Interactions between PESTLE, SWOT and TETE analysis.
\\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:"2156",leadTitle:null,fullTitle:"Finite Element Analysis - From Biomedical Applications to Industrial Developments",title:"Finite Element Analysis",subtitle:"From Biomedical Applications to Industrial Developments",reviewType:"peer-reviewed",abstract:"Finite Element Analysis represents a numerical technique for finding approximate solutions to partial differential equations as well as integral equations, permitting the numerical analysis of complex structures based on their material properties. This book presents 20 different chapters in the application of Finite Elements, ranging from Biomedical Engineering to Manufacturing Industry and Industrial Developments. 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His primary research interests concern biomedical imaging and biological signal processing, as well as biomechanical analysis.",institutionString:null,position:null,outsideEditionCount:0,totalCites:0,totalAuthoredChapters:"2",totalChapterViews:"0",totalEditedBooks:"2",institution:{name:"Universitat Politècnica de València",institutionURL:null,country:{name:"Spain"}}}],equalEditorOne:null,equalEditorTwo:null,equalEditorThree:null,coeditorOne:null,coeditorTwo:null,coeditorThree:null,coeditorFour:null,coeditorFive:null,topics:[{id:"602",title:"Discrete Mathematics",slug:"discrete-mathematics"}],chapters:[{id:"34505",title:"Past, Present and Future of Finite Element Analysis in Dentistry",doi:"10.5772/38037",slug:"past-present-and-future-of-finite-element-analysis-in-dentistry",totalDownloads:6003,totalCrossrefCites:2,totalDimensionsCites:5,hasAltmetrics:0,abstract:null,signatures:"Ching-Chang Ko, Eduardo Passos Rocha and Matt Larson",downloadPdfUrl:"/chapter/pdf-download/34505",previewPdfUrl:"/chapter/pdf-preview/34505",authors:[{id:"115292",title:"Prof.",name:"Ching-Chang",surname:"Ko",slug:"ching-chang-ko",fullName:"Ching-Chang Ko"}],corrections:null},{id:"34506",title:"Finite Element Analysis in Dentistry - Improving the Quality of Oral Health Care",doi:"10.5772/37353",slug:"finite-element-analysis-in-dentistry-improving-the-quality-of-oral-health-care",totalDownloads:3010,totalCrossrefCites:3,totalDimensionsCites:10,hasAltmetrics:0,abstract:null,signatures:"Carlos José Soares, Antheunis Versluis, Andréa Dolores Correia Miranda Valdivia, Aline Arêdes Bicalho, Crisnicaw Veríssimo, Bruno de Castro Ferreira Barreto and Marina Guimarães Roscoe",downloadPdfUrl:"/chapter/pdf-download/34506",previewPdfUrl:"/chapter/pdf-preview/34506",authors:[{id:"112357",title:"Prof.",name:"Carlos",surname:"Soares",slug:"carlos-soares",fullName:"Carlos Soares"},{id:"149153",title:"Prof.",name:"Antheunis",surname:"Versluis",slug:"antheunis-versluis",fullName:"Antheunis Versluis"},{id:"149154",title:"MSc.",name:"Andréa",surname:"Valdivia",slug:"andrea-valdivia",fullName:"Andréa Valdivia"},{id:"149156",title:"MSc.",name:"Aline",surname:"Bicalho",slug:"aline-bicalho",fullName:"Aline Bicalho"},{id:"149158",title:"MSc.",name:"Crisnicaw",surname:"Veríssimo",slug:"crisnicaw-verissimo",fullName:"Crisnicaw Veríssimo"},{id:"149159",title:"Dr.",name:"Bruno",surname:"Barreto",slug:"bruno-barreto",fullName:"Bruno Barreto"},{id:"149160",title:"MSc.",name:"Marina",surname:"Roscoe",slug:"marina-roscoe",fullName:"Marina Roscoe"}],corrections:null},{id:"34507",title:"FEA in Dentistry: A Useful Tool to Investigate the Biomechanical Behavior of Implant Supported Prosthesis",doi:"10.5772/38686",slug:"fea-in-dentistry-a-useful-tool-to-investigate-the-biomechanical-behavior-of-implant-supported-prosth",totalDownloads:3056,totalCrossrefCites:0,totalDimensionsCites:1,hasAltmetrics:0,abstract:null,signatures:"Wirley Gonçalves Assunção, Valentim Adelino Ricardo Barão, Érica Alves Gomes, Juliana Aparecida Delben and Ricardo Faria Ribeiro",downloadPdfUrl:"/chapter/pdf-download/34507",previewPdfUrl:"/chapter/pdf-preview/34507",authors:[{id:"118705",title:"Prof.",name:"Wirley",surname:"Assunção",slug:"wirley-assuncao",fullName:"Wirley