Parameters for the plots of \n
\r\n\tDiagnosis and management of complications while on ECMO therapy and weaning to recovery or advanced therapies will be also discussed.
\r\n\r\n\tChapters focusing on specific patient populations, such as cardiogenic shock, thoracic organ transplantation, trauma, and neonates, Covid-19 syndrome, will provide insight into the particular challenges in dealing with the unusual problems of these very diverse groups.
\r\n\r\n\tThe goal of this book is to provide, thanks to the thorough contributions by known experts in the field, a framework for successful program development. Hopefully, this text will also inspire others to further advance this delicate field.
",isbn:"978-1-80356-549-1",printIsbn:"978-1-80356-548-4",pdfIsbn:"978-1-80356-550-7",doi:null,price:0,priceEur:0,priceUsd:0,slug:null,numberOfPages:0,isOpenForSubmission:!1,isSalesforceBook:!1,isNomenclature:!1,hash:"254c18981115aeda50bdf71829902141",bookSignature:"Dr. Antonio Loforte",publishedDate:null,coverURL:"https://cdn.intechopen.com/books/images_new/11718.jpg",keywords:"Heart Failure, Cardiogenic Shock, Respiratory Failure, Circulatory Failure, End-Organ Dysfunction, VA-ECMO, VV ECMO, Central ECMO, ECMO Running, Weaning off ECMO, Adverse Events While on ECMO, Survival on ECMO",numberOfDownloads:null,numberOfWosCitations:0,numberOfCrossrefCitations:null,numberOfDimensionsCitations:null,numberOfTotalCitations:null,isAvailableForWebshopOrdering:!0,dateEndFirstStepPublish:"March 10th 2022",dateEndSecondStepPublish:"April 7th 2022",dateEndThirdStepPublish:"June 6th 2022",dateEndFourthStepPublish:"August 25th 2022",dateEndFifthStepPublish:"October 24th 2022",dateConfirmationOfParticipation:null,remainingDaysToSecondStep:"3 months",secondStepPassed:!0,areRegistrationsClosed:!0,currentStepOfPublishingProcess:4,editedByType:null,kuFlag:!1,biosketch:"Dr. Loforte is a dedicated and pioneering researcher in the surgical treatment of advanced heart failure in terms of LVAD, BVAD, ECLS, and TAH adoption in different clinical scenarios. He is a member of several professional organizations including the prestigious STS, ISHLT, ASAIO, EACTS, RHICS, SICCH, SITO, ELSO, and ESOT among others. His bibliography lists over 150 peer-reviewed original articles, 250 abstracts (communications) for international meetings, 20 book chapters, and 8 manuals.",coeditorOneBiosketch:null,coeditorTwoBiosketch:null,coeditorThreeBiosketch:null,coeditorFourBiosketch:null,coeditorFiveBiosketch:null,editors:[{id:"42172",title:"Dr.",name:"Antonio",middleName:null,surname:"Loforte",slug:"antonio-loforte",fullName:"Antonio Loforte",profilePictureURL:"https://mts.intechopen.com/storage/users/42172/images/system/42172.jpg",biography:"Dr. Loforte is currently staff surgeon and chair of the Mechanical Circulatory Support (MCS) program at the Department of Cardiothoracic, Transplantation and Vascular Surgery, S. Orsola Hospital, ALMA Mater Studiorum University of Bologna, IRCCS Bologna, Italy. He completed his cardiothoracic surgery recidency at the University of Bologna, S. Orsola Hospital (Italy), at St. Antonius Ziekenhuis, Nieuwegein (the Netherlands) and the Deutsches Herzzentrum Berlin (Germany). He additionally joined the Michael E. DeBakey Department of Surgery, Division of Transplant and Assist Devices, in Houston, Texas, USA.\nDr. Loforte is a member of several professional organizations including the prestigious STS, ISHLT, ASAIO, EACTS, RHICS, SICCH, SITO, ELSO, ESOT among others. His bibliography lists over 150 peer-reviewed original articles, 250 abstracts (communications) for international meetings, 20 book chapters, and 8 manuals. He serves as a reviewer for 25 international journals and is part of the editorial board in 10 of them. He received a ‘European Ph.D. label’ in Organ Transplantation and ten international awards in Europe and USA.",institutionString:"Division of Cardiac Surgery, S. Orsola University Hospital, IRCCS Bologna",position:null,outsideEditionCount:0,totalCites:0,totalAuthoredChapters:"2",totalChapterViews:"0",totalEditedBooks:"1",institution:null}],coeditorOne:null,coeditorTwo:null,coeditorThree:null,coeditorFour:null,coeditorFive:null,topics:[{id:"16",title:"Medicine",slug:"medicine"}],chapters:null,productType:{id:"1",title:"Edited Volume",chapterContentType:"chapter",authoredCaption:"Edited by"},personalPublishingAssistant:{id:"444318",firstName:"Nika",lastName:"Karamatic",middleName:null,title:"Ms.",imageUrl:"https://mts.intechopen.com/storage/users/444318/images/20011_n.jpg",email:"nika@intechopen.com",biography:"As