Different tracers identified in IM‐SLN.
\\n\\n
IntechOpen was founded by scientists, for scientists, in order to make book publishing accessible around the globe. Over the last two decades, this has driven Open Access (OA) book publishing whilst levelling the playing field for global academics. Through our innovative publishing model and the support of the research community, we have now published over 5,700 Open Access books and are visited online by over three million academics every month. These researchers are increasingly working in broad technology-based subjects, driving multidisciplinary academic endeavours into human health, environment, and technology.
\\n\\nBy listening to our community, and in order to serve these rapidly growing areas which lie at the core of IntechOpen's expertise, we are launching a portfolio of Open Science journals:
\\n\\nAll three journals will publish under an Open Access model and embrace Open Science policies to help support the changing needs of academics in these fast-moving research areas. There will be direct links to preprint servers and data repositories, allowing full reproducibility and rapid dissemination of published papers to help accelerate the pace of research. Each journal has renowned Editors in Chief who will work alongside a global Editorial Board, delivering robust single-blind peer review. Supported by our internal editorial teams, this will ensure our authors will receive a quick, user-friendly, and personalised publishing experience.
\\n\\n"By launching our journals portfolio we are introducing new, dedicated homes for interdisciplinary technology-focused researchers to publish their work, whilst embracing Open Science and creating a unique global home for academics to disseminate their work. We are taking a leap toward Open Science continuing and expanding our fundamental commitment to openly sharing scientific research across the world, making it available for the benefit of all." Dr. Sara Uhac, IntechOpen CEO
\\n\\n"Our aim is to promote and create better science for a better world by increasing access to information and the latest scientific developments to all scientists, innovators, entrepreneurs and students and give them the opportunity to learn, observe and contribute to knowledge creation. Open Science promotes a swifter path from research to innovation to produce new products and services." Alex Lazinica, IntechOpen founder
\\n\\nIn conclusion, Natalia Reinic Babic, Head of Journal Publishing and Open Science at IntechOpen adds:
\\n\\n“On behalf of the journal team I’d like to thank all our Editors in Chief, Editorial Boards, internal supporting teams, and our scientific community for their continuous support in making this portfolio a reality - we couldn’t have done it without you! With your support in place, we are confident these journals will become as impactful and successful as our book publishing program and bring us closer to a more open (science) future.”
\\n\\nWe invite you to visit the journals homepage and learn more about the journal’s Editorial Boards, scope and vision as all three journals are now open for submissions.
\\n\\nFeel free to share this news on social media and help us mark this memorable moment!
\\n\\n\\n"}]',published:!0,mainMedia:{caption:"",originalUrl:"/media/original/237"}},components:[{type:"htmlEditorComponent",content:'
After years of being acknowledged as the world's leading publisher of Open Access books, today, we are proud to announce we’ve successfully launched a portfolio of Open Science journals covering rapidly expanding areas of interdisciplinary research.
\n\n\n\nIntechOpen was founded by scientists, for scientists, in order to make book publishing accessible around the globe. Over the last two decades, this has driven Open Access (OA) book publishing whilst levelling the playing field for global academics. Through our innovative publishing model and the support of the research community, we have now published over 5,700 Open Access books and are visited online by over three million academics every month. These researchers are increasingly working in broad technology-based subjects, driving multidisciplinary academic endeavours into human health, environment, and technology.
\n\nBy listening to our community, and in order to serve these rapidly growing areas which lie at the core of IntechOpen's expertise, we are launching a portfolio of Open Science journals:
\n\nAll three journals will publish under an Open Access model and embrace Open Science policies to help support the changing needs of academics in these fast-moving research areas. There will be direct links to preprint servers and data repositories, allowing full reproducibility and rapid dissemination of published papers to help accelerate the pace of research. Each journal has renowned Editors in Chief who will work alongside a global Editorial Board, delivering robust single-blind peer review. Supported by our internal editorial teams, this will ensure our authors will receive a quick, user-friendly, and personalised publishing experience.
\n\n"By launching our journals portfolio we are introducing new, dedicated homes for interdisciplinary technology-focused researchers to publish their work, whilst embracing Open Science and creating a unique global home for academics to disseminate their work. We are taking a leap toward Open Science continuing and expanding our fundamental commitment to openly sharing scientific research across the world, making it available for the benefit of all." Dr. Sara Uhac, IntechOpen CEO
\n\n"Our aim is to promote and create better science for a better world by increasing access to information and the latest scientific developments to all scientists, innovators, entrepreneurs and students and give them the opportunity to learn, observe and contribute to knowledge creation. Open Science promotes a swifter path from research to innovation to produce new products and services." Alex Lazinica, IntechOpen founder
\n\nIn conclusion, Natalia Reinic Babic, Head of Journal Publishing and Open Science at IntechOpen adds:
\n\n“On behalf of the journal team I’d like to thank all our Editors in Chief, Editorial Boards, internal supporting teams, and our scientific community for their continuous support in making this portfolio a reality - we couldn’t have done it without you! With your support in place, we are confident these journals will become as impactful and successful as our book publishing program and bring us closer to a more open (science) future.”
\n\nWe invite you to visit the journals homepage and learn more about the journal’s Editorial Boards, scope and vision as all three journals are now open for submissions.
\n\nFeel free to share this news on social media and help us mark this memorable moment!
\n\n\n'}],latestNews:[{slug:"webinar-introduction-to-open-science-wednesday-18-may-1-pm-cest-20220518",title:"Webinar: Introduction to Open Science | Wednesday 18 May, 1 PM CEST"},{slug:"step-in-the-right-direction-intechopen-launches-a-portfolio-of-open-science-journals-20220414",title:"Step in the Right Direction: IntechOpen Launches a Portfolio of Open Science Journals"},{slug:"let-s-meet-at-london-book-fair-5-7-april-2022-olympia-london-20220321",title:"Let’s meet at London Book Fair, 5-7 April 2022, Olympia London"},{slug:"50-books-published-as-part-of-intechopen-and-knowledge-unlatched-ku-collaboration-20220316",title:"50 Books published as part of IntechOpen and Knowledge Unlatched (KU) Collaboration"},{slug:"intechopen-joins-the-united-nations-sustainable-development-goals-publishers-compact-20221702",title:"IntechOpen joins the United Nations Sustainable Development Goals Publishers Compact"},{slug:"intechopen-signs-exclusive-representation-agreement-with-lsr-libros-servicios-y-representaciones-s-a-de-c-v-20211123",title:"IntechOpen Signs Exclusive Representation Agreement with LSR Libros Servicios y Representaciones S.A. de C.V"},{slug:"intechopen-expands-partnership-with-research4life-20211110",title:"IntechOpen Expands Partnership with Research4Life"},{slug:"introducing-intechopen-book-series-a-new-publishing-format-for-oa-books-20210915",title:"Introducing IntechOpen Book Series - A New Publishing Format for OA Books"}]},book:{item:{type:"book",id:"10961",leadTitle:null,fullTitle:"Computational Statistics and Applications",title:"Computational Statistics and Applications",subtitle:null,reviewType:"peer-reviewed",abstract:"Nature evolves mainly in a statistical way. Different strategies, formulas, and conformations are continuously confronted in the natural processes. Some of them are selected and then the evolution continues with a new loop of confrontation for the next generation of phenomena and living beings. Failings are corrected without a previous program or design. The new options generated by different statistical and random scenarios lead to solutions for surviving the present conditions. This is the general panorama for all scrutiny levels of the life cycles. Over three sections, this book examines different statistical questions and techniques in the context of machine learning and clustering methods, the frailty models used in survival analysis, and other studies of statistics applied to diverse problems.",isbn:"978-1-83969-783-8",printIsbn:"978-1-83969-782-1",pdfIsbn:"978-1-83969-784-5",doi:"10.5772/intechopen.95652",price:119,priceEur:129,priceUsd:155,slug:"computational-statistics-and-applications",numberOfPages:206,isOpenForSubmission:!1,isInWos:null,isInBkci:!1,hash:"1c6b5b7c26b825d27383de72ec2e34f1",bookSignature:"Ricardo López-Ruiz",publishedDate:"April 6th 2022",coverURL:"https://cdn.intechopen.com/books/images_new/10961.jpg",numberOfDownloads:730,numberOfWosCitations:0,numberOfCrossrefCitations:0,numberOfCrossrefCitationsByBook:0,numberOfDimensionsCitations:1,numberOfDimensionsCitationsByBook:0,hasAltmetrics:1,numberOfTotalCitations:1,isAvailableForWebshopOrdering:!0,dateEndFirstStepPublish:"April 14th 2021",dateEndSecondStepPublish:"May 30th 2021",dateEndThirdStepPublish:"July 25th 2021",dateEndFourthStepPublish:"September 29th 2021",dateEndFifthStepPublish:"November 28th 2021",currentStepOfPublishingProcess:5,indexedIn:"1,2,3,4,5,6,7",editedByType:"Edited by",kuFlag:!1,featuredMarkup:null,editors:[{id:"9849",title:"Prof.",name:"Ricardo",middleName:null,surname:"López-Ruiz",slug:"ricardo-lopez-ruiz",fullName:"Ricardo López-Ruiz",profilePictureURL:"https://mts.intechopen.com/storage/users/9849/images/system/9849.jpeg",biography:"Ricardo López-Ruiz, MS, Ph.D., is an associate professor in the Department of Computer Science and Systems Engineering, Faculty of Science, University of Zaragoza, Spain. He is also an associate researcher in Complex Systems at the School of Mathematics, University of Zaragoza. Previously, he worked as a lecturer at the University of Navarra, the Public University of Navarra, and UNED Calatayud, all in Spain. He completed his postdoc with Prof. Yves Pomeau at the École Normale Supérieure, Paris, France, and with Prof. Gabriel Mindlin at the University of Buenos Aires, Argentina. His areas of interest include statistical complexity and nonlinear models, chaotic maps and applications, multiagent systems, econophysics, big data, and artificial intelligence techniques.",institutionString:"University of Zaragoza",position:null,outsideEditionCount:0,totalCites:0,totalAuthoredChapters:"3",totalChapterViews:"0",totalEditedBooks:"6",institution:{name:"University of Zaragoza",institutionURL:null,country:{name:"Spain"}}}],equalEditorOne:null,equalEditorTwo:null,equalEditorThree:null,coeditorOne:null,coeditorTwo:null,coeditorThree:null,coeditorFour:null,coeditorFive:null,topics:[{id:"613",title:"Statistics",slug:"numerical-analysis-and-scientific-computing-statistics"}],chapters:[{id:"79248",title:"A New Functional Clustering Method with Combined Dissimilarity Sources and Graphical Interpretation",doi:"10.5772/intechopen.100124",slug:"a-new-functional-clustering-method-with-combined-dissimilarity-sources-and-graphical-interpretation",totalDownloads:108,totalCrossrefCites:0,totalDimensionsCites:0,hasAltmetrics:0,abstract:"Clustering is an essential task in functional data analysis. In this study, we propose a framework for a clustering procedure based on functional rankings or depth. Our methods naturally combine various types of between-cluster variation equally, which caters to various discriminative sources of functional data; for example, they combine raw data with transformed data or various components of multivariate functional data with their covariance. Our methods also enhance the clustering results with a visualization tool that allows intrinsic graphical interpretation. Finally, our methods are model-free and nonparametric and hence are robust to heavy-tailed distribution or potential outliers. The implementation and performance of the proposed methods are illustrated with a simulation study and applied to three real-world applications.",signatures:"Wenlin Dai, Stavros Athanasiadis and Tomáš Mrkvička",downloadPdfUrl:"/chapter/pdf-download/79248",previewPdfUrl:"/chapter/pdf-preview/79248",authors:[{id:"416961",title:"Associate Prof.",name:"Tomáš",surname:"Mrkvička",slug:"tomas-mrkvicka",fullName:"Tomáš Mrkvička"},{id:"421027",title:"Dr.",name:"Wenlin",surname:"Dai",slug:"wenlin-dai",fullName:"Wenlin Dai"},{id:"421028",title:"MSc.",name:"Stavros",surname:"Athanasiadis",slug:"stavros-athanasiadis",fullName:"Stavros Athanasiadis"}],corrections:null},{id:"80606",title:"Computational Statistics with Dummy Variables",doi:"10.5772/intechopen.101460",slug:"computational-statistics-with-dummy-variables",totalDownloads:42,totalCrossrefCites:0,totalDimensionsCites:0,hasAltmetrics:0,abstract:"Cluster analysis is a technique commonly used to group objects and then further analysis is carried out to obtain a model, named cluster integration. This process can be continued with various analyzes, including path analyzes, discriminant analyzes, logistics, etc. In this chapter, the author discusses the reason to use dummy variables in this type of cluster analysis. Dummy variables are the main way that categorical variables are included as predictors in modeling. With statistical models such as linear regression, one of the dummy variables needs to be excluded, otherwise the predictor variables are perfectly correlated. Thus, usually if a categorical variable can take k values, we only need k-1 dummy variables, the k-th variable being redundant, it does not bring any new information. When more dummy variables than needed are used this is known as dummy variable trapping. The advantage to use dummy variables is that they are simple to use and the decision making process is easier to manage. The novelty in this chapter is the perspective of the dummy variable technique using cluster analysis in statistical modeling. The data used in this study is an assessment of the provision of credit risk at a bank in Indonesia. All analyzes were carried out using software R.",signatures:"Adji Achmad Rinaldo Fernandes, Solimun and Nurjannah",downloadPdfUrl:"/chapter/pdf-download/80606",previewPdfUrl:"/chapter/pdf-preview/80606",authors:[{id:"417477",title:"Dr.",name:"Adji Achmad Rinaldo",surname:"Fernandes",slug:"adji-achmad-rinaldo-fernandes",fullName:"Adji Achmad Rinaldo Fernandes"},{id:"418021",title:"Dr.",name:"Solimun",surname:null,slug:"solimun",fullName:"Solimun null"},{id:"418022",title:"Dr.",name:"Nurjannah",surname:null,slug:"nurjannah",fullName:"Nurjannah null"}],corrections:null},{id:"79053",title:"Sparse Boosting Based Machine Learning Methods for High-Dimensional Data",doi:"10.5772/intechopen.100506",slug:"sparse-boosting-based-machine-learning-methods-for-high-dimensional-data",totalDownloads:92,totalCrossrefCites:0,totalDimensionsCites:0,hasAltmetrics:0,abstract:"In high-dimensional data, penalized regression is often used for variable selection and parameter estimation. However, these methods typically require time-consuming cross-validation methods to select tuning parameters and retain more false positives under high dimensionality. This chapter discusses sparse boosting based machine learning methods in the following high-dimensional problems. First, a sparse boosting method to select important biomarkers is studied for the right censored survival data with high-dimensional biomarkers. Then, a two-step sparse boosting method to carry out the variable selection and the model-based prediction is studied for the high-dimensional longitudinal observations measured repeatedly over time. Finally, a multi-step sparse boosting method to identify patient subgroups that exhibit different treatment effects is studied for the high-dimensional dense longitudinal observations. This chapter intends to solve the problem of how to improve the accuracy and calculation speed of variable selection and parameter estimation in high-dimensional data. It aims to expand the application scope of sparse boosting and develop new methods of high-dimensional survival analysis, longitudinal data analysis, and subgroup analysis, which has great application prospects.",signatures:"Mu Yue",downloadPdfUrl:"/chapter/pdf-download/79053",previewPdfUrl:"/chapter/pdf-preview/79053",authors:[{id:"416901",title:"Dr.",name:"Mu",surname:"Yue",slug:"mu-yue",fullName:"Mu Yue"}],corrections:null},{id:"79594",title:"Fast Computation of the EM Algorithm for Mixture