | \n
C | \n29.000 | \n57.167 | \n39.250 | \n7.331 | \n2.03 | \n
Descriptive statistics for quantitative traits of sorghum germplasm.
SD, standard deviation; CV, coefficient of variation; AC, ash contents; ADL, acid detergent lignin; ADF, acid detergent fiber; C, cellulose; CP, crude protein; HC, hemicellulose; NDF, neutral detergent fiber.
Biplot analysis described that variables were greatly obliged as vectors; comparative length of the vector was distinguished as the relative proportion of the variability in each variable. The traits like ADL and CP, which were plotted near the central point, showed more similarities, while cellulose, ADF, NDF, and HC displayed more variability (Figure 2). Significant characters such as ADL, ADF, and cellulose were located at positive and positive coordinate region in biplot. Traits like AC, NDF, and HC were allocated at negative coordinate (Figure 2). Variability in the traits explains the variations among genotypes, which can be used in sorghum breeding plan effectively. Correlation analysis among biofuel-related stem compositional traits indicated that concentration of protein and lignin contents showed negative interaction with cellulose and hemicelluloses (Table 4). It showed that significant genetic variability is present among 24 sorghum genotypes. In sorghum, cellulose and hemicellulose contents play significant role in biofuel quality. For fiber analysis, NDF, ADL, and ADF are generally used as standard quality testing techniques [39], while lignin concentration markedly affects the efficiency of hydrolysis [40].
\nPCA grouping of 24 USDA sorghum genotypes using quantitative traits.
Traits | \nCP | \nAC | \nNDF | \nADF | \nADL | \nHC | \nC | \n
---|---|---|---|---|---|---|---|
CP | \n1 | \n0.347* | \n−0.128 | \n−0.066 | \n−0.182 | \n−0.051 | \n−0.080 | \n
AC | \n0.347 | \n1 | \n0.473* | \n0.362* | \n−0.173 | \n0.431* | \n0.311* | \n
NDF | \n−0.128 | \n0.473 | \n1 | \n0.293* | \n−0.033 | \n0.802** | \n0.289* | \n
ADF | \n−0.066 | \n0.362 | \n0.293 | \n1 | \n−0.153 | \n0.067 | \n0.955** | \n
ADL | \n−0.182 | \n−0.173 | \n−0.033 | \n0.153 | \n1 | \n−0.313 | \n0.335* | \n
HC | \n−0.051 | \n0.431 | \n0.802 | \n0.067 | \n−0.313 | \n1 | \n−0.016 | \n
C | \n−0.080 | \n0.311 | \n0.289 | \n0.955 | \n0.335 | \n−0.016 | \n1 | \n
Correlation coefficients of various traits of sorghum genotypes.
Normal correlation.
Strong correlation.
Study reports that by increasing the level of lignin, cellulose and hemicellulose concentrations decreased. The genetic relationships among 24 genotypes were identified through construction of dendrogram on the basis of similarity matrix utilizing the UPGMA algorithm (Figure 3). The genotypes were grouped into two main clusters: only two genotypes (PI-583832-02-SD and PI-456415-03-SD) were present in subcluster-1, while the subcluster-2 was divided into smaller groups. The genotypes PI-570039-02-SD, PI-330022-01-SD, and NSL-54978 were grouped together and showed some distinctness from rest of the members of the group, whereas the maximum genetic relatedness was found among genotypes PI-329569-01-SD and PI-303658-02-SD followed by genotypes PI-329733-01-SD, PI-525981-01-SD, PI-303656-01-SD, and PI-648187-01-SD. The genotypes PI-583832-02-SD and PI-329733-01-SD were also found genetically distinct from rest of the genotypes used in the study (Figure 4). Variance decomposition for optimal classification showed that there were 23.41 and 76.59% variances present within and between classes, respectively.
\nClassification of 24 sorghum genotypes using UPGMA cluster analysis.
Cladogenesis studies using homology-based classification of 24 sorghum genotypes.
The sorghum germplasm with less lignin and protein contents is desirable for biofuel production. Sorghum genotype PI-609239-01-SD had maximum value of NDF (83.5%) and ash contents (19.5%), while genotype PI-303658-02-SD exhibited the maximum value (57.5%) of cellulose content.
\nThough sorghum is viewed as a cheap source of biofuel being able to grow on marginal lands, few studies have indicated the lower biofuel potential of energy sorghums grown on marginal lands than the crop land [41]. Hence, screening of energy sorghum having stress tolerance, with efficient production technology and conservation tillage practices, is the key element of sustainable commercial production of energy sorghum [5].
\nThe mysterious relationship between phenotype and genotype can be revealed by applying various biotechnological approaches such as proteomics, transcriptomics, and metabolomics [42]. In transcriptomics, a huge set of gene libraries can be established by employing different techniques of bioinformatics and next-generation sequencing [43]. Over the last decade, expression profiling experiments for genome-wide investigation in sorghum have been carried out to analyze responses to numerous abiotic and biotic stresses, to determine tissue-specific and genotype-specific gene expression motifs, and to disclose the genetic modification and expression divergence between different sorghum varieties.
\nRNA-seq technology for expression profiling has been applied in sorghum to study different gene functions [44]. This technique gives a precise assessment of gene expression at different stages of sorghum plant development [45].
\nProteomics offers the set of the most efficient tools for recognition, assessment, and quantification of unique proteins. Our recent study [44] merged transcriptomic and proteomic approaches for screening sorghum germplasm best suited for bioenergy and for comparative analysis of protein expression of elite sorghum germplasm. The study was based on 24 USDA sorghum genotypes selected for biomass potential in the field experiments, which is already reported in this chapter [37]. For translational analysis, 12 out of 24 selected genotypes were divided into three groups based on stem height, since height is directly correlated with biomass in sorghum. Four short stature genotypes were chosen as negative control (Table 5).
\nSr. # | \nGenotypes | \nHeight-based groups | \n
---|---|---|
1. | \nNSL-54978 | \nTall | \n
2. | \nPI-456441-03-SD | \n|
3. | \nPI-525981-01-SD | \n|
4. | \nPI-303656-01-SD | \n|
5. | \nPI-457393-02-SD | \nMedium | \n
6. | \nPI-583832-02-SD | \n|
7. | \nPI-620625-01-SD | \n|
8. | \nPI-456415-03-SD | \n|
9. | \nPI-648187-01-SD | \nSmall | \n
10. | \nPI-609239-01-SD | \n|
11. | \nPI-330039-02-SD | \n|
12. | \nPI-329733-01-SD | \n|
13. | \nPI-643630-01-SD | \nNegative control | \n
14. | \nPI-643735-03-SD | \n|
15. | \nPI-643581-01-SD | \n|
16. | \nPI-642993-01-SD | \n
Sorghum genotypes and their respective groups based on height.
The
Genotype | \nProtein weight (kDa) | \n||||||||
---|---|---|---|---|---|---|---|---|---|
NSL-54978 | \n124 | \n97.6 | \n\n | 64 | \n56.1 | \n40.5 | \n38.7 | \n32 | \n14.9 | \n
PI-456441-03-SD | \n124 | \n97.6 | \n\n | 64 | \n56.1 | \n40.5 | \n38.8 | \n32 | \n14.9 | \n
PI-525981-01-SD | \n124 | \n97.6 | \n71 | \n64 | \n56.1 | \n40.5 | \n38.8 | \n32 | \n14.9 | \n
PI-303656-01-SD | \n124 | \n97.6 | \n\n | 64 | \n56.1 | \n40.5 | \n38.8 | \n32 | \n14.9 | \n
PI-457393-02-SD | \n\n | \n | 71 | \n64 | \n56.1 | \n40.5 | \n38.8 | \n32 | \n\n |
PI-583832-02-SD | \n\n | 97.6 | \n71 | \n64 | \n56.1 | \n40.5 | \n38.8 | \n32 | \n\n |
PI-620625-01-SD | \n\n | \n | 71 | \n64 | \n56.1 | \n40.5 | \n38.8 | \n32 | \n\n |
PI-456415-03-SD | \n\n | \n | 71 | \n64 | \n56.1 | \n40.5 | \n38.8 | \n32 | \n\n |
PI-648187-01-SD | \n\n | 97.6 | \n71 | \n64 | \n56.1 | \n40.5 | \n38.8 | \n32 | \n\n |
PI-609239-01-SD | \n\n | \n | 71 | \n64 | \n56.1 | \n40.5 | \n38.8 | \n32 | \n\n |
PI-330039-02-SD | \n\n | 97.6 | \n\n | 64 | \n56.1 | \n40.5 | \n38.8 | \n32 | \n\n |
PI-329733-01-SD | \n\n | 97.6 | \n\n | 64 | \n56.1 | \n40.5 | \n38.8 | \n32 | \n\n |
PI-643630-01-SD | \n\n | 97.6 | \n\n | 64 | \n\n | 40.5 | \n\n | 32 | \n\n |
PI-643735-03-SD | \n\n | 97.6 | \n\n | 64 | \n\n | 40.5 | \n\n | 32 | \n\n |
PI-643581-01-SD | \n\n | \n | \n | 64 | \n\n | 40.5 | \n\n | 32 | \n\n |
PI-642993-01-SD | \n\n | \n | \n | 64 | \n\n | 40.5 | \n\n | 32 | \n\n |
SDS-PAGE-based banding pattern of various proteins in sorghum genotypes.
