Frequency in % of CF patients with diabetes in 2018.
\r\n\tFurthermore, during the preparation of high-quality dairy products, several physical, chemical, enzymatic, and microbial transformations take place. We will consciously focus on this interaction of different constituents of milk under different processing conditions for the development of the products.
",isbn:"978-1-83768-093-1",printIsbn:"978-1-83768-092-4",pdfIsbn:"978-1-83768-094-8",doi:null,price:0,priceEur:0,priceUsd:0,slug:null,numberOfPages:0,isOpenForSubmission:!0,isSalesforceBook:!1,hash:"420e687768b56ca7b3238d77f63f1302",bookSignature:"Dr. Neelam Upadhyay",publishedDate:null,coverURL:"https://cdn.intechopen.com/books/images_new/12173.jpg",keywords:"Protein, Fat, Lactose, Carbohydrates, Milk Processing, Milk Products, Milk Constituents, Acid Coagulated, Enzyme Treated, Heat Treated, Dairy Products, Protocols of Manufacturing",numberOfDownloads:null,numberOfWosCitations:0,numberOfCrossrefCitations:null,numberOfDimensionsCitations:null,numberOfTotalCitations:null,isAvailableForWebshopOrdering:!0,dateEndFirstStepPublish:"May 18th 2022",dateEndSecondStepPublish:"June 15th 2022",dateEndThirdStepPublish:"August 14th 2022",dateEndFourthStepPublish:"November 2nd 2022",dateEndFifthStepPublish:"January 1st 2023",remainingDaysToSecondStep:"a month",secondStepPassed:!1,currentStepOfPublishingProcess:2,editedByType:null,kuFlag:!1,biosketch:"Dr. Upadhyay has received many awards most notable being the Young Woman Scientist Award 2020 from the Agro-Environmental Development Society and the Best Poster Award 2021 from the National Conference on Moringa Food Conclave 2021. She is a dedicated researcher in food and dairy processing and has published many research articles and papers in both national and international journals and publications.",coeditorOneBiosketch:null,coeditorTwoBiosketch:null,coeditorThreeBiosketch:null,coeditorFourBiosketch:null,coeditorFiveBiosketch:null,editors:[{id:"269538",title:"Dr.",name:"Neelam",middleName:null,surname:"Upadhyay",slug:"neelam-upadhyay",fullName:"Neelam Upadhyay",profilePictureURL:"https://mts.intechopen.com/storage/users/269538/images/system/269538.jpg",biography:"BRIEF BIODATA\n1.\tName in full: Neelam Upadhyay \n2.\tDate & Place of Birth: 29th December, 1987 at Delhi\n3.\tField of specialization: Food Technology\n4.\tPresent Position/ Designation: Scientist- Senior Scale\n5.\tAddress:\t(a)\tOfficial:\tTel. No.:0184-2259258\n\t\t\t\tE-mail: \ticar.neelam@gmail.com; neelam.upadhyay@icar.gov.in \n\t\t\t\tAddress: \tLaboratory No. 146, Dairy Technology Division, ICAR- \n\t\t\t\t\t\tNational Dairy Research Institute, Karnal \n\t\t\t(b)\tResidential: Tel. No.: +91-9255772587\n\tAddress (Permanent): 41-D, MIG DDA Flats, Shivam Enclave, Delhi-110032\n6.\t(a) Academic career and (b) professional attainments\n(a) Examination\tClass/ Percentage\tYear of Passing\tSubjects Taken\tName of University / Board\nXth \t1st/83\n(415/500)\t2003\tMathematics, Social Science, Science, English, Hindi\tK.V., Mumbai (CBSE)\nXIIth\t1st/78.2 \n(391/500)\t2005\tPhysics, Mathematics, Chemistry, Biology, English\tK.V., Delhi (CBSE)\nB.A.Sc. (Hons.)\t1st/83.43 (2044/2450)\n(3rd position)\t2008\tFood Technology\tSRCASW, University of Delhi, Delhi\nM.Sc.\t1st/8.62\n(1st position)\t2010\tFood Science & Technology\tCCS Har. Agri. Uni., Hisar, Haryana\nTitle of Research:\tDevelopment of flavoured whey-soya milk beverage\nMajor Advisor:\tDr. R. S. Dabur (Professor and Head)\nPh.D.\t1st/8.0\n(1st position)\t2014\tDairy Chemistry\tNational Dairy Research Institute, Karnal, Haryana\nTitle of Research: \tDetection of vegetable oil and animal body fat adulteration in ghee using solvent fractionation technique\nMajor Advisor:\tDr. Darshan Lal (Principal Scientist and Ex-Head)\nDistinctions during Academics\nDegree\tDistinctions\nBachelor of Applied Science (Hons.)\ti.\tY.K. Kapoor Memorial Scholarship 2006 by All India Food Processor’s Association \nii.\t3rd position in university\niii.\tReceived highest attendance award\niv.\tReceived trophy for ‘Most Disciplined Student’ for the graduation period 2005-2008\nv.\tCertificate of Honor from Honb’le Mr. Justice K.G. Balakrishnan, Chief Justice of India\nMaster of Science\ti.\t1st position in discipline and 2nd position in college\nii.\tReceived recognition for academic excellence from Jawaharlal Nehru Memorial Fund; \niii.\tQualified GATE\niv.\t2nd in inter-college yoga competition\nv.\tParticipated in various events of All India Youth Festival organized at UAS, Bangalore.\nDoctor of Philosophy\ti.\tReceived Merit Certificate for Academic Excellence in PhD course work\nii.\tReceived Certificate of Appreciation for outstanding work in the field of Dairy Processing during PhD\niii.\tQualified ICAR’s National Eligibility Test in 2010; Qualified the ICAR’s All India Examination, ICAR-SRF (PGS_-2011-2012 for award of ICAR-SRF (PGS) with 2nd rank (both in first attempt) \niv.\tQualified Agricultural Research Service Examination-2013 conducted by Agricultural Scientist Recruitment Board against the single vacancy (for UR) in the discipline of Food Technology\nv.\tStage Management Secretary of student’s council 2010-11\nvi.\tLiterary secretary of Student’s Council 2011-12\nvii.\tCompleted certificate e-course on “Publishing a Journal Manuscript - the Groundwork” directed by Springer in 2013\nviii.\tHave successfully completed certificate e-course – “Peer Review Academy” directed by Springer in 2013\nix.\tReceived a certificate on accomplishment IRIS 4-2 Information Literacy Plagiarism Quiz (on-line) in 2013 developed by Distance Learning Council of Washington, USA \n (b) Position Held\tInstitution \tPeriod of Appointment\tNature of Appointment\nScientist (Food Technology)\tICAR- National Academy of Agricultural Research Management, Hyderabad\t3 months\n(1st January, 2015 till 31st March, 2015)\tPermanent\n(Received ‘A’ grade for FOCARS)\nScientist \n(Food Technology)\tICAR- National Dairy Research Institute, Karnal\t10th March, 2015 till 31st December, 2018\n(after availing 10 days of transfer period)\tPermanent\nScientist-Senior Scale\n(Food Technology)\tICAR- National Dairy Research Institute, Karnal\t1st January, 2019 till date\tPermanent\n\n7. Special attainments in Research\n(https://scholar.google.co.in/citations?hl=en&user=PRz0Tz4AAAAJ&view_op=list_works&sortby=pubdate)\nPublications\tNumbers\tRemarks \nResearch Articles\t35\n(24 Intl, 9 National, 2 others)\tTotal Impact: 72.302\n\nBook Chapters\t7\t5 APA/CRC Press; 1 InTech Open; \n1 National\nReview Articles\t2\tTotal Impact:8.327\nTechnical Articles\t7\tCompendium of trainings, seminars, etc\nInstitute publication\t1\t\nPopular Article\t12\t6 in English; 5 in hindi\nCitations \t1066\t(as per googlescholar)\nH-index/ i10-index\t15/ 17\t\n.\n.\nJournal\tNumber of publications\tImpact factor\nResearch Articles\t35\t72.302\nInternational\t24 (15 as either corresponding or first author)\t72.302\nNational\t9 (3 as first or corresponding author)\tNAAS score\nOthers\t2\t\nReview article (International)\t2\t8.327\nInternational\t2\t8.327\n.\n \n\n\n\nRESEARCH ARTICLES\nInternational Journals \n1.\tTiwari, S., Upadhyay, N.*, Singh, A. K. (2022). Stability assessment of emulsion of carotenoids extracted from carrot bio-waste in flaxseed oil and its application in food model system. Food Bioscience, 47, 101631. https://doi.org/10.1016/j.fbio.2022.101631.\n2.\tPatil, A. T., Meena, G. S., Upadhyay, N., Khetra, Y., Singh, A. K., & Borad, S. G. (2021). Buffalo milk protein concentrate 60: Effect of skim milk heat treatment on its reconstitutability and functionality. Food Science & Technology – Lebensmittel -Wissenschaft & Tech, 148, 111638. \n3.\tUttamrao, H. J., Meena, G. S., Khetra, Y., Upadhyay, N., Singh, A. K., Arora, S., & Borad, S. G. (2022). Homogenization and sodium hydrogen phosphate induced effect on physical and rheological properties of ultrafilterd concentrated milk. Journal of Food Science and Technology, 59(3), 956-967. \n4.\tTiwari, S., Upadhyay, N.*, Malhotra, R. (2021). Three way ANOVA for emulsion of carotenoids extracted in flaxseed oil from carrot bio-waste. Waste Management, 121, 67-76. \n5.\tRanvir, S., Sharma, R., Gandhi, K., Upadhyay, N., Mann, B. (2020). Assessment of proteolysis in ultra-high temperature milk using attenuated total reflectance–Fourier transform infrared spectroscopy. International Journal of Dairy Technology. 73(2): 366-375. doi: 10.1111/1471-0307.12683. \n6.\tPonbhagavathi, T.R., Singh, A.K., Raju, P.N., Upadhyay, N. (2020). High performance liquid chromatographic (HPLC) determination of available lysine in milk protein-maize composite extrudates and its stability during storage. Journal of the Indian Chemical Society, 97(11a), 2344-2350\n7.\tTiwari, S., Upadhyay, N.*, Singh, A. K., Meena, G. S., & Arora, S. (2019). Organic solvent-free extraction of carotenoids from carrot bio-waste and its physico-chemical properties. Journal of Food Science and Technology, 1-10. 10.1007/s13197-019-03920-5\n8.\tBaria, B., Upadhyay, N.*, Singh, A. K., & Malhotra, R. K. (2019). Optimization of ‘green’extraction of carotenoids from mango pulp using split plot design and its characterization. Food Science & Technology – Lebensmittel -Wissenschaft & Tech, 104, 186-194. \n9.