Assunção"},{id:"118729",title:"MSc.",name:"Valentim",surname:"Barão",slug:"valentim-barao",fullName:"Valentim Barão"},{id:"118730",title:"Dr.",name:"Erica",surname:"Gomes",slug:"erica-gomes",fullName:"Erica Gomes"},{id:"118731",title:"MSc.",name:"Juliana",surname:"Delben",slug:"juliana-delben",fullName:"Juliana Delben"},{id:"138844",title:"Prof.",name:"Ricardo",surname:"Ribeiro",slug:"ricardo-ribeiro",fullName:"Ricardo Ribeiro"}],corrections:null},{id:"34508",title:"Critical Aspects for Mechanical Simulation in Dental Implantology",doi:"10.5772/38619",slug:"critical-aspects-for-mechanical-simulation-in-dental-implantology",totalDownloads:3147,totalCrossrefCites:1,totalDimensionsCites:5,hasAltmetrics:0,abstract:null,signatures:"Erika O. 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As female grows old with passing years, she undergoes different phases of life, from childhood to adulthood. Her body keeps on changing at all levels; may it be anatomical, physiological, and hormonal with the years of aging. Menopause is just another phase of life like puberty. It is the time when ovaries stop producing eggs any more.
Menopause is a Latin word where
It is neither a disease, an illness, a pathology, nor a state of being not well but just a normal physiological phenomenon of aging among females from transition of reproductive life to no more ability to reproduce. It has no impact on sexuality of a female. This transition occurs with some changes in hormones of female endocrine system predominantly estrogen leading to menopausal symptoms.
For women, the menopausal period is considered the climacterium, the middle adulthood; a period in life characterized by decreased biological and physiological functioning and may lead to psychosocial disturbance in form of interpersonal relationships [1]. It may start anywhere from the 40s to the early 50s but generally occurs between 47 and 53 years [1].
Considering the onset of menopausal age, one must keep in mind the difference between days per year in various calendars such as a lunar year of 354 days used by Muslims as compared to the solar year of 365 despite the fact that the later also known as Gregorian calendar is widely in use, but ancient calendars are also used by a significant number of peoples who belong to certain regions and religions, in the form of the Julian calendar, the Islamic calendar, etc.
The menopausal condition has been analog in men as andropause. For men, the climacterium has no clear demarcation; male hormones stay fairly constant through the 40s and 50s and then begin to decline [1].
All women will not experience menopause in the same way in terms of their onset and symptoms. Apart from a normal response or may be a positive feeling in the form of relief from pain or at least the burden of the management of menstruation each month, many premenopausal women have concerns that they will experience mental instability, sudden signs of aging, and diminution of sexuality at this time. Culture, health, previous experience of mood problems, lifestyle, and whether menopause onset is a natural, surgical, or chemotherapy-induced, will all impact on menopausal symptoms. Increased risk for psychiatric morbidity is seen in women who experienced early menopause or surgical menopause [2]. According to study of Bernice Neugarten, the famous American psychologist who is specialized in adult development and the psychology of aging, more than 50% of females described menopause as an unpleasant experience, some believed that their lives had not changed in any significant way, and many women experienced no adverse effects while some reports feeling sexually free after menopause of any worry of becoming pregnant.
Large epidemiological studies have shown that the years usually associated with natural menopause, that is 45–55, are not associated with increased psychiatric morbidity or more utilization of health services by women [2–5]. Various personal factors of an individual female may affect her menopausal experience. Such as follows:
Past experience of mood disorders.