SDS-PAGE showed nine different bands in 12 selected sorghum genotypes. The banding pattern of four negative controls was different from the selected ones, which revealed low expression of proteins. The study showed a unique band of 56.1 kDa present only in all selected genotypes. This band represents a hypothetical protein Sobic.009G229800, which has 510 amino acids (Figures 5 and 6) and controls the internodal length of stem in sorghum, which is why short-stature sorghum genotypes were devoid of this protein.
\nSecondary structure prediction of SORB1_3009G229800 protein responsible for stem internodal length.
Blast result for confirming the SORB1_3009G229800 protein against NCBI database.
Height is positively correlated with biomass production [46] and is reported to be independent of stem structural composition like cellulose, hemicellulose, and lignin contents [47]. The Quantitative trait loci (QTL) for total dry biomass has been found to be localized with height QTLs [48]. Hence, breeders aim for taller genotypes in sorghum biomass improvement plans. Chromosomes six, seven, and nine carry QTLs for height in sorghum. This protein (Sobic.0 09G229800) is considered to be translated from Dw1, a gene greatly conserved in plants (Table 7). Earlier reports showed that
Names and taxonomy | \n|
---|---|
Protein | \nUncharacterized protein | \n
Gene | \nSORBI_009G229800 | \n
Organism | \n|
Taxonomic identifier | \n4558 [NCBI] | \n
Proteomes | \nUP000000768 | \n
Chromosome | \n9 | \n
Sequence databases | \nCM000768 Genomic DNA Translation KXG22524.1 | \n
Last sequence update | \nNovember 2, 2016 | \n
Profile of SORBI_3009G229800 protein translated from
Energy sorghum is considered to be a promising biofuel feedstock to counteract the depleted fossil fuel reserves. To keep pace with fast progressing sorghum genomics, recent phenomics tools have been evolved that are more efficient than traditional laborious field-based manual phenotyping methods. This chapter describes the results of recent studies involving 24 selected biomass sorghums. The genotypes with low lignin, high cellulose, and hemicellulose components have been identified. Furthermore, with the help of translational analysis, an uncharacterized protein (Sobic.009G229800) is identified in tall sorghum genotypes. It regulates plant height by altering the length of internodes. Sorghum feedstock’s stem compositional analysis, genomics, phenomics, and proteomics are enabling technologies extensively used by sorghum researchers for selection of elite sorghum germplasm with biofuel potential.
\nModern diesel engines are the main mobile energy sources, are widely used as stationary power plants, and are distinguished by a high degree of design, working, and technological processes.
The advantages of diesel engines are determined by the high level of fuel efficiency and reliability due to the high level of workflow, all systems, and components refining. But this does not mean that all reserves for further improvement of diesel engine performance have been exhausted.
The main disadvantages of diesel engines include the consumption of natural organic fuels and the contribution to environmental pollution.
Taking into account, the prospects for increasing energy potential in stationary, and especially in transport energy, limited natural resources, deterioration of the environment, today it seems relevant to solve the following problems:
further improvement of the design of diesel engines in order to boost the liter capacity;
reduction of operating fuel consumption;
reduction of toxic emissions into the environment with exhaust gases;
reduction of emissions (СО2) into the environment with fuel combustion products.
The solution of these problems seems to be a much more rational direction, in comparison with the proposed solutions for the reduction and possible abandonment of the use of diesel engines in the future, which will invariably lead to the energy crisis, which may turn out to be much more painful for humanity in comparison with the ecological one.
In this chapter of the monograph, in order to systematize, select directions, and search for rational ways to improve the efficiency of diesel engines, the main results of fundamental and applied research carried out in recent years at the Department of Internal Combustion Engines of the National Technical University “KhPI” are considered. The experience of the authors in improving the quality of processes in cylinders of diesel engines, in increasing the reliability of the most loaded parts, in ensuring a reduction in the level of emissions of toxic substances and carbon dioxide, including the use of alternative fuels, is generalized.
It is proposed to evaluate the effectiveness of technical solutions to reduce the operating fuel consumption of transport diesel engines and emissions of toxic substances with exhaust gases, use of alternative and hybrid fuels, which includes green hydrogen, is proposed to be carried out using the fuel-ecological criterion. It is shown that further improvement of this criterion is associated with taking into account the impact of carbon dioxide emissions on the environment.
At the same time, the heat generated by the combustion of fuel in the engine cylinders cannot be completely converted into useful mechanical work. To study the efficiency of thermodynamic processes of diesel engines, it is proposed to use the anergy-energetic method of analysis, and the quality of heat conversion into work is estimated by the exergy efficiency, which makes it possible to identify the mechanisms of formation of internal and external losses and substantiate the ways to achieve optimal heat use.
Along with the improvement of economic and environmental indicators and the technical level, the improvement of diesel engines is associated with an increase in liter power, which requires ensuring reliability, first of all, the most heat-stressed engine parts and using modern industry 4.0 technologies.
Improving the efficiency of power plants, preserving natural resources, and improving the quality of the environment are global problems of our time. Diesel engines are the main source of energy for transport, and at the same time, they are one of the main consumers of fuel oil and an active pollutant of the environment.
The level of excellence and technical level of modern diesel engines is largely determined by fuel consumption and exhaust gas emissions (EG). Diesel engines have higher fuel efficiency and lower mass emissions of toxic substances compared to gasoline and other heat engines. However, research data shows that, along with a high level of toxicity of nitrogen oxides emitted into the atmosphere together with EG, particulate matter (PM) poses a great danger to humans and the environment due to the adsorption of carcinogens.
At the same time, it is known that technical solutions aimed at reducing fuel consumption have an impact on the environmental performance of an engine, and fuel consumption can increase with an improvement in its environmental performance. Therefore, a compromise is needed. A targeted search for compromise technical solutions requires a comprehensive approach using a criterion that takes into account the level of fuel consumption indicators, EG emissions, and operating conditions. The solution to this problem is of paramount importance for automobile engines, since, they are used in crowded places in cities, suburbs, industrial areas and, therefore, pose the greatest danger to people and the environment.
At the Department of Internal Combustion Engines of the National Technical University “Kharkiv Polytechnic Institute” (NTU “KhPI”), a dimensionless comprehensive criterion of fuel efficiency and EG toxicity for diesel engines has been developed [1].
This criterion is informative, simple, and user-friendly, takes into account the operating conditions, provides information on the degree of economic and environmental excellence, the effectiveness of the developed measures to improve the work process, engine design, and technology, the use of alternative and mixed fuels, exhaust gas neutralization systems for a specific diesel engine.
The initial data for the criterial comprehensive assessment of diesel engines are obtained with relatively simple, affordable, and minimal bench tests.
To determine the fuel-ecological criterion, it is necessary to know the average operating effective efficiency of the engine (η
Then the comprehensive criterion can be represented as:
Here,
where
Then, the unit costs for compensation of environmental damage from the harmful effects on the environment of the exhaust gases of a diesel engine during the combustion of 1 kg of fuel, referred to a unit of power for each representative fixed mode of operation of a diesel engine, are equal to:
And the total unit costs for reimbursement of environmental damage from the harmful effects of toxic emissions of exhaust gases of a diesel engine for all representative fixed modes of the operating model.
In formulas (3) and (4):
As mentioned above, it is advisable to evaluate the indicators of fuel efficiency and toxicity of exhaust gases of diesel engines under operating conditions during bench tests on typical fixed operating modes, which are selected taking into account the type, purpose, and generalized data on engine operating time. Selected and justified fixed modes of operation, in which bench tests are carried out, represent a model of engine operation.
As a result of the analysis and processing of the operational test data, the authors proposed a generalized model of the operation of a diesel truck in the form of probabilistic distribution of the centers of the operating ranges (Figure 1).
Probabilistic distribution of ranges of operating modes of a diesel engine of a truck during the aggregate movement in the city and on a suburban highway.
Thus, it is possible, based on the results of bench tests of a diesel engine, to determine the level of fuel costs and compensation for environmental damage from the harmful effects of EG on the human body and the environment, as well as to apply a dimensionless fuel and environmental criterion for comparative assessment.
The disadvantages of the proposed model include the comparative complexity of the procedure for carrying out bench tests of a diesel engine, which provides for the determination of a large number of parameters at 28 modes. In this regard, based on summarizing the results of the research carried out for diesel engines of trucks, a 9 regime test cycle is proposed. The basis for the development of the 9th mode test cycle was ensuring the maximum possible compliance with the comprehensive criterion in comparison with tests for the 28th mode cycle. As a result, the developed cycle with a limited number of load modes and crankshaft speeds of a diesel engine makes it possible to determine a comprehensive criterion of fuel efficiency and exhaust gas toxicity without introducing additional errors.
The proposed 9th mode cycle of bench tests to determine the comprehensive criterion of fuel consumption and toxicity of exhaust gases during the operation of diesel engines of trucks is presented in Table 1. At the rated speed mode, the diesel engine is tested under loads corresponding to Рn and 0.7 Рn. Three load modes (1.1, 0.7 and 0.3Рn) correspond to crankshaft speeds of 0.8 and 0.6 nn. Another mode takes into account the share of fuel and environmental costs when the diesel engine is operating at the minimum idle crankshaft speed (
Modes Nos. | Significance coefficient, z | ||
---|---|---|---|
1 | nn | Рn | 0.05 |
2 | nn | 0.7 Рn | 0.025 |
3 | 0.8 nn | 1.1 Рn | 0.3 |
4 | 0.8 nn | 0.7 Рn | 0.05 |
5 | 0.8 nn | 0.3 Рn | 0.05 |
6 | 0.6 nn | 1.1 Рn | 0.35 |
7 | 0.6 nn | 0.7 Рn | 0.1 |
8 | 0.6 nn | 0.3 Рn | 0.05 |
9 | 0 | 0.025 |
Model of operation of a diesel engine of a truck with the combined movement of the city and suburban highway.
