Sampling strategy.
\\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:"4506",leadTitle:null,fullTitle:"Advances in Optical Fiber Technology: Fundamental Optical Phenomena and Applications",title:"Advances in Optical Fiber Technology",subtitle:"Fundamental Optical Phenomena and Applications",reviewType:"peer-reviewed",abstract:"This book is a compilation of works presenting recent developments and practical applications in optical fiber technology. 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\r\n\tWith this rapid transformation of the computing and communication world, information-system security has moved from a largely self-contained bounded environment interacting with a generally known and disciplined user community to a worldwide scope with a body of users that may not be known and are not necessarily trusted. Importantly, security control now must deal with circumstances over which there is largely no control or expectation of avoiding their impact. Computer security, as it has evolved, shares a similarity with liability assurance: they each face a threat environment that is known in a very general way and can face attacks over a broad spectrum of sources. However, the exact details or even time or certainty of an attack are unknown until an incident occurs.
\r\n\tThe purpose of this book is to discuss some of the critical security challenges in today’s computing world and to discuss mechanisms for defending against those attacks by using classical and modern approaches to cryptography and other security solutions. With this objective, the book invites contributions from researchers in the field of cryptography and its applications in network security. Some illustrative topics of interest (but not limited to) are cryptography algorithms, authentication, authorization, integrity, confidentiality, privacy, security in wireless networks, security in wireless local area networks, wireless sensor networks, wireless ad hoc networks, vehicular ad hoc networks, security and privacy in the Internet of Things. Privacy of information, Blockchains, and Machine Learning in Security are three additional topics that the book will also deal with.
Milk and dairy products both are vital part of human nutrition and ideal sources of nutritional components because of their biochemical complexity for supplying essential mixture of proteins, vitamins, calcium, amino acids and antioxidants [1]. Pakistan is 4th largest milk producing country in the world and produces 45 billion liters per year [2]. The extensive and vast dairy industry of Pakistan faces a lot of problems including Aflatoxin M1 (AFM1). AFM1 are playing negative impacts on animal production as well as dangerous for human health [3, 4].
AFM1 is a monohydoxylated product of Aflatoxin B1 (AFB1). When lactating mammals consume AFB1 contaminated feed then production of AFM1 becomes enhanced. After ingestion of AFB1, hydroxylation reaction is occurred on tertiary carbon of difuran ring system which yields AFM1 [5, 6, 7]. The biotransformation frequency of AFB1 to AFM1 in excreted milk is different in all lactating animals. But AFM1 start producing in milk within 12 – 24 hours after AFB1 ingestion from feed [8].
80% people especially children consume dairy products as an important part of their diet [9]. But it is a dejected reality that dairy products are compromised badly because of mycotoxins. These fungal toxins not only destroy these dairy products but also produce dreadful disease which causes chronic diseases in the consumer. The World Health Organization (WHO) has endorsed the depletion of Aflatoxins in food by establishing tolerable limits for Aflatoxins to fulfill Farm-to-Fork principle.
International Agency for Research on Cancer (IARC) which is specialized cancer agency of World Health Organization (WHO) has categorized aflatoxins B1 and M1 into group 1 carcinogens [10, 11]. Therefore, different international organizations and countries have established standards for AFM1. The European Commission Regulation 1881/2006 set permissible limits for AFM1 in milk and dairy products of 0.050 μg/kg [12, 13]. According to Codex Alimentarius Commission permissible level of AFM1 in butter is 50 μg/kg and in cheese is 250 μg/kg [14]. So, permissible limits of AFM1 vary in milk and dairy products in different countries. But many countries including Pakistan also have no proper safety and regulatory limits and levels for AFM1 in milk and dairy products [15] which may be due to oversight of policy makers with negligible research on aflatoxins.
Hence, this study was designed to gauge AFM1 problem in milk and dairy products in and around Lahore from different sources. In the second phase of the study, efficacy of three different toxin binders were compared in a local dairy farm. The outcomes of the study will help dairy farmers on one hand and law enforcement agencies on the other to understand the gravity of AFM1 problem in milk and main dairy products, and formulate strategies to control it.
Sampling strategy is comprehensively discussed in Table 1. After collection, samples were transported in icebox to University of Veterinary and Animal Sciences, Lahore where these were stored at −4°C till further processing.
Sample | Sample category |
---|---|
Milk (n = 60) | 10 ml unprocessed milk from local milk shop (n = 20) |
10 ml unprocessed milk local dairy farm (n = 20) | |
10 ml processed milk sample from a commercial shop (n = 20) | |
Butter (n = 30) | 50 g Processed butter samples (n = 15) |
50 g unprocessed butter samples (n = 15) | |
Cream (n = 30) | 50 g processed cream samples (n = 15) |
50 g unprocessed cream samples (n = 15) | |
Cheese (n = 30) | 50 g processed cheese samples (n = 15) |
50 g unprocessed cheese samples (n = 15) | |
Yogurt (n = 30) | 50 g processed yogurt samples (n = 15) |
50 g unprocessed yogurt samples (n = 15) |
Sampling strategy.
Rapid test kit detects AFM1 to the limit of 0.5 ng/ml-ppb. The kit was used according to manufacturer instructions. Briefly, 200 μL milk samples were pipetted into reagent microwell and after mixing, these samples were incubated at room temperature for 2 minutes. Then dipstick was inserted in each sample and incubated for another 5 minutes at the same temperature. After that dipstick was taken out from each sample and samples were interpreted. There would be two lines i.e. test line (T) and control line (C) on dipstick. If T > = C then sample was considered negative while if T > C or there was no test line then it was considered as positive.
Chemicals and Reagents:
AFM1 standards (10 μg/l in acetonitrile), Celite and HPLC grade acetonitrile of Sigma–Aldrich, Steinheim, Germany and Immunoaffinity column AflaTm of VICAM, USA were used.
AFM1 standard curve or linearity curve was prepared by diluting the standards with acetonitrile at 0.05, 0.1, 0.2, 0.3, 0.4 and 0.5 μg/ml concentrations and stored in caped vials in refrigerator at – 4 C.
Samples Extraction:
5 g sample of each products and 5 g Celite mixed with 40 ml of dichloromethane in a 50 ml falcon tube. Then centrifuged at 21,000 rpm for 5 mins. After centrifugation the supernatant was separated and evaporated in water bath at 80 C. After evaporation the beaker was shifted in ultrasonic clean-up for 5 min. Then residues in beaker were dissolved in 10 ml mixture of methanol, water and n-hexane with the ratio of 3:5:2. Then 15 ml of this solution mixed by vortex mixture and again centrifuged at 21,000 rpm for 5 mins. After this, aqueous filtrate was passed through immunoaffinity column. The column was washed with 10 ml of water to remove toxins. After this column again washed with 2.5 ml of acetonitrile to get the final extract. This extract then dry under nitrogen steam at 40 C. After evaporation residues were dissolved with 2 ml mobile phase and mix by using vortex mixture. Finally, 20 μ/l sample was injected in HPLC for the analysis.
HPLC Conditions:
The HPLC used for the analysis was a Shimadzu LC-10A series (Japan) with the fluorescence detector (HPLC-FLD) having excitation wavelength of 365 nm and emission wavelength of 435 nm.
Three different toxin binders were used in respective groups A, B, and C each having 10 AFM1 positive animals. The Table 2 showed types of toxin binder and their dose rates. Each toxin binder was used on the daily basis for 7 days.
Groups | Type of toxin binders | Dose rate |
---|---|---|
A (n = 10) | Clay based toxin binder | 100 g/40 Kg feed |
B (n = 10) | Whole yeast-based toxin binder | 1 g/40 Kg feed |
C (n = 10) | Yeast (75%) + Algae (25%) | 10 g/40 Kg feed |
Therapeutic trials in different groups.
At days 2nd, 3rd, 4th, and 7th 10 ml milk samples from each animal were collected in plain vacutainers and serum was extracted through centrifugation. After that milk samples were checked by using AFM1 rapid test kit.
Collected data will be statistically scrutinized by SPSS 20.0 software and t-test as well as Chi square test was used to analyze the results.