Negative attitude to menopause and aging: women with more negative attitudes toward the menopause in general report more symptoms during the menopausal transition [6].
Life events, personality, and coping.
Self-esteem: women with a low self-esteem used to have more severe menopausal complaints [7].
They may include the following:
Lack of social support
Unemployment
Surgical menopause
Poor overall health status
Social interpersonal relationships also have their impact on a person’s life and general well-being. They constitute a major social support in a woman’s life and help her in managing stressors and problems in life with influencial effect on psychological health. They may include the following:
Relationship with a partner
Relationship with children
Relationship with friends/social support
Menopause could be a stressful transition due to various beliefs related to fertility and a gradual diminishing role or role shifts in society. Depression at menopause has been attributed to the
Education and socioeconomic statuses are also important factors found to influence the intensity and symptoms of menopause [8]. The influence of psychological factors, lifestyle, body image, interpersonal relationships, role, and sociocultural factors in predicting levels of depression and anxiety in the menopause cannot be ignored.
Role, social factors, and culture have a great impact on menopausal symptoms, as few studies have shown rates of depressive symptoms and hot flashes or sweats were significantly lower among Japanese women than females of American and Canadian population [9]. Such variations across cultures may reflect differences in
Beliefs and expectations regarding menopause and aging
Status and roles of women in a particular society
Sensitivity to specific symptoms
Biology, diet, and health behaviors
In developing countries where there is low literacy rate, it has been observed that females expect conception even after menopause, and this may be because the success of woman was considered to be related to production of more children, particularly males.
The factors that must be considered while dealing with menopausal women are the following:
The variation in reproductive period, i.e., from onset of menses (also termed “menarche)” to menopause.
Variation in life expectancy among different countries, e.g., life expectancy of woman is as low as 50.8 years in Sierra Leone and as high as 86.8 years in Japan.
As reproductive life could vary significantly among the various countries, we may consider average menarche age as 13 years and age of menopause as 51 years, and on calculating the reproductive period of women in developing country with average life expectancy of 50 years, they would have reproductive life that is 74% of their total life in comparison to women of developed country with life expectancy of 86 years who would have reproductive life constituting only 44% of their life from birth.
With the above fact, the period of menstruation is simulated to reproductive age or fertility is around half of their lives; therefore, loss of fertility or reproductive life may be a source of stress specially among tribes, where long reproductive age period is desired on the cultural belief that this will lead to a large family size that is considered as a symbol of success.
Popular psychiatric nosology such as the WHO International Classification of Diseases (ICD-10) and Diagnostic and Statistical Manual of Mental
ICD-10 coding for menopause and related disorders.
Menopause is not a time of high risk for psychiatric illness but may be a time of psychological stress for women. Some women will experience psychological symptoms during the perimenopausal years [10]. Since mild emotional symptoms occur in many women during the perimenopausal years, it is important to establish whether the symptoms are of sufficient severity and duration to constitute major depression, generalized anxiety disorder, or panic disorder. Psychological distress is usually seen more in females with disturbed sleep [11]. Sleep could be disturbed in midlife due to psychosocial stressors of life or as a result of symptoms of menopause like hot flushes (also termed as “flashes”) and night sweats. Female reproductive hormones and rapid changes in their levels may influence neurotransmitters in the brain, particularly the serotonin and gamma amino butyric acid systems. Estrogen modulates serotonin to increase serotonin presynaptic reuptake, modulates norepinephrine levels, decreases monoamine oxidase levels, affects dopamine turnover, increases brain excitability, affects endorphin levels, and possibly interacts with gamma amino butyric acid [12]. Progesterone is found to increase monoamine oxidase levels. In high doses, progesterone has an anesthetic effect and may decrease brain excitability through an interaction with the gamma amino butyric acid system [12]. The drop in estrogen levels during perimenopause and menopause can lead to hot flashes that disturb sleep. This can lead to anxiety, fears, and mood swings [1].