Models",doi:"10.5772/intechopen.101249",slug:"fast-computation-of-the-em-algorithm-for-mixture-models",totalDownloads:100,totalCrossrefCites:0,totalDimensionsCites:1,hasAltmetrics:0,abstract:"Mixture models become increasingly popular due to their modeling flexibility and are applied to the clustering and classification of heterogeneous data. The EM algorithm is largely used for the maximum likelihood estimation of mixture models because the algorithm is stable in convergence and simple in implementation. Despite such advantages, it is pointed out that the EM algorithm is local and has slow convergence as the main drawback. To avoid the local convergence of the EM algorithm, multiple runs from several different initial values are usually used. Then the algorithm may take a large number of iterations and long computation time to find the maximum likelihood estimates. The speedup of computation of the EM algorithm is available for these problems. We give the algorithms to accelerate the convergence of the EM algorithm and apply them to mixture model estimation. Numerical experiments examine the performance of the acceleration algorithms in terms of the number of iterations and computation time.",signatures:"Masahiro Kuroda",downloadPdfUrl:"/chapter/pdf-download/79594",previewPdfUrl:"/chapter/pdf-preview/79594",authors:[{id:"419698",title:"Dr.",name:"Masahiro",surname:"Kuroda",slug:"masahiro-kuroda",fullName:"Masahiro Kuroda"}],corrections:null},{id:"79845",title:"Dependent Dirichlet Processes for Analysis of a Generalized Shared Frailty Model",doi:"10.5772/intechopen.101502",slug:"dependent-dirichlet-processes-for-analysis-of-a-generalized-shared-frailty-model",totalDownloads:74,totalCrossrefCites:0,totalDimensionsCites:0,hasAltmetrics:0,abstract:"Bayesian paradigm takes advantage of well-fitting complicated survival models and feasible computing in survival analysis owing to the superiority in tackling the complex censoring scheme, compared with the frequentist paradigm. In this chapter, we aim to display the latest tendency in Bayesian computing, in the sense of automating the posterior sampling, through a Bayesian analysis of survival modeling for multivariate survival outcomes with the complicated data structure. Motivated by relaxing the strong assumption of proportionality and the restriction of a common baseline population, we propose a generalized shared frailty model which includes both parametric and nonparametric frailty random effects to incorporate both treatment-wise and temporal variation for multiple events. We develop a survival-function version of the ANOVA dependent Dirichlet process to model the dependency among the baseline survival functions. The posterior sampling is implemented by the No-U-Turn sampler in Stan, a contemporary Bayesian computing tool, automatically. The proposed model is validated by analysis of the bladder cancer recurrences data. The estimation is consistent with existing results. Our model and Bayesian inference provide evidence that the Bayesian paradigm fosters complex modeling and feasible computing in survival analysis, and Stan relaxes the posterior inference.",signatures:"Chong Zhong, Zhihua Ma, Junshan Shen and Catherine Liu",downloadPdfUrl:"/chapter/pdf-download/79845",previewPdfUrl:"/chapter/pdf-preview/79845",authors:[{id:"304195",title:"Dr.",name:"Catherine",surname:"Liu",slug:"catherine-liu",fullName:"Catherine Liu"},{id:"304196",title:"Dr.",name:"Junshan",surname:"Shen",slug:"junshan-shen",fullName:"Junshan Shen"},{id:"420776",title:"Mr.",name:"Chong",surname:"Zhong",slug:"chong-zhong",fullName:"Chong Zhong"},{id:"435774",title:"Dr.",name:"Zhihua",surname:"Ma",slug:"zhihua-ma",fullName:"Zhihua Ma"}],corrections:null},{id:"79477",title:"Modeling Heterogeneity Using Lindley Distribution",doi:"10.5772/intechopen.100340",slug:"modeling-heterogeneity-using-lindley-distribution",totalDownloads:80,totalCrossrefCites:0,totalDimensionsCites:0,hasAltmetrics:0,abstract:"Frailty models are intended for use in survival analysis to explain unobserved heterogeneity in an individual caused by various hereditary variables or environmental influences. A shared frailty model was utilized to examine the data. It is based on the idea that frailty affects the hazard rate in a multiplicative manner. In this manuscript, we introduce a new frailty model called the Lindley shared frailty model with exponential power and generalized Rayleigh as baseline distributions. The The Bayesian method of the Monte Carlo method of the Markov chain is used to estimate the parameters used in the model; simulation studies are also carried out to compare the actual and calculated values of the parameters; the proposed model is compared with the Bayesian comparison method Compare and propose the best model of infectious disease data.",signatures:"Arvind Pandey and Lalpawimawha",downloadPdfUrl:"/chapter/pdf-download/79477",previewPdfUrl:"/chapter/pdf-preview/79477",authors:[{id:"415620",title:"Assistant Prof.",name:"Lalpawimawha",surname:null,slug:"lalpawimawha",fullName:"Lalpawimawha null"},{id:"415664",title:"Dr.",name:"Arvind",surname:"Pandey",slug:"arvind-pandey",fullName:"Arvind Pandey"}],corrections:null},{id:"80086",title:"Network Meta-Analysis Using R for Diabetes Data",doi:"10.5772/intechopen.101788",slug:"network-meta-analysis-using-r-for-diabetes-data",totalDownloads:68,totalCrossrefCites:0,totalDimensionsCites:0,hasAltmetrics:0,abstract:"The objective of a meta-analysis is usually to estimate the overall treatment effect and make inferences about the difference between the effects of the two treatments. Meta-analysis is a quantitative method commonly used to combine the results of multiple studies in the medical and social sciences. There are three common types of meta-analysis. Pairwise, Multivariate and Network Meta-analysis. In general, network meta-analysis (NMA) offers the advantage of enabling the combined assessment of more than two treatments. Statistical approaches to NMA are largely classified as frequentist and Bayesian frameworks Because part of NMA has indirect, multiple comparisons, As reports of network meta-analysis become more common, it is essential to introduce the approach to readers and to provide guidance as to how to interpret the results. In this chapter, the terms used in NMA are defined, relevant statistical concepts are summarized, and the NMA analytic process based on the frequentist and Bayesian framework is illustrated using the R program and an example of a network involving diabetes treatments. The aim of the article is to compare the basic concepts and analyzes of network meta-analysis using diabetes data and the treatment methods used.",signatures:"Nilgün Yildiz",downloadPdfUrl:"/chapter/pdf-download/80086",previewPdfUrl:"/chapter/pdf-preview/80086",authors:[{id:"266040",title:"Dr.",name:"Nilgün",surname:"Yildiz",slug:"nilgun-yildiz",fullName:"Nilgün Yildiz"}],corrections:null},{id:"80261",title:"Variance Balanced Design",doi:"10.5772/intechopen.101847",slug:"variance-balanced-design",totalDownloads:48,totalCrossrefCites:0,totalDimensionsCites:0,hasAltmetrics:0,abstract:"In this chapter binary, ternary and n-ary variance balanced design is constructed using balanced incomplete block, resolvable balanced incomplete block, semi regular group divisible, factorial, fractional factorial designs. Constructed variance balanced designs are with v, (v + 1), (v + 2) and (v + r) treatments. Method of construction of variance balanced designs are supported by suitable examples. It is found that all most all variance balanced designs are with high efficiency factors.",signatures:"D.K. Ghosh",downloadPdfUrl:"/chapter/pdf-download/80261",previewPdfUrl:"/chapter/pdf-preview/80261",authors:[{id:"416938",title:"Prof.",name:"D.K",surname:"Ghosh",slug:"d.k-ghosh",fullName:"D.K Ghosh"}],corrections:null},{id:"80027",title:"Estimation of Means of Two Quantitative Sensitive Variables Using Randomized Response Technique",doi:"10.5772/intechopen.101269",slug:"estimation-of-means-of-two-quantitative-sensitive-variables-using-randomized-response-technique",totalDownloads:18,totalCrossrefCites:0,totalDimensionsCites:0,hasAltmetrics:0,abstract:"I propose an improved randomized response model for the simultaneous estimation of population means of two quantitative sensitive variables by using blank card option that make use of one scramble response and another fake response. The properties of the proposed estimator have been analysed. To judge the performance of the proposed model, I have considered a real data set and it is to be pointed out that the proposed model is more efficient in terms of relative efficiencies and privacy protection of respondents as well. Suitable recommendations have been made to the survey practitioners.",signatures:"Amod Kumar",downloadPdfUrl:"/chapter/pdf-download/80027",previewPdfUrl:"/chapter/pdf-preview/80027",authors:[{id:"420015",title:"Dr.",name:"Amod",surname:"Kumar",slug:"amod-kumar",fullName:"Amod Kumar"}],corrections:null},{id:"79864",title:"Causality Relationship between Import, Export and Exim Bank Loans: Turkish Economy",doi:"10.5772/intechopen.101733",slug:"causality-relationship-between-import-export-and-exim-bank-loans-turkish-economy",totalDownloads:101,totalCrossrefCites:0,totalDimensionsCites:0,hasAltmetrics:0,abstract:"Export promotion tools aim to increase exports and support the entrepreneur in reaching new foreign markets. The positive impact of incentives, especially on financial issues, on exports both before and after shipment is undeniable. Founded in 1987, Turkish Exim bank is Turkey’s official export credit institution. By observing macro-economic balances, Exim bank ensures that exporters, export-oriented production manufacturers and entrepreneurs operating abroad are supported by credit, guarantee and insurance programs to increase their competitiveness. The study aims to examine the causal relationship between imports, exports and Exim bank loans in the Turkish economy. In the study, stationarity with the extended Dickey-Fuller unit root test, long-term relationship with the Johansen co-integration test, and then causality with the Granger test were investigated. The causality relationship was analyzed using import, export and Eximbank loans data for the periods 2003–2020.",signatures:"Yüksel Akay Ünvan and Ulviyya Nahmatli",downloadPdfUrl:"/chapter/pdf-download/79864",previewPdfUrl:"/chapter/pdf-preview/79864",authors:[{id:"416940",title:"Associate Prof.",name:"Yüksel Akay",surname:"Ünvan",slug:"yuksel-akay-unvan",fullName:"Yüksel Akay Ünvan"},{id:"423513",title:"Ms.",name:"Ulviyya",surname:"Nahmatli",slug:"ulviyya-nahmatli",fullName:"Ulviyya Nahmatli"}],corrections:null}],productType:{id:"1",title:"Edited Volume",chapterContentType:"chapter",authoredCaption:"Edited by"},subseries:null,tags:null},relatedBooks:[{type:"book",id:"6554",title:"From Natural to Artificial Intelligence",subtitle:"Algorithms and Applications",isOpenForSubmission:!1,hash:"0b018b22e9462ac7c75edbc6392b2a6e",slug:"from-natural-to-artificial-intelligence-algorithms-and-applications",bookSignature:"Ricardo Lopez-Ruiz",coverURL:"https://cdn.intechopen.com/books/images_new/6554.jpg",editedByType:"Edited by",editors:[{id:"9849",title:"Prof.",name:"Ricardo",surname:"López-Ruiz",slug:"ricardo-lopez-ruiz",fullName:"Ricardo López-Ruiz"}],equalEditorOne:null,equalEditorTwo:null,equalEditorThree:null,productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}},{type:"book",id:"5198",title:"Numerical Simulation",subtitle:"From Brain Imaging to Turbulent Flows",isOpenForSubmission:!1,hash:"6bf6d0e6b25e77e717dd3b6c9d494cf9",slug:"numerical-simulation-from-brain-imaging-to-turbulent-flows",bookSignature:"Ricardo Lopez-Ruiz",coverURL:"https://cdn.intechopen.com/books/images_new/5198.jpg",editedByType:"Edited by",editors:[{id:"9849",title:"Prof.",name:"Ricardo",surname:"López-Ruiz",slug:"ricardo-lopez-ruiz",fullName:"Ricardo López-Ruiz"}],equalEditorOne:null,equalEditorTwo:null,equalEditorThree:null,productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}},{type:"book",id:"6216",title:"Complexity in Biological and Physical Systems",subtitle:"Bifurcations, Solitons and Fractals",isOpenForSubmission:!1,hash:"c511a26efc1b9c0638c8f9244240cb93",slug:"complexity-in-biological-and-physical-systems-bifurcations-solitons-and-fractals",bookSignature:"Ricardo López-Ruiz",coverURL:"https://cdn.intechopen.com/books/images_new/6216.jpg",editedByType:"Edited by",editors:[{id:"9849",title:"Prof.",name:"Ricardo",surname:"López-Ruiz",slug:"ricardo-lopez-ruiz",fullName:"Ricardo López-Ruiz"}],equalEditorOne:null,equalEditorTwo:null,equalEditorThree:null,productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}},{type:"book",id:"8872",title:"Multi Agent Systems",subtitle:"Strategies and Applications",isOpenForSubmission:!1,hash:"6b0454f8f575d5d65603f329af59c80b",slug:"multi-agent-systems-strategies-and-applications",bookSignature:"Ricardo López - 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From chapter submission and review, to approval and revision, copyediting and design, until final publication, I work closely with authors and editors to ensure a simple and easy publishing process. I maintain constant and effective communication with authors, editors and reviewers, which allows for a level of personal support that enables contributors to fully commit and concentrate on the chapters they are writing, editing, or reviewing. I assist authors in the preparation of their full chapter submissions and track important deadlines and ensure they are met. I help to coordinate internal processes such as linguistic review, and monitor the technical aspects of the process. As an ASM I am also involved in the acquisition of editors. 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Surgical management of the axilla, however, has undergone a paradigm change since the concept of lymphatic mapping in breast was introduced at the John Wayne Cancer Institute in 1991, and sentinel lymph node biopsy (SLNB) has replaced axillary lymph node dissection (ALND) for axillary staging in clinically node‐negative early breast cancer. There is a large body of evidence showing that SLNB is an accurate staging procedure in expert hands, and it is now the standard of care for staging clinically node‐negative invasive breast cancer. Furthermore, the results of the ACOSOG Z0011 trial indicated that the patients with a positive axillary sentinel lymph node (ASLN) that may avoid ALND include those with clinical T1–2, N0 breast cancer with one or two positive ASLN who plan to undergo lumpectomy with whole breast radiation and systemic therapy. However, the internal mammary sentinel lymph node biopsy (IM‐SLNB) is far behind that of the axilla for the low visualization rate of internal mammary sentinel lymph node (IM‐SLN) with the traditional radiotracer injection technique. Based on the hypothesis that the IM‐SLN receives the lymphatic drainage from not only the primary tumor area, but also the entire breast organ. The Modified radiotracer injection technique significantly improved the IM‐SLN visualization rate, making the routine IM‐SLNB possible in daily practice, and further offer individual management for IMLN. In this article, the technical matter, indication and clinical significance of IM‐SLNB were discussed, and we would like to identify the breast cancer patients who may benefit from this minimally invasive diagnostic technique.
\nIn addition to the axillary lymph nodes (ALN), the internal mammary lymph nodes (IMLN) drainage is another first‐echelon nodal drainage site in breast cancer [1]. The status of IMLN also provides important regional staging and treatment choice information for breast cancer patients [1, 2]. As reported in the previous studies of extended radical mastectomy, patients with no ALN/IMLN metastases had a 10‐year overall survival (OS) rate of 82% compared with 54% for only ALN metastases patients, 38% for only IMLN metastases patients, and 17% for patients with involvement of both nodal, suggesting that regional disease in either nodal chain has the same prognostic relevance [3–5]. The National Comprehensive Cancer Network (NCCN) Clinical Practice Guidelines recommend to strongly consider radiotherapy to IMLN for patients with positive ALN or tumor >5 cm (category 2B), noting “radiotherapy should be given to the IMLN that are clinically or pathologically positive; otherwise, the treatment to the IMLN is at the discretion of the treating radiation oncologist” on this topic.
\nThe nodal status of axillary has been well‐established with SLNB and/or ALND in breast cancer patients. However, regional staging and treatment choice could not be achieved just with the ALN status, which might cause under‐stage and under‐/over‐treatment. Handley and Thackray reported that 33% patients had IMLN involvement during survey biopsy, and a back‐up IMLN dissection was frequently added to the radical mastectomy starting in the 1950s [6–9]. However, this radical surgical procedure was abandoned due to its extra complications, longer operation time, and lack of survival benefit [10]. Imaging techniques, such as ultrasound, MRI, and PET/CT, could usually detect metastases lesions larger than 5 mm, but due to the deep anatomical location and small size of IMLN, the sensitivity of current imaging techniques cannot satisfy the clinical practice. Therefore, a minimally invasive method is still lacked to evaluate the status of IMLN, and individual IMLN radiotherapy could not be performed.