an Author Service Manager, my responsibilities include monitoring and facilitating all publishing activities for authors and editors. From chapter submission and review to approval and revision, copyediting and design, until final publication, I work closely with authors and editors to ensure a simple and easy publishing process. I maintain constant and effective communication with authors, editors and reviewers, which allows for a level of personal support that enables contributors to fully commit and concentrate on the chapters they are writing, editing, or reviewing. I assist authors in the preparation of their full chapter submissions and track important deadlines and ensure they are met. I help to coordinate internal processes such as linguistic review, and monitor the technical aspects of the process. As an ASM I am also involved in the acquisition of editors. Whether that be identifying an exceptional author and proposing an editorship collaboration, or contacting researchers who would like the opportunity to work with IntechOpen, I establish and help manage author and editor acquisition and contact."}},relatedBooks:[{type:"book",id:"6558",title:"Heart Transplantation",subtitle:null,isOpenForSubmission:!1,hash:"fa6adc2ed66fd8de1500ed382fd80f7a",slug:"heart-transplantation",bookSignature:"Antonio Loforte, Andrea Montalto and Cristiano Amarelli",coverURL:"https://cdn.intechopen.com/books/images_new/6558.jpg",editedByType:"Edited by",editors:[{id:"42172",title:"Dr.",name:"Antonio",surname:"Loforte",slug:"antonio-loforte",fullName:"Antonio Loforte"}],productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}},{type:"book",id:"6550",title:"Cohort Studies in Health Sciences",subtitle:null,isOpenForSubmission:!1,hash:"01df5aba4fff1a84b37a2fdafa809660",slug:"cohort-studies-in-health-sciences",bookSignature:"R. 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Venkateswarlu",coverURL:"https://cdn.intechopen.com/books/images_new/371.jpg",editedByType:"Edited by",editors:[{id:"58592",title:"Dr.",name:"Arun",surname:"Shanker",slug:"arun-shanker",fullName:"Arun Shanker"}],productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}},{type:"book",id:"72",title:"Ionic Liquids",subtitle:"Theory, Properties, New Approaches",isOpenForSubmission:!1,hash:"d94ffa3cfa10505e3b1d676d46fcd3f5",slug:"ionic-liquids-theory-properties-new-approaches",bookSignature:"Alexander Kokorin",coverURL:"https://cdn.intechopen.com/books/images_new/72.jpg",editedByType:"Edited by",editors:[{id:"19816",title:"Prof.",name:"Alexander",surname:"Kokorin",slug:"alexander-kokorin",fullName:"Alexander Kokorin"}],productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}},{type:"book",id:"314",title:"Regenerative Medicine and Tissue Engineering",subtitle:"Cells and Biomaterials",isOpenForSubmission:!1,hash:"bb67e80e480c86bb8315458012d65686",slug:"regenerative-medicine-and-tissue-engineering-cells-and-biomaterials",bookSignature:"Daniel Eberli",coverURL:"https://cdn.intechopen.com/books/images_new/314.jpg",editedByType:"Edited by",editors:[{id:"6495",title:"Dr.",name:"Daniel",surname:"Eberli",slug:"daniel-eberli",fullName:"Daniel Eberli"}],productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}},{type:"book",id:"57",title:"Physics and Applications of Graphene",subtitle:"Experiments",isOpenForSubmission:!1,hash:"0e6622a71cf4f02f45bfdd5691e1189a",slug:"physics-and-applications-of-graphene-experiments",bookSignature:"Sergey Mikhailov",coverURL:"https://cdn.intechopen.com/books/images_new/57.jpg",editedByType:"Edited by",editors:[{id:"16042",title:"Dr.",name:"Sergey",surname:"Mikhailov",slug:"sergey-mikhailov",fullName:"Sergey Mikhailov"}],productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}}]},chapter:{item:{type:"chapter",id:"54781",title:"Fractal to Non-Fractal Morphological Transitions in Stochastic Growth Processes",doi:"10.5772/67941",slug:"fractal-to-non-fractal-morphological-transitions-in-stochastic-growth-processes",body:'\nIn nature, fractal structures emerge in a wide variety of systexms as a local optimization of diverse growth processes restricted to the entropic and energetic inputs from the environment. Even more, the fractality of these systems determines many of their physical, chemical, and/or biological properties. Thus, to comprehend the mechanisms that originate and control the fractality is highly relevant in many areas of science and technology [1–3].