\tPatil, A. T., Meena, G. S., Upadhyay, N., Khetra, Y., Borad, S. G., & Singh, A. K. (2019). Effect of change in pH, heat treatment and diafiltration on properties of medium protein buffalo milk protein concentrate. Journal of Food Science and Technology, 56(3), 1462-1472. \n10.\tUttamrao, H. J., Meena, G. S., Borad, S. G., Punjaram, S. A., Khetra, Y., Upadhyay, N., & Singh, A. K. (2019). Effect of disodium phosphate and homogenization on physico-chemical and rheological properties of buffalo skim milk based ultrafiltered retentate. Journal of food science and technology, 56(5), 2426-2435. \n11.\tMeena, G.S., Dewan, A., Upadhyay, N., Barapatre, R., Kumar, N., Singh, A.K., & Rana, J.S. (2019). Fuzzy Analysis of Sensory Attributes of Gluten Free Pasta Prepared From Brown Rice, Amaranth, Flaxseed Flours and Whey Protein Concentrates. Journal of Food Science and Nutrition Research, 2(1), 022-037. DOI: 10.26502/jfsnr.2642-1100006\n12.\tPatil, A. T., Meena, G. S., Upadhyay, N.*, Khetra, Y., Borad, S., & Singh, A. K. (2018). Production and characterization of milk protein concentrates 60 (MPC60) from buffalo milk. Food Science & Technology – Lebensmittel -Wissenschaft & Tech, 91, 368-374. https://doi.org/10.1016/j.lwt.2018.01.028 \n13.\tUpadhyay, N.*, Jaiswal, P., & Jha, S. N. (2018). Application of attenuated total reflectance Fourier Transform Infrared spectroscopy (ATR–FTIR) in MIR range coupled with chemometrics for detection of pig body fat in pure ghee (heat clarified milk fat). Journal of Molecular Structure, 1153, 275-281. \n14.\tUpadhyay, N.*, Kumar A., Goyal A. and Lal, D. (2017). Complete liquification time test coupled with solvent fractionation technique to detect adulteration of foreign fats in ghee (heat-clarified milk fat). International Journal of Dairy Technology. 70(1): 110-118. doi: 10.1111/1471-0307.12323. \n15.\tUpadhyay, N.*, Goyal A., Kumar A. and Lal, D. (2017). Detection of adulteration of caprine body fat and mixture of caprine body fat and groundnut oil in bovine and buffalo ghee using Differential Scanning Calorimetry. International Journal of Dairy Technology. 70(2): 297-303. May 2017.doi:10.1111/1471-0307.12336. \n16.\tKumar, A., Upadhyay, N.*, Ghai, D.L., Kumar, A. Gandhi, K. and Sharma, V. (2016). Effect of preparation and storage of khoa on physico-chemical properties of milk fat. International Journal of Dairy Technology. 69(2): 294-300. doi: 10.1111/1471-0307.12266. \n17.\tUpadhyay, N.*, Jaiswal, P. & Jha, S.N. (2016). Detection of goat body fat adulteration in pure ghee using ATR-FTIR spectroscopy coupled with chemometric strategy. Journal of Food Science and Technology. 53 (10): 3752-3760. doi:10.1007/s13197-016-2353-2 ISSN 0022-1155\n18.\tRathi, M., Upadhyay, N.*, Dabur, R.S. and Goyal A. (2015). Formulation and physic-chemical analysis of whey –soymilk dahi. Journal of Food Science and Technology. 52(2): 968-975. doi 10.1007/s13197-013-1074-z. ISSN: 0022-1155. \n19.\tKanthale, P., Kumar, A. Upadhyay, N.*, Lal, D., Rathod G. and Sharma, V. (2015). Qualitative test for the detection of extraneous Thiocyanate in Milk. Journal of Food Science and Technology. 52(3): 1698-1704. DOI: 10.1007/s13197-013-1174-9. ISSN: 0022-1155.\n20.\tGoyal, A., Sharma, V., Upadhyay, N., Singh, A.K., Arora, S. and Ghai, D.L. (2015). Development of stable flaxseed oil emulsions as a potential delivery system of ω-3 fatty acids. Journal of Food Science and Technology. 52(7):4256-4265. \n21.\tUpadhyay, N.*, Kumar, A., Rathod, G., Goyal, A. and Lal, D. (2015). Development of a method employing reversed-phase thin-layer chromatography for establishing milk fat purity with respect to adulteration with vegetable oils. International Journal of Dairy Technology. 68(2): 207-217. doi. 10.1111/1471-0307.12178. \n22.\tGoyal, A., Siddiqui, S. Upadhyay, N., Soni, J. (2014). Effects of ultraviolet irradiation, pulsed electric field, hot water and ethanol vapours treatment on functional properties of mung bean sprouts. Journal of Food Science and Technology. 51(4): 708-714. doi 10.1007/s13197-011-0538-2. Publisher Springer. ISSN (electronic version): 0975-8402. \n23.\tKundu, H., Grewal, R.B., Goyal, A., Upadhyay, N.*, and Prakash S. (2014). Effect of incorporation of pumpkin (Cucurbita moshchata) powder and guar gum on the rheological properties of wheat flour. Journal of Food Science and Technology. 51(10):2600-2607. DOI: 10.1007/s13197-012-0777-x. ISSN: 0022-1155. \n24.\tUpadhyay, N.*, Kumar, A., Goyal, A. and Lal, D. (2014). A planar chromatographic method to detect adulteration of vegetable oils in ghee. JPC-Journal of Planar Chromatography-Modern TLC. 27 (6): 431-437. DOI: 10.1556/JPC.27.2014.6.5 \nNational Journals\n1.\tPonbhagavathi, T. R., Singh, A. K., Raju, P. N., Upadhyay, N. (2021). Textural and Sensory Characteristics of Milk Protein-Maize Flour-based Extrudates. Journal of Agricultural Engineering, 58(2), 124-136. 10.52151/jae2021581.1740\n2.\tPonbhagavathi, T.R., Singh, A.K., Raju, P.N., Upadhyay, N. (2020). Effect of Rennet Casein and Whey Protein Concentrate on Extrusion Behavior of Maize Flour. Current Journal of Applied Science and Technology. 39(33), 16-27, Article no.CJAST.57830.\n3.\tUpadhyay, N.*, Kumar, A., Lal, D., Kant, R., & Goyal, A. (2018). Detection of groundnut oil and goat body fat adulteration in ghee using principal component analysis on fatty acid profile. Indian Journal of Dairy Science. 71(5):464-472. \n4.\tUpadhyay, N.*, Kumar, A., Gandhi, K., Goyal, A. and Lal, D. (2014). Standardization of solvent fractionation technique for detection of adulteration in ghee by enriching animal body fat and vegetable oil in different fractions. Indian Journal of Dairy Science. 67 (4):323-327.\n5.\tGandhi. K., Upadhyay, N., Aghav, A.D., Sharma, V., and Lal, D. (2014). Detection of adulteration of ghee (clarified milk fat) with palmolein and sheep body fat using Reichert-Meissl (RM) value coupled with solvent fractionation technique. Indian Journal of Dairy Science. 67(5): 387-393. Received Second Best Paper Award during 44th Dairy Industry Conference organized by ICAR-NDRI, Karnal and Indian Dairy Association from 18-20, February 2016.\n6.\tAghav, A.D., Gandhi, K., Upadhyay, N., Kumar, A. and Lal, D. (2014). A study on the physico-chemical changes occurring in the milk fat during preparation of Paneer. Indian Journal of Dairy Science. 67 (5): 398-404.\n7.\tKumar, A., Upadhyay, N., Gandhi, K., Lal, D. and Sharma, V. (2013). Detection of soybean oil and buffalo depot fat in ghee using Normal-Phase Thin Layer Chromatography. Indian Journal of Dairy Science. 66(4): 294-99. ISSN: 0019-5146.\n8.\tKumar, A., Upadhyay, N., Gandhi, K., Kumar, A., Lal, D. and Sharma, V. (2013). Reverse-Phase Thin Layer Chromatography of Unsaponifiable Matter of ghee for detecting adulteration with soybean oil and buffalo depot fat. Indian Journal of Dairy Science. 66(6): 496-501. ISSN: 0019-5146.\n9.\tUpadhyay, N.*, Dabur R.S. and Rathi, M. (2011). Development and Shelf life Study of Flavoured Whey-soya milk beverage. Indian Journal of Dairy Science. 64(2): 92-101. ISSN: 0019-5146.\nOther Journals\n1.\tDewan, A., Meena, G.S., Upadhyay, N., Barapatre, R. Singh, A.K., Rana, J.S. (2017). Formulation of non-Gluten Pasta from the Optimized levels of Dairy and Non-Dairy ingredients. Madridge Journal of Food Technology. 2(2): 92–98. \n2.\tGalmessa, U., Prasad, S., Kumaresan, A., Oberoi, P. S., Baithalu, R. K., Upadhyay, N., and Dang, A. K. (2015). Modulation of Milk Fatty acid profile milk yield and composition through supplementation of omega-3 fatty acid in transition cow’s diet. Journal of Science and Sustainable Development. 3(1): 25-38. ISSN: 2070-1748\nREVIEW ARTICLES\n1.\tUpadhyay, N.*, Goyal, A. Kumar, A., Lal, D. and Singh, D. (2014). Preservation of milk and milk products for analytical purposes: A review. Food Reviews International. 30(3):203-224. DOI 10.1080/87559129.2014.913292. ISSN: 1525-6103\n2.\tGoyal, A., Sharma, V., Upadhyay, N., Gill, S. and Sihag, M. (2014). Flax and flaxseed oil: an ancient medicine & modern functional food. Journal of Food Science and Technology. 51(9): 1633-1653. DOI 10.1007/s13197-013-1247-9. ISSN: 0975-8402. \nBOOK CHAPTERS\n1.\tKumari, L., Sharma, M., & Upadhyay, N. (2021). Three-Dimensional Printing of Food Products: Printing Techniques, Novel Applications, and Printable Food Materials. Handbook of Research on Food Processing and Preservation Technologies: Volume 3: Computer-Aided Food Processing and Quality Evaluation Techniques, 55. Boca Raton, CRC Press\n2.\tUpadhyay, N.*, Harshitha, C. G., Pathak, N. K., & Sharma, R. (2021). Fourier Transform Infrared (FTIR) Spectroscopy with Chemometrics: Evaluation of Food Quality and Safety. Handbook of Research on Food Processing and Preservation Technologies: Volume 5: Emerging Techniques for Food Processing, Quality, and Safety Assurance, 271.\n3.\tNagarajappa, V., Upadhyay, N., Chawla, R., Mishra, S.K., & Nath, S. (2019). Functional Properties of Milk Proteins. In: Engineering Practices for milk products- Dairyceuticals, Novel Technologies, and Quality (pp 3-26). Apple Academic Press.\n4.\tUpadhyay, N., Kumar, M. C. T., Sharma, H., Borad, S., & Singh, A. K. (2019). Pulse Electric Field Processing of Milk and Milk Products. In: Non-thermal Processing of Foods (pp.129-144). Boca Raton, CRC Press\n5.