The results of this study were comprehensively described in Tables 3 and 4. Figure 1 showed the linearity curve of AFM1 standard concentrations of 0.05, 0.1, 0.2, 0.3, 0.4 and 0.5 μg/ml. The method showed linear response R2 = 1.
Type of Sample | Group | Mean ± S.D | Range of Conc. of Aflatoxin M1 in ppb | Samples Exceeding EC limits (0.05 ppb) |
---|---|---|---|---|
Processed | .0900 | .36 | (5/30) 16.7% | |
Local | .0000 | .00 | ||
Total | .0450 | .36 | ||
Processed | .3500 | 1.05 | (10/30) 33.3% | |
Local | .0000 | .00 | ||
Total | .1750 | 1.05 | ||
Processed | .0000 | .00 | (4/30) 13.3% | |
Local | .5425 | 2.17 | ||
Total | .2713 | 2.17 | ||
Processed | .5525 | 2.05 | (8/30) 26.6% | |
Local | .0000 | .00 | ||
Total | .2763 | 2.05 |
HPLC results of aflatoxin M1 in dairy products.
Groups | Positive | Negative | Percentage | |
A | 10 | 0 | 100% | 0.000 |
B | 9 | 1 | 90% | |
C | 3 | 7 | 30% | |
Groups | Positive | Negative | Percentage | |
A | 9 | 1 | 90% | 0.000 |
B | 7 | 3 | 70% | |
C | 0 | 10 | 00% | |
Groups | Positive | Negative | Percentage | |
A | 9 | 1 | 90% | 0.000 |
B | 6 | 4 | 60% | |
C | 0 | 10 | 00% | |
Groups | Positive | Negative | Percentage | |
A | 8 | 2 | 80% | 0.000 |
B | 6 | 40 | 60% | |
C | 0 | 100 | 00% |
Efficacy of different toxin binders in groups A, B, and C.
Linearity curve of aflatoxin M1 standard concentrations.
Table 3 shows the level of AFM1 of all dairy products that exceeds the tolerable limits (0.050 μg/kg) established by European Commission Regulation.
Our results concluded that 33.3% of processed butter sample showed positive recovery of AFM1 with range concentration above EU limits (0.050 μg/kg) while no local butter sample with AFM1 toxicity was found (Table 3). These results are only in agreement with a study conducted by Fallah et al. [16] who analyzed 31 butter samples and got 25.8% AFM1-positive ones with range above permissible limits established by EU.
The similar trend was found in case of processed cheese samples which were found contaminated (33.3%) with AFM1 (Table 3) whereas in another study the AFM1 concentration was found much higher i.e., 78% [15]. There are many other such studies having positive percentages of AFM1 higher than our results [16, 17, 18].
Similarly, analysis of processed and unprocessed yogurt samples showed that 26.6% of former were contaminated with AFM1 above EU permissible limit whereas no sample in latter was found affected with these aflatoxins. Our results showed low positive percentage than documented by Iqbal and Asi [15] who found 59 AFM1-positive samples. Many other such studies also showed higher incidents of AFM1 in yogurt samples than our study [19, 20, 21]. Lastly, results of unprocessed cream samples showed the highest concentration of AFM1 whereas no aflatoxin was detected in processed cream samples as shown in Table 3. These results have not only local impacts but high impact at global level too. Because at global level, particularly in underdeveloped and developing countries, the topic of aflatoxins in dairy sector impacting humans as well as animals is a neglected topic.
During the second phase of the study, milk samples collected on 2nd, 3rd, 4th, and 7th day showed significantly different efficacies of three toxin binders in groups A, B, and C. It was found that toxin binder used in group C had significantly higher (<0.05) efficacy as compared to those used in groups A and B. This toxin binder C had yeast wall (75%) in combination with algae (25%) so it showed best results and eradicated AFM1 from all the animals after 48 h. The reason behind is the main role of yeast wall in the whole yeast which binds with mycotoxin and its binding ability is catalyzed by algae so the product having this combination provided the best results. Whereas, the clay-based toxin binder used in group A showed comparatively worst results in controlling AFM1 due to their lack of binding with these mycotoxins as described by Chestnut et al. [22]. Other disadvantages associated with clay-based toxin binders are their probable interaction with the essential nutrients [23] and high inclusion rates [24]. On the other hand, whole yeast-based toxin binder showed significantly lower efficacy as compared to group C and higher efficacy as compared to group A. The reason behind would be that whole yeast alone does not have good binding ability with mycotoxins so it also failed to control AFM1, comparatively. The whole findings are summarized in Figure 2.
Positive percentage in each group after offering toxin binders.
The results of this study confirmed that processed and unprocessed milk and main dairy products i.e. butter, cheese, cream, and yogurt has significantly (
The authors declare no conflict of interest.
Applying non-linear theory and approaches has been a growing research interest in sports sciences fields such as performance analysis [1, 2, 3, 4]. It is assumed that time-based and team sports display non-linear characteristics [5, 6, 7, 8]. Football is deemed as a complex and dynamic system where players perform intermittent movements in time-space coordination [9, 10, 11]. The prominence of this research topic is due to several factors, amongst which the shift in the paradigm from linear to non-linear frameworks that has been applied to a wide variety of fields and settings, besided the ready access to technology (e.g., tracking systems) providing large datasets, time series outputs and new time-motion approaches [12, 13, 14].
Nonlinear theory and complex sciences are disruptive of linear frameworks [15, 16]. Linear systems assume a linearity on time-varying case, an input-output statistic and a linear state feedback [17]. Considering the linear system theory, an internal and external structure developing feedback control strategies for simultaneous stabilisation of the system [16]. Based on this, theoretical models quantify the relationship between human movement (input) and performance (output), considering the athlete as a linear system [18, 19]. Desynchronization between internal (such as heart rate measure, perceived exertion and biochemical procedures) and external components (i.e., movement speed, body impacts, metabolic power, accelerations and decelerations) may affect the performance [18, 20]. Small changes in the inputs determine proportional and measurable changes in the output, reporting linearity characteristics such as controllability, observability and canonical structure [21]. These assumptions determines approaches focused on the linearity of the system, reporting an fitness-fatigue binomial with a related dependence on dose-response relationships [22, 23]. However, the accuracy of these theoretical models has been challenged for being feeble and for the lack of individualised measurement [23]. Moreover, the ecological dynamisms of informational contexts, social relations and human movement variability are not considered in linear analyses [24, 25, 26]. Human movement and collective behaviour are not characterised by the linearity of the systems (as in team sports, like football) and the linear theory could be deemed as a reductionist approach to the problem [5, 6, 26]. Thus, the individual and collective performance has been reported using a complex and dynamic perspective [26, 27, 28, 29, 30, 31]. Under these assumptions, biological systems are characterised by non-linearity, interaction-dominant dynamics, emergent behaviour, self-similarity, self-organisation and a chaotic component [32]. Literature reports several nomenclatures for the topic as complex adaptive systems [8, 33, 34], complex and dynamic systems [6, 26] or non-linear and dynamical self-organisation systems [27, 34, 35].
The ready access to cutting-edge technology was another reason for this field of research to increase. Such technology eventually became more affordable and user friendly. The use of tracking data started by assessing the individual players’ movement, and later integrated spatial-temporal patterns based on Cartesian and Euclidean references [13, 36, 37]. Over the last two decades, positional data has been verified in football training and match-play to assess the complexity of the systems inherent to the individual movements and collective coordination [31, 38, 39]. Positional dataset can be applied to measure both physical and tactical measures [10, 40, 41, 42, 43, 44, 45]. However, analysis do not always integrate different performance indicators [10, 46, 47]. Usually, studies focused only in a single performance dimension, however, football is a multifaceted sport with the physical, tactical, and technical factors amalgamating to influence performance with each factor not mutually exclusive of another [47]. Integrating performance metrics remain rarely described in current literature, concerning football environments [36]. That creates issues in the performance analysis, leading to the fact that the integrative approaches remain understudied. This research gap may be a very important topic to enhance knowledge about the theoretical concepts, mathematical models and methodological procedures of the non-linear approaches to integrate physiological and behavioural data in football.