\nOne of the most successful approaches to this problem employs stochastic growth processes of particle aggregation. In general, aggregation phenomena are out-of-equilibrium processes of fractal pattern formation that are ubiquitous in nature [4]. As such, since the introduction of the diffusion-limited aggregation (DLA) and ballistic aggregation (BA) models, a plethora of studies has been developed trying to understand the ultimate aspects of the aggregation dynamics that give rise to
In particular, one striking feature of these systems is the morphological transition that they undergo as a result of the interplay of the entropic and energetic aspects of their growth dynamics that ultimately manifest themselves in the geometry of their structure [5]. It is here, where despite of their complexity, great insight can be obtained into the fundamental elements of their dynamics from the powerful concepts of fractal geometry [6, 7].
\nOne example of this is the well-known dielectric breakdown model (DBM) or generalized Laplacian growth model, which has importantly contributed to our understanding of far-from-equilibrium growth phenomena, to such extent that seemingly unrelated patterns found in nature, as river networks or bacterial colonies, are understood in terms of a single framework of complex growth [8, 9]. However, we are still in need for a complete scaling theory of growth for systems far-from-equilibrium, as well as a comprehensive description of the fractality of systems that exhibits fractal to nonfractal morphological transitions [10].
\nIn this chapter, starting from the mean-field result for the fractal dimension of Laplacian growth, we present a theoretical framework for the study of these transitions. Using a statistical approach to fundamental particle-cluster aggregation dynamics, under which it is possible to create four nontrivial fractal to nonfractal transitions that will capture all the main features of fractal growth, we show that, regardless of their space symmetry-breaking mechanism, they are well described by a universal dimensionality function, including the Laplacian one.
\nIn order to show this, we consider the following: first, we introduce a general dimensionality function that is able to describe the measured fractal dimensions and scaling of clusters generated form particle aggregation. Second, we apply this equation to a set of fractal to nonfractal morphological transitions, created by identifying the fundamental dynamics that drive the fractal growth in particle aggregation and by combining three fundamental
In the Laplacian theory of growth, the growth probability at a given point in space, \n
Schematic diagram of the fundamental aggregation models (top row) used in this work, where particles, that are launched one-by-one into the system from
For \n
Here, for \n
However, one of the most challenging aspect of the theory comes when the growth is not purely limited by diffusion, e.g., when it takes place under the presence of long-range attractive interactions, where strong screening and anisotropic effects must be considered [1, 5, 7]. In this case, a clever generalization to the Laplacian growth process was proposed within the context of the DBM, assuming \n
provides a good approximation to the dimensions of this transition but due to its mean-field limitations, it does not have a good correspondence with the numerical results [25, 26]. Nonetheless, as shown here, Eq. (3) is the starting point to clarify this aspect of the theory and, even, to establish a suitable and general framework to analyze more complex morphological transitions in stochastic growth processes.