\tUpadhyay, N., Nagaraj, V., & Singh, A. K. (2019). Advances in Fractionation of Milk Lipids: Analysis and Applications of fractions In: Recent Technologies in Dairy Science (pp. 325-344). Today and Tomorrow’s Printers and Publishers.\n6.\tNagaraj, V., Upadhyay, N.*, Nath, B. S., & Singh, A. K. (2018). Advances in Fractionation and Analysis of Milk Carbohydrates. In Technological Approaches for Novel Applications in Dairy Processing (pp. 127-147). IntechOpen. http://dx.doi.org/10.5772/intechopen.76312\n7.\tUpadhyay, N.*, Veena, N., Borad, S., & Singh, A. K. (2017). Application of Natural Antioxidants in Dairy Foods. In Natural Antioxidants (pp. 281-318). London: Apple Academic Press.\nINSTITUTE PUBLICATION\n1.\tDr. T. K. Datta, Dr. Meena Malik and Dr. Neelam Upadhyay (2017). Foundation Programme for Freshers at ICAR-NDRI 2017.\nPOPULAR AND LEAD ARTICLES\n1.\tPatil, A. T., Meena, G. S., Upadhyay, N., & Singh, A.K. (2017). Milk protein concentrates- Their Applications. Indian Dairyman, 69(9), 44-48.\n2.\tUpadhyay, N.* and R.K. Malik (2015). Nutritive Value of Milk. In: In Touch, Heinz Nutrition Foundation of India. Volume 17, Number 2&3, 2-11. (Lead Article). \n3.\tGoyal, A., Sharma, V., Upadhyay, N., Sihag, M. and Kaushik, R. (2013). High Pressure Processing and its impact on milk proteins: A Review. Research and Reviews: Journal of Dairy Science and Technology. 2 (1): 1-9. ISSN: 2319-3409.\n4.\tKumar, A., Upadhyay, N., and Naagar, S. (2012). Allergenicity of Milk Proteins, and its Management. Indian Food Industry. 31 (5&6): 45-50. ISSN: 0972-2610.\n5.\tGoyal, A. and Upadhyay, N. (2012). Nuclear Magnetic Resonance Spectroscopy in Dairy Science. Indian Food Industry. 31(1): 39-45. ISSN: 0972-2610.\n6.\tUpadhyay, N.*, Goyal, A. and Rathod, G. (2011). Microwave Spectroscopy and its applications in online processing. Indian Food Industry. 30(5&6): 63-73. ISSN: 0972-2610.\n7.\tउपाध्याय, नी*. (२०१८) भारत में कुपोषण: स्थिति और इससे निपटने के लिए रणनीतियाँ. दुग्ध—गंगा (आठवाँ अंक). अप्रैल-सितम्बर. २४-२९. \n8.\tउपाध्याय, नी.*, सिंह, आ.कु., गांगुली, स., सबिखी, ल. (२०१८) खाध्य और डेयरी क्षेत्र मे महिला उद्यमिता: कारण, समस्याए एवम उपलब्ध मंच. दुग्ध—गंगा (आठवाँ अंक). अप्रैल-सितम्बर. ६४-६९.\n9.\tउपाध्याय, नी*. (२०१९) ek¡ dk nw/k % f'k'kqvksa ds ekufld] 'kkjhfjd ,oa lkekftd mRFkku gsrq ve`r. दुग्ध—गंगा (नवाँ अंक). अकटूबर –मार्च १०२-१०४.\n10.\tउपाध्याय, नी*, fç;k ;koys (२०१९) [kk| inkFkksaZ esa —f=e ds cnys çk—frd jax o.kZd ds mi;ksx dh vko';drk दुग्ध—गंगा (दसवाँ अंक). अकटूबर –मार्च १०२-१०५.\n11.\tuhye mikè;k;, fuys'k dqekj ikBd (२०१९) d`f\"k] [kk| ,oa Ms;jh m|ksx ds Hkfo\"; eas lkSj ÅtkZ dk egRo दुग्ध—गंगा (दसवाँ अंक). अकटूबर –मार्च १२६-१३०. \n12.\tवैज्ञानिक और तकनीकी विषय के मूल हिंदी लेख जोकि गेहूँ एवम् जौ स्वर्णिमा में प्रकाशित हुए: उपाध्याय, नी*, राकेश कुमार (2020) महिला उद्यमिता के माध्यम से महिला सशक्तिकरण. गेहूँ एवम् जौ स्वर्णिमा (बारहवााँ अंक), पृष्ठ सं. 55-58; भाकृअनुप- भारतीय गेहूँ एवम् जौ अनुसंधान संस्थान, करनाल- १३२००१ द्वारा प्रकाशित\n\n8. Concepts/Processes/Products/Technologies/Patents/Others\n(i)\tConcepts \nCurrently, I am working on the integrated approach of application of green technology for the development of functional foods by utilizing under-utilized/ indigenous fruits and vegetables and/ or bio-waste. In the research projects, I am also keenly working on food chemistry and instrumental food analysis and applications of technologies/ products in dairy and non-dairy products. \nBesides this, I am working on development of functional food for addressing menopausal symptoms in osteopenic mice model. \n(ii)\tProducts/ Technologies ready for commercialization- 5\n1. Production of Milk Protein Concentrate 60 (MPC60), a high protein low lactose powder from buffalo milk (Co-Inventor)\n2. Technology for omega-3 rich mixed fat table spread (Inventor)\n3. Lipid and water soluble yellow natural colouring ingredient from bio-waste (Inventor)\n4. Technology for preparation of encapsulated flaxseed oil for its applications in foods (Inventor)\n5. Production of buffalo milk based Milk Protein Concentrate 60 (MPC60) powder with improved solubility (Co-Inventor)\n(iii) Expertise on\n1.Gas Liquid Chromatography\t5.Thin Layer Chromatography\n2.Fourier Transform Infra-red Spectroscopy\t6. Spectrophotometry\n3.Differential Scanning Calorimetry\t7.Chemical analysis including titration, distillation, etc.\n4.High Pressure Liquid Chromatography\t\n\n\n9. List of completed, on-going and submitted projects\nTitle of Project\tDuration\tRole\tFunding\tStatus\tRemarks\nEffect of storage on Baudouin test, sesamin test and RP-TLC test to detect adulteration of vanaspati and vegetable oils in ghee\t2015-2017\tCo-PI\tICAR-NDRI\n\tCompleted\tTwo research articles on RP-TLC\nPreparation and Characterization of Micro/nano delivery systems for “green” carotenoids\t2016-2019\tPI\t-Do-\t\t3 research articles+ 3 products/ technologies\nTechnology Development for the Production of Milk Protein Concentrate (MPC60) From Buffalo Milk\t2016-2019\tCo-PI\t-Do-\t\t4 research articles+ 2 products/ technologies\nTechnology of Goat Milk based Functional Beverage\t2017-2020\tCo-PI\t-Do-\t\tOne oral presentation\nTechnology for Moringa oleifera enriched cheese spread\t2020-2023\tPI\t-Do-\tOn-going\tCharacterization and incorporation of M. oleifera- pods in cheese spread is complete; shelf life study and animal trial is in progress\nDevelopment of flaxseed-rich probiotic dairy foods to address menopause symptoms\t2020-2023\tCo-PI\tDST\t\tDeveloped method -estimation of phytoestrogen; validation -in progress\nNutritional and therapeutic validation of chhachh and ghee prepared from indigenous cows by traditional method\tThree years (proposed)\tPI\tSEED Division, DST\tSubmitted \n \t\nCharacterization of Moringa oleifera leaves for functional bioactives and its application in table spread as model food system\tThree years (proposed)\tPI\tSYST, DST\t\t\nOther research work: \nDetection of adulteration of goat body fat and pig body fat in ghee using ATR-FTIR coupled with chemometrics; carried out during Professional Attachment Training at ICAR-CIPHET, Ludhiana\n\n\n\n10. Awards & honours \nName of Award\tYear\tAwarding Agency\nBest Paper Award\t2022\tGSAT (Gender Advancement for Transforming Institutions Self-Assessment Team), NDRI\nBest Poster Award\t2021\tNational Conference on Moringa Food Conclave-2021\nYoung Woman Scientist Award\t2020\tAgro Environmental Development Society during International Web-conference \nSecond Best Poster Award\t2020\tIndian Dairy Association\nCommendation certificate for Institute’s Magazine in which I am co-Editor\t2020\tTown Official Language Implementation Committee, Karnal\nLetter of Appreciation to editorial board of Institute’s magazine for receiving ICAR’s Second Prize and Trophy under Ganesh Shankar Vidyarthi Hindi Patrika Puraskar (2018-19)\t2020\tICAR- National Dairy Research Institute, Karnal\nAssociate Fellowship\t2019\tNational Academy of Dairy Science India\nFirst Prize in E-poster \t2018\tIndian Dairy Association\nOne Best oral Presentation\t2018\tHome Science Association of India\nBest Oral Presentation to my Master’s student\t2018\tICMR- National Institute of Nutrition\nBest Poster Award\t2016\tIndian Dairy Association\nSecond Best Paper Award\t2016\tIndian Dairy Association\nICAR-SRF (PGS) with 2nd rank\t2011-12\tICAR\nGATE (Engg Sciences: Food Tech; Thermodynamics)\t2010\tMHRD, GoI\nInstitution level awards\nThird prize in poster presentation \t2021\tICAR- National Dairy Research Institute, Karnal\nInstitute’s Rajbhasha Gaurav Certificate\t2020\t\nFirst prize in Scientific and Technical writing\t2019\t\nConsolation prize in Scientific and Technical writing \t2020, 2019 \t\nFirst prize in Poster Presentation- 2020, 2018, 2017\t\t\nThird prize in poster presentation\t2019\t\nFirst Prize in hindi extempore\t2017\t\nThird, first and second prize in hindi essay writing in consecutive years – 2020, 2019, 2018\t\t\n\n\n11. Teaching Assignments \n(a) Teaching: Actively involved either as course in-charge or associate \nClass\tB.Tech (DT)\tMSc/ MTech\n(FT) (till 2021)\tM.Tech (DT)\tPhD (DT/ DC/ FSQA)\nNo. of courses\t1-2\t2-3\t0-1\t2-3\nDT- Dairy Technology, DC- Dairy Chemistry, FT- Food Technology, FSQA- Food Safety Quality Assurance\n(b) Student’s guided\nDegree\tMajor Advisor \tCo-Advisory\tStatus/ Remarks\nM. Tech (DT)\t8\t2\tCompleted\n\t1\t0\tOn going\nM. Tech/ M Sc (FT/ FSN)\t2\t1\tCompleted\nM. Tech (DC)\t0\t3\tCompleted\nM. Tech (DM)\t0\t1\tCompleted\nPhD (DT)\t2 \t0\tOngoing \n\t0\t2\tCompleted\nPhD (DC)\t0\t1 \tCompleted\n\t\t1\tOn going\ni.\tThree students under my guidance as major advisor and one student as co-advisory member nominated for Best thesis award; \nii.\tOne represented NDRI at zonal-level student research convention ANVESHAN-2018\n\n12. Lectures/ member/convener of committees: \ni.\tLectures: \na.\tEntrepreneurship Development Programme (EDP) (conducted by SINED-TBI/BPD unit, ICAR-NDRI) and Online Training of Master Trainers on Fat and Oilseed processing conducted by SINED-TBI/BPD unit (ICAR-CIPHET); \nb.\tStudent’s Counselling session at SRCASW, University of Delhi, \nc.\tWorkshop conducted at DAV college, Karnal, etc\nd.\tDelivered talks at various villages on the importance of mother’s milk, nutrition in first 1000 days of an infant’s life, nutri-thali, etc\nii.\tTraining Organized: \na.