Football is an invasion game characterised as a complex and dynamical systems with a goal-oriented adaptation amongst teammate and opponents [9, 48]. Previously, to measure and tracking player’s movements, mapping tactical actions and modelling collective behaviour were time-consuming processes [2, 4, 49]. Observational and notational analysis had scarce technological and procedural means to support the occurrence of the large number of physical, technical and tactical actions of the football game [49, 50, 51]. The wearable technologies as tracking systems allowed real-time access the players’ position on the field during training and competition [31, 38, 39]. Positional dataset can be captured at different frequencies by using tracking systems as global positioning systems (GPS) tracking systems [52, 53], micro-electromechanical systems (MEMS) [36, 54], local radio-based local positioning systems (LPM) [55, 56], computerised-video systems [57, 58] and tracking system [59, 60]. This is largely due to the high cost associated with its use, which restricts its use almost exclusively to professional settings in male players [20, 61]. The validity and accuracy of these time-motion methodologies is well documented with an excellent reliability (coefficient of variation, CV: 1.02–1.04%) [52, 53]. However, the integration of the different devices still needs further studies [60, 62, 63]. Using this techniques to collect data, the players’ movements are possible to be framed in a Cartesian referential (football field), represented by time series of Cartesian coordinates (
where
The training process requires a systematic physiological and biomechanical stimulus to ensure optimal adaptations and an adequate performance [19]. Several theoretical frameworks have been developed to assess the quantity and quality of the training and competition demands [18, 19]. These training load-based consider the linear system theory, likewise dose-response relationship and fitness-fatigue binomial. Fitness-fatigue model approach was originally proposed by Bannister [73]:
were
Football performance, a multifactorial phenomenon, dependant on a variety of factors such as environmental, contextual, physical, technical, tactical and psychophysiological [46, 47, 83]. These factor are not mutually exclusive of one another, what makes relevant an integrated approach to provide holistic insights about performance analysis [47, 83]. On regular basis, each of these factors are analysed in isolation without taking the others into account, leading to 1-dimensional insights [83]. Bradley and Ade [47] proposed a theoretical model emphasising on high-intensity running efforts during match-play advocating a contextualization of these running-based actions amongst technical and tactical activities [47]. This becomes of utmost relevance considering the football game [9, 65]. This is what mediates the players’ decision making throughout the game according a team strategy previously defined [13]. Several authors have tried to establish ecological approaches to evaluate training and match outcomes, including non-linear approaches [11, 65]. Non-linear analyses were fundamentally performed on competitive game [41, 85] and limited training tasks as small and large-side games [42, 43, 44, 45, 67, 69]. It is therefore important to understand mathematical models and methodological procedures underpinning non-linear analyses to assess their significance in applied research and applied settings, identify possible research gaps to be explored and, be aware of potential limitations and criticisms (Figure 1).
Physiological and behavioural dataset in football environments.
Non-linear approaches have been recurrently applied in football using complexity principles [14, 31, 36]. The informational context and spatiotemporal determinants that mediate players’ perception and action are analysed by nonlinear and dynamic proprieties of the football game [6, 28]. It is assumed that environmental, task and organismic constraint influence individual and collective behaviour [5, 28]. This behaviour has a physiological cost over time that must be measured [18, 20, 76]. Informative content can be classified as different domains of variability, namely the frequency domain, the entropy domain and the scale-invariant domain [5, 86]. In biological systems, sequential time-series have become outstanding data analysis in multifaceted context [87, 88, 89, 90]. According to Bravi et al. [86] the time-series data can be described through five different domains of variability: (1) statistical (i.e., statistical properties of the distribution in a stochastic process); (2) geometric (i.e., properties of the dataset shaped in a certain space); (3) energetic (i.e., energy or power of the time-series); (4) informational (i.e., degree of irregularity/complexity inherent to the order of the elements in a time-series); invariant (i.e., fractality or unchanging attributes over time or space). In football, time-series data application has been widely applied [14, 36]. Low et al. [36] organised the non-linear methods into measures of the regularity (or predictability) and synchronisation. Geometrical centre and periodic phase oscillators has been considered to analyse players’ synchronisation and modelling the coordination of a team [14]. However, remains unclear the application of time-series data from an integrated approach perspective [10, 47, 83]. Thus, it is paramount to determine mathematical models and methodological procedures for non-linear time-series data analysis, bearing in mind an integrative approach. Therefore, the following subsections elaborate on the different non-linear mathematical models possible to apply in football.
Entropy is a non-linear and informational parameter applied to describe variability, regularity or predictability of the movement/performance uncover the inter-player’s interactions [86, 89, 91]. That, is entropy parameters describes the degree of irregularity/complexity inherent to the order of the elements in a time-series [86]. There are several types of entropy reported in the literature and applied in football research from the integrative perspective, amongst which Approximate Entropy (ApEn) [6, 11, 42], Sample Entropy (SampEn) [44, 92], Cross-sample Entropy (Cross-SampEn) [92] and Boltzmann-Gibbs-Shannon Entropy (ShannonEn) [43]. ApEn expresses the probability that the sequence configuration in a time-series data allows the prediction of the configuration from another sequence from a distance apart [89, 91]. ApEn was derivate from Kolmogorov-Sinai entropy and ranged amongst 0−2 where lower values correspond to more predictable and higher values stands more unpredicted patterns within time-series (0 ≤ ApEn ≤2) [89].
where
From a practical point of view, the imputed ApEn values should be computed with 2 to vector length (
Where,
Multiscale entropy (MSE) as Cross-ApEn and Cross-SampEn was recently introduced from the primary entropy procedures (i.e. ApEn and Cross-ApEn) [90, 95]. Therefore, cross-entropy methods quantify the degree or complexity of coupling between two cross-sequences while the primary entropy techniques evaluated the asynchronism between two time series [87, 90]. Cross-SampEn remain a greater relative consistent than Cross-ApEn, being defined as long as one template finds a time-series sequence [89]. Mostly, Cross-SampEn has been recurrently used in football settings to measure players’ synchrony [36, 92]. Cross-SampEn, the templates are chosen from the series
Boltzmann-Gibbs-Shannon entropy was applied by Ric et al. [43] to measure temporal diversity and structural flexibility of the players. This entropy-based technique was originally applied by Balescu [96], reporting the configuration’s probabilities as the large
where
MSE techniques was applied in football by Canton et al. [44] to identify how positioning the goals in diagonal configurations on the pitch modifies the external training load and the tactical behaviour in youth football environments (i.e., small-sided games). The authors applied a SampleEn algorithm to compute entropy values in different timescales, calculating the area under for complexity index as reported in multiple entropy analysis for time-series [90, 98]. MSE techniques reports the point-to-point fluctuations over a time-series range [44, 90, 98] as:
Where, timescales is
Where, En is the reported entropy parameter at the time scale
Relative phase was extensity reported in football within an integrative framework [40, 41, 67]. Using a Hilbert transform
Where,
Non-linear parameters are often transformed into reliable complexes indices to measure complexity in football settings [43, 69, 93]. Dynamic overlap is a complex index used to compare time-series against the average cosine auto-similarity of the overlap between configurations within time lags [102]. It is an informational non-linear parameter that expresses how timescale statured in a dynamic behaviour using the exploratory breadth at different timescales [43, 69]:
Where,
Another complex index reported in the literature is the stretch index, which can be defined as distances amongst players and the geometrical centre of the team [45, 85]. That is, this complex index measures the spatial expansion or contraction [103] as:
Here
Windowed and cross correlation were also applied to assess collective behaviour through positional data in football training and match environments [36, 65, 92]. Cross correlation function is well-supported in the human movement research, wherein the overlapping time windows that enclosed the time-series sequence under analysis [105, 106]. Cross-Correlation function multiplied the point-to-point amongst two time-series data series, reporting the sum of the products and the respective relationship quantification [105]:
Where
Where
where,
where
Fractal dimension is an invariant non-linear parameter characterised by the unchanged proprieties of the system over time and/or space [86]. Multifractal time series expresses different local scaling exponents for a time-series dataset scaling different exponents at different times [86, 110]. Few studies applied fractal dimension to predict stability and predictability of the football players along specific training tasks [110, 111] and competitive matches [110, 111, 112]. Fractal calculus (FC) was reported using Shanon and Grünwald-Letnikov approaches [111, 112]. Grünwald–Letnikov fractional differential consideres the matrix containing the multi-player positions [111, 113]:
where
whereby
A study applied multifractal dimension in football movement behaviour using Hausdorff dimension (
where
Clustering methods have become popular in data mining in several research areas, including sports sciences [70, 92, 115]. Rokach and Maimon [115] was described the clustering methods in different typologies as hierarchical, partitioning, density-based, model-based, grid-based, and soft-computing methods. Duarte et al. [92] pioneered applied a clustering method to measure overall and player team collective synchronisation in football. This method is derived from Hibert transform to calculate individual phase time-series and subsequently the cluster phase of these time-series by the natural exponential function [36, 92]. Originally, cluster phase analysis was proposed by Frank and Richardson [116] using Kuramoto’s parameters for group synchronisation [117]. This clustering method calculates the mean and continuous group synchronisation
where overall team synchronisation
Synchronisation cut-off values is zero to one representing synchronisation and unsynchronisation (
Furthermore, average mutual information (AMI) was also applied to measure complexity of the football patterns and expresses the amount of information one random variable contains another [118]. AMI is calculated by relative entropy between probabilities distribution and the product midst two selected variables [36]. The mathematical equation described by Cover and Thomas [118] for the calculation of mutual information is:
Where
Non-linear techniques as entropy measures can also be expressed in the frequency domain [86]. Several studies have evaluated the variability of movement comparing informational and frequency domains [10, 41, 42]. CV expresses the magnitude of the variability in the distance amongst players’, expressed as percentage (%) [10, 93]:
Speed synchronisation has also applied into a integrative approaches in some studies [10, 41]. The near-in-phase synchronisation to players’ displacements is expressed in time spent (%) of time according to speed intensity zones: 0.0–3.5 km h−1 (low intensity); 3.6–14.3 km h−1 (moderate intensity); 14.4–19.7 km h−1 (high intensity); and >19.8 km h−1 (very high intensity) [41]. Summary diagram for mathematical models and methodological procedures of the non-linear approaches are presented in Figure 2.