For each mode, coefficients were selected that took into account the conditions for the distribution of fuel and environmental costs over the ranges of the diesel engine operating model of a fully loaded truck when driving in the city and on the highway.
Interestingly, if we compare the ESC cycles in accordance with the UNECE rules for diesel engines of trucks and the KhPI cycle, it can be noted that with a smaller number of test modes, the KhPI cycle covers almost equal ranges in terms of load and speed.
Consequently, for a balanced assessment of the environmental hazard of diesel engines for various purposes, it is necessary to take into account the real conditions of their operation and an objective approach to calculating the damage from the harmful effects of exhaust gases. Since the emissions of toxic components of the exhaust gases and the fuel efficiency of a diesel engine are directly related to the organization of mixture formation and combustion, an integrated approach to this problem is required.
The choice of the significant coefficient for each of the modes is based on generalizing the share of costs for fuel consumption and compensation for environmental damage from the harmful effects of exhaust gases in the total costs of the aggregate modes. The proposed dimensionless comprehensive criterion of fuel efficiency and toxicity allows a targeted search and assessment of the effectiveness of the developed measures aimed at reducing fuel consumption and toxicity of exhaust gas emissions under engine operating conditions.
The comprehensive criterion allows:
to evaluate the efficiency of the internal combustion engine when operating conditions change;
to determine the operating modes in which
to develop measures aimed at increasing the efficiency of the internal combustion engine;
to evaluate the efficiency of using alternative fuels or EG neutralization systems.
The dimensionless comprehensive criterion of fuel efficiency and toxicity of harmful EG emissions, taking into account the degree of diesel loading and the factor of operating time, makes it possible to evaluate the quality of a diesel engine when used on different vehicles or to assess the fuel and environmental efficiency of various engines when used on the same vehicle. The use of a comprehensive criterion, or, if necessary, the ratio of relative operating environmental costs, in turn, allows an analysis of a compromise situation when a decision is required on the permissible increase in fuel costs provided that the overall level of fuel and environmental costs decreases. In this case, it is necessary to additionally agree on the degree of complexity of the implementation of these solutions, taking into account the potential costs of a significant reconstruction of the diesel engine and the costs of using, for example, electronic control systems or neutralization of EG.
Further improvement of the integrated fuel and environmental criterion is associated with taking into account the compensation for damage caused by diesel engines by СО2 emissions.
The most pressing for transport engines are fuel, energy, and environmental problems. These problems are directly related to the limitation of natural resources and environmental degradation. Currently, there are about 1 billion vehicles in the world that run on petroleum engine fuels and actively pollute the environment with hazardous toxic constituents of exhaust gases—carbon oxides (CO), hydrocarbons (CH), nitrogen oxides (NOx), particulate matter (PM), and also contribute to the expansion of the greenhouse effect by emissions of carbon dioxide (СО2).
In this regard, along with the further improvement of the power plants of vehicles, including those with diesel engines, the most important task is to expand the use of alternative fuels, as well as to reduce emissions of toxic components of exhaust gases and reduce the level of СО2 emissions.
It should be noted that the share of the level of СО2 emissions into the atmosphere by road transport and their average annual increase in relation to the total levels of emissions of СО2 with fuel combustion products is ∼23% and in relation to the technogenic СО2 emission into the atmosphere ∼ from 1 to 2%. These data give grounds to assert that vehicles with internal combustion engines, like all heat and power engineering, are not significant at the present stage in terms of the degree of accumulation of СО2 in the atmosphere, and the corresponding warming of the climate, are not significant. But, on the other hand, vehicles with internal combustion engines negatively affect the change in the natural environment, as a component of the creation of transport systems, their operation and maintenance, including the search, production, transportation, processing of all natural resources, including the oil industry, which has a negative impact on the environment. Under the influence of the above-listed factors, the transformation and destruction of natural massifs, land desertification, pollution of the waters of the World Ocean occurs. All this leads to the degradation and destruction of the planet’s photosynthetic systems, to a decrease in their natural biological productivity, a corresponding decrease in runoff levels of СО2 and, as a consequence, an increase in the content of СО2 in the atmosphere and the temperature of the surface air layer [3].
Currently, promising alternative fuels for diesel engines include:
natural gas, which, in terms of reserves and cost, is currently considered one of the most acceptable energy carriers for vehicles, especially those operating in large cities;
water-fuel emulsions, which are widely used in water transport, as well as for trucks with diesel engines [4, 5];
biofuel, which can be used for road transport and especially for self-propelled agricultural vehicles.
“Green” hydrogen is currently being considered as an additional energy carrier for oil and alternative fuels for vehicles. The presence of additives of “green” hydrogen provides a decrease in the energy of ignition of fuels, an increase in the rate of its combustion, and reduces the level of formation of NO
The Department of Internal combustion engines of NTU “KhPI” using a comprehensive fuel and environmental criterion (see Section 2.1 of this Chapter) has made a comparative analysis and a quantitative assessment of the effectiveness of the use of alternative fuels when operating a diesel engine of a truck in comparison with standard diesel fuel on a 6-cylinder diesel engine with a cylinder volume of 9.5 l.
The results of the tests and processing of experimental data are shown in Table 2 and Figure 2. The Figure and the Table show the relative change in the integrated fuel and environmental criterion Cf.ec.
Features of the piston design | Uncoated | Coated | |
---|---|---|---|
Engine boost level, kW/l | 25 | 29 | 29 |
Temperature at a heavier stationary mode (section b), °C | 314 | 343 | 322 |
Temperature at idle speed (section d), °С | 191 | 193 | 188 |
Stress in a heavier stationary mode (section b), MPa | −36 | −42.5 | −7.6 |
No-load stress (section d), MPa | −0.15 | 0 | −2.9 |
Parameter of the physical reliability of the structure for the resource Р | 0.552 | < −4 | 0.574 |
Parameters of thermal tension of the piston combustion chamber edge.
Relative change of Cf.ec., when using alternative types of fuel in a 6-cylinder automobile diesel engine with a cylinder capacity of 9.5 l.
The criterion was determined based on the results of bench tests using a model of operation of a truck diesel engine. The engine was tested on diesel fuel, compressed natural gas (CNG) with 15% pilot diesel, rapeseed methyl ester (RME), and water-fuel emulsion (WFE) which contained diesel fuel and 10% water.
The price of natural gas and diesel fuel in the calculations was taken according to the averaged data of filling and gas filling stations in Ukraine.
The costs of water and the preparation of a water-fuel emulsion were not taken into account in the calculations.
The cost of 1 kg of rapeseed oil methyl ester, obtained in pilot plants and in small quantities, exceeds the cost of 1 kg of diesel fuel by 1.4–1.6 times. However, when calculating the comprehensive criterion, the price of rapeseed oil methyl ester was taken to be equal to the price of diesel fuel, taking into account its possible decrease with the expansion of the production of this fuel.
It follows from the above data that any of the investigated alternative fuels in an automotive diesel engine provides an increase in fuel and environmental efficiency. This is mainly due to a decrease in toxic emissions at engine operating modes at maximum load at reduced speeds.
The use of a gas-diesel cycle with CNG allows increasing the value of the comprehensive criterion of fuel efficiency and toxicity of exhaust gases of a truck diesel engine by 11.9%. It should be noted that in this case, as the proportion of partial modes increases, the ratio between the constant doses of ignition diesel fuel supplied to the cylinders and the amount of compressed natural gas increases. Accordingly, fuel costs increase and environmental efficiency from the use of gas fuel decreases.
The complex fuel and environmental criterion increase by almost the same amount when a truck diesel engine runs on rapeseed oil methyl ether. In this case, the deterioration in the average operating efficiency occurs to a large extent when the engine is running at partial conditions, in comparison with the engine running on diesel fuel.
When a truck diesel engine runs on a water-fuel emulsion, the comprehensive criterion of fuel efficiency and toxicity of exhaust gases increases most significantly—by 15%. This is due to the simultaneous reduction in environmental operating costs, and an increase in the average diesel engine operating efficiency.
It should be noted that the presented results were obtained without any changes in the diesel engine settings and without any changes in their design in order to adapt to a specific type of alternative fuel. Consequently, there are reserves for increasing fuel efficiency and improving the environmental performance of diesel engines when using each of the considered alternative fuels. These reserves include the use of alternative hybrid fuels, which contain green hydrogen.
The heat generated by the combustion of fuel in the engine cylinders cannot be completely converted into useful mechanical work. In the thermodynamic cycle, the efficiency of converting heat into work is estimated by the thermal efficiency η
Currently, there are two directions in the thermodynamics of investigating the efficiency of diesel processes. The traditional direction is that for the thermodynamic study of motors, a heat balance is used, based on the first principle of thermodynamics, when the criterion for the quality of converting heat into work is the effective efficiency (η
It is known that heat and internal energy, as forms of energy, determined by the first law of thermodynamics, can only be partially converted into work. Accordingly, in a heat engine (Figure 3) it is possible to convert into work only a certain fraction of the energy supplied in the form of heat
Diagram of the circular process of a heat power plant.
In a generalized form, a consequence of the second law of thermodynamics is the statement that there are forms of energy that can be converted into any other form of energy. These forms of energy, covered by the general concept “exergy”, are completely mutually convertible during reversible processes, and by reversible and irreversible processes they can be transformed into limited convertible forms of energy—internal energy and heat. At the same time, limited convertible forms of energy cannot be converted in any quantities into exergy. All forms of energy that are not transformed into exergy are summarized by the term “anergy”.