\tTwenty one days Training at Centre for Advanced Faculty Training (DT Division) on ‘R & D strategies and interventions for effective agribusiness and entrepreneurship development in dairy and food sector’; \nb.\tone/two months or shorter duration trainings for students and others under BPD unit and KVK, NDRI, Karnal\nc.\tFive days training on the aspects of dairy processing to the farmers of Karnal district. \niii.\tGeneral Secretary, Staff Club, NDRI, Karnal\niv.\tMember: Student Empowerment Unit, Conferences organized from 2015 till 2018, convocation, credit seminar evaluation committees; Mera Gaon Mera Gaurav program, Farmer’s First Door programme, Swatchh Bharat Abhiyan, coordinator and mentor of different groups for organizing Foundation Program-2017, 2018, Nodal officer of Poshan Maah-2020 etc\nv.\tConvener/ Rapporteur of sessions: Conference, Dr. K. K. Iya Memorial oration; International conference of Proteomics Society of India\nvi.\tOther responsibilities: Management Representative of QMS-IS/ISO 9001:2008 and HACCP- IS 15000:2013 of Experimental Dairy (essential part of institute) until Jan 2019; one of the editors of Institute hindi magazine Dudgh Ganga which also received coveted award from ICAR (until 2019).\nvii.\tResource Generation on account of consultancy provided in field of dairy processing and by conducting sponsored trainings \nMore than ₹ 2 50 000/- (Two lakhs fifty thousand only)\nviii.\tBesides research, teaching and extension activities, I am also involved in promotion of Hindi language and have won several prizes during competitions (like extempore, essay, e-mail writing) organized by Official Language Units.\nix.\tLifetime Member of three scientific bodies: Indian Dairy Association- RE/NZ/LM/10852/HR; Association of Food Scientists & Technologists (INDIA)- AFST/LM/9-2018/KRN/2444; Lifetime member of Home Science Association of India; Membership number: HSAI-2017-HR-127-LF\nx.\tReviewed research papers of Journal of Ayurveda and Integrative Medicine (Elsevier), LWT, International Journal of Food Properties, Indian Journal of Dairy Science, Indian Journal of Natural Products and Resources, United Scientific Group, etc. \n\n\n\n\n\n\n\n\nDated: 12-04-2022\t \nNeelam Upadhyay",institutionString:"National Dairy Research Institute",position:null,outsideEditionCount:0,totalCites:0,totalAuthoredChapters:"0",totalChapterViews:"0",totalEditedBooks:"0",institution:{name:"National Dairy Research Institute",institutionURL:null,country:{name:"India"}}}],coeditorOne:null,coeditorTwo:null,coeditorThree:null,coeditorFour:null,coeditorFive:null,topics:[{id:"5",title:"Agricultural and Biological Sciences",slug:"agricultural-and-biological-sciences"}],chapters:null,productType:{id:"1",title:"Edited Volume",chapterContentType:"chapter",authoredCaption:"Edited by"},personalPublishingAssistant:{id:"444312",firstName:"Sara",lastName:"Tikel",middleName:null,title:"Ms.",imageUrl:"https://mts.intechopen.com/storage/users/444312/images/20015_n.jpg",email:"sara.t@intechopen.com",biography:"As an Author Service Manager, my responsibilities include monitoring and facilitating all publishing activities for authors and editors. 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Rath",authors:[{id:"59158",title:"Dr.",name:"Eitan Z.",middleName:null,surname:"Rath",fullName:"Eitan Z. Rath",slug:"eitan-z.-rath"}]},{id:"23842",title:"Steroid Induced Glaucoma",slug:"steroid-induced-glaucoma",signatures:"Avraham Cohen",authors:[{id:"61596",title:"Dr.",name:"Avraham",middleName:null,surname:"Cohen",fullName:"Avraham Cohen",slug:"avraham-cohen"}]},{id:"23843",title:"Glaucoma in Cases of Penetrating Keratoplasty, Lamellar Procedures and Keratoprosthesis",slug:"glaucoma-in-cases-of-penetrating-keratoplasty-lamellar-procedures-and-keratoprosthesis",signatures:"Shimon Rumelt",authors:[{id:"54335",title:"Dr.",name:"Shimon",middleName:null,surname:"Rumelt",fullName:"Shimon Rumelt",slug:"shimon-rumelt"}]}]}],publishedBooks:[{type:"book",id:"360",title:"Electroretinograms",subtitle:null,isOpenForSubmission:!1,hash:"bfbc5538173f11acb0f9549a85b70488",slug:"electroretinograms",bookSignature:"Gregor Belusic",coverURL:"https://cdn.intechopen.com/books/images_new/360.jpg",editedByType:"Edited by",editors:[{id:"44595",title:"Dr.",name:"Gregor",surname:"Belusic",slug:"gregor-belusic",fullName:"Gregor Belusic"}],equalEditorOne:null,equalEditorTwo:null,equalEditorThree:null,productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}},{type:"book",id:"540",title:"Age Related Macular Degeneration",subtitle:"The Recent Advances in Basic Research and Clinical Care",isOpenForSubmission:!1,hash:"457bf890ed1e947a2ed23fc8237e34f0",slug:"age-related-macular-degeneration-the-recent-advances-in-basic-research-and-clinical-care",bookSignature:"Gui-Shuang Ying",coverURL:"https://cdn.intechopen.com/books/images_new/540.jpg",editedByType:"Edited by",editors:[{id:"86603",title:"Dr.",name:"Gui-Shuang",surname:"Ying",slug:"gui-shuang-ying",fullName:"Gui-Shuang Ying"}],equalEditorOne:null,equalEditorTwo:null,equalEditorThree:null,productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}},{type:"book",id:"666",title:"Diabetic Retinopathy",subtitle:null,isOpenForSubmission:!1,hash:"cc9ab3a3c861825692bb9eea670aea2e",slug:"diabetic-retinopathy",bookSignature:"Mohammad Shamsul Ola",coverURL:"https://cdn.intechopen.com/books/images_new/666.jpg",editedByType:"Edited by",editors:[{id:"86018",title:"Dr.",name:"Mohammad Shamsul",surname:"Ola",slug:"mohammad-shamsul-ola",fullName:"Mohammad Shamsul Ola"}],equalEditorOne:null,equalEditorTwo:null,equalEditorThree:null,productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}},{type:"book",id:"751",title:"Advances in Ophthalmology",subtitle:null,isOpenForSubmission:!1,hash:"63feda93d7fee6fb1f164a52e9f6427c",slug:"advances-in-ophthalmology",bookSignature:"Shimon Rumelt",coverURL:"https://cdn.intechopen.com/books/images_new/751.jpg",editedByType:"Edited by",editors:[{id:"54335",title:"Dr.",name:"Shimon",surname:"Rumelt",slug:"shimon-rumelt",fullName:"Shimon Rumelt"}],equalEditorOne:null,equalEditorTwo:null,equalEditorThree:null,productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}},{type:"book",id:"1203",title:"Ocular Diseases",subtitle:null,isOpenForSubmission:!1,hash:"9b689c614692d77cfec2b92eea85c9d7",slug:"ocular-diseases",bookSignature:"Adedayo Adio",coverURL:"https://cdn.intechopen.com/books/images_new/1203.jpg",editedByType:"Edited by",editors:[{id:"139912",title:"Dr.",name:"Adedayo",surname:"Adio",slug:"adedayo-adio",fullName:"Adedayo Adio"}],equalEditorOne:null,equalEditorTwo:null,equalEditorThree:null,productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}}],publishedBooksByAuthor:[]},onlineFirst:{chapter:{type:"chapter",id:"72407",title:"Cystic Fibrosis-Related Diabetes (CFRD)",doi:"10.5772/intechopen.92767",slug:"cystic-fibrosis-related-diabetes-cfrd-",body:'CF is a multi-organ disease that also affects the exocrine and endocrine pancreas [1]. CFRD is a discrete entity of type 3 Diabetes mellitus, displaying aspects from both type 1 Diabetes mellitus and type 2 Diabetes mellitus. It is the most frequent comorbidity in CF involving around 31% of CF patients older than 18 years [2] and up to more than 40% in those older than 30 years [3]. It results from involvement of the endocrine pancreatic function and is the end stage of early onset impaired glucose homeostasis [4]. Today, additional CFRD is still a risk factor for decreased pulmonary function but no longer for increased mortality [3]. In the past, an increased mortality, in part depending on sex and severe CFTR mutation, was observed [5]. Several aspects of the disease’s pathophysiology are not yet completely understood [6], but some new insights might help to understand the process [7]. Clinically, there is a need for screening since earlier prospective studies regarding CFRD showed that most CF patients exhibited no clinical signs of hyperglycemia at the time they were diagnosed with CFRD by oral glucose tolerance tests (OGTTs) [8]. The advantages and disadvantages of different screening approaches will be discussed. Even after diagnosis, there is some discussion on how to treat patients with CFRD diagnosed by screening. Guidelines recommended insulin treatment [9] but registry data from the US [2] and Europe [10] showed that a relevant proportion of CF patients with CFRD are not treated with daily insulin. Alternative treatment options might be needed, and a recent study demonstrated that oral antidiabetic drugs are not inferior to insulin regarding HbA1c over 2 years after CFRD was diagnosed by annual OGTT screening [11]. Upcoming CFTR modulator treatment is an interesting area regarding glucose homeostasis and CFRD. The results of two small case studies [12, 13] on CF patients treated with ivacaftor imply that there is a possibility that CFTR modulation might also influence insulin secretion. Additionally, a registry study showed a trend to a reduced prevalence of CFRD in those treated with ivacaftor for a longer time [14]. In another case study with five patients (F508 del homozygous) treated with lumacaftor/ivacaftor, no consistent effect on glucose tolerance or insulin secretion was observed [15]. Overall, there are a number of important aspects of CFRD, from its pathophysiology to screening, diagnosis, treatment, best methods of follow-up, and new perspectives with CFTR modulator treatment options.