Summary diagram for mathematical models and methodological procedures of the non-linear approaches.
Table 1 displayed the corresponding equation, thresholds, advantages, disadvantages and practical application for each nonlinear variable.
Variable | Equation | Thresholds | Advantages | Disadvantages | Practical application |
---|---|---|---|---|---|
ApEn | 0 ≤ ApEn ≤2; close 0—predictable; close 2—unpredictable | Similar patterns will not be followed by subsequent similar observations. | Dependent on the length record causing lacks of relative consistency. | Interpersonal coordination (1-vs-1 sub-phase); Opposition and cooperation relationships on collective movement behaviour. | |
SampEn | 0 ≤ SampEn < | Shorter time-series records with a greater relative consistency | Lower complexity for a signal than white noise signal. | Diagonal positioning of the goals on SSG | |
ShannonEn | 0 ≤ | Multiple optimal weights on the evaluation and self-information. | Only consider a particular event, not the meaning of the events (criteria) themselves | Dynamics of tactical behaviour emerging on different time-scale using SSG | |
MSE | 0 ≤ Cross-SampEn < | Faster and allows to evaluate two time-series crossed | Loss of pattern information hidden in the time series | Assessing the dynamics of team–team and player–team synchronisation | |
Hilbert transform | In-phase (−30° ≤ | Require short signals than classical non-parametric methods | One dimensional processing causing phase ambiguities | Movement behaviour, speed synchronisation, inter-team distances, spatial interaction, oscillations of centroid position and surface area. | |
Dynamic overload | 0 ≤ | Compare dataset using a cosine auto-similarity that increase in each time lag | Analysis allowed the slow dynamics on a long timescale | Dynamical of tactical behaviour and constrained the perceptual-motor workspace | |
Stretch index | Near-in-phase synchronisation to players’ displacements is expressed in time spent (%) | Provide the centroid position of the team and the sum of each player’s dispersion on both axes | Relative stretch indexes has needed to measure two teams | Coordination and spatial interactions for opposite and team behaviours | |
Windowed and cross correlation | −1 ≤ | Measuring similarity, can determine time delay and the identity lagging signal | Bivariate linear association between group synchrony time-series data | Cross-correlation and peak picking for team synergies variability in tactical behaviour | |
Fractal Calcus | 0-Dimensional sets to 3-dimensional sets ( | Assessing fractal properties of human movement associated to sport skills and motor variability | Non-cyclicality of football movement using fractal analysis | Multifractal properties, dynamical stability and predictability of the movement. | |
Hausdorff dimension | |||||
Kuramoto’s Clustering | Unbiased measure of group coordination and measure to assess player–team synchrony | Achieve synchronisation modes in networks with different structures | Order, disorder and variability in spatio-temporal interactions amongst two teams | ||
AMI (clustering) | 0 ≤ AMI < 1; close 0—predictable; close 1—unpredictable | Measuring the nonlinear correlation of the two centroids’ movements | Disadvantages of redundancy in each class | Positional synchronisation an geometrical center modifications in team behaviour | |
CV% | NR | Statistical measure that is normalised and non-dimensional | Dependent on the mean values of the time-series | Speed synchronisation match-to-match variation |
Summary of the non-linear variables and respective equation, thresholds, advantages, disadvantages and practical application.
Matlab® routines (Math-Works, Inc., Massachusetts, USA) were the most selected procedure to analyse positional dataset in football. Universal Transverse Mercator (UTM) coordinate system were used to transform latitude and longitude data points [40, 66]. Methodological procedures differ on the correction guidelines to be used and reduce tracking signal noise, advising the use of 3 Hz Butterworth low pass filter [64, 92]. Several authors ran non-linear logarithms using 20 windows of 3000 points per data collect (i.e. ranged 5−25 Hz) [40, 67]. Integrating notational analysis and video-based tracking systems has been a worthwhile strategy to provide contextual significance to positional data [67, 68, 93]. Applying new analysis techniques based on big data still lack an integrative approach, and it will be interesting to understand how future studies can do so with techniques such as machine learning, deep learning or network analysis [13, 14]. These techniques have been extensively used to analyse positional and physiological variables, but there are still few studies under an integrative perspective [13, 36, 46]. There is a lack of standardisation on non-linear measures, measurement and thresholds [20, 76]. It is even more evident in the physiological measures, therefore, the results obtained in studies that integrate positional and physiological datasets should be interpreted with caution [120]. The application of integrative approaches should also consider the boundaries between different key performance indicators such as the psychophysiological [45, 121, 122, 123], technical [44, 67, 93] and contextual factors [83, 84]. Also, acceleration outputs, metabolic power and body impacts have been poorly integrated with positional data. Behavioural data should still be better contextualised and the related-bias for physiological thresholds must be considered upon the time-dependent and transient reduction [84]. An integration approach to physiology and behavioural data must overcome some challenges on data visualisation, data processing (inherent to big data) and real-time tracking [13]. Moreover, futures researches should focus their analysis on women and sub-elite performers [20, 61].
Physiological assessment to monitoring training and match load has been carried out mainly under a linear perspective. Positional data to assess tactical behaviour considers fundamentally the theory of the complex systems and non-linear dynamics. Thus, an integrative approach allows a more holistic and extensive evaluation of the performance as a multifactorial phenomenon. This chapter summarises the theoretical concepts, mathematical models and methodological procedures to be applied by researchers and practitioners in training and match settings in football. The non-linear techniques reported more often in the literature were entropy, relative phase, complex indexes, correlation matrixes, clustering methods, frequency-based measures, fractals and multifractals. Correlation matrixes, clustering methods and fractality have not yet been applied in an integrative perspective in football. Finally, using non-linear approaches to integrate physiological and behavioural data remains a research-practice gap to be explored in the next years.
This research was supported by Portuguese Foundation for Science and Technology, I.P. (project UIDB04045/2021).
The authors declare no conflict of interest.