\nThe IM‐SLNB provided a less invasive method for assessing IMLN than surgical dissection (Figure 1) and may affect decision‐making for regional and systemic therapy [11, 12]. Although the 2009 American Joint Committee on Cancer (AJCC) staging incorporated the IM‐SLNB concept, there has been little change in surgical practice patterns due to the low visualization rate of IM‐SLN with the traditional radiotracer injection technique [13, 14]. Several studies have discovered that superficial injection (intradermal, subdermal, periareolar, and subareolar) of radiotracer was hard to identify IM‐SLN, while intraparenchymal injection (peritumoral, intratumoral, or subtumoral) was more reliable [15–18]. These results suggest that the dermal and subdermal lymphatic flow is rarely directed to the internal mammary region, while some intraparenchymal lymphatic flow is directed to the internal mammary region. Unfortunately, with the traditional intraparenchymal injection technique, the internal mammary hotspots were only seen in a small proportion of patients (average 13%, range 0–37%), which has restricted the clinical studies and daily practice of IM‐SLNB to date (Table 4) [15–20].
\nInternal mammary sentinel lymph node biopsy. (A1 & A2 is mastectomy, B1 & B2 is lumpectomy.)
Qiu et al. tried injecting radiotracer with a modified technique (periareolar intraparenchymal, high volume, and ultrasound guidance) and got a high lymphoscintigraphy visualization rate of IM‐SLN (71.1%, 248/349) (Figure 2) [21, 22]. This might provide a technical feasibility of IM‐SLNB, therefore, IM‐SLNB could be performed routinely in clinical studies and daily practice and might potentially impact treatment decision‐making. However, the basic problem in Qiu\'s study is the same as all the previous research, because a back up IMLN dissection have not been performed following the IM‐SLNB, the accuracy of this minimally invasive technique have not been verified directly. During the IM‐SLNB studies, the IM‐SLN were concentrated in the 2nd and 3rd intercostal space, which were consistent with the sites of IMLN metastasis in the previous studies of IMLN dissection [6, 10]. These results indirectly confirmed accuracy of IM‐SLNB. However, a backup lMLN dissection should be required to validate accuracy of IM‐SLNB before its clinical application.
\nSchematic model of the modified injection techniques.
Additionally, the IM‐SLNB is more difficult than axillary SLNB, with success rates of 70–100%. Pleural breach and internal mammary vessel bleeding are the most commonly reported complications from IM‐SLNB, occurring in approximately 5% of patients, although pneumothorax and significant postoperative morbidity are rare. Several studies reported the change in clinical management caused by the additional information provided by IM‐SLNB [23–28]. IM‐SLNB leads to more complete regional staging.
\nIt is generally known that the hypothesis of ASLN lymphatic drainage pattern was proved with subsequent ALND in the breast cancer [29–31]. However, the hypothesis of IM‐SLN lymphatic drainage has not been confirmed. As the extended radical mastectomy (included complete internal mammary chain dissection) has been abandoned since 1960s [4, 32, 33], the hypothesis of IM‐SLN lymphatic drainage pattern cannot be validated by this way. Now, another method was used to validate the IM‐SLN lymphatic drainage hypothesis in our study. Two different tracers (fluorescence tracer [ICG] and radiotracer [99mTc‐labeled sulfur colloid]) were injected in different sites of the intra‐parenchyma to observe whether they could reach to the same IM‐SLN in the breast cancer patient. In the clinical practice, the ICG fluorescence tracer is a safe and effective method for sentinel lymph node biopsy (SLNB) in the breast cancer with acceptable sensitivity and specificity comparable to conventional methods (blue dye and radioisotope) [34–36]. In our breast cancer center, it has been compared with the combined method (blue dye with radiotracer [99mTc‐labeled sulfur colloid]) in identifying ASLN. The results showed that all ASLN identified by the combined method also were the ICG fluorescence positive and the non‐sentinel lymph nodes were the ICG negative after ALND (n = 69, P < 0.05). The anatomy study of the lymphatics in the breast found that IMLN commonly receive less than 25% of the total lymphatic drainage from the breast [37]. Due to little volume of ICG tracer is difficult to detect by the fluorescence imaging system, it is hard to find IM‐SLN by this tracer in the internal mammary lymph chain. But IM‐SLN can be detected by radiotracer with the modified radiotracer injection technique and can be performed biopsy in the internal mammary lymph chain guided by this technique. In the validation study of the IM‐SLN lymphatic drainage hypothesis, the ICG fluorescence tracer was injected intraparenchymally guided by breast ultrasound at the peritumoral, the radiotracer was injected intraparenchymally with the modified radiotracer injection technique. This method is used to identify different tracers injected in different sites that could reach to the same IM‐SLN. The radioactive IM‐SLNs were detected by preoperative lymphoscintigraphy (Figure 3) 30 min before the surgery and gamma probe during the surgery. IM‐SLNB was performed for patients with the radioactive IM‐SLNs. After IM‐SLN removed, the status of IM‐SLN was identified by intraoperative gamma probe and fluorescence imaging system (Figure 4). The correlations between the radiotracer and the fluorescence tracer in the same IM‐SLN were calculated using the Spearman rank correlation coefficient. The criteria for judging the size of the correlation coefficient were applied: correlations <0.30 are considered minor, correlations between 0.3 and 0.49 are considered medium, and ≥0.5 are considered strong. Cohen\'s kappa statistic was used to determine inter‐examiner agreement. According to Altman\'s guidelines, it is poor when kappa scores ≤0.20, fair when kappa between 0 and 0.40, moderate when kappa between 0.41 and 0.60, good when kappa 0.61–0.80, and very good when kappa ≥0.80. The results showed that 145 patients underwent IM‐SLNB successfully and 127 cases of them identified the radiotracer and the fluorescence tracer reached to the same IM‐SLN, 18 cases were detected only the radiotracer positive IM‐SLN (Table 1). Accordingly, the radiotracer and the fluorescence tracer in the same IM‐SLN showed a strong correlation coefficient at 0.836 (
Preoperation lymphoscintigram with radiotracer. Hotspots are evidently shown in both the second intercostal space (A) and the fourth intercostal space (B) in patient with left‐sided breast cancer.
Intraoperative IM‐SLNB identified the location of IM‐SLN in the fourth intercostal space. The fluorescence imaging system showed the IM‐SLN fluorescence tracer positive (B).
Tracers map | \nRadiotracer+ | \nRadiotracer- | \nTotal | \n
---|---|---|---|
127 | \n0 | \n127 | \n|
18 | \n71 | \n89 | \n|
145 | \n71 | \n216 | \n
Different tracers identified in IM‐SLN.
Furthermore, the radiotracer was not injected in peritumoral intra‐parenchyma but in periareolar intra‐parenchyma with the modified technique based on the hypothesis. The question arises as to whether all nodes detected by the modified technique should be considered as “true” IM‐SLN or whether some of them are actually “second‐tier” IMLN. The accuracy of the modified radiotracer injection technique has been confirmed by our team at the previous study [39]. The results showed that IM‐SLN detected by the modified technique could reflect the real lymphatic drainage of the whole breast parenchyma. In other words, the modified technique can detect the “true” sentinel node in the internal mammary chain. Also, the results of the metastases site and the number of IM‐SLNs were in accordance with the past study of extended radical mastectomy, which could reflect the accuracy of IM‐SLNB indirectly [2, 40, 41]. There were no serious adverse events or reactions after the radiotracer injected guiding by the modified injection technique.
\nSeveral studies indicated that IM‐SLNB have little clinical relevance because tumor‐positive IM‐SLN rarely influence adjuvant treatment strategy and did not affect overall survival [11, 13]. We agree with these results but it should be interpreted with caution for the limitation of their study population. The study population in all current research relate to SLNB (both axilla and internal mammary) was the patients with clinically negative ALN. Because the IMLN involvement is mostly found concomitantly with ALN involvement [10], more attention should be focused on the IM‐SLNB in clinically positive ALN patients. Huang et al. [42] retrospectively analyzed 2269 Chinese patients who received extended radical mastectomy and showed that the probability of IMLN metastases was 4.4% for patients with negative ALN, 18.8% for 1–3 positive ALN, 28.1% for 4–6 positive ALN and 41.5% for more than 6 positive ALN. Veronesi et al. also indicated that the IMLN positive rate increased significantly from 9.1% in negative ALN to 29.1% in positive ALN patients [6]. Qiu reported that the IM‐SLN positive rate was only 8.1% in clinically negative ALN patient, and adjuvant therapy was altered in a small proportion. However, the IM‐SLN positive rate was 20.5% in clinically positive ALN, and individual radiotherapy strategy could be tailored with this IM‐SLNB result [22]. To summarize, previous IM‐SLNB research failed to assess the IMLN status who really were in need, we could found the evidence from the above results that the patients with clinically positive ALN could get more benefit from the IM‐SLNB. Therefore, Qiu et al. suggested that the IM‐SLNB research should be encouraged in the clinically positive ALN patients [43].
\nFor many patients, improvement of systemic therapy will decrease the risk of death due to distant metastasis, after which the importance of optimized local therapy—which will already be better after systemic treatment—will, relatively, contribute more to survival [44]. Radiotherapy could reduce local recurrence and improve survival after mastectomy and breast conserving surgery [45, 46].
\nThe results of Early Breast Cancer Trialists’ Collaborative Group (EBCTCG) meta‐analysis showed that one breast cancer death being avoided in the first 15 years after radiotherapy for every four recurrences of any type (i.e., either loco‐regional or distant) avoided in the 10 years after radiotherapy for patients with breast conserving surgery. And about one breast cancer death was avoided in the 20 years after radiotherapy for every 1.5 recurrences of any type (i.e., either loco‐regional or distant) avoided during the first 10 years after radiotherapy for patients with positive lymph node [46].
\nThe meta‐analysis from EBCTCG involved 8135 patients and randomly assigned them to the chest wall and regional lymph nodes radiotherapy after mastectomy and axillary surgery versus the same surgery but no radiotherapy. For 1314 patients with 1–3 positive ALN after ALND, postmastectomy radiotherapy could reduce loco‐regional recurrence (LRR), overall recurrence (OR, rate ratio [RR] 0.68, 95% confidence interval [CI] 0.57–50.82), and breast cancer mortality (BCM, RR 0.80, 95% CI 0.67–60.95, all P < 0.05). For patients with systemic therapy (86.2%, 1133/1314), postmastectomy radiotherapy also could reduce LRR, OR (RR 0.67, 95% CI 0.55–50.82), and BCM (RR 0.78, 95% CI 0.64–60·94, all P < 0.05). Furthermore, for 1772 patients with ≥4 positive ALN after ALND, radiotherapy also could reduce LRR, OR (RR 0.79, 95% CI 0.69–60.90), and BCM (RR 0.87, 95% CI 0.77–70.99, all P < 0.05). However, the benefit of postmastectomy radiotherapy might be greater for patients irradiated today because of radiotherapy planning changing substantially and patients receiving better coverage of target areas. Today, with the rapid development of the radiotherapy techniques, the doses to normal tissues would be lower, the risks of radiotherapy would be lower, and the benefits of postmastectomy radiotherapy would be larger than in these trials. However, due to the improvement of detection and treatment in breast cancer, which makes the absolute risks lower in breast cancer recurrence and mortality, the absolute benefit of postmastectomy radiotherapy today would be smaller than in this study [47].
\nThe MA.20 trial from National Cancer Institute Common Clinical Trials Group found that the addition of regional nodal radiotherapy (including IMLN) to whole‐breast radiotherapy reduced the rate of breast cancer recurrence in patients with node‐positive or high‐risk node‐negative breast cancer. A total of 1832 patients were assigned to the nodal‐radiotherapy group or the control group (916 patients in each group) in this trial. At the 10‐year follow‐up, the rates of disease‐free survival (DFS) in the nodal‐radiotherapy group was better than that in the control group (82.0 vs
In the European Organization for Research and Treatment of Cancer (EORTC) 22922/10925 study, a total of 4004 patients were assigned randomly to the regional nodal radiotherapy (included IMLN) group or the control group. At a median follow‐up of 10.9 years, the results showed that regional nodal radiotherapy did not change overall survival (OS) (82.3 vs. 80.7%, HR 0.87, 95% CI, 0.76–71.00, P = 0.06), but improved DFS (72.1 vs. 69.1%, HR, 0.89, 95% CI, 0.80–81.00, P = 0.04), the distant metastasis‐free survival (DMFS) (78.0 vs. 75.0%, HR, 0.86, 95% CI, 0.76–70.98, P = 0.02), and reduced the breast cancer mortality (12.5 vs. 14.4%, HR, 0.82, 95% CI, 0.70–0.97, P = 0.02) [49].
\nIn the French study, all patients received postoperative radiotherapy to the chest wall and supraclavicular nodes and were randomly assigned to receive IMLN radiotherapy or not. A total of 1334 patients were analyzed after a median follow‐up of 11.3 years among the survivors. No benefit of IMLN radiotherapy on OS could be demonstrated: the 10‐year OS was 59.3% in the IMLN non‐irradiated group versus 62.6% in the IMLN irradiated group (P = 0.8). The overestimation of the risk of IMLN involvement (25%) probably decreased the power of the study [50].
\nBudach et al. did a meta‐analysis of the MA. 20, EORTC22922/10925, French trials and the results showed that additional regional radiotherapy to IMLN statistically significantly improves DFS, DMFS, and OS in stage I–III breast cancer. The absolute benefits in 5‐year OS were 1.6% in the MA.20 trial, 10‐year OS were 1.6% in the EORTC trial, and 10‐year OS were 3.3% in the French trial (HR 0.88 [95% CI 0.80–0.97], P = 0.012). Regional nodal (the medial supraclavicular lymph node and IMLN) irradiation (MA.20 and EORTC) was associated with a significant improvement of DFS (HR 0.85 [95% CI 0.77–0.94]) and DMFS (HR 0.82 [95% CI 0.73–0.92]) [51].
\nThe 2016 NCCN Breast Cancer Clinical Practice Guidelines recommend radiotherapy to IMLN for patients with ≥4 positive ALN (category 1), and strongly consider radiotherapy to IMLN for patients with 1–3 positive axillary nodes (category 2A), both after mastectomy and lumpectomy [52].
\nThe DBCG‐IMN Study initiated by Danish Breast Cancer Cooperative Group, a prospective population‐based cohort study, found that IMLN radiotherapy increased OS in patients with early‐stage node‐positive breast cancer. A total of 3089 patients were included in the study, 1492 of them received IMLN radiotherapy and others were no IMLN radiotherapy. With a median of 8.9 years of follow‐up time, the 8‐year OS rates of IMLN radiotherapy group was higher than that in the no radiotherapy group (75.9% [95% CI 73.6–78.0] vs
In sum, IMLN radiotherapy could reduce loco‐regional and distant recurrence and improve survival in breast cancer.
\nAlthough the 2016 NCCN Breast Cancer Clinical Practice Guidelines recommend radiotherapy to IMLN for patients with ≥4 positive ALN, and strongly consider radiotherapy to IMLN for patients with 1–3 positive axillary nodes, but according to the status of ALN to estimate the metastasis risk in IMLN, low‐risk did not mean IMLN negative and high‐risk did not mean IMLN metastases [54]. Studies of extended radical mastectomy reported that 38.3% (36.8–46.2%) patients with ≥4 positive ALN, 19.6% (18.8–26.7%) patients with 1–3 positive ALN identified IMLN metastases, and 9.2% (4.4–16.8%) with negative ALN identified IMLN metastases. It is obvious that negative IMLN was found in about 60% patients with ≥4 positive ALN and positive IMLN was found in about 9% patients with negative ALN [33, 42, 55]. Thus, these inclusion criteria of NCCN Guidelines might induce over‐ and under‐treatment. We should use a more accurate technique to evaluate the pathology status of IMLN and to guide IMLN radiotherapy.
\nThe study by Veronesi et al. found that radiotherapy to IMLN will improve the survival obviously after identifying the metastases by IMLN biopsy. In this clinical study of 68 (10.3%, 68/663) patients receiving radiotherapy to IMLN for histologically proven metastases, radiotherapy was highly effective yielded a 5‐year OS of 95% [56].
\nCurrently, IM‐SLNB via intercostal space could make it possible—tailored IMLN radiotherapy and minimally invasive staging. Even though breast cancer staging has incorporated IM‐SLNB concept since the 6th edition of AJCC, IM‐SLNB has not been performed routinely [57]. The studies of IM‐SLNB showed that the success rate of IM‐SLNB has reached 60–100% with minimal or no changes in operative time, but the visualization rate of IM‐SLN was low [12–14, 58], which has been the restriction for both clinical study and daily practice of IM‐SLNB.