In 1994, a first study reporting the prevalence of CFRD was published [16]. Prevalence was 14.7% in all Danish CF patients. More recent data from the CFF patient registry showed an age-dependent prevalence from around 2% in those younger than 10 years up to around 40–50% in adults [2]. The prevalence is in the same range as reported from Germany (Table 1) [17] as a European country. The prevalence varies between different European countries based on a recent report of the ECFS patient registry [18]. While diabetes prevalence has risen, incidence has fallen significantly: from 4 cases per 100 patient-years during the 1998–2002 interval to 2.7 cases per 100 patient-years between 2003 and 2008, representing a 40% decrease in the number of diabetes diagnoses in the US [3]. In a longitudinal study from the UK, the incidence was 3.5% (observation period 1996–2005) [19].
Severe genotype, pancreatic insufficiency, and female gender remain considerable intrinsic risk factors for early acquisition of CFRD [18]. In a large prospective study with 1093 patients, impaired fasting glucose, impaired glucose tolerance, and indeterminate glucose tolerance were all predictors of future CFRD [20] .
Diabetes in CF | 0–5 years | 6–11 yeas | 12–17 years | 18–29 years | 30–39 years | >40 years |
---|---|---|---|---|---|---|
Diabetes | 0.1 | 1.2 | 11.1 | 21.6 | 32.0 | 46.6 |
Of these CFRD | 0.0 | 100 | 86.7 | 96.5 | 94.5 | 94.3 |
Of these not CFRD | 0.1 | 0.0 | 13.3 | 3.6 | 5.5 | 5.7 |
Frequency in % of CF patients with diabetes in 2018.
Adapted from table 17 and table 18 [17].
An increased mortality used to be described mainly for female CF patients with CFRD [21]. Mortality rate decreased from 1992–1997 to 2003–2008 in females from 6.9 to 3.2 deaths per 100 patient-years and in male subjects from 6.5 to 3.8 deaths per 100 patient-years. There was no longer a sex difference in mortality [3]. A follow-up study (2008–2012) from the same CF center reported that there still was a sex difference in adults, but only in severe genotypes with higher prevalence of CFRD, resulting in an increased mortality in females [22]. Consequently, there is still a discussion about the gender influence on CFRD and survival.
Since the CF gene was detected, there has been the question of a CFTR mutation/mutation class-related risk for CFRD or whether there are other mutations outside of the CFTR gene that may modify the risk of developing CFRD.
In a longitudinal study from the UK, CFTR mutation classes I and II were shown to increase the risk of CFRD independently of other known risk factors [19]. A more recent study reported the risk for CFRD and mortality in adults studied in the years 2008–2012 [22]. CFRD was associated with increased mortality independently of mutation category (mild or severe) [22].
A study looking for CFRD frequency in different age groups and the influence of mutation classes of the CFTR gene found that the prevalence of CFRD increased with age from 2.6% in patients <18 years to 22.1% in patients 18 years or older in those homozygous for group II (including del phen 508, the most frequent CFTR mutation) mutations. It was only 1.5% in patients 18 years or older in group IV/any CFTR mutations [23]. In general, group IV mutations are less severe than class II mutations and this results also in a low risk for CFRD. If CFRD as a complication of CF has developed, there is still an increased mortality risk even in mild mutation classes (e.g., CFTR mutation class IV), but the risk for developing CFRD is higher in severe CFTR mutation classes (e.g., CFTR mutation class I or II).
The frequency of HLA types related to type 1 or type 2 diabetes were in the same range in CF patients with or without diabetes. There was also no difference in frequency compared to normal population [23]. As for other comorbidities, there are also modifiers for CFRD. Susceptibility to CFRD is at least in part determined by variants at SLC26A9 and at four loci associated with type 2 diabetes in the general population [24]. In a very recent study, a wide overlap with genetic modifiers of type 2 diabetes was described [25]. This might allow for a stratification of CFRD screening. Those with less risk depending on CFTR mutation classes and modifier genes might be screened starting at an older age and less frequently than those with a high risk for CFRD.
The mechanism of how diabetes develops in CF is not yet completely understood. Difficult access to animal models and human pancreatic tissue may contribute to this situation. Two recent reviews focused on the pathogenesis of CFRD [26, 27]. Insulin secretion is reduced even with normal OGTT and this is observed even in kids [28]. Insulin sensitivity is not or only minimally impaired apart from severe infections or systemic glucocorticoid treatment [29]. An often-discussed question concerned the possible existence of a direct influence of CFTR on α or β-cells. In an elegant study, murine models of β-cell CFTR deletion and human pancreas and islets from controls and CF patients were used [7]. There were some important results: (1) In the murine cell model, CFTR did not affect β-cell function. (2) In human islets, nearly no expression of CFTR mRNA was detected. (3) Additionally, there was no CFTR protein or electrical activity. (4) The secretion of islet hormones (insulin and glucagon) was in the normal range and only minimal changes in important islet-regulatory transcripts were detected. (5) As a consequence of inflammation, only 35% of β-cell area was conserved and the other part of the islet was compounded by immune infiltration. Overall, CFRD seems to be a consequence of beta-cell loss, accompanied by inflammation of the islets. There is no reason to think that CFTR mutations directly cause islet dysfunction [7].
As there are usually no typical diabetes-related symptoms [8], there is a need to screen for CFRD. Guidelines recommended a regular oral glucose tolerance test (OGTT) for screening [9]. Annual screening should start at the age of 10 years, as recommended in the US and by the ECFS, or at 12 years, as recommended in the UK. Because OGTT is time-consuming for patients and CF center staff, there is some interest in more comfortable alternative methods. The screening rate with OGTT in CF is nowhere near the recommendations in guidelines. In median, only 61.3% of CF patients aged 10–17 years and only 32.8% of adults were screened by OGTT in the US [2]. Nevertheless, it is possible to increase the rate of screening by OGTT, as shown from a program in a pediatric CF center that increased its annual screening rate for outpatients from 45% to 71% [30].
In a registry study, it has recently been reported that CF centers that screen more frequently for CFRD detected CFRD earlier and that those that screened less often had a faster decrease in pulmonary function [31]. This supports the view that screening for CFRD is an important tool to optimize CF care.
HbA1c is quickly collected and simple to measure, which makes it a comfortable test for both patients and CF center staff. To reduce the need for OGTT, the question was whether HbA1c was able to identify those patients at risk for CFRD. However, because of low sensitivity to detect CFRD, HbA1c has not been recommended as a screening tool for CFRD [32] for many years. This has recently become controversial. If a low HbA1c (<5.5%) as threshold was used to identify CF patients with CFRD, the sensitivity covered a wide range from 93% [33] to only 78% [34]. As of now, there is not enough evidence that HbA1c is a reliable tool to screen for CFRD.
To make OGTT more comfortable for patients and staff, different modifications of the OGTT procedure were investigated. A shorter sample time (1 h) [35, 36] was discussed, as well as a lower glucose load (50 g) [37]. Both approaches need evaluation in a larger cohort. So far, standard (WHO) OGTT is still recommended.
Another way to uncover impaired glucose homeostasis and CFRD even earlier than using OGTT is CGM. OGTTs were compared with 6 days of CGM in detecting glucose disturbance in 30 CF patients (age: 10–18 years). CGM identified glucose changes that had been missed by OGTT. This might help to initiate treatment of glucose disturbance before CFRD is diagnosed [38]. However, since even OGTT is only rarely used in many CF centers there is no reason to expect that the more sophisticated CGM will be used more frequently.
OGTT: Glucose 1.75 g/kg body weight in 250–300 ml water max 75 g glucose drinking in 5 min
Performed after >8 h of fasting in the morning.
No physical activity during the test.
Often the OGTT is done during the annual assessment. No other investigations during the OGTT (such as an ultrasound) are allowed.
Blood glucose is measured before (0 min) and 60 min and 120 min after drinking the glucose load.
Disturbance of glucose homeostasis starts early in life, CFRD being the end stage [4]. This opens the discussion on the best time to start treatment even before CFRD is diagnosed by OGTT. Insulin is the only recommended treatment. This should be accompanied by an education program and dietary advice. Despite recommendations, insulin is used only in around 75% of all CFRD patients all over the world [2, 17, 40].