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\n\n2. STATEMENTS OF CONCERN
\n\nA Statement of Concern detailing alleged misconduct will be issued by the Academic Editor or publisher following a 3rd party report of scientific misconduct when:
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\n\nA Correction will be issued by the Academic Editor when:
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\n\nAn Erratum will be issued by the Academic Editor when it is determined that a mistake in a Chapter originates from the production process handled by the publisher.
\n\nA published Erratum will adhere to the Retraction Notice publishing guidelines outlined above.
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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. 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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. 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Shohel"}],equalEditorOne:null,equalEditorTwo:null,equalEditorThree:null,productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}}]},subject:{topic:{id:"803",title:"Power Plant Engineering",slug:"power-plant-engineering",parent:{id:"119",title:"Industrial Engineering and Management",slug:"industrial-engineering-and-management"},numberOfBooks:4,numberOfSeries:0,numberOfAuthorsAndEditors:70,numberOfWosCitations:10,numberOfCrossrefCitations:11,numberOfDimensionsCitations:28,videoUrl:null,fallbackUrl:null,description:null},booksByTopicFilter:{topicId:"803",sort:"-publishedDate",limit:12,offset:0},booksByTopicCollection:[{type:"book",id:"9888",title:"Nuclear Power Plants",subtitle:"The Processes from the Cradle to the Grave",isOpenForSubmission:!1,hash:"c2c8773e586f62155ab8221ebb72a849",slug:"nuclear-power-plants-the-processes-from-the-cradle-to-the-grave",bookSignature:"Nasser Awwad",coverURL:"https://cdn.intechopen.com/books/images_new/9888.jpg",editedByType:"Edited by",editors:[{id:"145209",title:"Prof.",name:"Nasser",middleName:"S",surname:"Awwad",slug:"nasser-awwad",fullName:"Nasser Awwad"}],equalEditorOne:null,equalEditorTwo:null,equalEditorThree:null,productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}},{type:"book",id:"6838",title:"Power Plants in the Industry",subtitle:null,isOpenForSubmission:!1,hash:"5e647d27dab23e014dd8881ac3d5931c",slug:"power-plants-in-the-industry",bookSignature:"Tolga Taner",coverURL:"https://cdn.intechopen.com/books/images_new/6838.jpg",editedByType:"Edited by",editors:[{id:"197240",title:"Associate Prof.",name:"Tolga",middleName:null,surname:"Taner",slug:"tolga-taner",fullName:"Tolga Taner"}],equalEditorOne:null,equalEditorTwo:null,equalEditorThree:null,productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}},{type:"book",id:"6332",title:"Thermal Power Plants",subtitle:"New Trends and Recent Developments",isOpenForSubmission:!1,hash:"616ffd286d75ca988abf59b408880a98",slug:"thermal-power-plants-new-trends-and-recent-developments",bookSignature:"Pawe? Madejski",coverURL:"https://cdn.intechopen.com/books/images_new/6332.jpg",editedByType:"Edited by",editors:[{id:"179645",title:"Dr.",name:"Paweł",middleName:null,surname:"Madejski",slug:"pawel-madejski",fullName:"Paweł Madejski"}],equalEditorOne:null,equalEditorTwo:null,equalEditorThree:null,productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}},{type:"book",id:"5807",title:"Recent Improvements of Power Plants Management and Technology",subtitle:null,isOpenForSubmission:!1,hash:"5f357d049b0e0c8d41243c794ef8d923",slug:"recent-improvements-of-power-plants-management-and-technology",bookSignature:"Aleksandar B. Nikolic and Zarko S. Janda",coverURL:"https://cdn.intechopen.com/books/images_new/5807.jpg",editedByType:"Edited by",editors:[{id:"19724",title:"Dr.",name:"Aleksandar",middleName:"B",surname:"Nikolic",slug:"aleksandar-nikolic",fullName:"Aleksandar Nikolic"}],equalEditorOne:null,equalEditorTwo:null,equalEditorThree:null,productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}}],booksByTopicTotal:4,seriesByTopicCollection:[],seriesByTopicTotal:0,mostCitedChapters:[{id:"62970",doi:"10.5772/intechopen.80241",title:"Nuclear Fusion Power Plants",slug:"nuclear-fusion-power-plants",totalDownloads:1763,totalCrossrefCites:1,totalDimensionsCites:4,abstract:"Nuclear fusion, the process that powers the sun and the stars, is heralded as the ultimate energy source for the future of mankind. The promise of nuclear fusion to provide clean and safe energy, while having abundant fuel resources continues to drive global research and development. However, the goal of reaching so-called “breakeven” energy conditions, whereby the energy produced from a fusion reaction is greater than the energy put in, is yet to be demonstrated. It is the role of ITER, an international collaborative experimental reactor, to achieve breakeven conditions and to demonstrate technologies that will allow fusion to be realized as a viable energy source. However, with significant delays and cost overruns to ITER, there has been increased interest in the development of other fusion reactor concepts, particularly by private-sector start-ups, all of which are exploring the possibility of an accelerated route to fusion. This chapter gives a comprehensive overview of nuclear fusion science, and provides an account of current approaches and their progress towards the realization of future fusion energy power plants. The range of technical issues, associated technology development challenges and future commercial opportunities are explored, with a focus on magnetic confinement approaches.",book:{id:"6838",slug:"power-plants-in-the-industry",title:"Power Plants in the Industry",fullTitle:"Power Plants in the Industry"},signatures:"Shutaro Takeda and Richard Pearson",authors:[{id:"251254",title:"Prof.",name:"Shutaro",middleName:null,surname:"Takeda",slug:"shutaro-takeda",fullName:"Shutaro Takeda"},{id:"262366",title:"Mr.",name:"Richard",middleName:null,surname:"Pearson",slug:"richard-pearson",fullName:"Richard Pearson"}]},{id:"54655",doi:"10.5772/67858",title:"Key Technical Performance Indicators for Power Plants",slug:"key-technical-performance-indicators-for-power-plants",totalDownloads:3295,totalCrossrefCites:1,totalDimensionsCites:3,abstract:"In this chapter, we will underline the importance of the key performance indicators (KPIs) computation for power plants’ management. The main scope of the KPIs is to continuously monitor and improve the business and technological processes. Such indicators show the efficiency of a process or a system in relation with norms, targets or plans. They usually provide investors and stakeholders a better image regarding location, equipment technology, layout and design, solar and wind exposure in case of renewable energy sources and maintenance strategies. We will present the most important KPIs such as energy performance index, compensated performance ratio, power performance index, yield, and performance, and we will compare these KPIs in terms of relevance and propose a set of new KPIs relevant for maintenance activities. We will also present a case study of a business intelligence (BI) dashboard developed for renewable power plant operation in order to analyze the KPIs. The BI solution contains a data level for data management, an analytical model with KPI framework and forecasting methods based on artificial neural networks (ANN) for estimating the generated energy from renewable energy sources and an interactive dashboard for advanced analytics and decision support.",book:{id:"5807",slug:"recent-improvements-of-power-plants-management-and-technology",title:"Recent Improvements of Power Plants Management and Technology",fullTitle:"Recent Improvements of Power Plants Management and Technology"},signatures:"Simona Vasilica Oprea and Adela Bâra",authors:[{id:"139804",title:"Prof.",name:"Adela",middleName:null,surname:"Bara",slug:"adela-bara",fullName:"Adela Bara"},{id:"188586",title:"Dr.",name:"Simona Vasilica",middleName:null,surname:"Oprea",slug:"simona-vasilica-oprea",fullName:"Simona Vasilica Oprea"}]},{id:"71264",doi:"10.5772/intechopen.90939",title:"Fast-Spectrum Fluoride Molten Salt Reactor (FFMSR) with Ultimately Reduced Radiotoxicity of Nuclear Wastes",slug:"fast-spectrum-fluoride-molten-salt-reactor-ffmsr-with-ultimately-reduced-radiotoxicity-of-nuclear-wa",totalDownloads:899,totalCrossrefCites:3,totalDimensionsCites:3,abstract:"A mixture of NaF-KF-UF4 eutectic and NaF-KF-TRUF3 eutectic containing heavy elements as much as 2.8 g/cc makes a fast-spectrum molten salt reactor based upon the U-Pu cycle available without a blanket. It does not