“Exergy is the maximum possible work that the system can perform in the reversible transition from this state to a state of equilibrium with the environment; anergy is the energy that cannot be converted into exergy” [7].
For all forms of energy, the following general correlation is valid:
According to the principle of irreversibility, all natural, actually occurring processes are irreversible. Thus, in these processes, the supply of exergy decreases due to its transformation into anergy. Part of the exergy that is converted into anergy during irreversible processes is the loss of exergy in the process.
To use the concept of exergy and anergy, it is necessary to know the proportions of these quantities for various forms of energy. When determining exergy, the heat supplied to the heat-power plant is considered, the working fluid of which performs a circular process. The exergy of heat appears here as useful work, and anergy as the unused heat of a circular process. However, the useful work of the circular process coincides with the exergy of the supplied heat under the following conditions:
the circular process is reversible (otherwise it turns into anergy and useful work will be less than the applied exergy);
heat removal is carried out at ambient temperature, so that the removed heat consists only of anergy and corresponds to the anergy of the supplied heat (Figure 3).
Heat supplied to the working fluid
As a result of the heat supply
transferred with it is equal to the perceived entropy
for the given heat we get
The heat removed to the environment consists only of anergy and represents the desired anergy of heat.
The exergy of heat is manifested as the work of an imaginary reversible circular process
If heat is perceived or given off by the system in a certain temperature range, then the exergy of heat perceived or given off with heat
In a similar way for the anergy of heat
Here
As well as
According to the theory [8], any heat and enthalpy can be represented as components of exergy and anergy.
In addition, the anergy balance equations are valid for any ICE unit
and balance of exergy
where ΣЕin and ΣEout may include work supplied to the assembly or taken away from it.
From these equations, it can be concluded that the exergy losses ΣD
Anergo-exergy scheme of the internal combustion engine. SC—supercharger; S—air cooler; C—cylinders; EX—exhaust manifold; T—gas turbine; EM—engine mechanisms; FP—fuel pump; WP—water pump; OP—oil pump; W—water system unit that receives frictional heat transferred to water; O—oil system unit that receives frictional heat transferred to oil;
The bifurcation of the ICE assemblies made it possible to reveal the corresponding losses of exergy:
For a diesel engine cylinder, you can write
where
At the same time
To find
In general,
For process (e–a)
If the law of heat transfer in the gas exchange section is known, then
where,
Having found
According to Eq. (12)), one can find
If the law of heat transfer is known in the area of compression, combustion, expansion, then
where
In this case
The balance of the exergy flows of the internal combustion engine can be obtained by considering the contour
Let us take into account that
With this in mind, we get
or
Note that in this expression
Since
This dependence is the equation of the energy balance of the engine. It can be seen from it that the exergy
Then
The efficiency of converting exergy supplied to the internal combustion engine into useful work can be estimated by the exergy efficiency
Let us give an example of determining exergy losses using the proposed anergo-exergy method for a 6ChN12/14 tractor diesel engine with a power of 150 kW in one of its operating modes.
The performed calculation shows that in the diesel cycle, when the heat of the fuel is transferred to the working fluid, 21.3% of the anergy of this heat was formed. In addition, due to the irreversibility of real processes, losses of exergy amounted to 16.75%, that is, 38.05% of inoperable heat was also formed in the cycle. Part of the workable heat (20.95%) is carried away into the environment by heat carriers—oil, water, air, and exhaust gases. The rest of the heat turned into useful work (41.05%).
The largest amount of workable heat is carried away by waste gases (16.84%). The loss of performance in the lubrication and cooling systems is 2.16 and 7.84%, respectively. Attention is drawn to the noticeable total loss of performance during filling and when gases enter the exhaust manifold—1.34%. Noteworthy are DSC = 1.25% and DT = 3.83%—losses of exergy in the supercharger and gas turbine. In reducing the indicated losses of exergy, reserves for increasing the efficiency of a diesel engine are laid. Figure 5 shows the items of the exergy balance.
Exergy balance of a diesel engine.
In the diesel cycle, the exergy of the chemical heat of the fuel is supplied to the working fluid
However, exergy took part in the process of converting this heat into work.
Due to the irreversibility of real processes, 29% of
The remaining 71% of exergy turned into effective work. The exergy losses in the exergy balance are “significant”, since the exergy losses in water are 13.58%, that is, almost half of all exergy losses. Turbine losses are less and amount to about 6%. Both should be dealt with at the same time by the researcher in order to reduce them.
So, the use of anergo-exergy method of analysis makes it possible to identify the mechanisms of the formation of internal and external losses of diesel engines and their systems, and to substantiate the ways to achieve their maximum efficiency.
Modernization of existing and creation of new engines of high specific power causes significant difficulties since it is necessary to minimize costs during the life cycle of a structure while ensuring a set of quality indicators during given service life. At the same time, for the most thermally stressed engine parts, the provision of their physical and parametric reliability must be taken into account. The practice of operating engines testifies to cases of failure of the combustion chamber parts due to their cracking during the declared resource and the appearance of chafes and scuffs on the lateral surface of the piston [11]. A substantiated increase in the reliability of heat-stressed parts of an internal combustion engine requires the use at the design stage of mathematical models that take into account a complex of factors affecting the physical and parametric reliability.
Let us consider the process of loss of structural reliability based on the model of material damage accumulation in time
Typical zones of change in the reliability factor of the ICE heat-stressed part.
Figure 7a shows a diagram of the part critical zone deformation for the case of possible instantaneous plastic deformations and creep deformations under the conditions of deformations structural limitation. Typical examples of such zones are the edges of the pistons combustion chamber and the cylinder head cross-sections between the valve orifice and the injector bore. Here, sections 1–2–3–4 denote the initial engine load, 4–5—work in a stationary heavy operating mode, 5–6–7–8—load reduction to a certain partial mode, 8–9—work in a stationary partial mode, 9–10—subsequent engine load to previous heavy-duty level. In this case, sections 1–2 and 5–6 correspond to the material elastic deformation, sections 2–3 and 6–7: creep deformation and stress relaxation, in sections 3–4 and 7–8 the creep process is accompanied by instant plastic deformations, and in Section 4–5 and 8–9 are characterized by stress relaxation.
Typical variants of deformation of the critical zone of ICE heat-stressed part.
In this case, the common condition for ensuring physical reliability during the work of the part material in such zones on the verge of strength are:
where Ξ is the operating model of an engine for a specific purpose,
In practice, the choice of technical solutions to improve the physical reliability of the high specific power ICE heat-stressed parts corresponds to the solution of the problem of transition of the calculated result in Eq. (13), in accordance with Figure 1, from zone IV to zone III.
Figure 7b presents a variant of the part critical zone deformation with practically no limitation of creep deformations. Side surface of the piston is a typical example of such a zone. Here sections 1–2–3 denote the initial engine load, 3–4—work on the stationary heavy operation mode, 4–5—load reduction to a certain partial mode and work on the stationary partial mode, 5–6-7—subsequent engine load to the level of the previous heavy-duty and 7–8—subsequent work on the stationary mode. In this case, sections 1–2 and 5–6 correspond to the material elastic deformation, and 2–3–4 and 6–7–8 correspond to creep deformation
Methods for determining the profile of the piston lateral surface are known. They consist in determining the clearance Δ
With an increase in the level of engine boost due to the appearance of creep deformation, in accordance with Figure 7b, the size of the gap along with some coordinates hi, θ
where
Thus, the choice of technical solutions to improve the parametric reliability of the ICE piston side surface corresponds to the solution of the problem of transition of the calculated result from zone II to zone I (Figure 6).
To obtain a reliable result of the part guaranteed reliability, it is necessary to have input information about the non-stationary low-frequency and high-frequency temperature state of the structure in accordance with the adopted operating model:
where the values
Formulation of the problem in the form Eqs. (16) and (17) with the subsequent use of model Eq. (13) significantly increases the design time. Therefore, a simplification of problem Eqs. (16) and (17) is proposed, which does not contradict the principle of guaranteed ensuring the strength of a part during design [13]. With a load surge and engine operation in a heavy stationary mode, we take:
With a load drop and engine operation in a less heavy stationary mode, we take:
A graphical explanation of the values used is shown in Figure 8.
Local temperature (left) and thermal stress (right) in a single loading cycle of the studied zone of the piston: a—temperature and b—stress state of the studied area of the part: a—load surge; b—heavily loaded stationary mode; c—load drop; d—less loaded stationary mode.
On the basis of the proposed approaches, we determined the reliability criteria
The calculated data on the structure thermal stress are also sufficient to determine the parametric reliability of the piston lateral surface
Control points on the piston: a—Location of control points on the piston for levels a—D; b—Change in the thermally stressed state for control points.
The proposed approach to the analysis of the reliability of structures of heat-stressed parts of highly accelerated engines takes into account the operating model and allows you to search for technical solutions while ensuring the operation of materials of structures on the verge of strength.
For monitoring and predicting the residual life of the most thermally stressed parts under engine operating conditions, the proposed methodology allows using modern 4.0 technologies.
The improvement of diesel engines, as the main source of modern energy, is associated with a further increase in fuel efficiency, liter capacity, and reliability, with a significant reduction in emissions of toxic substances and carbon dioxide into the environment.
The proposed systematic approach to a comprehensive assessment of fuel efficiency and emissions toxicity allowed proposing a dimensionless criterion that takes into account the operating conditions of the engine. Using this criterion, an assessment of the efficiency of using alternative fuels is given and the prospect of such an assessment is shown when using hybrid fuels that include green hydrogen.