\nNow, the modified radiotracer injection technique could improve the IM‐SLN detection rate from 15.5 to 71% (
Characteristic | \nNo. | \n% | \n
---|---|---|
Age (years) | \n\n | |
Median | \n50 | \n|
Range | \n27–79 | \n|
≤50 | \n119 | \n55.1 | \n
>50 | \n97 | \n44.9 | \n
BMI | \n\n | |
Median | \n24.1 | \n|
Range | \n17.2–33.5 | \n|
Tumor size | \n\n | |
Tis | \n16 | \n7.4 | \n
T1 | \n99 | \n45.8 | \n
T2 | \n79 | \n36.6 | \n
T3 | \n22 | \n10.2 | \n
Tumor location | \n\n | |
UOQ | \n92 | \n42.6 | \n
LOQ | \n25 | \n11.6 | \n
UIQ | \n48 | \n22.2 | \n
LIQ | \n5 | \n2.3 | \n
Central | \n46 | \n21.3 | \n
Tumor type | \n\n | |
Ductal | \n187 | \n86.6 | \n
Lobular | \n8 | \n3.7 | \n
Mixed | \n5 | \n2.3 | \n
Other | \n16 | \n7.4 | \n
Radiotracer intensity (MBq) | \n\n | |
Median | \n36 | \n|
Radiotracer volume (mL/point) | \n\n | |
Median | \n0.5 | \n|
Intervals from injection to SLNB (h) | \n\n | |
2–5 | \n89 | \n41.2 | \n
16–22 | \n127 | \n58.8 | \n
Descriptive characteristics of eligible patients (N = 216).
Abbreviations: BMI, body mass index: UOQ, upper outer quadrant; LOQ, lower outer quadrant: UIQ, upper inner quadrant; LIQ, lower inner quadrant.
Characteristic | \nNo. | \n% | \n
---|---|---|
T stage | \n\n | |
Tis | \n9 | \n6.2 | \n
T1 | \n70 | \n48.3 | \n
T2 | \n57 | \n39.3 | \n
T3 | \n9 | \n6.2 | \n
N stage | \n\n | |
N0 | \n70 | \n48.3 | \n
N1 | \n57 | \n39.3 | \n
N2 | \n7 | \n4.8 | \n
N3 | \n11 | \n7.6 | \n
ER | \n\n | |
Positive | \n101 | \n69.7 | \n
Negative | \n44 | \n30.3 | \n
PR | \n\n | |
Positive | \n98 | \n67.6 | \n
Negative | \n47 | \n32.4 | \n
HER‐2 | \n\n | |
Positive | \n44 | \n30.3 | \n
Negative | \n101 | \n69.7 | \n
Type of surgery | \n\n | |
Lumpectomy + ASLNB | \n9 | \n6.2 | \n
Lumpectomy + ALND | \n3 | \n2.1 | \n
Mastectomy + ASLNB | \n93 | \n64.1 | \n
Mastectomy + ALND | \n40 | \n27.6 | \n
Radiotherapy | \n\n | |
WBI | \n7 | \n4.8 | \n
WBI + RNI | \n5 | \n3.5 | \n
PMRT + RNI | \n79 | \n54.5 | \n
No | \n54 | \n37.2 | \n
Chemotherapy | \n\n | |
Yes | \n121 | \n83.4 | \n
No | \n24 | \n16.6 | \n
Clinical outcome of patients who underwent IM‐SLNB (N = 145).
Abbreviations: ER, estrogen receptor status; PR, progesterone receptor status; HER‐2, human epidermal growth factor receptor‐2; WBI, whole breast irradiation; RNI, regional node irradiation; PMRT, postmastectomy radiotherapy.
Characteristic | \nNo. | \n% | \n
---|---|---|
IM‐SLN map+ | \n155 | \n71.8 (155/216) | \n
Pt. performed IM‐SLNB | \n149 | \n96.1 (149/155) | \n
Success rate of IM‐SLNB | \n145 | \n97.3 (145/149) | \n
Total no. of IM‐SLN | \n279 | \n|
Median | \n2 | \n|
Range | \n1–4 | \n|
IM‐SLN metastatic | \n18 | \n12.4 (18/145) | \n
IM‐SLNB time (min) | \n\n | |
Median | \n10 | \n|
Range | \n3–55 | \n|
IM‐SLN size (mm) | \n\n | |
Median | \n5 | \n|
Range | \n3–12 | \n
Details of IM‐SLN mapping and biopsy.
No. | \nTumor location | \nT stage | \nNo. of positive ALN | \nN stage without IM‐SLN | \nNo. of positive IM‐SLN | \nN stage with IM‐SLN | \nFinally stage | \nChemo- therapy | \nRadio- therapy | \n
---|---|---|---|---|---|---|---|---|---|
1 | \nUOQ | \nT2 | \n0 | \npN0 | \n2 | \npN1b | \nIIA→IIB | \nYes | \nNo→Yes | \n
2 | \nUIQ | \nT2 | \n2 | \npN1a | \n1 | \npN1c | \nIIB (no change) | \nYes | \n? →Yes | \n
3 | \nCentral | \nT2 | \n14 | \npN3a | \n1 | \npN3b | \nIIIC (no change) | \nYes | \nYes | \n
4 | \nUOQ | \nT2 | \n9 | \npN2a | \n1 | \npN3b | \nIIIA→IIIC | \nYes | \nYes | \n
5 | \nUIQ | \nT1c | \n2 | \npN1a | \n1 | \npN1c | \nIIA (no change) | \nYes | \n? →Yes | \n
6 | \nUOQ | \nT2 | \n1 | \npN1a | \n1 | \npN1c | \nIIB (no change) | \nYes | \n? →Yes | \n
7 | \nUIQ | \nT1a | \n0 | \npN0 | \n1 | \npN1b | \nIA→IIA | \nNo→Yes | \nNo→Yes | \n
8 | \nUOQ | \nT2 | \n9 | \npN2a | \n2 | \npN3b | \nIIIA→IIIC | \nYes | \nYes | \n
9 | \nLIQ | \nT2 | \n5 | \npN2a | \n1 | \npN3b | \nIIIA→IIIC | \nYes | \nYes | \n
10 | \nUOQ | \nT1a | \n3 | \npN1a | \n1 | \npN1c | \nIIA (no change) | \nYes | \n? →Yes | \n
11 | \nUIQ | \nT2 | \n0 | \npN0 | \n1 | \npN1b | \nIIA→IIB | \nYes | \nNo→Yes | \n
12 | \nUOQ | \nT3 | \n13 | \npN3a | \n1 | \npN3b | \nIIIC (no change) | \nYes | \nYes | \n
13 | \nCentral | \nT1c | \n1 | \npN1a | \n1 | \npN1c | \nIIA (no change) | \nYes | \n? →Yes | \n
14 | \nUOQ | \nT2 | \n13 | \npN3a | \n1 | \npN3b | \nIIIC (no change) | \nYes | \nYes | \n
15 | \nCentral | \nT2 | \n11 | \npN3a | \n1 | \npN3b | \nIIIC (no change) | \nYes | \nYes | \n
16 | \nUOQ | \nT2 | \n20 | \npN3a | \n1 | \npN3b | \nIIIC (no change) | \nYes | \nYes | \n
17 | \nUOQ | \nT2 | \n5 | \npN2a | \n1 | \npN3b | \nIIIA→IIIC | \nYes | \nYes | \n
18 | \nUIQ | \nT1c | \n0 | \npN0 | \n1 | \npN1b | \nIA→IIA | \nNo→Yes | \nNo→Yes | \n
The clinical, pathological, and treatment details of patients with positive IM‐SLN.
Abbreviations: UOQ, upper outer quadrant; UIQ, upper inner quadrant; LIQ, lower inner quadrant; ?, radiotherapy is controversy.
Modified injection technique (two‐quadrant, high volume, and ultrasound guidance) could significantly improve the detection rate of IM‐SLN and would promote research on IM‐SLNB. The hypothesis of IM‐SLN lymphatic drainage pattern was demonstrated. As IMLN metastasis is mostly concomitant with ALN metastasis, IM‐SLNB should be encouraged in clinically positive ALN patients. IM‐SLNB should be performed routinely, for it could lead to accurate IMLN staging and provide IM‐SLNB guided IMLN‐RT.
\nThis work was supported by National Natural Science Foundation of China (81672038), National Natural Science Foundation of China (81502314), Natural Science Foundation of Shandong Province (ZR2014HZ003), and Natural Science Foundation of Shandong Province (ZR2015PH025).
\nThe development of railway transport is related to strategic planning and selection of one or another strategy for the development of the railway infrastructure, railway services and rolling stock. The railway managers need to choose the most appropriate development strategy between set of alternatives. This is a complex process in which it is necessary to take into account a set of factors that have to accounted both the expectations of users of railway services and the capabilities of railway operators and the possibilities of investment in railway transport. The strategic planning methods are a powerful tool for analyzing groups of criteria. Such approaches are Strengths – Weakness – Opportunities – Threats (SWOT), Political, Economic, Social and Technological, Legal and Environmental (PESTLE), PESTEL, and others. The SWOT method is a useful procedure to determine the internal and external influences on the investigated system. The PESTLE or PESTEL analysis is more waste and helpful and as compare to the SWOT analysis. It provides the environmental factors to tackle the problems. An integration between these techniques also it is possible. The strategic planning approaches help managers formulate and analyze criteria in each of the groups. Appropriate techniques for assessing the criteria and their influences, as well as for selecting a suitable alternative for development, are the methods of Multi Criteria Decision Making (MCDM). The different multi-criteria decision-making methods have been applied to study various transport problems. In general, the multi-criteria methods can be summarized as follows: Pair-wise comparisons; Distance based; Utility based; Outranking; Linear programming based. Some of multi-criteria methods can be used only to determine the weights of criteria; others serve ranking the alternatives, by setting the weights of the criteria; third solved weights of criteria by applying expert’s assessment and scale of evaluating, and also ranking the alternatives. The Sequential Interactive Modeling for Urban Systems (SIMUS) method is a different multi-criteria approach applied linear programming and does not used the weights of criteria for ranking the alternatives. The use of one or another method depends on the decision maker according the problem to be solved.
The aim of this research is to increase the level of decision making by integrating the advantages of strategic planning as PESTLE and SWOT analysis with the advantages of the multi-criteria methods to assess the influence of criteria and evaluate the alternatives of strategic planning. The proposed techniques could help transport managers in their analysis and decisions when chose a suitable strategy in railway transport development. In this study different multi-criteria analysis techniques have been experimented and discussed as a tool for integration with PESTLE-SWOT approach.
This chapter represents a case study for Bulgarian railway network and railway passenger transport. The Bulgarian railway network is a part of TEN-T network. The current situation shows that the average technical speed of passenger trains is one of the lowest in Europe. The railway infrastructure is in process of rehabilitation in order to increase the safety and technical speed of railway sections and lines. The existing rolling stock have low quality and capabilities and have to be renewed and modernized. The existing structure of trains by types could be improved through implementation of new type of trains. Three strategies for improvement of the Bulgarian railway transport development have been assess in this chapter based on proposed integrated approach PESTLE - SWOT- MCDM.
The structure of the chapter is as follows: Section 2 shows literature review; Section 3 provides the methodology of research. Different multi-criteria approaches are included in methodology. The linear programming approach as SIMUS method, the distance-based approach as Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) and evaluation based on distance from average solution (EDAS) methods, the utility-based approach as multi-objective optimization on the basis of ratio analysis (MOORA) and COmplex PRoportional ASsessment method (COPRAS) methods, and outranking approach as Preference Ranking Organization METHod for Enrichment of Evaluations (PROMETHEE) method are represented. The integration of PESTLE-SWOT-MSDM is shown. Section 4 shows the obtained results for Bulgarian railway network and discussion. Finally, Section 5 provides the conclusions.
The methods of strategic planning as SWOT, PEST and its modification as STEEP, PESTLE, PESTEL, STEEPLE or others have been applied in the following ways:
Analysis the sub-criteria in SWOT, PESTLE, or other modification of strategic planning methods groups;
Combination of PESTLE and SWOT analysis in order to expand the analysis of defined sub-criteria. This approach serves also for identifying the internal and external factors that influence a given system.
Integration of the PESTLE (SWOT) analysis with multi-criteria analysis methods to determine the weights of sub-criteria in each PESTLE (SWOT) group. This approach is used to identify the sub-criteria that have the main impact of the investigated system.
Ranking of alternatives based on SWOT (PESTLE) sub-criteria. The determination of the weights of sub-criteria and the ranking is performed by using multi-criteria analysis methods.
Some authors used the strategic management techniques as SWOT, PESTLE or others as a tool to analyze the studied system with purpose to strategic planning. The weights of the criteria in these cases are not determined. The PESTLE analysis has been implemented to analyze of the suborbital flight operation [1]; to determine the weak signals classification to detect threats and opportunities from web [2]; to analyze the renewable energy sector environment [3]. The integration of PESTLE and SWOT analysis is presented in [4] to analyze the Renewable Energy for Island Countries. The PESTEL analysis has been used for assessing the situation of Polish transport enterprises [5]. Some authors consider only the problem with the formulation of the SWOT factors. The SWOT analysis have been conducted to of railway freight transport [6]; of China’s High-speed Rail [7]; to develop city public transport strategies [8]; to study the automobile reverse logistics [9]; to analyze the underground pedestrian systems [10].
The PESTLE framework has been also integrated with the methods to decision making and multi-criteria analysis. In [11] the integration of PESTEL analysis and AHP method has been applied to select an optimal location of logistic hubs. The green building industry in Turkey has been assessed by using PESTLE analysis and fuzzy model of the macro-environmental assessment, [12]. The PESTLE analysis and Multi Attribute Value Theory (MAVT) method have been integrated to study Carbon Capture and Storage process, [13]. The unconventional modes of transport have been analyzed based on PESTLE, and an AHP-TOPSIS approach, [14]. The SWOT/PESTLE analysis has been applied to investigate the water system in Serbia [15]; for Port Energy Management System to define the positive or negative effect, [16].
The city’s transportation system strategies were evaluated and prioritized based on SWOT analysis and fuzzy complex proportional assessment (COPRAS) method [17]. An integrated SWOT – FUZZY PIPRECIA model was formed to analyze and improve logistics performances for transport of goods [18]. Some of the researchers combined the SWOT analysis with Analytic Hierarchy Process (AHP) or Analytic Network Process (ANP) methods. This approach has been used to study the strategy of development of railway transport in West Africa [19]; to study different mode of transport to determine the transport strategy [20]; to analyses the Long-Distance Passenger Transportation on a Highway Network [21]; to investigate urban planning [22]; for energy automobile industry [23]. Other authors used an integration of more multi-criteria methods with SWOT analysis, [24, 25, 26]. In these cases, one method is used to determine the weights of criteria, and another method is applied to assess the alternatives.
The methodology of the research consists fifth stages, Figure 1:
First stage: Formulation the alternatives of the policies for railway operator.
Second stage: Definition of the criteria in PESTLE groups. The initial decision matrix represented the values of each criterion for each alternative is formed.
Third stage: The SIMUS method is applied to rank the alternatives and assess the criteria in PESTLE groups. The criteria significance is dependent on the set of alternatives to evaluate. It is a similar concept to using Shannon entropy, to evaluate criteria weights.
Fourth stage: Ranking by application the following distance based multi-criteria methods: TOPSIS and EDAS, utility based multi-criteria methods: MOORA and COPRAS; and outranking approach PROMETEE. These multi-criteria methods have different techniques versus SIMUS method. They have been selected to compare the results of PESTLE – SIMUS approach with the integration of PESTLE with other multi-criteria approach. Because these methods use the weights of criteria, they have been taken into account as equal to these determined by SIMUS method.
Fifth stage: Combination the PESTLE analysis with other analysis for strategic planning. This serves to determine the weights of the main groups criteria of the compared types of analysis. The methodology consists two types of combination: (a) combination the PESTLE analysis with the SWOT analysis. For this purpose, the interpretation of the PESTLE criteria as SWOT criteria is formed. (b) Combination the PESTLE analysis with the technical, economical, technological and ecological (TETE) group criteria.
Scheme of methodology.
The alternatives represent strategies of the railway manager about the development the railway transport. The case for Bulgarian railway is considered as follows: there are three alternatives, or strategies, the first of which is to maintain the state of affairs as it is; the second, to replace the rolling stock only on some lines of the network, which is a partial improvement; the third, partial improvement on some lines with replacement of some of the rolling stock and also partial improvement of the railway infrastructure.