object breeding but a stable operation without fissile makeup under practical contingencies. It is highly integrated with online dry chemical processes based on “selective oxide precipitation” to create a U-Pu cycle to provide as low as 0.01% leakage of TRU and nominated as the FFMSR. This certifies that the radiotoxicity of HLW for 1500 effective full power days (EFPD) operation can be equivalent to 405 tons of depleted uranium after 500 years cooling without Partition and Transmutation (P&T). A certain amount of U-TRU mixture recovered from LWR spent fuel is loaded after the initial criticality until U-Pu equilibrium but the fixed amount of 238U only thereafter. The TRU inventory in an FFMSR stays at an equilibrium perpetually. Accumulation of spent fuel of an LWR for 55 years should afford to start up the identical thermal capacity of FFMSR and to keep operation hypothetically until running out of 238U. Full deployment of the FFMSR should make the entire fuel cycle infrastructures needless except the HLW disposal site.",book:{id:"9888",slug:"nuclear-power-plants-the-processes-from-the-cradle-to-the-grave",title:"Nuclear Power Plants",fullTitle:"Nuclear Power Plants - The Processes from the Cradle to the Grave"},signatures:"Yasuo Hirose",authors:[{id:"315264",title:"Dr.",name:"Yasuo",middleName:null,surname:"Hirose",slug:"yasuo-hirose",fullName:"Yasuo Hirose"}]},{id:"54413",doi:"10.5772/67597",title:"Scalable, Self‐Contained Sodium Metal Production Plant for a Hydrogen Fuel Clean Energy Cycle",slug:"scalable-self-contained-sodium-metal-production-plant-for-a-hydrogen-fuel-clean-energy-cycle",totalDownloads:1828,totalCrossrefCites:0,totalDimensionsCites:2,abstract:"In this chapter, we present a detailed design study of a novel, scalable, self‐contained solar powered electrolytic sodium (Na) metal production plant meant to enable a hydrogen (H2) fuel, sustainable, closed clean energy cycle. The hydrogen fuel is generated on demand inside a motor vehicle using an efficient hydrogen generation apparatus that safely implements a controlled chemical reaction between either ordinary salinated (sea) or desalinated (fresh) water and sodium metal. The sodium hydroxide (NaOH) byproduct of the hydrogen generating chemical reaction is stored temporarily within the hydrogen generation apparatus and is recovered during motor vehicle refueling to be reprocessed in the self‐contained sodium (Na) metal production plant. The electric power for NaOH electrolysis is produced using photovoltaic (PV) device panels spatially arrayed and electrically interconnected on a tower structure that maximizes the use of scarce land area. Our analysis shows that the scalable, self‐contained sodium (Na) metal production plant using solar power is technically and economically viable for meeting the hydrogen fuel clean energy needs of all the motor vehicles in the U.S.A. by constructing approximately 450,000 scalable, self‐contained sodium (Na) metal production plant units in the southwestern desert region that includes West Texas, New Mexico, Arizona and Southern California.",book:{id:"5807",slug:"recent-improvements-of-power-plants-management-and-technology",title:"Recent Improvements of Power Plants Management and Technology",fullTitle:"Recent Improvements of Power Plants Management and Technology"},signatures:"Alvin G. Stern",authors:[{id:"199190",title:"Dr.",name:"Alvin",middleName:null,surname:"Stern",slug:"alvin-stern",fullName:"Alvin Stern"}]},{id:"55841",doi:"10.5772/intechopen.68772",title:"Risk Assessment of NPP Safety in Case of Emergency Situations on Technology",slug:"risk-assessment-of-npp-safety-in-case-of-emergency-situations-on-technology",totalDownloads:1327,totalCrossrefCites:0,totalDimensionsCites:2,abstract:"The last accidents of the nuclear power plant (NPP) in Chernobyl and Fukushima give us the new inspiration to verify the safety level of the NPP structures. This paper presents the new requirements to test the safety and reliability of the NPP structures due to the recent accidents in the world. The IAEA in Vienna required in the document ‘Stress tests’ the verification of the safety of the NPP structures under impact of the extreme loads as the earthquakes, the extreme climatic actions and the technology accidents. The new recommendations to load combinations and design criteria were defined. The risk assessment to verify the safety and reliability of the NPP structures based on probabilistic and nonlinear analysis is presented. The uncertainties of material model (behaviour of the reinforcement and liner, concrete cracking and crushing), degradation effects, the loads level (dead and live loads, extreme climatic and accidental temperature and overpressure) as well as other effects following from the inaccuracy of the calculated model and numerical methods were taken into account in the response surface method (RSM) method. The results of the deterministic and probabilistic analysis of the NPP structures are presented.",book:{id:"5807",slug:"recent-improvements-of-power-plants-management-and-technology",title:"Recent Improvements of Power Plants Management and Technology",fullTitle:"Recent Improvements of Power Plants Management and Technology"},signatures:"Juraj Králik",authors:[{id:"139600",title:"Prof.",name:"Juraj",middleName:null,surname:"Králik",slug:"juraj-kralik",fullName:"Juraj Králik"}]}],mostDownloadedChaptersLast30Days:[{id:"54655",title:"Key Technical Performance Indicators for Power Plants",slug:"key-technical-performance-indicators-for-power-plants",totalDownloads:3284,totalCrossrefCites:1,totalDimensionsCites:3,abstract:"In this chapter, we will underline the importance of the key performance indicators (KPIs) computation for power plants’ management. The main scope of the KPIs is to continuously monitor and improve the business and technological processes. Such indicators show the efficiency of a process or a system in relation with norms, targets or plans. They usually provide investors and stakeholders a better image regarding location, equipment technology, layout and design, solar and wind exposure in case of renewable energy sources and maintenance strategies. We will present the most important KPIs such as energy performance index, compensated performance ratio, power performance index, yield, and performance, and we will compare these KPIs in terms of relevance and propose a set of new KPIs relevant for maintenance activities. We will also present a case study of a business intelligence (BI) dashboard developed for renewable power plant operation in order to analyze the KPIs. The BI solution contains a data level for data management, an analytical model with KPI framework and forecasting methods based on artificial neural networks (ANN) for estimating the generated energy from renewable energy sources and an interactive dashboard for advanced analytics and decision support.",book:{id:"5807",slug:"recent-improvements-of-power-plants-management-and-technology",title:"Recent Improvements of Power Plants Management and Technology",fullTitle:"Recent Improvements of Power Plants Management and Technology"},signatures:"Simona Vasilica Oprea and Adela Bâra",authors:[{id:"139804",title:"Prof.",name:"Adela",middleName:null,surname:"Bara",slug:"adela-bara",fullName:"Adela Bara"},{id:"188586",title:"Dr.",name:"Simona Vasilica",middleName:null,surname:"Oprea",slug:"simona-vasilica-oprea",fullName:"Simona Vasilica Oprea"}]},{id:"55019",title:"Spatial Aspects of Environmental Impact of Power Plants",slug:"spatial-aspects-of-environmental-impact-of-power-plants",totalDownloads:1300,totalCrossrefCites:0,totalDimensionsCites:1,abstract:"Strategic Environmental Assessment (SEA) is one of the key instruments for implementing sustainable development strategies in planning in general, namely for analysing and assessing the spatial development concepts, in this case in the field of energy and planning of power plants. The SEA in energy sector planning has become a tool for considering the benefits and consequences of the proposed changes in space, also taking into account the capacity of space to sustain the implementation of the planned activities. This chapter examines the multi-criteria evaluation (MCE) method for carrying out an SEA for the power plants in Energy Sector Development Strategy of the Republic of Serbia (case study). The MCE method has found its use in the analysis and assessment of the energy sector spatial impacts on the environment and elements of sustainable development and, in this context, also considering the importance of impacts, spatial dispersion of