The greater frequency of symptoms during the years prior to the end of the menses and the reduction of symptoms once menopause has occurred suggest that emotional symptoms are related to changing hormone levels rather than low hormone levels [12].
Research has shown that reproductive hormones produced during menopause contribute to mood alterations, such as depression [13]. Menopausal status, however, remains an independent predictor of depressive symptoms [14]. Some women experience anxiety and depression, but women who have a history of poor adaptation to stress are more predisposed to the menopausal syndrome [1].
The two most common psychiatric conditions are anxiety and depression. Therefore, all the general physicians and gynecologists must ask two screening questions for each of these conditions from women of perimenopausal age, as suggested by experts, given in Figures 2 and 3 (*in Urdu—for developing countries where Urdu language is medium of communication).
Screening questions for depression among perimenopausal cases (Urdu).
Screening questions for anxiety among perimenopausal cases.
The changes that occur in hormone levels along with general health, shifts, and stresses of family life in a woman\'s menopausal years as a whole effect the onset of depression among them [15]. According to a study at Harvard on Moods and Cycles constituting premenopausal women aged 36–44 years with no history of major depression with a follow-up of these women for 9 years to detect new onsets of major depression. Clinically significant depressive symptoms likely to develop among perimenopausal women were twice as common than women who had not yet gone under menopausal transition [16].
Typical symptoms of depression include depressed mood, anhedonia, and fatigue. Reaching diagnosis of Depressive Disorder, two internationally recognized criteria are of ICD-10 and DSM-5. Symptoms should be there for at least 2 weeks and leading to poor social or occupational functioning and condition should not be due to any substance use. Presence of at least two typical expressions with two common symptoms constitutes the criteria of Major Depressive Disorder (F32) according to International Classification of Diseases version 10 (ICD-10), while presence of at least one typical and five or more common symptoms constitute criteria to diagnose Depressive Disorder in Diagnostic and Statistical Manual (DSM). List of Symptoms is shown in Figure 4.
ICD-10 and DSM diagnostic criteria for depressive disorder.
Women who are more anxious experience greater extent of menopausal symptoms. Many of the symptoms of anxiety and menopause coincide like sweating, palpitations (increased heart rate), restlessness, sleep disturbance, which may confuse some. But no correlations have been found in between hormonal changes during menopause with incidence of anxiety disorder. Other psychosocial factors may contribute in development of anxiety among females of midlife.
Symptoms of anxiety include the following:
apprehension
irritability
impatience
fearfulness
restlessness
difficulty concentrating
trouble falling asleep
increased frequency of urination
hyperventilation
sweating, especially in the palms
muscle tension
The symptoms of anxiety and depression may sometimes coincide and may be present simultaneously so if asked what are the defining symptoms of anxiety and depression? The clear difference and presentation of symptoms have been described in Figure 5 with various differences and the similarities of anxiety and depressive disorder.
Features that differentiate anxiety and depression.
Apart from anxiety and depressive disorder, the other psychiatric conditions that have been linked to menopause are premenstrual dysphoric syndrome and surprisingly a rare condition Trichotillomania discussed as under.
Anecdotally, many cases as they approach to menopause report that their symptoms of premenstrual dysphoric syndrome worsen at onset of perimenopause and alleviate with menopause [17].
The art of assessing menopausal symptoms and menses may be threatening in some culture; therefore, reaching this condition needs proper working and skills which are less cumbersome because in general females are sensitive about aging process and loss of fertility.
Estrogen and androgen alone or in combination of both is found to be more effective in improving symptoms in nonclinically depressed perimenopausal and menopausal women according to meta-analysis [18] of various studies on effects of hormone replacement therapies on mood. Progesterone had a much smaller effect, and when combined with estrogen, reduced the positive effects of the estrogen. The most robust effect was noted with androgen, either alone or in combination with estrogen.
Studies have shown that combined estrogen-progestin drugs (e.g., premarin) cause small increases in breast cancer, heart attack, stroke, and blood clots among menopausal women. Studies of the effects of estrogen alone in women who have had hysterectomies (because estrogen alone increases the risk for uterine cancer) are ongoing [1].