Insulin is the recommended treatment for CFRD. There are two problems with this recommendation. (1) A relevant percentage of CFRD patients do not use insulin (see Table 2). This is the case in the US [2], the UK [41], and Germany [17] at least, as the national registers documented. All these are registries sponsored by CF organizations. Data from a German/Austrian general diabetes registry [42] that collects data from both CFRD patients and type 1 and 2 diabetes patients have shown that only 77% of CFRD patients were on insulin [40]. There might be several reasons for this. First of all, most patients do not realize symptoms of hyperglycemia early in the course of CFRD [8]. Secondly, CF treatment is an enormous burden for adult CF patients and families [43] as well as for children with CF. They spent 74 min a day with treatment, compared to type 1 diabetes with 56 min and asthma with 6 min [44]. Perhaps they like to avoid this additional burden of insulin treatment. (2) The optimal insulin regime is not defined and different regimes are in use. This includes long-term once-daily insulin, intensified insulin treatment several times a day, or an insulin pump with continuous insulin and pushes with meals. The more intensive insulin treatment with a pump is less in use, at least in adolescents and young adults, compared to type 1 diabetes patients in the same age range [45]. In adult CFRD patients treated with insulin, the mean daily dose was not different to matched type 1 or type 2 diabetes patients [46].
Blood glucose mmol/l (mg/dl) | |||
---|---|---|---|
Start | 60 min | 120 min | |
Normal glucose tolerance (NGT) | <5·6 (100) | <11·1 (200) | <7·8 (140) |
Fasting hyperglycemia (FH) | >5·6 (100) and <7·0 (126) | <11·1 (200) | <7·8 (140) |
Impaired glucose tolerance (IGT) | <7·0 (126) | <11·1 (200) | >7·8 (140) <11·1 (200) |
Indeterminate glycemia (INDET) | <7·0 (126 ) | >11·1 (200) | <7·8 (140) |
Diabetes (CFRD) without FH | <7·0 (126) | – | >11·1 (200) |
CFRD with FH | ≥7·0 (126) | – | >11·1 (200) |
One single optimal insulin regime for all CFRD patients does not exist, since individual adjustment to medical needs and patients’ options is required. The treatment of CFRD is a team approach including dieticians, diabetologists, psychologists, and the CF physician.
Oral antidiabetic drugs have been used in CFRD for many years [47]. The group of sulfonylurea (glibenclamide) had some disadvantages. They showed inhibitions of CFTR Cl channels in vitro [48, 49, 50]. The non-sulfonylurea hypoglycemic agent repaglinide showed only a weak inhibition of CFTR Cl channels [51]. In 2001, a study was published that showed postprandial effects of premeal insulin lispro and premeal repaglinide on postprandial glucose levels in humans. Glucose decreased (peak, 2 h and 5 h AUC) with insulin lispro, and glucose decreased with repaglinide only 5 h AUC. Insulin secretion (5 h AUC) increased only with insulin lispro [52]. In the latest Cochrane review regarding the use of oral antidiabetic drugs in CFRD, published in 2016, it was concluded that controlled prospective studies are needed [53]. There are two prospective randomized controlled trials comparing the effects of insulin versus repaglinide in patients with newly diagnosed CFRD [11, 54]. In a 12-month trial, there was a significant increase in BMI only in the insulin group. Comparing the insulin to the repaglinide group, there was no significant difference in BMI, HbA1c, or pulmonary function changes over the study period [54]. In the other study over 24 months, there was no difference between the groups (insulin and repaglinide) regarding HbA1c, BMI, and pulmonary function. It was concluded from that study that at least a subgroup of patients with newly diagnosed CFRD can be treated initially with oral antidiabetic drugs [11]. This might be an option for those who refuse insulin due to the additional treatment burden (Table 3).
Indication therapy in case of CFRD | 0–5 years | 6–11 yeas | 12–17 years | 18–29 years | 30–39 years | >40 years |
---|---|---|---|---|---|---|
Insulin | 100 | 72.7 | 64.0 | 67.6 | 76.9 | 75.7 |
Oral antidiabetics | 0 | 9.1 | 11.0 | 9.3 | 9.3 | 8.8 |
Dietary measures | 0 | 27.3 | 39.0 | 21 | 25 | 23.3 |
Frequency in % of CF patients with indication therapies related to diabetes in 2018.
Adapted from table 22 and table 23 [17].
The well-known diet restrictions and advice for type 1 or type 2 diabetes are not transferable to CFRD. In CFRD, the patients need a high-caloric nutrition, in contrast to what is recommended in other types of diabetes. Therefore, a dietician trained in CFRD is needed to support the patient with detailed information regarding nutrition in the special situation of CFRD [55].
HbA1c is not recommended to diagnose CFRD (see Section 4.1.1.). The situation is different for monitoring CFRD. HbA1c is used to monitor glycemic control in CFRD. In CFRD, the target value for HbA1c should be lower than in type 1 diabetes, because in CFRD mean plasma glucose does not correlate with HbA1c [56]. This is, for example, incorporated in the Australian Standards of Care for CFRD [57]. Adults with CFRD have a significantly lower HbA1c value compared to type 1 diabetes adults (6.8% vs. 7.9%) [58]. How low HbA1c values should be to prevent long-term diabetic comorbidities like microangiopathies (see also Section 6.1) is unknown.
A more strict control of glucose homeostasis with insulin treatment is achievable with CGM and is accompanied by an improved clinical outcome [59]. This requires the cooperation of the entire CFRD team and particularly the support by a diabetologist.
In general, adherence to diabetes care guidelines (ADA/CFF) is suboptimal [40] and improvement is urgently needed.
With decreased mortality, CF patients spend more years living with CFRD. Today, CF patients tend to develop microvascular complications, much like patients with type 1 or type 2 diabetes [60]. In long-standing CFRD (>10 years) with fasting hyperglycemia, 14% of patients had microalbuminuria and 16% had retinopathy [61]. The percentage of patients with hypertension was lower in adult CFRD patients while the percentage of patients suffering from nephropathy was higher compared to type 1 and 2 diabetes [58]. These data underline the need for routine screening for CFRD complications.
More sophisticated eye investigations demonstrated changes at the retina level.
Screening for this kind of complication should be also mandatory [62]. Percentage of patients with retinopathy did not differ between adults with CFRD and type 1 or type 2 diabetes [58].
Macrovascular complications have not been described so far. However, with increasing duration of CFRD in older CF patients, this kind of complication has to be expected. Even microvascular complications develop later in CFRD than in other types of diabetes.
The risk for acute severe hyperglycemia exists but the condition is very rare [63]. Most CFRD patients do not develop a ketoacidosis. This might be related to residual insulin secretion and glucagon counter regulation. Hyperglycemia measured by HbA1c is a risk factor for mortality. In a prospective observational study, a HbA1c ≥ 6.5% was associated with a threefold increased risk of death [64]. Measuring HbA1c is mandatory and it should be kept in mind that the target value is lower than in type 1 or type 2 diabetes (see also Section 5.2.1).
The detected frequency of hypoglycemia is higher with CGM than with OGTT [65]. There is no prognostic relevance of hypoglycemia during OGT for later development of CFRD [66]. In general, it seems that the risk of hypoglycemia is not different from other types of diabetes and instruction on how to handle CFRD in daily life should address this risk.
With improved clinical course of CF and improved life expectancy, more female CF patients want to become pregnant. According to the UK guidelines [55], there are four groups.
CFRD and IGT: optimized diabetes control and needs to be referred to a specialized diabetes team.
NGT (tested in the last 3 months): OGT in first trimester and the next between week 24 and week 28.
Unknown glycemic status: OGT before becoming pregnant, if possible.
With better clinical conditions, physical activities in all age groups of CF patients increased. Patients with CFRD should exercise and be educated about the risk of hypoglycemia, like other diabetic patients. CFRD is no reason to stop physical activities.
Since 2012, there is a new class of medication for CF patients on the market. These drugs are called “CFTR modulators.” They are CFTR mutation specific and are administered orally. This offers the chance that these drugs might affect different organs that are reached by the bloodstream. The regulation of glucose homeostasis is a complex process and CFTR modulators might interfere at different steps.
Ivacaftor is a CFTR potentiator and acts with gating mutations (e.g., G551D). It increases pulmonary function, weight, and quality of life (QoL) and decreases sweat chloride concentration [67].
In two siblings, insulin secretion and glucose AUC were measured during an OGTT before and 16 weeks after initiation of ivacaftor [12]. This paper described the beneficial effect of 4-month ivacaftor treatment on the pathologic OGTT of two patients with CF carrying the S549R gating mutation. This beneficial effect may be partially due to the increased earlier insulin secretion capacity [12]. Two other studies also reported an increase in insulin secretion after ivacaftor was initiated in CF patients with a gating mutation [68, 69]. As of now, reports have included only small numbers of patients and/or are uncontrolled studies. Sufficiently powered studies are still missing. In a registry study using data from the US and the UK with a follow-up of more than 5 years, a trend to a reduced prevalence of CFRD in ivacaftor-treated patients [14] was reported. If this observation will be corroborated in future studies, many CF patients would benefit from a postponed CFRD treatment burden.
The combination therapy with ivacaftor/lumacaftor was administered to patients with the del F508 mutation [70]. The overall clinical effect regarding pulmonary function, weight, and QoL was low compared to ivacaftor in patients with a gating mutation [67]. Using CGM and OGTT to control glucose homeostasis in five patients after initiation of ivacaftor/lumacaftor treatment, glycemic abnormalities persisted [71]. A consistent impact of the combination of ivacaftor/lumacaftor on insulin secretion or glucose tolerance was not detected in five patients [15]. In a very recent article from France [72], the change of OGTT categories after 1 year of lumacaftor/ivacaftor treatment was described in an uncontrolled study design. The reported improvement, for example, from CFRD to IGT is within the range of the well-known high variability of OGTT results in CF patients [73]. It is not surprising that the combination treatment, which had less of an effect on clinical outcome in gating mutations compared to ivacaftor, has so far no proven effect on CFRD, even if only a small number of CF patients were investigated.
The recently published results with a triple combination CFTR modulator therapy in patients with a del phen 508 allele are impressive regarding pulmonary function increase, sweat chloride decrease, and other outcomes [74]. With a highly clinically effective CFTR modulator treatment and a sufficient number of patients, the demonstration of a positive influence on glucose homeostasis in a prospective study seems realistic.
However, there is currently no evidence-based information that CFTR modulators have a relevant influence on the complex pathophysiology regarding glucose homeostasis.
CFRD is still a highly relevant comorbidity in CF. Nevertheless, there are many questions regarding its optimal handling from both patients’ and physicians’ point of view. CFRD is a team approach, which includes the CF team but also the diabetes team.