impacts, their probability and frequency of occurrence, along with the elaboration of the obtained results in a specific, simple and unambiguous way. The chapter focuses on the consideration of aspects of environmental impact of all kinds of power plants, without taking into account the details regarding other aspects of energy sector development that are dealt with in the case study.",book:{id:"5807",slug:"recent-improvements-of-power-plants-management-and-technology",title:"Recent Improvements of Power Plants Management and Technology",fullTitle:"Recent Improvements of Power Plants Management and Technology"},signatures:"Boško Josimović and Saša Milijić",authors:[{id:"125578",title:"Dr.",name:"Bosko",middleName:null,surname:"Josimovic",slug:"bosko-josimovic",fullName:"Bosko Josimovic"},{id:"200736",title:"Dr.",name:"Sasa",middleName:null,surname:"Milijic",slug:"sasa-milijic",fullName:"Sasa Milijic"}]},{id:"64317",title:"Hybrid Power Plants: A Case Study",slug:"hybrid-power-plants-a-case-study",totalDownloads:1125,totalCrossrefCites:0,totalDimensionsCites:0,abstract:"Energy can be treated as an essential element for the development of society. Therefore, aspects like process’ efficiency and environmental impacts must be considered when choosing the supply source. In Brazil, an event showed the fragility of a system that relies on in only one source to attend their necessities; a truckers strike made the whole country stop. The energy sector has a similar situation; more than 60% of Brazilian energetic matrix is represented by one source, hydroelectric power plants. The availability of solar radiation and wind in Brazil makes it possible to diversify its energetic matrix. Thus, the aim of this study is investigating the potential of hybrid solar-wind power plants in two basins of Minas Gerais—Brazil, São Francisco Basin and Jequitinhonha Basin, as well as compare their viabilities in order to address social issues. By analyzing INMET database and economic factors, the study has shown that it is feasible to implement renewable power plants in the basins of the study area, whether individually (solar or wind energy) or hybrid system. It shows in addition that hybrid system should be prioritized, since it presents lower cost, when compared to solar power plant, and more reliability due to seasonality of both sources.",book:{id:"6838",slug:"power-plants-in-the-industry",title:"Power Plants in the Industry",fullTitle:"Power Plants in the Industry"},signatures:"Eduarda Moreira Nascimento, Júnio de Souza Damasceno and\nSabrinne Kelly Souza",authors:[{id:"252477",title:"Dr.",name:"Junio",middleName:null,surname:"Damasceno",slug:"junio-damasceno",fullName:"Junio Damasceno"},{id:"262354",title:"Ms.",name:"Sabrinne",middleName:"Kelly",surname:"Souza",slug:"sabrinne-souza",fullName:"Sabrinne Souza"},{id:"262363",title:"BSc.",name:"Eduarda",middleName:null,surname:"Nascimento",slug:"eduarda-nascimento",fullName:"Eduarda Nascimento"}]},{id:"58753",title:"Detection of Malfunctions and Abnormal Working Conditions of a Coal Mill",slug:"detection-of-malfunctions-and-abnormal-working-conditions-of-a-coal-mill",totalDownloads:1114,totalCrossrefCites:0,totalDimensionsCites:0,abstract:"Coal mill malfunctions are some of the most common causes of failing to keep the power plant crucial operating parameters or even unplanned power plant shutdowns. Therefore, an algorithm has been developed that enable online detection of abnormal conditions and malfunctions of an operating mill. Based on calculated diagnostic signals and defined thresholds, this algorithm informs about abnormal operating conditions. Diagnostic signals represent the difference between the measured and the modeled values of two selected mill operating parameters. Models of mill motor current and outlet temperature of pulverized fuel were developed based on the linear regression theory. Various data analysis and feature selection procedures have been performed to obtain the best possible model. The model based on linear regression has been compared with two alternative models. The algorithm validation was carried out based on historical data containing values of operating parameters from 10 months of mill operation. Historical data were downloaded from distributed control system (DCS) of a 200-MW coal-fired power plant. Tests carried out on historical data show that this algorithm can be successfully used to detect certain abnormal conditions and malfunctions of the operating mill, such as feeder blockage, lack of coal and mill overload.",book:{id:"6332",slug:"thermal-power-plants-new-trends-and-recent-developments",title:"Thermal Power Plants",fullTitle:"Thermal Power Plants - New Trends and Recent Developments"},signatures:"Teresa Kurek, Konrad Wojdan, Daniel Nabagło and Konrad Świrski",authors:[{id:"179942",title:"MSc.",name:"Daniel",middleName:null,surname:"Nabagło",slug:"daniel-nabaglo",fullName:"Daniel Nabagło"},{id:"212957",title:"Dr.",name:"Teresa",middleName:null,surname:"Kurek",slug:"teresa-kurek",fullName:"Teresa Kurek"},{id:"212961",title:"Dr.",name:"Konrad",middleName:null,surname:"Wojdan",slug:"konrad-wojdan",fullName:"Konrad Wojdan"},{id:"212962",title:"Prof.",name:"Konrad",middleName:null,surname:"Świrski",slug:"konrad-swirski",fullName:"Konrad Świrski"},{id:"212963",title:"MSc.",name:"Łukasz",middleName:null,surname:"Śladewski",slug:"lukasz-sladewski",fullName:"Łukasz Śladewski"}]},{id:"72177",title:"Nuclear Power Plant or Solar Power Plant",slug:"nuclear-power-plant-or-solar-power-plant",totalDownloads:635,totalCrossrefCites:2,totalDimensionsCites:2,abstract:"Both solar energy and nuclear energy face significant economic challenges. Sustainable energy costs have traditionally been greater than any of those associated with the growth of fossil fuel power generation, although the costs of renewable energy technologies (especially photovoltaic) have dropped. Furthermore, capital costs remain a big challenge in the nuclear generation. In many nations, the cost of building small nuclear power plants is quite large due to time, technology, and environmental and safety challenges for consumers. Such problems might not be as big for state-owned corporations or controlled industries for which utilities have quick access to cheap resources, and this partially explains why the interest for nuclear reactors in Asia is far greater than in the United States or Europe. 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Topics include, but are not limited to: Advanced techniques of cellular and molecular biology (Molecular methodologies, imaging techniques, and bioinformatics); Biological activities at the molecular level; Biological processes of cell functions, cell division, senescence, maintenance, and cell death; Biomolecules interactions; Cancer; Cell biology; Chemical biology; Computational biology; Cytochemistry; Developmental biology; Disease mechanisms and therapeutics; DNA, and RNA metabolism; Gene functions, genetics, and genomics; Genetics; Immunology; Medical microbiology; Molecular biology; Molecular genetics; Molecular processes of cell and organelle dynamics; Neuroscience; Protein biosynthesis, degradation, and functions; Regulation of molecular interactions in a cell; Signalling networks and system biology; Structural biology; Virology and microbiology.",annualVolume:11410,isOpenForSubmission:!0,coverUrl:"https://cdn.intechopen.com/series_topics/covers/14.jpg",editor:{id:"165627",title:"Dr.",name:"Rosa María",middleName:null,surname:"Martínez-Espinosa",fullName:"Rosa María Martínez-Espinosa",profilePictureURL:"https://mts.intechopen.com/storage/users/165627/images/system/165627.jpeg",institutionString:null,institution:{name:"University of Alicante",institutionURL:null,country:{name:"Spain"}}},editorTwo:null,editorThree:null,editorialBoard:[{id:"79367",title:"Dr.",name:"Ana Isabel",middleName:null,surname:"Flores",fullName:"Ana Isabel Flores",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bRpIOQA0/Profile_Picture_1632418099564",institutionString:null,institution:{name:"Hospital Universitario 12 De Octubre",institutionURL:null,country:{name:"Spain"}}},{id:"328234",title:"Ph.D.",name:"Christian",middleName:null,surname:"Palavecino",fullName:"Christian Palavecino",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0033Y000030DhEhQAK/Profile_Picture_1628835318625",institutionString:null,institution:{name:"Central University of Chile",institutionURL:null,country:{name:"Chile"}}},{id:"186585",title:"Dr.",name:"Francisco Javier",middleName:null,surname:"Martin-Romero",fullName:"Francisco Javier