Depression during perimenopause and menopause is treated in much the same way as depression that strikes at any other time.
Although symptoms of depression are relieved by a majority of antidepressants including SSRIs such as Fluoxetine, Paroxetine, SNRIs, e.g., venlafaxine, des-venlafaxine, and TCA as amitriptyline, but desvenlafaxine (the dual serotonin and norepinephrine reuptake inhibitor) is used popularly, off label, for symptoms of depression with menopause despite the fact that the US Food and Drug Administration (FDA) has denied an application for its use for the treatment of moderate-to-severe vasomotor symptoms such as hot flashes associated with menopause.
A meta-analysis shows that desvenlafaxine was associated with a statistically significant reduction in the number and severity of daily moderate-to-severe hot flashes. The number of nighttime awakenings because of hot flashes was also significantly decreased. However, the rate of desvenlafaxine treatment discontinuation because of adverse events was significantly higher than placebo-treated women and the risk ratios of adverse events such as asthenia, hypertension, anorexia, constipation, diarrhea, dry mouth, nausea, dizziness, insomnia, somnolence, and
A healthy lifestyle can help to reduce symptoms of menopause
Exercise
Being physically active helps with hot flushes, stress, and mood
Exercise has beneficial effects on hot flashes, well-being, Body Mass Index (BMI) and Coronary Heart Diseases risks [20]
Activities that stimulate the brain can help rejuvenate memory such as doing crossword puzzles, longhand mathematics, and reading books.
Diet
A nutritious diet helps with fatigue and moodiness.
A healthy diet, low in fat, high in fiber, with plenty of fruits, vegetables, and whole-grain foods.
Intake of foods with phytoestrogen.
Phytoestrogens are estrogen-like substances found in some cereals, vegetables, legumes (including soy), and herbs. They might work in the body like a weak form of estrogen. The first widely attributed health benefit of phytoestrogen consumption was relief from vasomotor perimenopausal symptoms, including hot flushes and night sweats. Moderation is a likely key and the incorporation of real foods, as opposed to supplements or processed foods to which soy protein is added, is probably essential for maximizing health benefits [21]. Consumption of 30 mg/day of soy isoflavones reduces hot flashes by up to 50% [22].
Ensure enough calcium and vitamin D intake on regular basis
Avoid smoking and alcohol, as it is known to make hot flushes worse
Foods that should be avoided in menopause
Caffeine
Spicy foods
Social interactions with family and community, nurturing relationship, and healthy emotional support from friends are very effective means. A professional help from a counselor and mental health professional is quite effective and must be readily available. Misconception as described by individuals as potentially difficult, embarrassing, and stigmatized leading to fear and avoidance in some individuals at developing countries must be addressed.
The 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.
"Open access contributes to scientific excellence and integrity. It opens up research results to wider analysis. It allows research results to be reused for new discoveries. And it enables the multi-disciplinary research that is needed to solve global 21st century problems. Open access connects science with society. It allows the public to engage with research. To go behind the headlines. And look at the scientific evidence. And it enables policy makers to draw on innovative solutions to societal challenges".
\n\nCarlos Moedas, the European Commissioner for Research Science and Innovation at the STM Annual Frankfurt Conference, October 2016.
",metaTitle:"About Open Access",metaDescription:"Open access contributes to scientific excellence and integrity. It opens up research results to wider analysis. It allows research results to be reused for new discoveries. And it enables the multi-disciplinary research that is needed to solve global 21st century problems. Open access connects science with society. It allows the public to engage with research. To go behind the headlines. And look at the scientific evidence. And it enables policy makers to draw on innovative solutions to societal challenges.\n\nCarlos Moedas, the European Commissioner for Research Science and Innovation at the STM Annual Frankfurt Conference, October 2016.",metaKeywords:null,canonicalURL:"about-open-access",contentRaw:'[{"type":"htmlEditorComponent","content":"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)
\\n\\nIntechOpen’s co-founders, both scientists themselves, created the company while undertaking research in robotics at Vienna University. Their goal was to spread research freely “for scientists, by scientists’ to the rest of the world via the Open Access publishing model. The company soon became a signatory of the Budapest Initiative, which currently has more than 1000 supporting organizations worldwide, ranging from universities to funders.