Adherence to all aspects of CFRD diagnosis and treatment is low and needs urgent efforts to increase.
As long as no better screening procedure is established, 2h of OGTT should be used annually as screening for CFRD.
Education regarding CFRD should include patients, families, physicians, and the entire team.
Treatment as recommended by guidelines prefers only insulin. The recently published controlled prospective trials may endorse the use of oral antidiabetic drugs, at least in a subgroup of patients.
Monitoring must include all the measurements that are recommended for other types of diabetes. HbA1c target value for treatment should be lower than in type 1 or 2 diabetes.
Typical microvascular complications are reported and patients should be regularly checked for these.
In future, the new and effective CFTR modulator therapies might also influence the prevalence of CFRD. In a perfect world, they might also improve glucose homeostasis in patients with CFRD and postpone CFRD entirely.
The authors declare no conflict of interest.
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Since then, numerous applications were developed with the implementation of Kalman filter, such as applications in the fields of navigation and computer vision's object tracking. Kalman filter consists of two separate processes, namely the prediction process and the measurement process, which work in a recursive manner. Both processes are modeled by groups of equations in the state space model to achieve optimal estimation outputs. Prior knowledge on the state space model is needed, and it differs between different systems. In this chapter, the authors outlined and explained the fundamental Kalman filtering model in real‐time discrete form and devised two real‐time applications that implemented Kalman filter. The first application involved using vision camera to perform real‐time image processing for vehicle tracking, whereas the second application discussed the real‐time Global Positioning System (GPS)‐aided Strapdown Inertial Navigation Unit (SINU) system implementation using Kalman filter. Detail descriptions, model derivations, and results are outlined in both applications.",book:{id:"5254",slug:"real-time-systems",title:"Real-time Systems",fullTitle:"Real-time Systems"},signatures:"Lim Chot Hun, Ong Lee Yeng, Lim Tien Sze and Koo Voon Chet",authors:[{id:"162863",title:"Dr.",name:"Lim",middleName:null,surname:"Chot Hun",slug:"lim-chot-hun",fullName:"Lim Chot Hun"},{id:"162864",title:"Dr.",name:"Lim",middleName:null,surname:"Tien Sze",slug:"lim-tien-sze",fullName:"Lim Tien Sze"},{id:"162865",title:"Prof.",name:"Koo",middleName:null,surname:"Voon Chet",slug:"koo-voon-chet",fullName:"Koo Voon Chet"},{id:"181409",title:"Ms.",name:"Lee Yeng",middleName:null,surname:"Ong",slug:"lee-yeng-ong",fullName:"Lee Yeng Ong"}]},{id:"50530",doi:"10.5772/63033",title:"A Real-Time Bilateral Teleoperation Control System over Imperfect Network",slug:"a-real-time-bilateral-teleoperation-control-system-over-imperfect-network",totalDownloads:1524,totalCrossrefCites:1,totalDimensionsCites:1,abstract:"Functionality and performance of modern machines are directly affected by the implementation of real-time control systems. Especially in networked teleoperation applications, force feedback control and networked control are two of the most important factors, which determine the performance of the whole system. In force feedback control, generally it is necessary but difficult and expensive to attach sensors (force/torque/pressure sensors) to detect the environment information in order to drive properly the feedback force. In networked control, there always exist inevitable random time-varying delays and packet dropouts, which may degrade the system performance and, even worse, cause the system instability. Therefore in this chapter, a study on a real-time bilateral teleoperation control system (BTCS) over an imperfect network is discussed. First, current technologies for teleoperation as well as BTCSs are briefly reviewed. Second, an advanced concept for designing a bilateral teleoperation networked control (BTNCS) system is proposed, and the working principle is clearly explained. Third, an approach to develop a force-sensorless feedback control (FSFC) is proposed to simplify the sensor requirement in designing the BTNCS, while the correct sense of interaction between the slave and the environment can be ensured. Fourth, a robust-adaptive networked control (RANC)-based master controller is introduced to deal with control of the slave over the network containing both time delays and information loss. Case studies are carried out to evaluate the applicability of the suggested methodology.",book:{id:"5254",slug:"real-time-systems",title:"Real-time Systems",fullTitle:"Real-time Systems"},signatures:"Truong Quang Dinh, Jong Il Yoon, Cheolkeun Ha and James\nMarco",authors:[{id:"168437",title:"Prof.",name:"Cheolkeun",middleName:null,surname:"Ha",slug:"cheolkeun-ha",fullName:"Cheolkeun Ha"},{id:"181747",title:"Dr.",name:"Truong Quang",middleName:null,surname:"Dinh",slug:"truong-quang-dinh",fullName:"Truong Quang Dinh"},{id:"185978",title:"Dr.",name:"Jong Il",middleName:null,surname:"Yoon",slug:"jong-il-yoon",fullName:"Jong Il Yoon"},{id:"185979",title:"Prof.",name:"James",middleName:null,surname:"Marco",slug:"james-marco",fullName:"James Marco"}]},{id:"50636",doi:"10.5772/62632",title:"Real‐Time Reconfiguration of Distribution Network with Distributed Generation",slug:"real-time-reconfiguration-of-distribution-network-with-distributed-generation",totalDownloads:1868,totalCrossrefCites:2,totalDimensionsCites:1,abstract:"This chapter shows a methodology to accomplish the real‐time reconfiguration of distribution networks considering distributed generation in normal operating conditions. The availability of the wind power generation, solar photovoltaic power generation, and hydroelectric power generation is considered in the reconfiguration procedure. The real‐time reconfiguration methodology is based on the branch‐exchange technique and assumes that only remote‐controlled switches are considered in the analysis. The multicriteria analysis, analytic hierarchy process (AHP) method, is used to determine the best switching sequence. The developed algorithms are integrated into a supervisory system, which allows real‐time communication with the network equipment. The methodology is verified in a real network of a power utility in Brazil with different typical daily demand curves and distributed generation scenarios.",book:{id:"5254",slug:"real-time-systems",title:"Real-time Systems",fullTitle:"Real-time Systems"},signatures:"Daniel Bernardon, Ana Paula Carboni de Mello and Luciano\nPfitscher",authors:[{id:"180154",title:"Dr.",name:"Daniel",middleName:"P",surname:"Bernardon",slug:"daniel-bernardon",fullName:"Daniel Bernardon"},{id:"181139",title:"MSc.",name:"Ana",middleName:null,surname:"Mello",slug:"ana-mello",fullName:"Ana Mello"},{id:"181140",title:"Dr.",name:"Luciano",middleName:null,surname:"Pfitscher",slug:"luciano-pfitscher",fullName:"Luciano Pfitscher"}]},{id:"50267",doi:"10.5772/62679",title:"Wireless Real-Time Monitoring System for the Implementation of Intelligent Control in Subways",slug:"wireless-real-time-monitoring-system-for-the-implementation-of-intelligent-control-in-subways",totalDownloads:1681,totalCrossrefCites:1,totalDimensionsCites:1,abstract:"This chapter looks into the technical features of state-of-the-art wireless sensors networks for environmental monitoring. Technology advances in low-power and wireless devices have made the deployment of those networks more and more affordable. In addition, wireless sensor networks have become more flexible and adaptable to a wide range of situations. Hence, a framework for their correct implementation will be provided. Then, one specific application about real-time environmental monitoring in support of a model-based predictive control system installed in a metro station will be described. In these applications, filtering, resampling, and post-processing functions must be developed, in order to convert raw data into a dataset arranged in the right format, so that it can inform the algorithms of the control system about the current state of the domain under control. Finally, the whole architecture of the model-based predictive control and its final performances will be reported.",book:{id:"5254",slug:"real-time-systems",title:"Real-time Systems",fullTitle:"Real-time Systems"},signatures:"Alessandro Carbonari, Massimo Vaccarini, Mikko Valta and\nMaddalena Nurchis",authors:[{id:"10486",title:"Dr.",name:"Alessandro",middleName:null,surname:"Carbonari",slug:"alessandro-carbonari",fullName:"Alessandro Carbonari"},{id:"150738",title:"Dr.",name:"Massimo",middleName:null,surname:"Vaccarini",slug:"massimo-vaccarini",fullName:"Massimo Vaccarini"},{id:"185509",title:"Dr.",name:"Mikko",middleName:null,surname:"Valta",slug:"mikko-valta",fullName:"Mikko Valta"},{id:"185510",title:"Dr.",name:"Maddalena",middleName:null,surname:"Nurchis",slug:"maddalena-nurchis",fullName:"Maddalena Nurchis"}]},{id:"50400",doi:"10.5772/62691",title:"Uniform Interfaces for Resource-Sharing Components in Hierarchically Scheduled Real-Time Systems",slug:"uniform-interfaces-for-resource-sharing-components-in-hierarchically-scheduled-real-time-systems",totalDownloads:1454,totalCrossrefCites:0,totalDimensionsCites:0,abstract:"In literature, several hierarchical scheduling frameworks (HSFs) have been proposed for enabling resource sharing between components on a uni-processor system. Each HSF comes with its own set of composition rules which take into account a specific synchronization protocol for arbitrating access to resources. However, the inventors of these synchronization protocols have also chosen to describe these composition rules with the help of protocol-specific component interfaces. This creates unnecessary framework dependencies on components.",book:{id:"5254",slug:"real-time-systems",title:"Real-time Systems",fullTitle:"Real-time Systems"},signatures:"Martijn M. H. P. van den Heuvel, Reinder J. Bril, Johan J. 