The characteristics of the alternatives are presented as follows:
A1 – Reconstruction on railway infrastructure. This mean rehabilitation of railway sections and railway lines to increase transport speeds and safety. This process is carried out in accordance with national transport programs.
A2 - New rolling stock on some lines. It means a staged update of rolling stocks, decommissioning of depreciated and obsolete rolling stock. This strategy takes also into account the reconstruction of railway infrastructure.
A3 –Introduction of new services. In this research, a strategy for the service “car on the train” named also motorail trains is proposed. The motorail trains offer service at which passengers can take their car along with them on their journey. The passengers are carried in the train, while the cars are loaded separately in specialized wagons of the same train. This strategy takes also into account the reconstruction of railway infrastructure.
The PESTLE analysis consists Political, Economic, Social, Technological, Legal and Environmental factors that have an impact on the investigated alternatives. A PESTLE analysis helps to understand the business and strategically position of the investigated system. In this study the criteria in PESTLE groups can be defined as quantitative and qualitative. The quantitative criteria are set with their values for each of the studied alternatives. The quality criteria are set in the following ways: with a scale for evaluating the performance of the criterion or by using the answer “yes” or “no”. In the first case, the following rating scale is proposed: 0, 1, 2 or 3. The value “0” indicates non-fulfillment of the respective indicator; a value of “1”, “2” or “3” means low, medium or high performance respectively. In the second case, if the answer is “yes” - “1”is written, otherwise - “0”.
In this study the following criteria in PESTLE groups are proposed:
Political (P) with the following criteria:
P1 - Increasing the quality of railway infrastructure. This means some reconstructions in railway infrastructure to increase the operating speed of the trains. The possible values of this criterion are 1 or 2. The values of “1” means increase of the admissible speed of the railway. The value of “2” means that the investigated alternative allows an increase in the permissible speed also by the rolling stock. The objective of this criterion is of maximum.
P2 - Development of the TEN-T network. This means the development the core TEN-T network in Bulgaria through the implementation of European programs and projects for the development of railway junctions, railway nodes, railway section, harmonization the Bulgarian ‘railway system with the European ones. The possible values of this criterion are 1 or 2. The values of “1” means increase of the development of the railway infrastructure core TEN-T network in Bulgaria. The value of “2” means development the harmonization of the railway system with European railway. The new rolling stocks allows the introduction of new systems for electronic on-board system of locomotives and the development of the European railway traffic management system. The objective of this criterion is of maximum.
P3 – Modernization of the rolling stock. This means purchasing the new locomotives, new type of wagons and electric multiple units to operate in some railway routes. The possible values of this criterion are 1, 2 or 3. The values of “1” means carriage with existing rolling stocks, some modernization in locomotives could to be done. The values of “2” means implementation of the new locomotives and electric multiple units to operate in the main railway routes; the values of “3” means implementation of new type of wagons for carriage the cars. The objective of this criterion is of maximum.
P4 - Increasing the quality of road infrastructure. The road transport is competitive with the railway transport, especially on parallel routes. Improving the quality of road infrastructure makes it possible an increase of the speed of cars and busses. The possible values of this criterion are 0 or 1. Value 1 shows benefit of carriage for road operators. Value “0” shows benefit of carriage for railway operators. The quality of railway transport services increases when offering comfortable, high-speed and safe transport. The objective of this criterion is of minimum.
P5 - Delayed purchase of rolling stock. This means a delay in the scheduled purchasing time due to financial and other reasons. The values of this criterion are 0 or 1. The value “0” is set for alternatives which do not depend on the purchase of new rolling stock. The value of 1 indicates lack of purchase of rolling stock or delay in the purchase plan. The objective of this criterion is of minimization.
P6 - National policy for priority railway transport development. This means that the state should prioritize railway transport by assisting in the financing of railway infrastructure projects and the renewal of rolling stock. The values of this criterion are 0 or 1. The value “0” is set when the national policy is aimed at infrastructure projects for railway rehabilitation. The value “1” means that the expanding national policy by investing in the modernization of rolling stock and trains. The objective of this criterion is of minimum.
P7 - Development of intercity railway transportation. This means development the network of intensity trains with increasing speed. The values of this criterion are 0 or 1. The intercity trains suggest comfort, security and high-quality service between major cities in the railway network. The value “0” is set when only some reconstructions in railway line is met. The value of “1” means the high quality of intercity railway service. The objective of this criterion is of maximum.
Economic (EC) with the following criteria:
EC1 - Operating costs (EUR/day). The operating costs depend on the number of trains. They include the costs for train movement (electricity), costs for maintenance and repair of rolling stock, costs for locomotive crew, depreciation costs and other operating costs, and also the infrastructure charge. The costs for investments for rolling stock, as well as for reconstruction are not taken into account. The objective of this criterion is of minimization.
EC2 - Additional fees for loading and unloading operations. These fees are connected with motorail trains for loading and unloading the cars. The values of this criterion are 0 or 1. The value “0” is set when no service is offered with motorail trains. The value “1” means presence of motorail services. The objective of this criterion is of minimum.
Social (S) with the following criteria:
S1 – Security. The values of this criterion are 1, 2 or 3, which show the level of security. The reconstructions on railway infrastructure, the modernization the rolling stocks, the introduction the motorail services increase the level of security of transport. The larger number indicates the availability of more security in railway service. The objective of this criterion is to maximize security.
S2 – Reliability. This criterion is assessed as 1, 2 and 3. The renovation of the railway lines increase the reliability. The modernization of the rolling stock increases also the reliability of transport. The motorail trains also increase additionally the ratability od railway transport taken into account that the cars carried by trains reduce the traffic on the road infrastructure. The larger number indicates the availability of more reliability in railway service. The objective of this criterion is of maximum.
S3 – Comfort. This criterion is assessed as 1, 2 and 3. Travel comfort is expressed by ensuring the convenience of traveling in clean, renovated or renewed rolling stock. The comfort also increases when the motorail service is added because the drivers could use their free time to rest. The larger number indicates the availability of more comfort in traveling. The objective of this criterion is of maximum.
S4 – Additional services. The values of this criterion are 0,1 or 2. The new rolling stock has equipment with modern information systems, and WIFI networks in the trains. The motorail trains offer the carriage the cars of the passengers. The larger number indicates the availability of more additional services. The objective of this criterion is of maximization.
S5 - Position in the transport market (quality). This criterion can have values 1, 2 or 3. The position of the railway transport on the market of transport services increases, with the improvement of the condition of the rolling stock and the railway infrastructure. The larger number shows a higher position in the transport market. The objective of this criterion is of maximization.
S6 – Transport in certain months. The values of this criterion are 0 or 1. The motorail services usually applied during the summer months, mine are associated with an increase in tourist travel. The objective of this criterion is of minimum.
Technological (T) with the following criteria.
T1 - Frequency, pair trains/day. The number of trains increase when the new rolling stocks is added. The objective of this criterion is of maximization.
T2 – Average operating speed, km/h. This criterion is determined according all fast and high-speed trains in the railway network. The increase of the operational speed is achieved with the reconstruction of the infrastructure and also the modernization of rolling stock. The value of average operating speed increases when there are conditions for some trains to run at high speed. The objective of this criterion is of maximization.
T3 – Directness. This criterion means services with a reduced number of intermediate stops. This criterion may have the following values: 0 or 1. The value “0” means lack of direct trains with increased speed. The introduction of direct express intercity trains, which have reduced stops in only a few places along the route, allows to increase the directness of the journey, to reduce its duration between stations, as well as for the entire route. The value “1” means presence of direct trains with increased speed. The objective of this criterion is of maximization.
T4 - Total travel time. This criterion includes the time for travel and the tome for acceptance and loading of cars in specialized wagons in motorail train composition. This criterion may have the following values: 0 or 1. The value “1” means increased total time due to motorail service; the value “0” is set when such service is not available. The objective of this criterion is of maximization.
T5 – Frequency of motorail trains. This criterion shows the number of pairs motorail trains per day. The objective of this criterion is of maximization taken into account that such service increases the transport satisfaction of the passengers of railway services. The objective of this criterion is of maximization.
T6 – Transport door-to-door. This means the possibility for passengers to travel with their own car from their home to the start railway station, then to load the car on the specialized wagon, and at the final railway station the car is unloaded and the passenger continues his journey with his own car to the final destination. This criterion may have the following values: 0 or 1. The value “1” means service door-to-door; the value “0” is set otherwise. The objective of this criterion is of maximization.
Legal (L) with the following criteria.
L1 - Possibility of increase the level of European Rail Traffic Management System (ERTMS) system. This criterion may have the following values: 0 or 1. ERTMS is a train signaling and traffic management system, created to assist interoperability by using a unique signaling and communication standard throughout Europe. There are three levels of the application of ERTMS depending on the need for existing railway infrastructure. The value “1” shows increase the level of ERTMS taking into account the level of communication system in locomotives and moving block technology. The objective of this criterion is of maximization.
Environmental (EN) with the following criteria.
EN1 - CO2 emissions. The values of CO2 emissions are calculated according the electricity generation for movement of the trains, t/MWhe.
EN2 - Saved CO2 emissions. This criterion takes into account the CO2 emissions saved by cars when transported in a specialized wagon. The value depends on the number of motorail trains.
The SIMUS method is based on Linear Programming, Weighted Sum and Outranking, [27]. This approach considered the criteria as objectives in Linear optimization models. The first step of the method consists of the forming the initial decision matrix with alternatives in the columns and criteria in the rows. In the next step the normalization of the initial decision matrix is made by applying some of the normalizing procedures. In the third step, the linear optimization models are formed taken into account each criterion as objective and the optimal scores for the alternatives are determined. The results are placed in an Efficient Result Matrix (ERM). This matrix is considered as a new decision matrix, composed of the optimal values. The next step consists ranking the alternatives. The SIMUS uses two different multi-criteria procedures to rank the alternatives - Weighted Sum method and outranking approach. The first approach is called ERM ranking and is based on ERM matrix; the second ones is called Project Dominance Matrix (PDM) ranking and uses a new matrix which is formed based on ERM matrix. The results of both methods give the same ranking. This allows the result to be validated. The SIMUS method give also the marginal utilities for each criterion, and allow to determine the robustness of the solution. For this purpose, the ERM matrix is used to determine the weights of criteria. Determining the weights of the criteria allows the decision maker to assess their impact on the investigated system. The values of criteria are not used when ranking the alternatives.
The Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) is based on the principle that best alternative should have the shortest distance from the ideal solution and farthest distance from the negative ideal solution. TOPSIS consists the following steps, [28]:
Step 1: Determination the decision matrix
where:
Step 2: Calculate weighted normalized matrix
where:
Step 3: Calculate the ideal best
Step 4: Determination the Euclidean distance from the ideal best
Step 5: Calculate Performance Score
The ranking of the alternatives is based on the
EDAS method determines the optimal alternative based on the higher distance from the nadir solution and lowest distance from the ideal solution. The EDAS method consists the following steps, [29]:
Step 1: Determination the decision matrix
Step 2. Determination the average solution according to all criteria.
Step 3: Determination the positive
Step 4: Determination of the weighted sum of positive
Step 5: Normalization of the weighted sum of positive
Step 6: Determination the appraisal score. The ranking is according to the decreasing values of appraisal score. The optimal alternative based on the appraisal score has the highest assessment value.
The multi-objective optimization on the basis of ratio analysis (MOORA) method uses both beneficial and non-beneficial objectives (criteria) for ranking the alternatives. This method is based on ratio system. The MOORA method is utility-based method and consists the following steps, [30]:
Step 1: Determination the decision matrix
Step 2: The ratio represented the normalized performances
Step 3: Determination the normalized performances in the case of maximation (for beneficial criteria) and the normalized performances in the case of minimization (for non-beneficial criteria). The optimal alternative based on the ratio system has the highest assessment value. The
Where:
The COPRAS method uses simple evaluating procedure to determine the influence of maximizing and minimizing criteria on ranking the alternatives. The best alternative is based on both the ideal and the anti-ideal solutions. The COPRAS method is utility-based method and consists the following steps, [31]:
Step 1: Determination the decision matrix
Step 2: Normalization of the decision matrix. The elements are calculated as follows:
Step 3: Determination of the weighted normalized matrix
Step 4: Determination of the maximizing index
Where:
Step 5: Determination of the relative weights of each alternative. The best alternative is based on the highest the relative weights.
The Preference ranking organization method for enrichment evaluation (PROMETHEE) method is outranking approach in multi-criteria analysis. The explanation and mathematical calculation steps of the PROMETHEE method are summarized below [28]:
Step 1: This step computes, for each pair of possible decisions and for each criterion, the value of the preference degree.
Step 2: This step consists of aggregating the preference degrees of all criteria for each pair of possible decisions.
Step 3: This step includes the computing of the outranking flows. For each possible decision the positive outranking flow
Step 4: In this step the net outranking flows
For net outranking flow, the following conditions are valid:
The fifth stage of methodology consists a combination of the PESTLE analysis with other analysis for strategic planning as SWOT technique. In this chapter is studied also the integration between PESTLE and technical, economic, technological and environmental (TETE) group criteria. This serves to determine the weights of the main groups criteria of the compared types of analysis. Table 1 represents the interactions between PESTLE and SWOT analysis on the one hand and between PESTLE and TETE analysis on the other hand. The symbol “x” indicate that the criterion of PESTLE is also a criterion in SWOT or TETE analysis.
PESTLE | Criteria | S | W | O | T | PESTLE | Criteria | T | E | T | E |
---|---|---|---|---|---|---|---|---|---|---|---|
P1 | x | P1 | х | ||||||||
P2 | x | P2 | х | ||||||||
P3 | x | P3 | х | ||||||||
P4 | x | P4 | х | ||||||||
P5 | x | P5 | х | ||||||||
P6 | x | P6 | х | ||||||||
P7 | x | P7 | х | ||||||||
EC1 | x | EC1 | х | ||||||||
EC2 | x | EC2 | х | ||||||||
S1 | x | S1 | х | ||||||||
S2 | x | S2 | х | ||||||||
S3 | x | S3 | х | ||||||||
S4 | x | S4 | х | ||||||||
S5 | x | S5 | х | ||||||||
S6 | х | S6 | х | ||||||||
T1 | x | T1 | х | ||||||||
T2 | x | T2 | х | ||||||||
T3 | x | T3 | х | ||||||||
T4 | x | T4 | х | ||||||||
T5 | х | T5 | х | ||||||||
T6 | x | T6 | х | ||||||||
L1 | х | L1 | х | ||||||||
EN1 | х | EN1 | х | ||||||||
EN2 | х | EN2 | х |
Interactions between PESTLE, SWOT and TETE analysis.
The proposed methodology is applied for Bulgarian railway network. The following categories of intercity passenger trains have been studied: fast trains, accelerated fast trains and express trains. The fast trains serve intermediate stations between cities, big transport and important administrative centers. The accelerated fast trains have mandatory seat reservations and serve major cities and transport nodes. The direct express trains have a lower number of stops in comparison to accelerated fast trains. They also have mandatory seat reservations. The alternative A1 consists two categories of trains – fast and accelerated fast trains, while alternatives A2 and A3 offers three categories of trains – fast trains, accelerated fast trains and direct express trains.
Alternative A1 is close to the current situation in which some reconstructions in railway lines are carried out according to the operational program transport for Bulgaria. The trains are composed of wagons, only some intercity trains are electric multiple units. In current situation the average technical speed of movement of passenger trains in Bulgarian railway network is one of the lowest in Europe. The movement of trains is achieved at 75 ÷ 80 km/h, and in certain areas it is limited to 40–60 km/h in order to ensure traffic safety. The express trains and accelerated fast trains in alternatives A2 and A3 are composed of novel electric multiple unit trains. Alternative A3 offer new service with motorail trains in direction Sofia - Plovdiv – Burgas (this is part of the core TEN-T network). In this case, new rolling stooks for carriage of cars are taken into account.
The third stage of methodology includes application the SUMUS method to select the appropriate alternative. Table 2 consists two parts. The first part represents the initial decision matrix for SIMUS procedure. This matrix consists the values of quantitative and qualitative criteria in PESTLE groups. The values of criteria P5, P6, P7, EC1, S6, T3, T4, T6 and L1 are determined using scale 0, 1. The values of criteria P1, P2, P3, S1-S5 and T5 are determined using a scale of 0, 1, 2, 3.