\nThis is done by considering that the fundamental dynamical elements of aggregation, which drive the fractal growth, are mainly two: a stochastic one, coming from the particles’ trajectories randomness, and an energetic one, coming from attractive interactions. With regard to the latter, there are two physical mechanisms related to these interactions and two models that are able to reproduce their effects. First, the model we will refer to as \n
Schematic diagrams of the
In the following and as explained below, all data for \n
In all of the numerical calculations, we choose as a unit of distance, the particles’ diameter here is set to one. For generating aggregates based on BA or MF (Figure 1a and 1c), a standard procedure was used in which particles are launched at random, with equal probability in position and direction of motion, from a circumference of radius \n
Regarding the \n
In all measurements, we performed an ensemble average over \n
where the double bracket indicates an average over all possible origins \n
where \n
In particular, for the \n
(a) Multiscaling aggregates based on DLA, containing
(a) Multiscaling aggregates based on BA, containing
In (a) and (b), aggregates grown with specific values of
Clusters of
Despite the complexity leading to morphological transitions, simple models can be established to describe their fractality or scaling as a function of the control parameter, in our case, the branching parameter \n
with \n
In this form, by setting \n
where \n
with \n
Furthermore, let us introduce the reduced parameter, \n
where
is an effective parameter associated to a generalized screening/anisotropy-driven force. Its first-order approximation is then,
where the effective parameter is now given as,
With this prescription, the dynamical change in growth regime is now located at \n
In the first approach to morphological transitions, we will consider the case when long-range attractive interactions are introduced in the growth dynamics. In this case, the way to obtain self-similar clusters, that is, clusters with a single fractal dimension, is to maintain a proper balance between the energetic and entropic contributions to the growth process. This can be done by considering an aggregation radius, \n
For example, for \n
It can be appreciated that this growth presents three well-defined stages as illustrated in Figures 3d and 4d. In the first one, the growth is limited by the interactions and is characterized by \n
However, taking into account that the spatial size of the clusters is proportional to the radius of gyration \n
Additionally, this model allows one to estimate \n
In the second approach, a general stochastic aggregation process can be model under a Monte Carlo scheme involving three fundamental and simple
It is necessary to remark that the DLA-MF and BA-MF transitions in the \n
Model | \nTransition | \nMethod | \nScale | \nΛ | \n|||
---|---|---|---|---|---|---|---|
DLA-MF | \n\n\n | \n15.4 | \n2.24 | \n1.67 | \n0.29 | \n||
\n | \n\n | \n\n | \n\n\n | \n71.5 | \n1.82 | \n\n | \n0.08 | \n
\n | \n\n | \n\n\n | \n33.8 | \n1.41 | \n1.71 | \n0.03 | \n|
\n | \n\n | \n\n | \n\n\n | \n101.6 | \n1.32 | \n\n | \n0.01 | \n
\n | \nBA-MF | \n\n\n | \n11.6 | \n1.61 | \n1.94 | \n0.18 | \n|
\n | \n\n | \n\n | \n\n\n | \n45.4 | \n1.38 | \n\n | \n0.04 | \n
\n | \n\n | \n\n\n | \n124.8 | \n1.95 | \n1.95 | \n0.06 | \n|
\n | \n\n | \n\n | \n\n\n | \n1547.7 | \n2.05 | \n\n | \n0.02 | \n
\n\n | \nDLA-MF | \n103 to 105 | \n6.10 | \n1.52 | \n1.70 | \n0.21 | \n|
\n | \nBA-MF | \n103 to 105 | \n6.35 | \n1.43 | \n1.95 | \n0.19 | \n|
DLA-MF | \n– | \n– | \n1.69 | \n1.67 | \n1.0 | \n||
\n | \n\n | \n– | \n– | \n1.34 | \n1.71 | \n1.0 | \n|
\n | \nBA-MF | \n– | \n– | \n1.39 | \n1.94 | \n1.0 | \n|
\n | \n\n | \n– | \n– | \n1.88 | \n1.95 | \n1.0 | \n|
\n\n | \nDLA-MF | \n– | \n– | \n1.52 | \n1.70 | \n1.0 | \n|
\n | \nBA-MF | \n– | \n– | \n1.43 | \n1.95 | \n1.0 | \n
Parameters for the plots of \n
In the first block, we present the parameter values used to describe \n
Scaling analysis for the
Model | \nData | \n\n\n | \n\n\n | \n|||||
---|---|---|---|---|---|---|---|---|
BA-MF (\n | \n1.94 | \n1.39 | \n2.3 | \n4.5 | \n3.0 | \n5.4 | \n1.72 | \n|
\n | \nDLA-MF (\n | \n1.67 | \n1.69 | \n2.3 | \n2.8 | \n3.0 | \n3.2 | \n1.46 | \n
\n | \nBA-MF (\n | \n1.95 | \n1.88 | \n9.0 | \n6.0 | \n19.0 | \n9.0 | \n1.73 | \n
\n | \nDLA-MF (\n | \n1.71 | \n1.34 | \n9.0 | \n21.7 | \n19.0 | \n37.8 | \n1.62 | \n
\n\n | \nBA-MF | \n1.95 | \n1.43 | \n2.3 | \n4.2 | \n3.0 | \n5.0 | \n1.70 | \n
\n | \nDLA-MF | \n1.71 | \n1.52 | \n2.3 | \n3.5 | \n3.0 | \n4.2 | \n1.50 | \n
Transitional points for which the reduced co-dimension \n
The labels \n
By observing the description of the transitions based on the function \n
A final important implication of the previous findings is that the DBM and BA-MF transitions (for both \n
where the effective parameter \n
(a) Snapshots of typical clusters present in fractal to nonfractal morphological transitions obtained from the
It has been stated above that the entropic and energetic elements are the two aspects of the complex aggregation dynamics which in nature are strongly correlated. Nonetheless, this reductionist approach that essentially encapsulates the information of all the finer details of the dynamics into an effective interaction (in the \n
Additionally, the descriptive framework for the scaling of fractal to nonfractal morphological transitions in stochastic growth processes, which includes the concept of an effective screening/anisotropy force and reduced codimensionality transformations, has revealed that the DLA-MF, BA-MF, and DBM transitions exhibit a well-defined universal scaling \n
The results and models discussed in this chapter represent an important unifying step toward a complete scaling theory of fractal growth and far-from-equilibrium pattern formation. Additionally, the possibility of applying the dimensionality function to discuss complex structures in other research areas, ranging from biology [4, 1], intelligent materials engineering [31, 32] to medicine [33], seems to be in some cases straightforward.