To identify the mechanisms of the formation of internal and external losses and substantiate the ways to achieve optimal heat use, the use of the anergy-energetic method of analysis is justified.
In order to increase the reliability of the most thermally stressed parts of highly accelerated engines, taking into account the operating conditions, the approach has been proposed, taking into account the complexity of factors affecting the physical and parametric reliability.
The directions for improving diesel engines, considered in the chapter, are only a part of a set of tasks, the solution of which seems to be extremely relevant from the point of view of preventing an energy crisis and, at the same time, are only a part of the possible ones for practical implementation.
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\\n\\nA Conflict of Interest is a situation in which a person's professional judgment may be influenced by a range of factors, including financial gain, material interest, or some other personal or professional interest. For IntechOpen as a publisher, it is essential that all possible Conflicts of Interest are avoided. Each contributor, whether an Author, Editor, or Reviewer, who suspects they may have a Conflict of Interest, is obliged to declare that concern in order to make the publisher and the readership aware of any potential influence on the work being undertaken.
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\\n\\nEXAMPLES OF CONFLICTS OF INTEREST:
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\\n\\nAuthors are required to declare all potentially relevant non-financial, financial and material Conflicts of Interest that may have had an influence on their scientific work.
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\\n"}]'},components:[{type:"htmlEditorComponent",content:"In each instance of a possible Conflict of Interest, IntechOpen aims to disclose the situation in as transparent a way as possible in order to allow readers to judge whether a particular potential Conflict of Interest has influenced the Work of any individual Author, Editor, or Reviewer. IntechOpen takes all possible Conflicts of Interest into account during the review process and ensures maximum transparency in implementing its policies.
\n\nA Conflict of Interest is a situation in which a person's professional judgment may be influenced by a range of factors, including financial gain, material interest, or some other personal or professional interest. For IntechOpen as a publisher, it is essential that all possible Conflicts of Interest are avoided. Each contributor, whether an Author, Editor, or Reviewer, who suspects they may have a Conflict of Interest, is obliged to declare that concern in order to make the publisher and the readership aware of any potential influence on the work being undertaken.
\n\nA Conflict of Interest can be identified at different phases of the publishing process.
\n\nIntechOpen requires:
\n\nCONFLICT OF INTEREST - AUTHOR
\n\nAll Authors are obliged to declare every existing or potential Conflict of Interest, including financial or personal factors, as well as any relationship which could influence their scientific work. Authors must declare Conflicts of Interest at the time of manuscript submission, although they may exceptionally do so at any point during manuscript review. For jointly prepared manuscripts, the corresponding Author is obliged to declare potential Conflicts of Interest of any other Authors who have contributed to the manuscript.
\n\nCONFLICT OF INTEREST – ACADEMIC EDITOR
\n\nEditors can also have Conflicts of Interest. Editors are expected to maintain the highest standards of conduct, which are outlined in our Best Practice Guidelines (templates for Best Practice Guidelines). Among other obligations, it is essential that Editors make transparent declarations of any possible Conflicts of Interest that they might have.
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\n\nFor manuscripts submitted by the Academic Editor (or a scientific advisor), an appropriate person will be appointed to handle and evaluate the manuscript. The appointed handling Editor's identity will not be disclosed to the Author in order to maintain impartiality and anonymity of the review.
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\n\nAll Reviewers are required to declare possible Conflicts of Interest at the beginning of the evaluation process. If a Reviewer feels he or she might have any material, financial or any other conflict of interest with regards to the manuscript being reviewed, he or she is required to declare such concern and, if necessary, request exclusion from any further involvement in the evaluation process. A Reviewer's potential Conflicts of Interest are declared in the review report and presented to the Academic Editor, who then assesses whether or not the declared potential or actual Conflicts of Interest had, or could be perceived to have had, any significant impact on the review itself.
\n\nEXAMPLES OF CONFLICTS OF INTEREST:
\n\nFINANCIAL AND MATERIAL
\n\nNON-FINANCIAL
\n\nAuthors are required to declare all potentially relevant non-financial, financial and material Conflicts of Interest that may have had an influence on their scientific work.
\n\nAcademic Editors and Reviewers are required to declare any non-financial, financial and material Conflicts of Interest that could influence their fair and balanced evaluation of manuscripts. If such conflict exists with regards to a submitted manuscript, Academic Editors and Reviewers should exclude themselves from handling it.
\n\nAll Authors, Academic Editors, and Reviewers are required to declare all possible financial and material Conflicts of Interest in the last five years, although it is advisable to declare less recent Conflicts of Interest as well.
\n\nEXAMPLES:
\n\nAuthors should declare if they were or they still are Academic Editors of the publications in which they wish to publish their work.
\n\nAuthors should declare if they are board members of an organization that could benefit financially or materially from the publication of their work.
\n\nAcademic Editors should declare if they were coauthors or they have worked on the research project with the Author who has submitted a manuscript.
\n\nAcademic Editors should declare if the Author of a submitted manuscript is affiliated with the same department, faculty, institute, or company as they are.
\n\nPolicy last updated: 2016-06-09
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After finishing his P. hD degree in 1992, he served in the Industry as a Scientific Officer and continued his academic career as a visiting scholar for a number of educational institutions. In 1996 he joined National University of Science & Technology Pakistan (NUST) as an Associate Professor; NUST is one of the top few universities in Pakistan. In 1999 he joined an International Company Lineo Inc, Canada as Manager Compiler Group, where he headed the group for developing Compiler Tool Chain and Porting of Operating Systems for the BLACKfin processor. The processor development was a joint venture by Intel and Analog Devices. In 2002 Lineo Inc., was taken over by another company, so he joined Aalborg University Denmark as an Assistant Professor.\nProfessor Akbar has truly a multi-disciplined career and he continued his legacy and making progress in many areas of his interests both in teaching and research. 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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. 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He was elected a Yangtze River Scholars Distinguished Professor in 2013, a member of the International Statistical Institute (ISI) in 2016, a member of the board of the International Chinese Statistical Association (ICSA) in 2018, and a fellow of the Institute of Mathematical Statistics (IMS) in 2021. He received the ICSA Outstanding Service Award in 2018 and the National Science Foundation for Distinguished Young Scholars of China in 2012. He serves as a member of the editorial board of Statistics and Its Interface and Journal of Systems Science and Complexity. He is also a field editor for Communications in Mathematics and Statistics. His research interests include biostatistics, empirical likelihood, missing data analysis, variable selection, high-dimensional data analysis, Bayesian statistics, and data science. He has published more than 190 research papers and authored five books.",institutionString:"Yunnan University",institution:{name:"Yunnan University",country:{name:"China"}}},{id:"1177",title:"Prof.",name:"António",middleName:"J. R.",surname:"José Ribeiro Neves",slug:"antonio-jose-ribeiro-neves",fullName:"António José Ribeiro Neves",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/1177/images/system/1177.jpg",biography:"Prof. António J. R. Neves received a Ph.D. in Electrical Engineering from the University of Aveiro, Portugal, in 2007. Since 2002, he has been a researcher at the Institute of Electronics and Informatics Engineering of Aveiro. Since 2007, he has been an assistant professor in the Department of Electronics, Telecommunications, and Informatics, University of Aveiro. He is the director of the undergraduate course on Electrical and Computers Engineering and the vice-director of the master’s degree in Electronics and Telecommunications Engineering. He is an IEEE Senior Member and a member of several other research organizations worldwide. His main research interests are computer vision, intelligent systems, robotics, and image and video processing. He has participated in or coordinated several research projects and received more than thirty-five awards. He has 161 publications to his credit, including books, book chapters, journal articles, and conference papers. He has vast experience as a reviewer of several journals and conferences. As a professor, Dr. Neves has supervised several Ph.D. and master’s students and was involved in more than twenty-five different courses.",institutionString:null,institution:{name:"University of Aveiro",country:{name:"Portugal"}}},{id:"11317",title:"Dr.",name:"Francisco",middleName:null,surname:"Javier Gallegos-Funes",slug:"francisco-javier-gallegos-funes",fullName:"Francisco Javier Gallegos-Funes",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/11317/images/system/11317.png",biography:"Francisco J. Gallegos-Funes received his Ph.D. in Communications and Electronics from the Instituto Politécnico Nacional de México (National Polytechnic Institute of Mexico) in 2003. He is currently an associate professor in the Escuela Superior de Ingeniería Mecánica y Eléctrica (Mechanical and Electrical Engineering Higher School) at the same institute. His areas of scientific interest are signal and image processing, filtering, steganography, segmentation, pattern recognition, biomedical signal processing, sensors, and