Criterion | Initial matrix | Normalized matrix | Action | Type | RHS | ||||
---|---|---|---|---|---|---|---|---|---|
A1 | A2 | A3 | A1 | A2 | A3 | ||||
P1 | 1.00 | 2.00 | 2.00 | 0.20 | 0.40 | 0.40 | max | ≤ | 0.40 |
P2 | 1.00 | 2.00 | 2.00 | 0.20 | 0.40 | 0.40 | max | ≤ | 0.40 |
P3 | 1.00 | 2.00 | 3.00 | 0.17 | 0.33 | 0.50 | max | ≤ | 0.50 |
P4 | 1.00 | 0.00 | 0.00 | 1.00 | 0.00 | 0.00 | min | ≥ | 0.00 |
P5 | 0.00 | 1.00 | 1.00 | 0.00 | 0.50 | 0.50 | min | ≥ | 0.00 |
P6 | 0.00 | 1.00 | 1.00 | 0.00 | 0.50 | 0.50 | max | ≤ | 0.50 |
P7 | 0.00 | 1.00 | 1.00 | 0.00 | 0.50 | 0.50 | max | ≤ | 0.50 |
EC1 | 50807.00 | 51957.00 | 61491.00 | 0.31 | 0.32 | 0.37 | min | ≥ | 0.31 |
EC2 | 0.00 | 0.00 | 1.00 | 0.00 | 0.00 | 1.00 | min | ≥ | 0.00 |
S1 | 1.00 | 2.00 | 3.00 | 0.17 | 0.33 | 0.50 | max | ≤ | 0.50 |
S2 | 1.00 | 2.00 | 3.00 | 0.17 | 0.33 | 0.50 | max | ≤ | 0.50 |
S3 | 1.00 | 2.00 | 3.00 | 0.17 | 0.33 | 0.50 | max | ≤ | 0.50 |
S4 | 0.00 | 1.00 | 2.00 | 0.00 | 0.33 | 0.67 | max | ≤ | 0.67 |
S5 | 1.00 | 2.00 | 3.00 | 0.17 | 0.33 | 0.50 | max | ≤ | 0.50 |
S6 | 0.00 | 0.00 | 1.00 | 0.00 | 0.00 | 1.00 | min | ≥ | 0.00 |
T1 | 36.00 | 38.00 | 40.00 | 0.32 | 0.33 | 0.35 | max | ≤ | 0.35 |
T2 | 65.00 | 80.00 | 80.00 | 0.29 | 0.36 | 0.36 | max | ≤ | 0.36 |
T3 | 0.00 | 1.00 | 1.00 | 0.00 | 0.50 | 0.50 | max | ≤ | 0.50 |
T4 | 0.00 | 0.00 | 1.00 | 0.00 | 0.00 | 1.00 | min | ≥ | 0.00 |
T5 | 0.00 | 0.00 | 3.00 | 0.00 | 0.00 | 1.00 | max | ≤ | 1.00 |
T6 | 0.00 | 0.00 | 1.00 | 0.00 | 0.00 | 1.00 | max | ≤ | 1.00 |
L1 | 0.00 | 1.00 | 1.00 | 0.00 | 0.50 | 0.50 | max | ≤ | 0.50 |
EN1 | 23511.00 | 25225.00 | 25225.00 | 0.32 | 0.34 | 0.34 | min | ≥ | 0.32 |
EN2 | 0.00 | 0.00 | 2808000.00 | 0.00 | 0.00 | 1.00 | max | ≤ | 1.00 |
Initial decision matrix. Normalized “sum” matrix.
The number of trains for alternatives A2 and A3 increases due to the replacement of old rolling stock with new one. The alternative A2 and A3 there are an increase in electricity consumption due to increased maximum speed 100–120 km/h in the direction Sofia - Plovdiv – Burgas (this is part of the core TEN-T network). The carbon dioxide emissions for the production of electricity by the power plants also decrease.
The second part of Table 2 shows the normalized matrix, the type of actions for each criterion, the type of the operator for the restrictive conditions, the limits called “Right Hand Side” (RHS). The normalization has been performed by using the Sum of All Values method. In general, the normalization could be made based on some of different ways. The values of the RHS are obtained from the left normalized values and the type of action. In the case of minimum, RHS is equal to the minimum value of the row; in the case of maximum, the RHS value is equal to the maximum value of the row in normalized matrix. The type of operator depends on the type of objective function. In the case of maximum, the operator is “≤”; in the case of minimum, the operator is “≥ ”.
The linear optimization models are performed by using the data in Table 2. For example, the first optimization linear model is formed for the first objective Z1(criterion P1) as follows:
where:
The restrictive conditions for the optimization model are formed by using the others rows of the ERM matrix. For example, for criterion P2, the restrictive condition is:
The restrictive conditions are formed successively using all other rows in the Normalized Sum Matrix. The final restrictive condition for the first optimization model is performed by criterion EN2 (objective Z24) based on the data in the last row in the Normalized Sum Matrix, as follows:
For all variables the following condition is set:
Similar optimization linear models are performed for all other criteria. The results for the scores are recorded in Efficient Results Matrix. The next step of the SIMUS procedure includes the normalization of the ERM matrix. Then two approaches are used for ranking the alternatives - weighted sum method and outranking approach. In the first approach the sum method has been applied to normalize the ERM matrix. The results are presented in the first part of Table 3. The second part shows the steps of the ranking. First the sum of column is determined. The number of satisfactions of each alternative by each objective are determined and recorded as participation factors (PF). The normalization of the participation factor is carried out by dividing the number of criteria. The final results of the alternatives are calculated by multiplying the sum of the columns by the normalized participation factor. The alternatives are ranked in descending order. Table 4 shows the ERM matrix and the determination of the weights of criteria. The first part of the table indicates the ERM matrix and the values of the objective function for each optimization. The second part of Table 4 shows haw to calculate the weights of criteria. For this purpose, first the maximum value of the row for ERM matrix
Criterion | Objective | Alternatives | ||
---|---|---|---|---|
A1 | A 2 | A3 | ||
P1 | Z1 | 1.00 | ||
P2 | Z2 | 1.00 | ||
P3 | Z3 | 1.00 | ||
P4 | Z4 | 1.00 | ||
P5 | Z5 | 1.00 | ||
P6 | Z6 | 1.00 | ||
P7 | Z7 | 1.00 | ||
EC1 | Z8 | 1.00 | ||
EC2 | Z9 | 1.00 | ||
S1 | Z10 | 1.00 | ||
S2 | Z11 | 1.00 | ||
S3 | Z12 | 1.00 | ||
S4 | Z13 | 1.00 | ||
S5 | Z14 | 1.00 | ||
S6 | Z15 | 1.00 | ||
T1 | Z16 | 1.00 | ||
T2 | Z17 | 0.11 | 0.89 | |
T3 | Z18 | 1.00 | ||
T4 | 1.00 | |||
T5 | Z19 | 1.00 | ||
T6 | Z20 | 1.00 | ||
L1 | Z21 | 1.00 | ||
EN1 | Z22 | 1.00 | ||
EN2 | Z23 | 1.00 | ||
Sum of Column (SC) | 2.11 | 4.89 | 17.00 | |
Participation Factor (PF) | 3 | 5 | 17 | |
Norm. Participation Factor (NPF) | 0.13 | 0.21 | 0.71 | |
Final Result (SC x NPF) | 0.26 | 1.02 | 12.04 | |
ERM Ranking | A3 - A2 - A1 |
Normalized efficient results matrix. Ranking. (The values equal to 0 are not shown).
Criterion | Objective | A 1 | A 2 | A 3 | Objective function values | SIMUS | SIMUS | ||
---|---|---|---|---|---|---|---|---|---|
P1 | Z1 | 0.00 | 0.00 | 1.00 | 0.40 | 1.00 | 0.042 | 0.29 | |
P2 | Z2 | 0.00 | 0.00 | 1.00 | 0.40 | 1.00 | 0.042 | ||
P3 | Z3 | 0.00 | 0.00 | 1.00 | 0.50 | 1.00 | 0.042 | ||
P4 | Z4 | 0.00 | 0.00 | 0.93 | 0.00 | 0.93 | 0.039 | ||
P5 | Z5 | 1.00 | 0.00 | 0.00 | 0.00 | 1.00 | 0.042 | ||
P6 | Z6 | 0.00 | 0.00 | 1.00 | 0.50 | 1.00 | 0.042 | ||
P7 | Z7 | 0.00 | 0.00 | 1.00 | 0.50 | 1.00 | 0.042 | ||
EC1 | Z8 | 0.00 | 0.93 | 0.00 | 0.29 | 0.93 | 0.039 | 0.08 | |
EC2 | Z9 | 0.00 | 0.98 | 0.00 | 0.00 | 0.98 | 0.041 | ||
S1 | Z10 | 0.00 | 0.00 | 1.00 | 0.50 | 1.00 | 0.042 | 0.25 | |
S2 | Z11 | 0.00 | 0.00 | 1.00 | 0.50 | 1.00 | 0.042 | ||
S3 | Z12 | 0.00 | 0.00 | 1.00 | 0.50 | 1.00 | 0.042 | ||
S4 | Z13 | 0.00 | 0.00 | 1.00 | 0.67 | 1.00 | 0.042 | ||
S5 | Z14 | 0.00 | 0.00 | 1.00 | 0.50 | 1.00 | 0.042 | ||
S6 | Z15 | 0.00 | 0.98 | 0.00 | 0.00 | 0.98 | 0.041 | ||
T1 | Z16 | 1.23 | 0.00 | 0.00 | 0.39 | 1.23 | 0.052 | 0.26 | |
T2 | Z17 | 0.12 | 0.94 | 0.00 | 0.37 | 0.94 | 0.040 | ||
T3 | Z18 | 0.00 | 0.00 | 1.00 | 0.50 | 1.00 | 0.042 | ||
T4 | Z19 | 0.00 | 0.98 | 0.00 | 0.00 | 0.98 | 0.041 | ||
T5 | Z20 | 0.00 | 0.00 | 1.00 | 1.00 | 1.00 | 0.042 | ||
T6 | Z21 | 0.00 | 0.00 | 1.00 | 1.00 | 1.00 | 0.042 | ||
L1 | Z22 | 0.00 | 0.00 | 1.00 | 0.50 | 1.00 | 0.042 | 0.04 | |
EN1 | Z23 | 0.00 | 0.00 | 0.83 | 0.28 | 0.83 | 0.035 | 0.08 | |
EN2 | Z24 | 0.00 | 0.00 | 1.00 | 1.00 | 1.00 | 0.042 | ||
Total | 23.80 | 1.00 | 1.00 |
Efficient results matrix (ERM). Weights of criteria.
Table 5 shows the results of ranking according the outranking approach of SIMUS method. The number of columns and the rows in PDM is equal to the number of alternatives. The ERM matrix is used for compiling PDM ranking. Starting from the highest value in the first row the difference between values in the same row of normalized ERM is calculated. The procedure is repeated with all the values. The net dominance is calculated as the difference between row sum and column sum. The alternatives are ranked according to the maximal value of the net dominance. The results presented in Tables 3 and 5 show that the ranking formed using both procedures is the same. Alternative A1 is the most suitable.
Dominant alternatives | A1 | A2 | A3 | Row sum | Net dominance |
---|---|---|---|---|---|
A1 | — | 2.0 | 2.1 | 4.1 | −17.7 |
A2 | 4.8 | — | 4.9 | 9.7 | −9.3 |
A3 | 17.0 | 17.0 | — | 34.0 | 27.0 |
Column sum | 21.8 | 19.0 | 7.0 | — | — |
PDM Ranking | A3 - A2 - A1 |
Project dominance matrix (PDM). Ranking.
The main advantages of the SIMUS method are that it does not use expert’s assessment and does not use the weights of criteria for ranking the alternatives. There is no subjectivism in decision making. SIMUS applied Linear Programming that does not use any type of weights, that’s why they are not needed in the SIMUS procedure. The results of optimization are Pareto efficient. The weights of criteria can be determined in the end of optimization to determine its impact on the studied system. Two approaches are used to rank the alternatives; thus, verifying the results.
The fourth stage of methodology includes ranking by application the following multi-criteria methods: distance based: TOPSIS and EDAS, utility based: MOORA and COPRAS; and outranking approach PROMETEE. All these methods require the weights of the criteria to be set. What because, the weights determined on the basis of the ERM matrix of the SIMUS method are used as input to the studied methods. The results of the criteria weights show that they have almost equal values. For this reason, they may not be taken into account. Table 6 shows the results of application the distance based multi-criteria methods: TOPSIS and EDAS methods. Eqs. (1–12) have been applied. It can be seen that the ranking of alternatives is similar to those by SIMIS method. Table 7 represents the results of MOORA and COPRAS methods. Eqs. (13–17) have been used. The ranking is also similar to those received by SIMUS approach.
Alternative | TOPSIS | EDAS | ||||||||
---|---|---|---|---|---|---|---|---|---|---|
Rank | Rank | |||||||||
A1 | 2.910 | 1.843 | 0.388 | 3 | 4.135 | 0.318 | 13.486 | 0.000 | 0.159 | 3 |
A2 | 2.198 | 2.323 | 0.514 | 2 | 6.518 | 0.501 | 3.505 | 0.475 | 0.488 | 2 |
A3 | 1.843 | 2.910 | 0.612 | 1 | 13.019 | 1.000 | 6.681 | 0.000 | 0.500 | 1 |
TOPSIS, EDAS – results.
Alternative | MOORA | COPRAS | ||||||
---|---|---|---|---|---|---|---|---|
Rank | Rank | |||||||
A1 | 3.048 | 2.074 | 0.974 | 3 | 3.048 | 2.074 | 10.262 | 3 |
A2 | 8.472 | 1.833 | 6.639 | 2 | 8.472 | 1.833 | 15.686 | 2 |
A3 | 13.285 | 4.963 | 8.322 | 1 | 13.285 | 4.963 | 20.500 | 1 |
MOORA, COPRAS - results.
Table 8 shows the net outranking flows, the positive outranking flow
Alternative | Rank | |||
---|---|---|---|---|
A1 | 0.292 | 0.500 | 0.208 | 3 |
A2 | 0.104 | 0.292 | 0.188 | 2 |
A3 | −0.396 | 0.188 | 0.583 | 1 |
PROMETHEE - results.
The most suitable alternative according all represented approached is alternative A3. This means that introduction of new service “car on the train” named also motorail trains is proposed. This strategy takes also into account the reconstruction of railway infrastructure.
In this chapter is studied the integration between PESTLE and SWOT analysis and also the integration between PESTLE and TETE analysis. This serves to determine the weights of the main groups criteria of the compared types of analysis. Table 9 represents the dependencies between the criteria. The weights of predefined criteria in PESTLE group are recorded in the relevant places in SWOT or TETE group. Thus, the weights are determined for SWOT and TETE criteria. Finally, the main criteria for groups are calculated. It can be seen that the main importance for SWOT groups have Weakness (0.42) and Opportunities (0.38) groups criteria. The main impact for TETE groups criteria has technical (0.29) and technological (0.51) groups criteria.