\\n\\nAt IntechOpen today, we are still as committed to working with organizations and people who care about scientific discovery, to putting the academic needs of the scientific community first, and to providing an Open Access environment where scientists can maximize their contribution to scientific advancement. By opening up access to the world’s scientific research articles and book chapters, we aim to facilitate greater opportunity for collaboration, scientific discovery and progress. We subscribe wholeheartedly to the Open Access definition:
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\\n\\nOAI-PMH
\\n\\nAs a firm believer in the wider dissemination of knowledge, IntechOpen supports the Open Access Initiative Protocol for Metadata Harvesting (OAI-PMH Version 2.0). Read more
\\n\\nLicense
\\n\\nBook chapters published in edited volumes are distributed under the Creative Commons Attribution 3.0 Unported License (CC BY 3.0). IntechOpen upholds a very flexible Copyright Policy. There is no copyright transfer to the publisher and Authors retain exclusive copyright to their work. All Monographs/Compacts are distributed under the Creative Commons Attribution-NonCommercial 4.0 International (CC BY-NC 4.0). Read more
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\\n\\nThe Open Access publishing model employed by IntechOpen eliminates subscription charges and pay-per-view fees, enabling readers to access research at no cost. In order to sustain operations and keep our publications freely accessible we levy an Open Access Publishing Fee for manuscripts, which helps us cover the costs of editorial work and the production of books. Read more
\\n\\nDigital Archiving Policy
\\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:
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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)
\n\nIntechOpen’s co-founders, both scientists themselves, created the company while undertaking research in robotics at Vienna University. Their goal was to spread research freely “for scientists, by scientists’ to the rest of the world via the Open Access publishing model. The company soon became a signatory of the Budapest Initiative, which currently has more than 1000 supporting organizations worldwide, ranging from universities to funders.
\n\nAt IntechOpen today, we are still as committed to working with organizations and people who care about scientific discovery, to putting the academic needs of the scientific community first, and to providing an Open Access environment where scientists can maximize their contribution to scientific advancement. By opening up access to the world’s scientific research articles and book chapters, we aim to facilitate greater opportunity for collaboration, scientific discovery and progress. We subscribe wholeheartedly to the Open Access definition:
\n\n“By “open access” to [peer-reviewed research literature], we mean its free availability on the public internet, permitting any users to read, download, copy, distribute, print, search, or link to the full texts of these articles, crawl them for indexing, pass them as data to software, or use them for any other lawful purpose, without financial, legal, or technical barriers other than those inseparable from gaining access to the internet itself. The only constraint on reproduction and distribution, and the only role for copyright in this domain, should be to give authors control over the integrity of their work and the right to be properly acknowledged and cited” (reference: http://www.budapestopenaccessinitiative.org)
\n\nOAI-PMH
\n\nAs a firm believer in the wider dissemination of knowledge, IntechOpen supports the Open Access Initiative Protocol for Metadata Harvesting (OAI-PMH Version 2.0). Read more
\n\nLicense
\n\nBook chapters published in edited volumes are distributed under the Creative Commons Attribution 3.0 Unported License (CC BY 3.0). IntechOpen upholds a very flexible Copyright Policy. There is no copyright transfer to the publisher and Authors retain exclusive copyright to their work. All Monographs/Compacts are distributed under the Creative Commons Attribution-NonCommercial 4.0 International (CC BY-NC 4.0). Read more
\n\nPeer Review Policies
\n\nAll scientific works are Peer Reviewed prior to publishing. Read more
\n\nOA Publishing Fees
\n\nThe Open Access publishing model employed by IntechOpen eliminates subscription charges and pay-per-view fees, enabling readers to access research at no cost. In order to sustain operations and keep our publications freely accessible we levy an Open Access Publishing Fee for manuscripts, which helps us cover the costs of editorial work and the production of books. Read more
\n\nDigital Archiving Policy