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The first application involved using vision camera to perform real‐time image processing for vehicle tracking, whereas the second application discussed the real‐time Global Positioning System (GPS)‐aided Strapdown Inertial Navigation Unit (SINU) system implementation using Kalman filter. Detail descriptions, model derivations, and results are outlined in both applications.",book:{id:"5254",slug:"real-time-systems",title:"Real-time Systems",fullTitle:"Real-time Systems"},signatures:"Lim Chot Hun, Ong Lee Yeng, Lim Tien Sze and Koo Voon Chet",authors:[{id:"162863",title:"Dr.",name:"Lim",middleName:null,surname:"Chot Hun",slug:"lim-chot-hun",fullName:"Lim Chot Hun"},{id:"162864",title:"Dr.",name:"Lim",middleName:null,surname:"Tien Sze",slug:"lim-tien-sze",fullName:"Lim Tien Sze"},{id:"162865",title:"Prof.",name:"Koo",middleName:null,surname:"Voon Chet",slug:"koo-voon-chet",fullName:"Koo Voon Chet"},{id:"181409",title:"Ms.",name:"Lee Yeng",middleName:null,surname:"Ong",slug:"lee-yeng-ong",fullName:"Lee Yeng Ong"}]},{id:"50400",title:"Uniform Interfaces for Resource-Sharing Components in Hierarchically Scheduled Real-Time Systems",slug:"uniform-interfaces-for-resource-sharing-components-in-hierarchically-scheduled-real-time-systems",totalDownloads:1456,totalCrossrefCites:0,totalDimensionsCites:0,abstract:"In literature, several hierarchical scheduling frameworks (HSFs) have been proposed for enabling resource sharing between components on a uni-processor system. Each HSF comes with its own set of composition rules which take into account a specific synchronization protocol for arbitrating access to resources. However, the inventors of these synchronization protocols have also chosen to describe these composition rules with the help of protocol-specific component interfaces. This creates unnecessary framework dependencies on components.",book:{id:"5254",slug:"real-time-systems",title:"Real-time Systems",fullTitle:"Real-time Systems"},signatures:"Martijn M. H. P. van den Heuvel, Reinder J. Bril, Johan J. Lukkien, Moris Behnam and Thomas Nolte",authors:[{id:"116304",title:"Prof.",name:"Johan",middleName:null,surname:"Lukkien",slug:"johan-lukkien",fullName:"Johan Lukkien"},{id:"138504",title:"Dr.",name:"Reinder",middleName:"Jaap",surname:"Bril",slug:"reinder-bril",fullName:"Reinder Bril"},{id:"180341",title:"Dr.",name:"Martijn",middleName:null,surname:"Van Den Heuvel",slug:"martijn-van-den-heuvel",fullName:"Martijn Van Den Heuvel"},{id:"181808",title:"Dr.",name:"Moris",middleName:null,surname:"Behnam",slug:"moris-behnam",fullName:"Moris Behnam"},{id:"181809",title:"Prof.",name:"Thomas",middleName:null,surname:"Nolte",slug:"thomas-nolte",fullName:"Thomas Nolte"}]},{id:"50530",title:"A Real-Time Bilateral Teleoperation Control System over Imperfect Network",slug:"a-real-time-bilateral-teleoperation-control-system-over-imperfect-network",totalDownloads:1524,totalCrossrefCites:1,totalDimensionsCites:1,abstract:"Functionality and performance of modern machines are directly affected by the implementation of real-time control systems. Especially in networked teleoperation applications, force feedback control and networked control are two of the most important factors, which determine the performance of the whole system. In force feedback control, generally it is necessary but difficult and expensive to attach sensors (force/torque/pressure sensors) to detect the environment information in order to drive properly the feedback force. In networked control, there always exist inevitable random time-varying delays and packet dropouts, which may degrade the system performance and, even worse, cause the system instability. Therefore in this chapter, a study on a real-time bilateral teleoperation control system (BTCS) over an imperfect network is discussed. First, current technologies for teleoperation as well as BTCSs are briefly reviewed. Second, an advanced concept for designing a bilateral teleoperation networked control (BTNCS) system is proposed, and the working principle is clearly explained. Third, an approach to develop a force-sensorless feedback control (FSFC) is proposed to simplify the sensor requirement in designing the BTNCS, while the correct sense of interaction between the slave and the environment can be ensured. Fourth, a robust-adaptive networked control (RANC)-based master controller is introduced to deal with control of the slave over the network containing both time delays and information loss. Case studies are carried out to evaluate the applicability of the suggested methodology.",book:{id:"5254",slug:"real-time-systems",title:"Real-time Systems",fullTitle:"Real-time Systems"},signatures:"Truong Quang Dinh, Jong Il Yoon, Cheolkeun Ha and James\nMarco",authors:[{id:"168437",title:"Prof.",name:"Cheolkeun",middleName:null,surname:"Ha",slug:"cheolkeun-ha",fullName:"Cheolkeun Ha"},{id:"181747",title:"Dr.",name:"Truong Quang",middleName:null,surname:"Dinh",slug:"truong-quang-dinh",fullName:"Truong Quang Dinh"},{id:"185978",title:"Dr.",name:"Jong Il",middleName:null,surname:"Yoon",slug:"jong-il-yoon",fullName:"Jong Il Yoon"},{id:"185979",title:"Prof.",name:"James",middleName:null,surname:"Marco",slug:"james-marco",fullName:"James Marco"}]},{id:"50267",title:"Wireless Real-Time Monitoring System for the Implementation of Intelligent Control in Subways",slug:"wireless-real-time-monitoring-system-for-the-implementation-of-intelligent-control-in-subways",totalDownloads:1683,totalCrossrefCites:1,totalDimensionsCites:1,abstract:"This chapter looks into the technical features of state-of-the-art wireless sensors networks for environmental monitoring. Technology advances in low-power and wireless devices have made the deployment of those networks more and more affordable. In addition, wireless sensor networks have become more flexible and adaptable to a wide range of situations. Hence, a framework for their correct implementation will be provided. Then, one specific application about real-time environmental monitoring in support of a model-based predictive control system installed in a metro station will be described. In these applications, filtering, resampling, and post-processing functions must be developed, in order to convert raw data into a dataset arranged in the right format, so that it can inform the algorithms of the control system about the current state of the domain under control. Finally, the whole architecture of the model-based predictive control and its final performances will be reported.",book:{id:"5254",slug:"real-time-systems",title:"Real-time Systems",fullTitle:"Real-time Systems"},signatures:"Alessandro Carbonari, Massimo Vaccarini, Mikko Valta and\nMaddalena Nurchis",authors:[{id:"10486",title:"Dr.",name:"Alessandro",middleName:null,surname:"Carbonari",slug:"alessandro-carbonari",fullName:"Alessandro Carbonari"},{id:"150738",title:"Dr.",name:"Massimo",middleName:null,surname:"Vaccarini",slug:"massimo-vaccarini",fullName:"Massimo Vaccarini"},{id:"185509",title:"Dr.",name:"Mikko",middleName:null,surname:"Valta",slug:"mikko-valta",fullName:"Mikko Valta"},{id:"185510",title:"Dr.",name:"Maddalena",middleName:null,surname:"Nurchis",slug:"maddalena-nurchis",fullName:"Maddalena Nurchis"}]},{id:"50459",title:"Real-Time Systems",slug:"real-time-systems",totalDownloads:1332,totalCrossrefCites:0,totalDimensionsCites:0,abstract:"Since 2004, most of chip vendors have begun to shift their major focus from single-core to multi-core architecture (W. Wolf. Signal Processing Magazine, IEEE, 26(6):50–54, 2009). One major reason of this shift is that it reaches a physical limit by scaling transistor size and increasing the clock frequency to improve the computing performance on a single-core architecture (Agarwal et al. Proceedings of the 27th International Symposium on, pages 248–259, June 2000), that is, the overall chip cannot be reached within a single clock cycle. Multi-core architecture, however, brings innovative and promising opportunities to further improve the computing performance. By providing multiple processing cores on a single chip, multi-core systems can dramatically increase the computing performance and mitigate the power and thermal issues with the same performance achievement as single-core systems. As multi-core architecture has been more and more dominant in the industrial market, there is an urgent demand for effective and efficient techniques for the design of multi-core systems.",book:{id:"5254",slug:"real-time-systems",title:"Real-time Systems",fullTitle:"Real-time Systems"},signatures:"Ming Fan",authors:[{id:"180345",title:"Dr.",name:"Ming",middleName:null,surname:"Fan",slug:"ming-fan",fullName:"Ming Fan"}]}],onlineFirstChaptersFilter:{topicId:"753",limit:6,offset:0},onlineFirstChaptersCollection:[],onlineFirstChaptersTotal:0},preDownload:{success:null,errors:{}},subscriptionForm:{success:null,errors:{}},aboutIntechopen:{},privacyPolicy:{},peerReviewing:{},howOpenAccessPublishingWithIntechopenWorks:{},sponsorshipBooks:{sponsorshipBooks:[],offset:0,limit:8,total:null},allSeries:{pteSeriesList:[],lsSeriesList:[],hsSeriesList:[],sshSeriesList:[],testimonialsList:[]},series:{item:{id:"14",title:"Artificial Intelligence",doi:"10.5772/intechopen.79920",issn:"2633-1403",scope:"Artificial Intelligence (AI) is a rapidly developing multidisciplinary research area that aims to solve increasingly complex problems. In today's highly integrated world, AI promises to become a robust and powerful means for obtaining solutions to previously unsolvable problems. This Series is intended for researchers and students alike interested in this fascinating field and its many applications.",coverUrl:"https://cdn.intechopen.com/series/covers/14.jpg",latestPublicationDate:"May 18th, 2022",hasOnlineFirst:!0,numberOfPublishedBooks:9,editor:{id:"218714",title:"Prof.",name:"Andries",middleName:null,surname:"Engelbrecht",slug:"andries-engelbrecht",fullName:"Andries Engelbrecht",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bRNR8QAO/Profile_Picture_1622640468300",biography:"Andries Engelbrecht received the Masters and PhD degrees in Computer Science from the University of Stellenbosch, South Africa, in 1994 and 1999 respectively. He is currently appointed as the Voigt Chair in Data Science in the Department of Industrial Engineering, with a joint appointment as Professor in the Computer Science Division, Stellenbosch University. Prior to his appointment at Stellenbosch University, he has been at the University of Pretoria, Department of Computer Science (1998-2018), where he was appointed as South Africa Research Chair in Artifical Intelligence (2007-2018), the head of the Department of Computer Science (2008-2017), and Director of the Institute for Big Data and Data Science (2017-2018). In addition to a number of research articles, he has written two books, Computational Intelligence: An Introduction and Fundamentals of Computational Swarm Intelligence.",institutionString:null,institution:{name:"Stellenbosch University",institutionURL:null,country:{name:"South Africa"}}},editorTwo:null,editorThree:null},subseries:{},overviewPageOFChapters:[],overviewPagePublishedBooks:[],openForSubmissionBooks:{},onlineFirstChapters:{},subseriesFiltersForOFChapters:[],publishedBooks:{},subseriesFiltersForPublishedBooks:[],publicationYearFilters:[],authors:{paginationCount:148,paginationItems:[{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:null},{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:"Polytechnic University of Timişoara",institution:{name:"Polytechnic University of Timişoara",country:{name:"Romania"}}},{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:null},{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:"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. 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