SIMUS | S | W | O | T | Te | Ec | Tn | En | ||||
---|---|---|---|---|---|---|---|---|---|---|---|---|
P1 | 0.042 | — | 0.042 | — | P1 | 0.042 | — | — | — | |||
P2 | 0.042 | — | 0.042 | — | P2 | 0.042 | — | — | — | |||
P3 | 0.042 | — | 0.042 | — | P3 | 0.042 | — | — | — | |||
P4 | 0.039 | — | 0.039 | P4 | 0.039 | — | — | — | ||||
P5 | 0.042 | — | 0.042 | P5 | — | 0.042 | — | — | ||||
P6 | 0.042 | — | 0.042 | — | P6 | — | 0.042 | — | ||||
P7 | 0.042 | — | 0.042 | — | P7 | — | 0.042 | — | ||||
EC1 | 0.039 | — | 0.039 | — | EC1 | — | 0.039 | — | — | |||
EC2 | 0.041 | — | 0.041 | — | EC2 | — | 0.041 | — | — | |||
S1 | 0.042 | 0.042 | — | S1 | 0.042 | — | — | |||||
S2 | 0.042 | 0.042 | — | S2 | 0.042 | — | — | |||||
S3 | 0.042 | — | 0.042 | — | S3 | — | 0.042 | — | ||||
S4 | 0.042 | — | 0.042 | — | S4 | — | — | 0.042 | — | |||
S5 | 0.042 | — | 0.042 | — | S5 | — | — | 0.042 | — | |||
S6 | 0.041 | — | 0.041 | — | S6 | — | — | 0.041 | — | |||
T1 | 0.052 | — | 0.052 | — | T1 | — | — | 0.052 | — | |||
T2 | 0.040 | — | 0.04 | — | T2 | — | — | 0.040 | — | |||
T3 | 0.042 | — | 0.042 | — | T3 | — | — | 0.042 | — | |||
T4 | 0.041 | — | 0.041 | — | T4 | — | — | 0.041 | — | |||
T5 | 0.042 | — | 0.042 | — | T5 | — | — | 0.042 | — | |||
T6 | 0.042 | — | 0.042 | — | T6 | — | — | 0.042 | — | |||
L1 | 0.042 | — | 0.042 | — | L1 | 0.042 | — | — | — | |||
EN1 | 0.035 | 0.035 | — | EN1 | — | — | — | 0.035 | ||||
EN2 | 0.042 | — | 0.042 | — | EN2 | — | — | — | 0.042 | |||
1.00 | 0.12 | 0.42 | 0.38 | 0.08 | 0.29 | 0.12 | 0.51 | 0.08 |
PESTLE – SWOT – TETE relations and weights.
Figure 2 illustrates the impact of the criteria according compared analysis. The established dependencies between the criteria in the use of different types of strategic analyzes help the decision maker to expand the analysis of the influence of factors on the studied system.
PESTLE, SWOT, TETE weights.
This chapter proposes a methodology for assessment of the strategies of development the railway passenger transport using integration of PESTLE and SWOT criteria and MCDM methods. Different multi-criteria methods, as linear programming-based, distance-based, utility-based and outranking have been applied to rank the alternatives. All studied methods except SIMUS use weights of criteria in the procedures of ranking the alternatives. The SIMUS method only applies linear optimization, while the other applied methods use formulas to determine the distance to the ideal solution or utility. It is also a hybrid MCDM method because the ranking is based on weighted sum method and outranking approach. SUMUS also give the weights of the criteria as a result by the optimization and thus there is no subjectivism. The defined weights are valid for the set data.
The main advantages of the PROMETHEE method as an outranking method compared to the distance-based, utility-based multi-criteria methods are the following: it uses a preference functions for each criterion; normalization of the initial decision matrix is not used; availability of software that allows easy sensitivity analysis; the type of optimization can be taken into account - maximum or minimum.
The main advantages of the EDAS method are that it does not use normalization of the initial matrix for decision making; the criteria can be of maximum or minimum, i.e., of costs or benefits. This method determines the best alternative using the distance from average solution instead of calculating the distance from ideal and negative ideal solutions as in the compromise MCDM methods such as TOPSIS. The method is quite comprehensible and easy to apply. The TOPSIS method uses criteria that must be of one type - benefits. The subtraction-based conversion procedure for non-beneficial criteria is needed, which converts criterion type using the differences between criterion values and the maximum value in the criterion column. Thus, can completely distort the results of the analysis. The utility-based methods MOORA and COPRAS also use matrix normalization for decision making, the criteria can be of costs or of benefits. COPRAS separately evaluates influence of maximized and minimized criteria. It could be concluded that the SIMUS method is the most suitable multi-criteria method as based on linear programming it can assessed different quantitative and qualitative criteria and alternatives considering all criteria. There is also software that can solve SIMUS procedure.
The research propose PESTLE – SWOT – SIMUS approach as the most suitable to assess the alternatives and criteria. The advantages of application the SIMUS technique with PESTLE – SWOT criteria consists in the lack of subjectivism in decision making because the weights of criteria are not used, consideration the criteria as objectives in Linear programming optimization models. The PESTLE criteria are presented as objectives and the ranking of the alternatives of strategic planning is conducted without the use of subjective expert evaluation. The results of SIMUS ranking are compared with distance based, utility based and outranking multi-criteria approaches to make decision. These methods use weights of criteria in their procedures. In this research these weights have been set based on the results given by SIMUS method. The weights of criteria in PESTLE groups have been determined based on the results given by linear optimization in SIMUS, and the set of alternatives to evaluate. This approach depends of the data, there is not a subjectivism. It was found that the most important are the political (0.29), social (0.25) and technological (0.25) groups in PESTLE analysis. By establishing dependencies between PESTLE and SWOT groups criteria, the weights of Strengths - Weaknesses – Opportunities – Threats has been determined. It was found that the main importance in SWOT groups have Weakness (0.42) and Opportunities (0.38) groups criteria. The independences between PESTLE criteria and technical, economic, technological and environmental (TETE) criteria were determined. It was found that the main impact for TETE groups criteria has technical (0.29) and technological (0.51) criteria. It could be summed based on PESTLE and TETE analysis that the technological criteria have of great importance when choosing a strategy for railway development. The most suitable strategy for Bulgarian railway passenger transport has been proposed, including the service with motorail trains.
This work was supported by the National Science Fund of the Ministry of Education and Science of Bulgaria [project number No.KP-06-H27/12 of 11.12.2018 “Modelling and elaboration of complex system for selection of transport technology in transport network”].
The author declares no conflict of interest.
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The Open Access publishing movement started in the early 2000s when academic leaders from around the world participated in the formation of the Budapest Initiative. They developed recommendations for an Open Access publishing process, “which has worked for the past decade to provide the public with unrestricted, free access to scholarly research—much of which is publicly funded. Making the research publicly available to everyone—free of charge and without most copyright and licensing restrictions—will accelerate scientific research efforts and allow authors to reach a larger number of readers” (reference: http://www.budapestopenaccessinitiative.org)
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\n\nIntechOpen is committed to ensuring the long-term preservation and the availability of all scholarly research we publish. We employ a variety of means to enable us to deliver on our commitments to the scientific community. Apart from preservation by the Croatian National Library (for publications prior to April 18, 2018) and the British Library (for publications after April 18, 2018), our entire catalogue is preserved in the CLOCKSS archive.
\n\nOpen Science is transparent and accessible knowledge that is shared and developed through collaborative networks.
\n\nOpen Science is about increased rigour, accountability, and reproducibility for research. It is based on the principles of inclusion, fairness, equity, and sharing, and ultimately seeks to change the way research is done, who is involved and how it is valued. It aims to make research more open to participation, review/refutation, improvement and (re)use for the world to benefit.
\n\nOpen Science refers to doing traditional science with more transparency involved at various stages, for example by openly sharing code and data. It implies a growing set of practices - within different disciplines - aiming at:
\n\nWe aim at improving the quality and availability of scholarly communication by promoting and practicing:
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His studies in robotics lead him not only to a PhD degree but also inspired him to co-found and build the International Journal of Advanced Robotic Systems - world's first Open Access journal in the field of robotics.",institutionString:null,institution:{name:"TU Wien",country:{name:"Austria"}}},{id:"441",title:"Ph.D.",name:"Jaekyu",middleName:null,surname:"Park",slug:"jaekyu-park",fullName:"Jaekyu Park",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/441/images/1881_n.jpg",biography:null,institutionString:null,institution:{name:"LG Corporation (South Korea)",country:{name:"Korea, South"}}},{id:"465",title:"Dr",name:"Christian",middleName:null,surname:"Martens",slug:"christian-martens",fullName:"Christian Martens",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:null},{id:"479",title:"Dr.",name:"Valentina",middleName:null,surname:"Colla",slug:"valentina-colla",fullName:"Valentina Colla",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/479/images/358_n.jpg",biography:null,institutionString:null,institution:{name:"Sant'Anna School of Advanced Studies",country:{name:"Italy"}}},{id:"494",title:"PhD",name:"Loris",middleName:null,surname:"Nanni",slug:"loris-nanni",fullName:"Loris Nanni",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/494/images/system/494.jpg",biography:"Loris Nanni received his Master Degree cum laude on June-2002 from the University of Bologna, and the April 26th 2006 he received his Ph.D. in Computer Engineering at DEIS, University of Bologna. On September, 29th 2006 he has won a post PhD fellowship from the university of Bologna (from October 2006 to October 2008), at the competitive examination he was ranked first in the industrial engineering area. He extensively served as referee for several international journals. He is author/coauthor of more than 100 research papers. He has been involved in some projects supported by MURST and European Community. 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Delac received his B.Sc.E.E. degree in 2003 and is currentlypursuing a Ph.D. degree at the University of Zagreb, Faculty of Electrical Engineering andComputing. His current research interests are digital image analysis, pattern recognition andbiometrics.",institutionString:null,institution:{name:"University of Zagreb",country:{name:"Croatia"}}},{id:"557",title:"Dr.",name:"Andon",middleName:"Venelinov",surname:"Topalov",slug:"andon-topalov",fullName:"Andon Topalov",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/557/images/1927_n.jpg",biography:"Dr. Andon V. Topalov received the MSc degree in Control Engineering from the Faculty of Information Systems, Technologies, and Automation at Moscow State University of Civil Engineering (MGGU) in 1979. He then received his PhD degree in Control Engineering from the Department of Automation and Remote Control at Moscow State Mining University (MGSU), Moscow, in 1984. From 1985 to 1986, he was a Research Fellow in the Research Institute for Electronic Equipment, ZZU AD, Plovdiv, Bulgaria. In 1986, he joined the Department of Control Systems, Technical University of Sofia at the Plovdiv campus, where he is presently a Full Professor. He has held long-term visiting Professor/Scholar positions at various institutions in South Korea, Turkey, Mexico, Greece, Belgium, UK, and Germany. And he has coauthored one book and authored or coauthored more than 80 research papers in conference proceedings and journals. His current research interests are in the fields of intelligent control and robotics.",institutionString:null,institution:{name:"Technical University of Sofia",country:{name:"Bulgaria"}}},{id:"585",title:"Prof.",name:"Munir",middleName:null,surname:"Merdan",slug:"munir-merdan",fullName:"Munir Merdan",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/585/images/system/585.jpg",biography:"Munir Merdan received the M.Sc. degree in mechanical engineering from the Technical University of Sarajevo, Bosnia and Herzegovina, in 2001, and the Ph.D. degree in electrical engineering from the Vienna University of Technology, Vienna, Austria, in 2009.Since 2005, he has been at the Automation and Control Institute, Vienna University of Technology, where he is currently a Senior Researcher. His research interests include the application of agent technology for achieving agile control in the manufacturing environment.",institutionString:null,institution:null},{id:"605",title:"Prof",name:"Dil",middleName:null,surname:"Hussain",slug:"dil-hussain",fullName:"Dil Hussain",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/605/images/system/605.jpg",biography:"Dr. Dil Muhammad Akbar Hussain is a professor of Electronics Engineering & Computer Science at the Department of Energy Technology, Aalborg University Denmark. Professor Akbar has a Master degree in Digital Electronics from Govt. College University, Lahore Pakistan and a P-hD degree in Control Engineering from the School of Engineering and Applied Sciences, University of Sussex United Kingdom. Aalborg University has Two Satellite Campuses, one in Copenhagen (Aalborg University Copenhagen) and the other in Esbjerg (Aalborg University Esbjerg).\n· He is a member of prestigious IEEE (Institute of Electrical and Electronics Engineers), and IAENG (International Association of Engineers) organizations. \n· He is the chief Editor of the Journal of Software Engineering.\n· He is the member of the Editorial Board of International Journal of Computer Science and Software Technology (IJCSST) and International Journal of Computer Engineering and Information Technology. \n· He is also the Editor of Communication in Computer and Information Science CCIS-20 by Springer.\n· Reviewer For Many Conferences\nHe is the lead person in making collaboration agreements between Aalborg University and many universities of Pakistan, for which the MOU’s (Memorandum of Understanding) have been signed.\nProfessor Akbar is working in Academia since 1990, he started his career as a Lab demonstrator/TA at the University of Sussex. After finishing his P. hD degree in 1992, he served in the Industry as a Scientific Officer and continued his academic career as a visiting scholar for a number of educational institutions. In 1996 he joined National University of Science & Technology Pakistan (NUST) as an Associate Professor; NUST is one of the top few universities in Pakistan. In 1999 he joined an International Company Lineo Inc, Canada as Manager Compiler Group, where he headed the group for developing Compiler Tool Chain and Porting of Operating Systems for the BLACKfin processor. The processor development was a joint venture by Intel and Analog Devices. In 2002 Lineo Inc., was taken over by another company, so he joined Aalborg University Denmark as an Assistant Professor.\nProfessor Akbar has truly a multi-disciplined career and he continued his legacy and making progress in many areas of his interests both in teaching and research. He has contributed in stochastic estimation of control area especially, in the Multiple Target Tracking and Interactive Multiple Model (IMM) research, Ball & Beam Control Problem, Robotics, Levitation Control. He has contributed in developing Algorithms for Fingerprint Matching, Computer Vision and Face Recognition. He has been supervising Pattern Recognition, Formal Languages and Distributed Processing projects for several years. He has reviewed many books on Management, Computer Science. Currently, he is an active and permanent reviewer for many international conferences and symposia and the program committee member for many international conferences.\nIn teaching he has taught the core computer science subjects like, Digital Design, Real Time Embedded System Programming, Operating Systems, Software Engineering, Data Structures, Databases, Compiler Construction. 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In the Caribbean region, air quality is widely affected by African dust which causes several diseases, particularly, respiratory diseases. This is why it is crucial to improve the understanding of PM10 fluctuations in order to elaborate strategies and construct tools to predict dust events. A first step consists to characterize the dynamical properties of PM10 fluctuations, for instance, to highlight possible scaling in PM10 density power spectrum. For that, the scale-invariant properties of PM10 daily time series during 6 years are investigated through the theoretical Hilbert frame. Thereafter, the Hilbert spectrum in time-frequency domain is considered. The choice of theoretical frame must be relevant. A comparative analysis is also provided between the results achieved in the Hilbert and Fourier spaces.",book:{id:"7785",slug:"functional-calculus",title:"Functional Calculus",fullTitle:"Functional Calculus"},signatures:"Thomas Plocoste and Rudy Calif",authors:null},{id:"59832",doi:"10.5772/intechopen.73291",title:"Solution of Nonlinear Partial Differential Equations by New Laplace Variational Iteration Method",slug:"solution-of-nonlinear-partial-differential-equations-by-new-laplace-variational-iteration-method",totalDownloads:1603,totalCrossrefCites:3,totalDimensionsCites:4,abstract:"Nonlinear equations are of great importance to our contemporary world. Nonlinear phenomena have important applications in applied mathematics, physics, and issues related to engineering. Despite the importance of obtaining the exact solution of nonlinear partial differential equations in physics and applied mathematics, there is still the daunting problem of finding new methods to discover new exact or approximate solutions. The purpose of this chapter is to impart a safe strategy for solving some linear and nonlinear partial differential equations in applied science and physics fields, by combining Laplace transform and the modified variational iteration method (VIM). This method is founded on the variational iteration method, Laplace transforms and convolution integral, such that, we put in an alternative Laplace correction functional and express the integral as a convolution. Some examples in physical engineering are provided to illustrate the simplicity and reliability of this method. The solutions of these examples are contingent only on the initial conditions.",book:{id:"6637",slug:"differential-equations-theory-and-current-research",title:"Differential Equations",fullTitle:"Differential Equations - Theory and Current Research"},signatures:"Tarig M. Elzaki",authors:[{id:"190781",title:"Dr.",name:"Tarig M.",middleName:null,surname:"Elzaki",slug:"tarig-m.