\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. His research interests include pattern recognition, bioinformatics, and biometric systems (fingerprint classification and recognition, signature verification, face recognition).",institutionString:null,institution:null},{id:"496",title:"Dr.",name:"Carlos",middleName:null,surname:"Leon",slug:"carlos-leon",fullName:"Carlos Leon",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"University of Seville",country:{name:"Spain"}}},{id:"512",title:"Dr.",name:"Dayang",middleName:null,surname:"Jawawi",slug:"dayang-jawawi",fullName:"Dayang Jawawi",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"University of Technology Malaysia",country:{name:"Malaysia"}}},{id:"528",title:"Dr.",name:"Kresimir",middleName:null,surname:"Delac",slug:"kresimir-delac",fullName:"Kresimir Delac",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/528/images/system/528.jpg",biography:"K. Delac received his B.Sc.E.E. degree in 2003 and is currentlypursuing a Ph.D. degree at the University of Zagreb, Faculty of Electrical Engineering andComputing. His current research interests are digital image analysis, pattern recognition andbiometrics.",institutionString:null,institution:{name:"University of Zagreb",country:{name:"Croatia"}}},{id:"557",title:"Dr.",name:"Andon",middleName:"Venelinov",surname:"Topalov",slug:"andon-topalov",fullName:"Andon Topalov",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/557/images/1927_n.jpg",biography:"Dr. Andon V. Topalov received the MSc degree in Control Engineering from the Faculty of Information Systems, Technologies, and Automation at Moscow State University of Civil Engineering (MGGU) in 1979. He then received his PhD degree in Control Engineering from the Department of Automation and Remote Control at Moscow State Mining University (MGSU), Moscow, in 1984. From 1985 to 1986, he was a Research Fellow in the Research Institute for Electronic Equipment, ZZU AD, Plovdiv, Bulgaria. In 1986, he joined the Department of Control Systems, Technical University of Sofia at the Plovdiv campus, where he is presently a Full Professor. He has held long-term visiting Professor/Scholar positions at various institutions in South Korea, Turkey, Mexico, Greece, Belgium, UK, and Germany. And he has coauthored one book and authored or coauthored more than 80 research papers in conference proceedings and journals. His current research interests are in the fields of intelligent control and robotics.",institutionString:null,institution:{name:"Technical University of Sofia",country:{name:"Bulgaria"}}},{id:"585",title:"Prof.",name:"Munir",middleName:null,surname:"Merdan",slug:"munir-merdan",fullName:"Munir Merdan",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/585/images/system/585.jpg",biography:"Munir Merdan received the M.Sc. degree in mechanical engineering from the Technical University of Sarajevo, Bosnia and Herzegovina, in 2001, and the Ph.D. degree in electrical engineering from the Vienna University of Technology, Vienna, Austria, in 2009.Since 2005, he has been at the Automation and Control Institute, Vienna University of Technology, where he is currently a Senior Researcher. 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. In the Engineering side, Digital Signal Processing, Computer Architecture, Electronics Devices, Digital Filtering and Engineering Management.\nApart from his Academic Interest and activities he loves sport especially, Cricket, Football, Snooker and Squash. He plays cricket for Esbjerg city in the second division team as an opener wicket keeper batsman. 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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. 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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. 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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. 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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. 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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 is a member of the Turkish Biochemical Society, American Chemical Society, and German Genetics society. Dr. Ekinci published around ninety scientific papers, reviews and book chapters, and presented several conferences to scientists. He has received numerous publication awards from several scientific councils. 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He 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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Since then, he has been working as an Adjunct Professor in the same Department at the University of Pavia. His research activity during the first years was primarily focused on the purification and structural characterization of enzymes from animal and plant sources. During this period, Prof. Iadarola familiarized himself with the conventional techniques used in column chromatography, spectrophotometry, manual Edman degradation, and electrophoresis). Since 1995, he has been working on: i) the determination in biological fluids (serum, urine, bronchoalveolar lavage, sputum) of proteolytic activities involved in the degradation processes of connective tissue matrix, and ii) on the identification of biological markers of lung diseases. 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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. 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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. 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