\nThe authors gratefully acknowledge the computing time granted on the supercomputers MIZTLI (DGTIC-UNAM) and THUBAT-KAAL (CNS-IPICyT) and on XIUHCOATL (CINVESTAV) through M.A. Rodriguez (ININ, Mexico). We acknowledge the partial financial support by CONACyT and VIEP-BUAP through the grants: 257352, DIRV-EXC16-I, and CAEJ-EXC16-G.
\nCardiorespiratory fitness presents individuals’ ability to transport oxygen from the atmosphere to the mitochondria to perform physical work and therefore reflects the overall capacity of the cardiovascular and respiratory systems to perform prolonged exercise [1]. Cardiovascular fitness is therefore reflected in the ability of physical activity, which is critical in childhood as it lays the foundations for later physical activity – the base on which children can build more specific motor skills or develop movement patterns [2].
Epidemiologically, physical activity has been decreasing in the last decades [2], even more before the year of 2000, after which the trend stabilised with negligible changes [3] apart from COVID-19 epidemics, where cardiorespiratory fitness declined significantly [4, 5]. The decline in the last decades was more pronounced in children over the school-age years. Boys were usually more fit than girls [6]. Cardiorespiratory fitness was found to be higher in socially advantaged children [7].
Lower cardiorespiratory fitness is associated with low physical activity and increased fat mass. Increasing obesity in children is therefore strongly inversely associated with cardiorespiratory fitness and indicates reduced physical activity in the paediatric population in recent decades. Interestingly, fitness scores also decreased among lean children [8]. Association between low cardiorespiratory fitness and metabolic risk factors might therefore be only partially mediated through obesity [9]. Sedentary time also negatively affects cardiorespiratory fitness [10], which is independently linked to poor metabolic health [10]. Physical activity and sedentary time are clearly interrelated but a reciprocal relationship between them cannot be assumed [11]. Physical activity and training undoubtedly improve cardiovascular fitness with high-intensity interval training being more successful in enhancing cardiovascular fitness compared to moderate-intensity continuous training [12].
Cardiorespiratory fitness has been also associated with inflammatory biomarkers in children with a positive association with body fat. Similarly, the association between lifestyle behaviours, such as diet, physical activity and sedentary behaviour, and inflammation were found in the paediatric population [13].
Improved cardiorespiratory fitness was associated with the reduced inflammatory profile, independently of body composition and lifestyle behaviours [13]. Cardiorespiratory fitness and sports-related physical activity were also inversely associated with arterial stiffness in young adults [14].
Low cardiorespiratory fitness is strongly associated with the clustering of cardiovascular risk factors in children [15]. Evaluation and improvement of cardiorespiratory fitness in children with cardiovascular risk factors might be associated with improved health parameters in later life [1]. In this review, we present methods on how to evaluate cardiovascular fitness in children along with available data on cardiovascular fitness in children with some traditional and novel cardiovascular risk factors. Some specific strategies to improve cardiovascular fitness in children are also added.
Cardiorespiratory fitness was clearly associated with body mass index, fat mass, and metabolic syndrome development, however, other cardiovascular risk factors are not always convincing in the literature. Partly, this might be the result of the different evaluation of cardiovascular fitness in different studies [16]. The barriers to cardiovascular fitness assessment include the lack of standardisation in the test protocols, the health outcome being evaluated as well as the absence of evidence-based clinical cut points at these ages [17].