-elzaki",fullName:"Tarig M. Elzaki"}]},{id:"60553",doi:"10.5772/intechopen.74560",title:"Fixed Point Theory Approach to Existence of Solutions with Differential Equations",slug:"fixed-point-theory-approach-to-existence-of-solutions-with-differential-equations",totalDownloads:1838,totalCrossrefCites:2,totalDimensionsCites:3,abstract:"In this chapter, we introduce a generalized contractions and prove some fixed point theorems in generalized metric spaces by using the generalized contractions. Moreover, we will apply the fixed point theorems to show the existence and uniqueness of solution to the ordinary difference equation (ODE), Partial difference equation (PDEs) and fractional boundary value problem.",book:{id:"6637",slug:"differential-equations-theory-and-current-research",title:"Differential Equations",fullTitle:"Differential Equations - Theory and Current Research"},signatures:"Piyachat Borisut, Konrawut Khammahawong and Poom Kumam",authors:[{id:"191850",title:"Dr.",name:"Poom",middleName:null,surname:"Kumam",slug:"poom-kumam",fullName:"Poom Kumam"},{id:"241908",title:"Mr.",name:"Piyachat",middleName:null,surname:"Borisut",slug:"piyachat-borisut",fullName:"Piyachat Borisut"},{id:"241909",title:"Mr.",name:"Konrawut",middleName:null,surname:"Khammahawong",slug:"konrawut-khammahawong",fullName:"Konrawut Khammahawong"}]},{id:"60295",doi:"10.5772/intechopen.75523",title:"Existence Theory of Differential Equations of Arbitrary Order",slug:"existence-theory-of-differential-equations-of-arbitrary-order",totalDownloads:848,totalCrossrefCites:1,totalDimensionsCites:2,abstract:"The aims of this chapter are devoted to investigate a system of fractional-order differential equations (FDEs) with multipoint boundary conditions. Necessary and sufficient conditions are investigated for at most one solution to the proposed problem. Also, results for the existence of at least one or two positive solutions are developed by using a fixed-point theorem of concave-type operator for the considered problem. Further, we extend the conditions for more than two solutions and established some adequate conditions for multiplicity results to the proposed problem. Also, a result devoted to Hyers-Ulam stability is discussed. Suitable examples are provided to verify the established results.",book:{id:"6637",slug:"differential-equations-theory-and-current-research",title:"Differential Equations",fullTitle:"Differential Equations - Theory and Current Research"},signatures:"Kamal Shah and Yongjin Li",authors:[{id:"231748",title:"Dr.",name:"Kamal",middleName:null,surname:"Shah",slug:"kamal-shah",fullName:"Kamal Shah"},{id:"240625",title:"Prof.",name:"Yongjin",middleName:null,surname:"Li",slug:"yongjin-li",fullName:"Yongjin Li"}]},{id:"59445",doi:"10.5772/intechopen.74355",title:"Differential Equations Arising from the 3-Variable Hermite Polynomials and Computation of Their Zeros",slug:"differential-equations-arising-from-the-3-variable-hermite-polynomials-and-computation-of-their-zero",totalDownloads:988,totalCrossrefCites:1,totalDimensionsCites:2,abstract:"In this paper, we study differential equations arising from the generating functions of the 3-variable Hermite polynomials. We give explicit identities for the 3-variable Hermite polynomials. Finally, we investigate the zeros of the 3-variable Hermite polynomials by using computer.",book:{id:"6637",slug:"differential-equations-theory-and-current-research",title:"Differential Equations",fullTitle:"Differential Equations - Theory and Current Research"},signatures:"Cheon Seoung Ryoo",authors:[{id:"230100",title:"Prof.",name:"Cheon Seoung",middleName:null,surname:"Ryoo",slug:"cheon-seoung-ryoo",fullName:"Cheon Seoung Ryoo"}]}],mostDownloadedChaptersLast30Days:[{id:"70922",title:"Approximate Solutions of Some Boundary Value Problems by Using Operational Matrices of Bernstein Polynomials",slug:"approximate-solutions-of-some-boundary-value-problems-by-using-operational-matrices-of-bernstein-pol",totalDownloads:702,totalCrossrefCites:0,totalDimensionsCites:0,abstract:"In this chapter, we develop an efficient numerical scheme for the solution of boundary value problems of fractional order differential equations as well as their coupled systems by using Bernstein polynomials. On using the mentioned polynomial, we construct operational matrices for both fractional order derivatives and integrations. Also we construct a new matrix for the boundary condition. Based on the suggested method, we convert the considered problem to algebraic equation, which can be easily solved by using Matlab. In the last section, numerical examples are provided to illustrate our main results.",book:{id:"7785",slug:"functional-calculus",title:"Functional Calculus",fullTitle:"Functional Calculus"},signatures:"Kamal Shah, Thabet Abdeljawad, Hammad Khalil and Rahmat Ali Khan",authors:[{id:"231748",title:"Dr.",name:"Kamal",middleName:null,surname:"Shah",slug:"kamal-shah",fullName:"Kamal Shah"}]},{id:"59899",title:"Local Discontinuous Galerkin Method for Nonlinear Ginzburg- Landau Equation",slug:"local-discontinuous-galerkin-method-for-nonlinear-ginzburg-landau-equation",totalDownloads:1e3,totalCrossrefCites:0,totalDimensionsCites:0,abstract:"The Ginzburg-Landau equation has been applied widely in many fields. It describes the amplitude evolution of instability waves in a large variety of dissipative systems in fluid mechanics, which are close to criticality. In this chapter, we develop a local discontinuous Galerkin method to solve the nonlinear Ginzburg-Landau equation. The nonlinear Ginzburg-Landau problem has been expressed as a system of low-order differential equations. Moreover, we prove stability and optimal order of convergence OhN+1 for Ginzburg-Landau equation where h and N are the space step size and polynomial degree, respectively. The numerical experiments confirm the theoretical results of the method.",book:{id:"6637",slug:"differential-equations-theory-and-current-research",title:"Differential Equations",fullTitle:"Differential Equations - Theory and Current Research"},signatures:"Tarek Aboelenen",authors:[{id:"235289",title:"Dr.",name:"Tarek",middleName:null,surname:"Aboelenen",slug:"tarek-aboelenen",fullName:"Tarek Aboelenen"}]},{id:"68618",title:"Folding on the Chaotic Graph Operations and Their Fundamental Group",slug:"folding-on-the-chaotic-graph-operations-and-their-fundamental-group",totalDownloads:688,totalCrossrefCites:0,totalDimensionsCites:0,abstract:"Our aim in the present chapter is to introduce a new type of operations on the chaotic graph, namely, chaotic connected edge graphs under the identification topology. The concept of chaotic foldings on the chaotic edge graph will be discussed from the viewpoint of algebra and geometry. The relation between the chaotic homeomorphisms and chaotic foldings on the chaotic connected edge graphs and their fundamental group is deduced. The fundamental group of the limit chaotic chain of foldings on chaotic. Many types of chaotic foldings are achieved. Theorems governing these relations are achieved. We also discuss some applications in chemistry and biology.",book:{id:"7785",slug:"functional-calculus",title:"Functional Calculus",fullTitle:"Functional Calculus"},signatures:"Mohammed Abu Saleem",authors:null},{id:"60553",title:"Fixed Point Theory Approach to Existence of Solutions with Differential Equations",slug:"fixed-point-theory-approach-to-existence-of-solutions-with-differential-equations",totalDownloads:1838,totalCrossrefCites:2,totalDimensionsCites:3,abstract:"In this chapter, we introduce a generalized contractions and prove some fixed point theorems in generalized metric spaces by using the generalized contractions. 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Much of biochemistry is devoted to enzymes, proteins that catalyze chemical reactions, enzyme structures, mechanisms of action and their roles within cells. Biochemistry also studies small signaling molecules, coenzymes, inhibitors, vitamins, and hormones, which play roles in life processes. Biochemical experimentation, besides coopting classical chemistry methods, e.g., chromatography, adopted new techniques, e.g., X-ray diffraction, electron microscopy, NMR, radioisotopes, and developed sophisticated microbial genetic tools, e.g., auxotroph mutants and their revertants, fermentation, etc. More recently, biochemistry embraced the ‘big data’ omics systems. Initial biochemical studies have been exclusively analytic: dissecting, purifying, and examining individual components of a biological system; in the apt words of Efraim Racker (1913 –1991), “Don’t waste clean thinking on dirty enzymes.” Today, however, biochemistry is becoming more agglomerative and comprehensive, setting out to integrate and describe entirely particular biological systems. The ‘big data’ metabolomics can define the complement of small molecules, e.g., in a soil or biofilm sample; proteomics can distinguish all the comprising proteins, e.g., serum; metagenomics can identify all the genes in a complex environment, e.g., the bovine rumen. 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Dr. Blumenberg’s research is focused on the epidermis, expression of keratin genes, transcription profiling, keratinocyte differentiation, inflammatory diseases and cancers, and most recently the effects of the microbiome on the skin. He has published more than 100 peer-reviewed research articles and graduated numerous Ph.D. and postdoctoral students.",institutionString:null,institution:{name:"New York University Langone Medical Center",institutionURL:null,country:{name:"United States of America"}}},editorTwo:null,editorThree:null},subseries:{paginationCount:4,paginationItems:[{id:"14",title:"Cell and Molecular Biology",coverUrl:"https://cdn.intechopen.com/series_topics/covers/14.jpg",isOpenForSubmission:!0,editor:{id:"165627",title:"Dr.",name:"Rosa María",middleName:null,surname:"Martínez-Espinosa",slug:"rosa-maria-martinez-espinosa",fullName:"Rosa María Martínez-Espinosa",profilePictureURL:"https://mts.intechopen.com/storage/users/165627/images/system/165627.jpeg",biography:"Dr. Rosa María Martínez-Espinosa has been a Spanish Full Professor since 2020 (Biochemistry and Molecular Biology) and is currently Vice-President of International Relations and Cooperation development and leader of the research group 'Applied Biochemistry” (University of Alicante, Spain). Other positions she has held at the university include Vice-Dean of Master Programs, Vice-Dean of the Degree in Biology and Vice-Dean for Mobility and Enterprise and Engagement at the Faculty of Science (University of Alicante). She received her Bachelor in Biology in 1998 (University of Alicante) and her PhD in 2003 (Biochemistry, University of Alicante). She undertook post-doctoral research at the University of East Anglia (Norwich, U.K. 2004-2005; 2007-2008).\nHer multidisciplinary research focuses on investigating archaea and their potential applications in biotechnology. She has an H-index of 21. She has authored one patent and has published more than 70 indexed papers and around 60 book chapters.\nShe has contributed to more than 150 national and international meetings during the last 15 years. Her research interests include archaea metabolism, enzymes purification and characterization, gene regulation, carotenoids and bioplastics production, antioxidant\ncompounds, waste water treatments, and brines bioremediation.\nRosa María’s other roles include editorial board member for several journals related\nto biochemistry, reviewer for more than 60 journals (biochemistry, molecular biology, biotechnology, chemistry and microbiology) and president of several organizing committees in international meetings related to the N-cycle or respiratory processes.",institutionString:null,institution:{name:"University of Alicante",institutionURL:null,country:{name:"Spain"}}},editorTwo:null,editorThree:null},{id:"15",title:"Chemical Biology",coverUrl:"https://cdn.intechopen.com/series_topics/covers/15.jpg",isOpenForSubmission:!0,editor:{id:"441442",title:"Dr.",name:"Şükrü",middleName:null,surname:"Beydemir",slug:"sukru-beydemir",fullName:"Şükrü Beydemir",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0033Y00003GsUoIQAV/Profile_Picture_1634557147521",biography:"Dr. Şükrü Beydemir obtained a BSc in Chemistry in 1995 from Yüzüncü Yıl University, MSc in Biochemistry in 1998, and PhD in Biochemistry in 2002 from Atatürk University, Turkey. 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He worked on the structure-function relationships of glycoconjugates and his main project was the investigations on the biological roles of the de-N-glycosylation enzymes (Endo-N-acetyl-β-D-glucosaminidase and peptide-N4-(N-acetyl-β-glucosaminyl) asparagine amidase). From 2002 he contributes to the understanding of the Blood-brain barrier functioning using proteomics approaches. He has published more than 70 papers. 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Waisundara",profilePictureURL:"https://mts.intechopen.com/storage/users/194281/images/system/194281.jpg",biography:"Dr. Viduranga Waisundara obtained her Ph.D. in Food Science and Technology from the Department of Chemistry, National University of Singapore, in 2010. She was a lecturer at Temasek Polytechnic, Singapore from July 2009 to March 2013. She relocated to her motherland of Sri Lanka and spearheaded the Functional Food Product Development Project at the National Institute of Fundamental Studies from April 2013 to October 2016. She was a senior lecturer on a temporary basis at the Department of Food Technology, Faculty of Technology, Rajarata University of Sri Lanka. She is currently Deputy Principal of the Australian College of Business and Technology – Kandy Campus, Sri Lanka. She is also the Global Harmonization Initiative (GHI) Ambassador to Sri Lanka.",institutionString:"Australian College of Business & Technology",institution:null}]},{type:"book",id:"6820",title:"Keratin",subtitle:null,coverURL:"https://cdn.intechopen.com/books/images_new/6820.jpg",slug:"keratin",publishedDate:"December 19th 2018",editedByType:"Edited by",bookSignature:"Miroslav Blumenberg",hash:"6def75cd4b6b5324a02b6dc0359896d0",volumeInSeries:2,fullTitle:"Keratin",editors:[{id:"31610",title:"Dr.",name:"Miroslav",middleName:null,surname:"Blumenberg",slug:"miroslav-blumenberg",fullName:"Miroslav Blumenberg",profilePictureURL:"https://mts.intechopen.com/storage/users/31610/images/system/31610.jpg",biography:"Miroslav Blumenberg, Ph.D., was born in Subotica and received his BSc in Belgrade, Yugoslavia. He completed his Ph.D. at MIT in Organic Chemistry; he followed up his Ph.D. with two postdoctoral study periods at Stanford University. Since 1983, he has been a faculty member of the RO Perelman Department of Dermatology, NYU School of Medicine, where he is codirector of a training grant in cutaneous biology. Dr. Blumenberg’s research is focused on the epidermis, expression of keratin genes, transcription profiling, keratinocyte differentiation, inflammatory diseases and cancers, and most recently the effects of the microbiome on the skin. He has published more than 100 peer-reviewed research articles and graduated numerous Ph.D. and postdoctoral students.",institutionString:null,institution:{name:"New York University Langone Medical Center",institutionURL:null,country:{name:"United States of America"}}}]},{type:"book",id:"7978",title:"Vitamin A",subtitle:null,coverURL:"https://cdn.intechopen.com/books/images_new/7978.jpg",slug:"vitamin-a",publishedDate:"May 15th 2019",editedByType:"Edited by",bookSignature:"Leila Queiroz Zepka, Veridiana Vera de Rosso and Eduardo Jacob-Lopes",hash:"dad04a658ab9e3d851d23705980a688b",volumeInSeries:3,fullTitle:"Vitamin A",editors:[{id:"261969",title:"Dr.",name:"Leila",middleName:null,surname:"Queiroz Zepka",slug:"leila-queiroz-zepka",fullName:"Leila Queiroz Zepka",profilePictureURL:"https://mts.intechopen.com/storage/users/261969/images/system/261969.png",biography:"Prof. Dr. Leila Queiroz Zepka is currently an associate professor in the Department of Food Technology and Science, Federal University of Santa Maria, Brazil. She has more than fifteen years of teaching and research experience. She has published more than 550 scientific publications/communications, including 15 books, 50 book chapters, 100 original research papers, 380 research communications in national and international conferences, and 12 patents. She is a member of the editorial board of five journals and acts as a reviewer for several national and international journals. Her research interests include microalgal biotechnology with an emphasis on microalgae-based products.",institutionString:"Universidade Federal de Santa Maria",institution:{name:"Universidade Federal de Santa Maria",institutionURL:null,country:{name:"Brazil"}}}]},{type:"book",id:"7953",title:"Bioluminescence",subtitle:"Analytical Applications and Basic Biology",coverURL:"https://cdn.intechopen.com/books/images_new/7953.jpg",slug:"bioluminescence-analytical-applications-and-basic-biology",publishedDate:"September 25th 2019",editedByType:"Edited by",bookSignature:"Hirobumi Suzuki",hash:"3a8efa00b71abea11bf01973dc589979",volumeInSeries:4,fullTitle:"Bioluminescence - Analytical Applications and Basic Biology",editors:[{id:"185746",title:"Dr.",name:"Hirobumi",middleName:null,surname:"Suzuki",slug:"hirobumi-suzuki",fullName:"Hirobumi Suzuki",profilePictureURL:"https://mts.intechopen.com/storage/users/185746/images/system/185746.png",biography:"Dr. Hirobumi Suzuki received his Ph.D. in 1997 from Tokyo Metropolitan University, Japan, where he studied firefly phylogeny and the evolution of mating systems. 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