real-time applications.",institutionString:"Instituto Politécnico Nacional",institution:{name:"Instituto Politécnico Nacional",country:{name:"Mexico"}}},{id:"428449",title:"Dr.",name:"Ronaldo",middleName:null,surname:"Ferreira",slug:"ronaldo-ferreira",fullName:"Ronaldo Ferreira",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/428449/images/21449_n.png",biography:null,institutionString:null,institution:{name:"University of Aveiro",country:{name:"Portugal"}}},{id:"165328",title:"Dr.",name:"Vahid",middleName:null,surname:"Asadpour",slug:"vahid-asadpour",fullName:"Vahid Asadpour",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/165328/images/system/165328.jpg",biography:"Vahid Asadpour, MS, Ph.D., is currently with the Department of Research and Evaluation, Kaiser Permanente Southern California. He has both an MS and Ph.D. in Biomedical Engineering. He was previously a research scientist at the University of California Los Angeles (UCLA) and visiting professor and researcher at the University of North Dakota. He is currently working in artificial intelligence and its applications in medical signal processing. In addition, he is using digital signal processing in medical imaging and speech processing. Dr. Asadpour has developed brain-computer interfacing algorithms and has published books, book chapters, and several journal and conference papers in this field and other areas of intelligent signal processing. He has also designed medical devices, including a laser Doppler monitoring system.",institutionString:"Kaiser Permanente Southern California",institution:null},{id:"169608",title:"Prof.",name:"Marian",middleName:null,surname:"Găiceanu",slug:"marian-gaiceanu",fullName:"Marian Găiceanu",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/169608/images/system/169608.png",biography:"Prof. Dr. Marian Gaiceanu graduated from the Naval and Electrical Engineering Faculty, Dunarea de Jos University of Galati, Romania, in 1997. He received a Ph.D. (Magna Cum Laude) in Electrical Engineering in 2002. Since 2017, Dr. Gaiceanu has been a Ph.D. supervisor for students in Electrical Engineering. He has been employed at Dunarea de Jos University of Galati since 1996, where he is currently a professor. Dr. Gaiceanu is a member of the National Council for Attesting Titles, Diplomas and Certificates, an expert of the Executive Agency for Higher Education, Research Funding, and a member of the Senate of the Dunarea de Jos University of Galati. He has been the head of the Integrated Energy Conversion Systems and Advanced Control of Complex Processes Research Center, Romania, since 2016. He has conducted several projects in power converter systems for electrical drives, power quality, PEM and SOFC fuel cell power converters for utilities, electric vehicles, and marine applications with the Department of Regulation and Control, SIEI S.pA. (2002–2004) and the Polytechnic University of Turin, Italy (2002–2004, 2006–2007). He is a member of the Institute of Electrical and Electronics Engineers (IEEE) and cofounder-member of the IEEE Power Electronics Romanian Chapter. He is a guest editor at Energies and an academic book editor for IntechOpen. He is also a member of the editorial boards of the Journal of Electrical Engineering, Electronics, Control and Computer Science and Sustainability. Dr. Gaiceanu has been General Chairman of the IEEE International Symposium on Electrical and Electronics Engineering in the last six editions.",institutionString:'"Dunarea de Jos" University of Galati',institution:{name:'"Dunarea de Jos" University of Galati',country:{name:"Romania"}}},{id:"4519",title:"Prof.",name:"Jaydip",middleName:null,surname:"Sen",slug:"jaydip-sen",fullName:"Jaydip Sen",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/4519/images/system/4519.jpeg",biography:"Jaydip Sen is associated with Praxis Business School, Kolkata, India, as a professor in the Department of Data Science. His research areas include security and privacy issues in computing and communication, intrusion detection systems, machine learning, deep learning, and artificial intelligence in the financial domain. He has more than 200 publications in reputed international journals, refereed conference proceedings, and 20 book chapters in books published by internationally renowned publishing houses, such as Springer, CRC press, IGI Global, etc. Currently, he is serving on the editorial board of the prestigious journal Frontiers in Communications and Networks and in the technical program committees of a number of high-ranked international conferences organized by the IEEE, USA, and the ACM, USA. He has been listed among the top 2% of scientists in the world for the last three consecutive years, 2019 to 2021 as per studies conducted by the Stanford University, USA.",institutionString:"Praxis Business School",institution:null},{id:"320071",title:"Dr.",name:"Sidra",middleName:null,surname:"Mehtab",slug:"sidra-mehtab",fullName:"Sidra Mehtab",position:null,profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0033Y00002v6KHoQAM/Profile_Picture_1584512086360",biography:"Sidra Mehtab has completed her BS with honors in Physics from Calcutta University, India in 2018. She has done MS in Data Science and Analytics from Maulana Abul Kalam Azad University of Technology (MAKAUT), Kolkata, India in 2020. Her research areas include Econometrics, Time Series Analysis, Machine Learning, Deep Learning, Artificial Intelligence, and Computer and Network Security with a particular focus on Cyber Security Analytics. Ms. Mehtab has published seven papers in international conferences and one of her papers has been accepted for publication in a reputable international journal. She has won the best paper awards in two prestigious international conferences – BAICONF 2019, and ICADCML 2021, organized in the Indian Institute of Management, Bangalore, India in December 2019, and SOA University, Bhubaneswar, India in January 2021. Besides, Ms. Mehtab has also published two book chapters in two books. Seven of her book chapters will be published in a volume shortly in 2021 by Cambridge Scholars’ Press, UK. Currently, she is working as the joint editor of two edited volumes on Time Series Analysis and Forecasting to be published in the first half of 2021 by an international house. Currently, she is working as a Data Scientist with an MNC in Delhi, India.",institutionString:"NSHM College of Management and Technology",institution:{name:"Association for Computing Machinery",country:{name:"United States of America"}}},{id:"226240",title:"Dr.",name:"Andri Irfan",middleName:null,surname:"Rifai",slug:"andri-irfan-rifai",fullName:"Andri Irfan Rifai",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/226240/images/7412_n.jpg",biography:"Andri IRFAN is a Senior Lecturer of Civil Engineering and Planning. He completed the PhD at the Universitas Indonesia & Universidade do Minho with Sandwich Program Scholarship from the Directorate General of Higher Education and LPDP scholarship. He has been teaching for more than 19 years and much active to applied his knowledge in the project construction in Indonesia. His research interest ranges from pavement management system to advanced data mining techniques for transportation engineering. He has published more than 50 papers in journals and 2 books.",institutionString:null,institution:{name:"Universitas Internasional Batam",country:{name:"Indonesia"}}},{id:"314576",title:"Dr.",name:"Ibai",middleName:null,surname:"Laña",slug:"ibai-lana",fullName:"Ibai Laña",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/314576/images/system/314576.jpg",biography:"Dr. Ibai Laña works at TECNALIA as a data analyst. He received his Ph.D. in Artificial Intelligence from the University of the Basque Country (UPV/EHU), Spain, in 2018. He is currently a senior researcher at TECNALIA. His research interests fall within the intersection of intelligent transportation systems, machine learning, traffic data analysis, and data science. He has dealt with urban traffic forecasting problems, applying machine learning models and evolutionary algorithms. He has experience in origin-destination matrix estimation or point of interest and trajectory detection. Working with large volumes of data has given him a good command of big data processing tools and NoSQL databases. He has also been a visiting scholar at the Knowledge Engineering and Discovery Research Institute, Auckland University of Technology.",institutionString:"TECNALIA Research & Innovation",institution:{name:"Tecnalia",country:{name:"Spain"}}},{id:"314575",title:"Dr.",name:"Jesus",middleName:null,surname:"L. Lobo",slug:"jesus-l.-lobo",fullName:"Jesus L. Lobo",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/314575/images/system/314575.png",biography:"Dr. Jesús López is currently based in Bilbao (Spain) working at TECNALIA as Artificial Intelligence Research Scientist. In most cases, a project idea or a new research line needs to be investigated to see if it is good enough to take into production or to focus on it. That is exactly what he does, diving into Machine Learning algorithms and technologies to help TECNALIA to decide whether something is great in theory or will actually impact on the product or processes of its projects. So, he is expert at framing experiments, developing hypotheses, and proving whether they’re true or not, in order to investigate fundamental problems with a longer time horizon. He is also able to design and develop PoCs and system prototypes in simulation. He has participated in several national and internacional R&D projects.\n\nAs another relevant part of his everyday research work, he usually publishes his findings in reputed scientific refereed journals and international conferences, occasionally acting as reviewer and Programme Commitee member. Concretely, since 2018 he has published 9 JCR (8 Q1) journal papers, 9 conference papers (e.g. ECML PKDD 2021), and he has co-edited a book. He is also active in popular science writing data science stories for reputed blogs (KDNuggets, TowardsDataScience, Naukas). Besides, he has recently embarked on mentoring programmes as mentor, and has also worked as data science trainer.",institutionString:"TECNALIA Research & Innovation",institution:{name:"Tecnalia",country:{name:"Spain"}}},{id:"103779",title:"Prof.",name:"Yalcin",middleName:null,surname:"Isler",slug:"yalcin-isler",fullName:"Yalcin Isler",position:null,profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bRyQ8QAK/Profile_Picture_1628834958734",biography:"Yalcin Isler (1971 - Burdur / Turkey) received the B.Sc. degree in the Department of Electrical and Electronics Engineering from Anadolu University, Eskisehir, Turkey, in 1993, the M.Sc. degree from the Department of Electronics and Communication Engineering, Suleyman Demirel University, Isparta, Turkey, in 1996, the Ph.D. degree from the Department of Electrical and Electronics Engineering, Dokuz Eylul University, Izmir, Turkey, in 2009, and the Competence of Associate Professorship from the Turkish Interuniversity Council in 2019.