Martin-Romero",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bSB3HQAW/Profile_Picture_1631258137641",institutionString:null,institution:{name:"University of Extremadura",institutionURL:null,country:{name:"Spain"}}}]},{id:"15",title:"Chemical Biology",keywords:"Phenolic Compounds, Essential Oils, Modification of Biomolecules, Glycobiology, Combinatorial Chemistry, Therapeutic peptides, Enzyme Inhibitors",scope:"Chemical biology spans the fields of chemistry and biology involving the application of biological and chemical molecules and techniques. In recent years, the application of chemistry to biological molecules has gained significant interest in medicinal and pharmacological studies. This topic will be devoted to understanding the interplay between biomolecules and chemical compounds, their structure and function, and their potential applications in related fields. Being a part of the biochemistry discipline, the ideas and concepts that have emerged from Chemical Biology have affected other related areas. This topic will closely deal with all emerging trends in this discipline.",annualVolume:11411,isOpenForSubmission:!0,coverUrl:"https://cdn.intechopen.com/series_topics/covers/15.jpg",editor:{id:"441442",title:"Dr.",name:"Şükrü",middleName:null,surname:"Beydemir",fullName:"Şükrü Beydemir",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0033Y00003GsUoIQAV/Profile_Picture_1634557147521",institutionString:null,institution:{name:"Anadolu University",institutionURL:null,country:{name:"Turkey"}}},editorTwo:{id:"13652",title:"Prof.",name:"Deniz",middleName:null,surname:"Ekinci",fullName:"Deniz Ekinci",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002aYLT1QAO/Profile_Picture_1634557223079",institutionString:null,institution:{name:"Ondokuz Mayıs University",institutionURL:null,country:{name:"Turkey"}}},editorThree:null,editorialBoard:[{id:"241413",title:"Dr.",name:"Azhar",middleName:null,surname:"Rasul",fullName:"Azhar Rasul",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bRT1oQAG/Profile_Picture_1635251978933",institutionString:null,institution:{name:"Government College University, Faisalabad",institutionURL:null,country:{name:"Pakistan"}}},{id:"178316",title:"Ph.D.",name:"Sergey",middleName:null,surname:"Sedykh",fullName:"Sergey Sedykh",profilePictureURL:"https://mts.intechopen.com/storage/users/178316/images/system/178316.jfif",institutionString:null,institution:{name:"Novosibirsk State University",institutionURL:null,country:{name:"Russia"}}}]},{id:"17",title:"Metabolism",keywords:"Biomolecules Metabolism, Energy Metabolism, Metabolic Pathways, Key Metabolic Enzymes, Metabolic Adaptation",scope:"Metabolism is frequently defined in biochemistry textbooks as the overall process that allows living systems to acquire and use the free energy they need for their vital functions or the chemical processes that occur within a living organism to maintain life. Behind these definitions are hidden all the aspects of normal and pathological functioning of all processes that the topic ‘Metabolism’ will cover within the Biochemistry Series. Thus all studies on metabolism will be considered for publication.",annualVolume:11413,isOpenForSubmission:!0,coverUrl:"https://cdn.intechopen.com/series_topics/covers/17.jpg",editor:{id:"138626",title:"Dr.",name:"Yannis",middleName:null,surname:"Karamanos",fullName:"Yannis Karamanos",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002g6Jv2QAE/Profile_Picture_1629356660984",institutionString:null,institution:{name:"Artois University",institutionURL:null,country:{name:"France"}}},editorTwo:null,editorThree:null,editorialBoard:[{id:"243049",title:"Dr.",name:"Anca",middleName:null,surname:"Pantea Stoian",fullName:"Anca Pantea Stoian",profilePictureURL:"https://mts.intechopen.com/storage/users/243049/images/system/243049.jpg",institutionString:null,institution:{name:"Carol Davila University of Medicine and Pharmacy",institutionURL:null,country:{name:"Romania"}}},{id:"203824",title:"Dr.",name:"Attilio",middleName:null,surname:"Rigotti",fullName:"Attilio Rigotti",profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",institutionString:null,institution:{name:"Pontifical Catholic University of Chile",institutionURL:null,country:{name:"Chile"}}},{id:"300470",title:"Dr.",name:"Yanfei (Jacob)",middleName:null,surname:"Qi",fullName:"Yanfei (Jacob) Qi",profilePictureURL:"https://mts.intechopen.com/storage/users/300470/images/system/300470.jpg",institutionString:null,institution:{name:"Centenary Institute of Cancer Medicine and Cell Biology",institutionURL:null,country:{name:"Australia"}}}]},{id:"18",title:"Proteomics",keywords:"Mono- and Two-Dimensional Gel Electrophoresis (1-and 2-DE), Liquid Chromatography (LC), Mass Spectrometry/Tandem Mass Spectrometry (MS; MS/MS), Proteins",scope:"With the recognition that the human genome cannot provide answers to the etiology of a disorder, changes in the proteins expressed by a genome became a focus in research. Thus proteomics, an area of research that detects all protein forms expressed in an organism, including splice isoforms and post-translational modifications, is more suitable than genomics for a comprehensive understanding of the biochemical processes that govern life. The most common proteomics applications are currently in the clinical field for the identification, in a variety of biological matrices, of biomarkers for diagnosis and therapeutic intervention of disorders. From the comparison of proteomic profiles of control and disease or different physiological states, which may emerge, changes in protein expression can provide new insights into the roles played by some proteins in human pathologies. Understanding how proteins function and interact with each other is another goal of proteomics that makes this approach even more intriguing. Specialized technology and expertise are required to assess the proteome of any biological sample. Currently, proteomics relies mainly on mass spectrometry (MS) combined with electrophoretic (1 or 2-DE-MS) and/or chromatographic techniques (LC-MS/MS). MS is an excellent tool that has gained popularity in proteomics because of its ability to gather a complex body of information such as cataloging protein expression, identifying protein modification sites, and defining protein interactions. The Proteomics topic aims to attract contributions on all aspects of MS-based proteomics that, by pushing the boundaries of MS capabilities, may address biological problems that have not been resolved yet.",annualVolume:11414,isOpenForSubmission:!0,coverUrl:"https://cdn.intechopen.com/series_topics/covers/18.jpg",editor:{id:"200689",title:"Prof.",name:"Paolo",middleName:null,surname:"Iadarola",fullName:"Paolo Iadarola",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bSCl8QAG/Profile_Picture_1623568118342",institutionString:null,institution:{name:"University of Pavia",institutionURL:null,country:{name:"Italy"}}},editorTwo:{id:"201414",title:"Dr.",name:"Simona",middleName:null,surname:"Viglio",fullName:"Simona Viglio",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bRKDHQA4/Profile_Picture_1630402531487",institutionString:null,institution:{name:"University of Pavia",institutionURL:null,country:{name:"Italy"}}},editorThree:null,editorialBoard:[{id:"72288",title:"Dr.",name:"Arli Aditya",middleName:null,surname:"Parikesit",fullName:"Arli Aditya Parikesit",profilePictureURL:"https://mts.intechopen.com/storage/users/72288/images/system/72288.jpg",institutionString:null,institution:{name:"Indonesia International Institute for Life Sciences",institutionURL:null,country:{name:"Indonesia"}}},{id:"40928",title:"Dr.",name:"Cesar",middleName:null,surname:"Lopez-Camarillo",fullName:"Cesar Lopez-Camarillo",profilePictureURL:"https://mts.intechopen.com/storage/users/40928/images/3884_n.png",institutionString:null,institution:{name:"Universidad Autónoma de la Ciudad de México",institutionURL:null,country:{name:"Mexico"}}},{id:"81926",title:"Dr.",name:"Shymaa",middleName:null,surname:"Enany",fullName:"Shymaa Enany",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bRqB9QAK/Profile_Picture_1626163237970",institutionString:null,institution:{name:"Suez Canal University",institutionURL:null,country:{name:"Egypt"}}}]}]}},libraryRecommendation:{success:null,errors:{},institutions:[]},route:{name:"chapter.detail",path:"/chapters/78506",hash:"",query:{},params:{id:"78506"},fullPath:"/chapters/78506",meta:{},from:{name:null,path:"/",hash:"",query:{},params:{},fullPath:"/",meta:{}}}},function(){var e;(e=document.currentScript||document.scripts[document.scripts.length-1]).parentNode.removeChild(e)}()