\n\nHe was Lecturer at Burdur Vocational School in Suleyman Demirel University (1993-2000, Burdur / Turkey), Software Engineer (2000-2002, Izmir / Turkey), Research Assistant in Bulent Ecevit University (2002-2003, Zonguldak / Turkey), Research Assistant in Dokuz Eylul University (2003-2010, Izmir / Turkey), Assistant Professor at the Department of Electrical and Electronics Engineering in Bulent Ecevit University (2010-2012, Zonguldak / Turkey), Assistant Professor at the Department of Biomedical Engineering in Izmir Katip Celebi University (2012-2019, Izmir / Turkey). He is an Associate Professor at the Department of Biomedical Engineering at Izmir Katip Celebi University, Izmir / Turkey, since 2019. In addition to academics, he has also founded Islerya Medical and Information Technologies Company, Izmir / Turkey, since 2017.\n\nHis main research interests cover biomedical signal processing, pattern recognition, medical device design, programming, and embedded systems. He has many scientific papers and participated in several projects in these study fields. He was an IEEE Student Member (2009-2011) and IEEE Member (2011-2014) and has been IEEE Senior Member since 2014.",institutionString:null,institution:{name:"Izmir Kâtip Çelebi University",country:{name:"Turkey"}}},{id:"339677",title:"Dr.",name:"Mrinmoy",middleName:null,surname:"Roy",slug:"mrinmoy-roy",fullName:"Mrinmoy Roy",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/339677/images/16768_n.jpg",biography:"An accomplished Sales & Marketing professional with 12 years of cross-functional experience in well-known organisations such as CIPLA, LUPIN, GLENMARK, ASTRAZENECA across different segment of Sales & Marketing, International Business, Institutional Business, Product Management, Strategic Marketing of HIV, Oncology, Derma, Respiratory, Anti-Diabetic, Nutraceutical & Stomatological Product Portfolio and Generic as well as Chronic Critical Care Portfolio. A First Class MBA in International Business & Strategic Marketing, B.Pharm, D.Pharm, Google Certified Digital Marketing Professional. Qualified PhD Candidate in Operations and Management with special focus on Artificial Intelligence and Machine Learning adoption, analysis and use in Healthcare, Hospital & Pharma Domain. Seasoned with diverse therapy area of Pharmaceutical Sales & Marketing ranging from generating revenue through generating prescriptions, launching new products, and making them big brands with continuous strategy execution at the Physician and Patients level. Moved from Sales to Marketing and Business Development for 3.5 years in South East Asian Market operating from Manila, Philippines. Came back to India and handled and developed Brands such as Gluconorm, Lupisulin, Supracal, Absolut Woman, Hemozink, Fabiflu (For COVID 19), and many more. In my previous assignment I used to develop and execute strategies on Sales & Marketing, Commercialization & Business Development for Institution and Corporate Hospital Business portfolio of Oncology Therapy Area for AstraZeneca Pharma India Ltd. Being a Research Scholar and Student of ‘Operations Research & Management: Artificial Intelligence’ I published several pioneer research papers and book chapters on the same in Internationally reputed journals and Books indexed in Scopus, Springer and Ei Compendex, Google Scholar etc. Currently, I am launching PGDM Pharmaceutical Management Program in IIHMR Bangalore and spearheading the course curriculum and structure of the same. I am interested in Collaboration for Healthcare Innovation, Pharma AI Innovation, Future trend in Marketing and Management with incubation on Healthcare, Healthcare IT startups, AI-ML Modelling and Healthcare Algorithm based training module development. I am also an affiliated member of the Institute of Management Consultant of India, looking forward to Healthcare, Healthcare IT and Innovation, Pharma and Hospital Management Consulting works.",institutionString:null,institution:{name:"Lovely Professional University",country:{name:"India"}}},{id:"1063",title:"Prof.",name:"Constantin",middleName:null,surname:"Volosencu",slug:"constantin-volosencu",fullName:"Constantin Volosencu",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/1063/images/system/1063.png",biography:"Prof. Dr. Constantin Voloşencu graduated as an engineer from\nPolitehnica University of Timișoara, Romania, where he also\nobtained a doctorate degree. He is currently a full professor in\nthe Department of Automation and Applied Informatics at the\nsame university. Dr. Voloşencu is the author of ten books, seven\nbook chapters, and more than 160 papers published in journals\nand conference proceedings. He has also edited twelve books and\nhas twenty-seven patents to his name. He is a manager of research grants, editor in\nchief and member of international journal editorial boards, a former plenary speaker, a member of scientific committees, and chair at international conferences. His\nresearch is in the fields of control systems, control of electric drives, fuzzy control\nsystems, neural network applications, fault detection and diagnosis, sensor network\napplications, monitoring of distributed parameter systems, and power ultrasound\napplications. He has developed automation equipment for machine tools, spooling\nmachines, high-power ultrasound processes, and more.",institutionString:'"Politechnica" University Timişoara',institution:null},{id:"221364",title:"Dr.",name:"Eneko",middleName:null,surname:"Osaba",slug:"eneko-osaba",fullName:"Eneko Osaba",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/221364/images/system/221364.jpg",biography:"Dr. Eneko Osaba works at TECNALIA as a senior researcher. He obtained his Ph.D. in Artificial Intelligence in 2015. He has participated in more than twenty-five local and European research projects, and in the publication of more than 130 papers. He has performed several stays at universities in the United Kingdom, Italy, and Malta. Dr. Osaba has served as a program committee member in more than forty international conferences and participated in organizing activities in more than ten international conferences. He is a member of the editorial board of the International Journal of Artificial Intelligence, Data in Brief, and Journal of Advanced Transportation. He is also a guest editor for the Journal of Computational Science, Neurocomputing, Swarm, and Evolutionary Computation and IEEE ITS Magazine.",institutionString:"TECNALIA Research & Innovation",institution:{name:"Tecnalia",country:{name:"Spain"}}},{id:"275829",title:"Dr.",name:"Esther",middleName:null,surname:"Villar-Rodriguez",slug:"esther-villar-rodriguez",fullName:"Esther Villar-Rodriguez",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/275829/images/system/275829.jpg",biography:"Dr. Esther Villar obtained a Ph.D. in Information and Communication Technologies from the University of Alcalá, Spain, in 2015. She obtained a degree in Computer Science from the University of Deusto, Spain, in 2010, and an MSc in Computer Languages and Systems from the National University of Distance Education, Spain, in 2012. Her areas of interest and knowledge include natural language processing (NLP), detection of impersonation in social networks, semantic web, and machine learning. Dr. Esther Villar made several contributions at conferences and publishing in various journals in those fields. Currently, she is working within the OPTIMA (Optimization Modeling & Analytics) business of TECNALIA’s ICT Division as a data scientist in projects related to the prediction and optimization of management and industrial processes (resource planning, energy efficiency, etc).",institutionString:"TECNALIA Research & Innovation",institution:{name:"Tecnalia",country:{name:"Spain"}}},{id:"49813",title:"Dr.",name:"Javier",middleName:null,surname:"Del Ser",slug:"javier-del-ser",fullName:"Javier Del Ser",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/49813/images/system/49813.png",biography:"Prof. Dr. Javier Del Ser received his first PhD in Telecommunication Engineering (Cum Laude) from the University of Navarra, Spain, in 2006, and a second PhD in Computational Intelligence (Summa Cum Laude) from the University of Alcala, Spain, in 2013. He is currently a principal researcher in data analytics and optimisation at TECNALIA (Spain), a visiting fellow at the Basque Center for Applied Mathematics (BCAM) and a part-time lecturer at the University of the Basque Country (UPV/EHU). His research interests gravitate on the use of descriptive, prescriptive and predictive algorithms for data mining and optimization in a diverse range of application fields such as Energy, Transport, Telecommunications, Health and Industry, among others. In these fields he has published more than 240 articles, co-supervised 8 Ph.D. theses, edited 6 books, coauthored 7 patents and participated/led more than 40 research projects. He is a Senior Member of the IEEE, and a recipient of the Biscay Talent prize for his academic career.",institutionString:"Tecnalia Research & Innovation",institution:{name:"Tecnalia",country:{name:"Spain"}}},{id:"278948",title:"Dr.",name:"Carlos Pedro",middleName:null,surname:"Gonçalves",slug:"carlos-pedro-goncalves",fullName:"Carlos Pedro Gonçalves",position:null,profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bRcmyQAC/Profile_Picture_1564224512145",biography:'Carlos Pedro Gonçalves (PhD) is an Associate Professor at Lusophone University of Humanities and Technologies and a researcher on Complexity Sciences, Quantum Technologies, Artificial Intelligence, Strategic Studies, Studies in Intelligence and Security, FinTech and Financial Risk Modeling. He is also a progammer with programming experience in:\n\nA) Quantum Computing using Qiskit Python module and IBM Quantum Experience Platform, with software developed on the simulation of Quantum Artificial Neural Networks and Quantum Cybersecurity;\n\nB) Artificial Intelligence and Machine learning programming in Python;\n\nC) Artificial Intelligence, Multiagent Systems Modeling and System Dynamics Modeling in Netlogo, with models developed in the areas of Chaos Theory, Econophysics, Artificial Intelligence, Classical and Quantum Complex Systems Science, with the Econophysics models having been cited worldwide and incorporated in PhD programs by different Universities.\n\nReceived an Arctic Code Vault Contributor status by GitHub, due to having developed open source software preserved in the \\"Arctic Code Vault\\" for future generations (https://archiveprogram.github.com/arctic-vault/), with the Strategy Analyzer A.I. module for decision making support (based on his PhD thesis, used in his Classes on Decision Making and in Strategic Intelligence Consulting Activities) and QNeural Python Quantum Neural Network simulator also preserved in the \\"Arctic Code Vault\\", for access to these software modules see: https://github.com/cpgoncalves. He is also a peer reviewer with outsanding review status from Elsevier journals, including Physica A, Neurocomputing and Engineering Applications of Artificial Intelligence. Science CV available at: https://www.cienciavitae.pt//pt/8E1C-A8B3-78C5 and ORCID: https://orcid.org/0000-0002-0298-3974',institutionString:"University of Lisbon",institution:{name:"Universidade Lusófona",country:{name:"Portugal"}}},{id:"310576",title:"Prof.",name:"Erick Giovani",middleName:null,surname:"Sperandio Nascimento",slug:"erick-giovani-sperandio-nascimento",fullName:"Erick Giovani Sperandio Nascimento",position:null,profilePictureURL:"https://intech-files.s3.amazonaws.com/0033Y00002pDKxDQAW/ProfilePicture%202022-06-20%2019%3A57%3A24.788",biography:"Prof. Erick Sperandio is the Lead Researcher and professor of Artificial Intelligence (AI) at SENAI CIMATEC, Bahia, Brazil, also working with Computational Modeling (CM) and HPC. He holds a PhD in Environmental Engineering in the area of Atmospheric Computational Modeling, a Master in Informatics in the field of Computational Intelligence and Graduated in Computer Science from UFES. He currently coordinates, leads and participates in R&D projects in the areas of AI, computational modeling and supercomputing applied to different areas such as Oil and Gas, Health, Advanced Manufacturing, Renewable Energies and Atmospheric Sciences, advising undergraduate, master's and doctoral students. He is the Lead Researcher at SENAI CIMATEC's Reference Center on Artificial Intelligence. In addition, he is a Certified Instructor and University Ambassador of the NVIDIA Deep Learning Institute (DLI) in the areas of Deep Learning, Computer Vision, Natural Language Processing and Recommender Systems, and Principal Investigator of the NVIDIA/CIMATEC AI Joint Lab, the first in Latin America within the NVIDIA AI Technology Center (NVAITC) worldwide program. He also works as a researcher at the Supercomputing Center for Industrial Innovation (CS2i) and at the SENAI Institute of Innovation for Automation (ISI Automação), both from SENAI CIMATEC. He is a member and vice-coordinator of the Basic Board of Scientific-Technological Advice and Evaluation, in the area of Innovation, of the Foundation for Research Support of the State of Bahia (FAPESB). He serves as Technology Transfer Coordinator and one of the Principal Investigators at the National Applied Research Center in Artificial Intelligence (CPA-IA) of SENAI CIMATEC, focusing on Industry, being one of the six CPA-IA in Brazil approved by MCTI / FAPESP / CGI.br. He also participates as one of the representatives of Brazil in the BRICS Innovation Collaboration Working Group on HPC, ICT and AI. He is the coordinator of the Work Group of the Axis 5 - Workforce and Training - of the Brazilian Strategy for Artificial Intelligence (EBIA), and member of the MCTI/EMBRAPII AI Innovation Network Training Committee. He is the coordinator, by SENAI CIMATEC, of the Artificial Intelligence Reference Network of the State of Bahia (REDE BAH.IA). He leads the working group of experts representing Brazil in the Global Partnership on Artificial Intelligence (GPAI), on the theme \"AI and the Pandemic Response\".",institutionString:null,institution:null},{id:"241400",title:"Prof.",name:"Mohammed",middleName:null,surname:"Bsiss",slug:"mohammed-bsiss",fullName:"Mohammed Bsiss",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/241400/images/8062_n.jpg",biography:null,institutionString:null,institution:null},{id:"276128",title:"Dr.",name:"Hira",middleName:null,surname:"Fatima",slug:"hira-fatima",fullName:"Hira Fatima",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/276128/images/14420_n.jpg",biography:"Dr. Hira Fatima\nAssistant Professor\nDepartment of Mathematics\nInstitute of Applied Science\nMangalayatan University, Aligarh\nMobile: no : 8532041179\nhirafatima2014@gmal.com\n\nDr. Hira Fatima has received his Ph.D. degree in pure Mathematics from Aligarh Muslim University, Aligarh India. Currently working as an Assistant Professor in the Department of Mathematics, Institute of Applied Science, Mangalayatan University, Aligarh. She taught so many courses of Mathematics of UG and PG level. Her research Area of Expertise is Functional Analysis & Sequence Spaces. She has been working on Ideal Convergence of double sequence. She has published 17 research papers in National and International Journals including Cogent Mathematics, Filomat, Journal of Intelligent and Fuzzy Systems, Advances in Difference Equations, Journal of Mathematical Analysis, Journal of Mathematical & Computer Science etc. She has also reviewed few research papers for the and international journals. She is a member of Indian Mathematical Society.",institutionString:null,institution:null},{id:"417317",title:"Mrs.",name:"Chiedza",middleName:null,surname:"Elvina Mashiri",slug:"chiedza-elvina-mashiri",fullName:"Chiedza Elvina Mashiri",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"Midlands State University",country:{name:"Zimbabwe"}}},{id:"352140",title:"Dr.",name:"Edina",middleName:null,surname:"Chandiwana",slug:"edina-chandiwana",fullName:"Edina Chandiwana",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"Midlands State University",country:{name:"Zimbabwe"}}},{id:"342259",title:"B.Sc.",name:"Leonard",middleName:null,surname:"Mushunje",slug:"leonard-mushunje",fullName:"Leonard Mushunje",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"Midlands State University",country:{name:"Zimbabwe"}}},{id:"347042",title:"Mr.",name:"Maxwell",middleName:null,surname:"Mashasha",slug:"maxwell-mashasha",fullName:"Maxwell Mashasha",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"Midlands State University",country:{name:"Zimbabwe"}}},{id:"2941",title:"Dr.",name:"Alberto J.",middleName:"Jorge",surname:"Rosales-Silva",slug:"alberto-j.-rosales-silva",fullName:"Alberto J. 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He worked on the structure-function relationships of glycoconjugates and his main project was the investigations on the biological roles of the de-N-glycosylation enzymes (Endo-N-acetyl-β-D-glucosaminidase and peptide-N4-(N-acetyl-β-glucosaminyl) asparagine amidase). From 2002 he contributes to the understanding of the Blood-brain barrier functioning using proteomics approaches. He has published more than 70 papers. 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essential area of research in its own right, but also in relation to medicine and health sciences. The scope of this topic will range from molecular, biochemical, cellular, and physiological processes in all animal species. Work pertaining to the whole organism, organ systems, individual organs and tissues, cells, and biomolecules will be included. Medical, animal, cell, and comparative physiology and allied fields such as anatomy, histology, and pathology with physiology links will be covered in this topic. Physiology research may be linked to development, aging, environment, regular and pathological processes, adaptation and evolution, exercise, or several other factors affecting, or involved with, animal physiology.",coverUrl:"https://cdn.intechopen.com/series_topics/covers/10.jpg",keywords:"Physiology, Comparative, Evolution, Biomolecules, Organ, Homeostasis, Anatomy, Pathology, Medical, Cell Division, Cell Signaling, Cell Growth, Cell Metabolism, Endocrine, Neuroscience, Cardiovascular, Development, Aging, Development"},{id:"11",title:"Cell Physiology",scope:"\r\n\tThe integration of tissues and organs throughout the mammalian body, as well as the expression, structure, and function of molecular and cellular components, is essential for modern physiology. The following concerns will be addressed in this Cell Physiology subject, which will consider all organ systems (e.g., brain, heart, lung, liver; gut, kidney, eye) and their interactions: (1) Neurodevelopment and Neurodevelopmental Disease (2) Free Radicals (3) Tumor Metastasis (4) Antioxidants (5) Essential Fatty Acids (6) Melatonin and (7) Lipid Peroxidation Products and Aging Physiology.
",coverUrl:"https://cdn.intechopen.com/series_topics/covers/11.jpg",keywords:"Neurodevelopment and Neurodevelopmental Disease, Free Radicals, Tumor Metastasis, Antioxidants, Essential Fatty Acids, Melatonin, Lipid Peroxidation Products and Aging Physiology"},{id:"12",title:"Human Physiology",scope:"Human physiology is the scientific exploration of the various functions (physical, biochemical, and mechanical properties) of humans, their organs, and their constituent cells. The endocrine and nervous systems play important roles in maintaining homeostasis in the human body. Integration, which is the biological basis of physiology, is achieved through communication between the many overlapping functions of the human body's systems, which takes place through electrical and chemical means. Much of the basis of our knowledge of human physiology has been provided by animal experiments. Because of the close relationship between structure and function, studies in human physiology and anatomy seek to understand the mechanisms that help the human body function. The series on human physiology deals with the various mechanisms of interaction between the various organs, nerves, and cells in the human body.",coverUrl:"https://cdn.intechopen.com/series_topics/covers/12.jpg",keywords:"Anatomy, Cells, Organs, Systems, Homeostasis, Functions"},{id:"13",title:"Plant Physiology",scope:"Plant Physiology explores fundamental processes in plants, and it includes subtopics such as plant nutrition, plant hormone, photosynthesis, respiration, and plant stress. In recent years, emerging technologies such as multi-omics, high-throughput technologies, and genome editing tools could assist plant physiologists in unraveling molecular mechanisms in specific critical pathways. The global picture of physiological processes in plants needs to be investigated continually to increase our knowledge, and the resulting technologies will benefit sustainable agriculture.",coverUrl:"https://cdn.intechopen.com/series_topics/covers/13.jpg",keywords:"Plant Nutrition, Plant Hormone, Photosynthesis, Respiration, Plant Stress, Multi-omics, High-throughput Technology, Genome Editing"}],annualVolumeBook:{},thematicCollection:[],selectedSeries:null,selectedSubseries:null},seriesLanding:{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 16th, 2022",hasOnlineFirst:!0,numberOfOpenTopics:4,numberOfPublishedChapters:124,numberOfPublishedBooks:13,editor:{id:"131400",title:"Prof.",name:"Alfonso J.",middleName:null,surname:"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},subseries:[{id:"3",title:"Bacterial Infectious Diseases",keywords:"Antibiotics, Biofilm, Antibiotic Resistance, Host-microbiota Relationship, Treatment, Diagnostic Tools",scope:"