The most widely used indicator of cardiorespiratory fitness is the volume of oxygen that is consumed at maximal physical exertion (VO2max), measured from the respiratory gas exchange by indirect calorimetry [18]. It can be objectively and accurately measured through laboratory tests such as progressive run or cycle, however, these protocols require sophisticated equipment (run/cycle ergometer tests with respiratory gas analysis), the availability of trained technicians, making these tests expensive and time-consuming. Alternatively, field tests are more appropriate for universal screening and include a 550-m timed run/walk or “Maximal Multistage 20-m Shuttle Run Test” [18]. The latter was identified as the most scalable and reliable field test, where VO2max can be predicted by special equations [19, 20]. For a field test to be valid it is required to accurately and reliably measure what it claims to measure, however, field-based tests usually suffer from low relative validity when compared to VO2max measurement and are producing conflicting results [18, 21]. Other similar screening tests are being developed, such as the 3-minute Kasch Pulse Recovery Test, where a reference range for the classification of cardiorespiratory fitness was developed on the basis of the age-specific percentile distribution of heart rate after exercise in 6- to 9- and 10- to 12-year-old children. The value of heart rate after exercise is considered an indicator of cardiorespiratory fitness [22].
Another obstacle in the cardiorespiratory fitness evaluation is the lack of age-specific cut-off points for increased cardiovascular risk. They were attempted to be set by a systematic review in children aged 8–19 years that determined that fitness levels below 42 and 35 mL/kg/min (VO2max measurement) for boys and girls, respectively, should raise a red flag. These cut-points identify children and adolescents who may benefit from primary and secondary cardiovascular prevention programming [17]. Similarly, a study using a 20-m Shuttle Run Test with VO2max prediction by estimation revealed cut-off points in 8- to 12-year-olds for obesity identified as 39 mL/kg/min and 41 mL/kg/min for girls and boys, respectively [23].
Recommendations for future research must include standardised measurements with standardised outcome assessments of cardiorespiratory fitness. For universal screening, a field test approach might be more appropriate, however, in children with cardiovascular risk, or suboptimal results in the field test, a more accurate approach might be more appropriate with cut-off points determined for gender and age.
Children with obesity have lower cardiorespiratory fitness than normal-weight children [24], which is more pronounced in girls [25] and is commonly associated with reduced physical activity [26]. Body mass index also mediates the association between cardiorespiratory fitness and metabolic syndrome in schoolchildren. Higher levels of cardiorespiratory fitness are associated with lower cardiometabolic risk, particularly, when accompanied by weight reduction [27]. Lower cardiorespiratory fitness in children with obesity was associated with overall and abdominal fat mass, whereas both central and total obesity were lower in overweight and obese children with high cardiorespiratory fitness [28, 29, 30]. There is extensive evidence to support the fat-but-fit paradigm, which shows that cardiorespiratory fitness can counteract the adverse effects of obesity on cardiovascular risk factors. Unfit children with obesity had exaggerated systolic blood pressure at rest and during sympathetic activation, presumably coupled with higher cardiac output and cardiac oxygen demand [31]. Even from the molecular point of view, fit children with obesity or overweight had a distinct pattern of whole-blood gene expression [32]. Concerning the autonomic nervous system’s role, greater parasympathetic cardiac activity was associated with higher levels of cardiorespiratory fitness in both girls and boys, while the sympathetic-vagal balance was negatively related to maximal oxygen uptake in girls [33].
Additionally, in obesity, low-grade chronic inflammation and homeostatic stress produced mainly in adipocytes can result in abnormal adipokine secretion, which could be involved in the pathogenesis of lowered cardiorespiratory fitness. The secretion of adipokines is also influenced by physical fitness. It has been demonstrated that in children with obesity, VO2max can be predicted from haematological parameters, such as leptin and fibrinogen [34].
Obesity-related hypertension is a problem on the rise with obesity epidemics. Cardiorespiratory fitness was associated with total and central obesity as well as hypertension [35, 36]. Systolic and diastolic blood pressure showed curvilinear relation with cardiorespiratory fitness along with waist circumference and the sum of skinfolds [37]. However, regardless of obesity, cardiorespiratory fitness in children has been associated with other metabolic risk factors and future health. Teenagers with low cardiorespiratory fitness were more likely to develop hypertension in adulthood, even among participants with a normal body mass index [24]. Children who are fit and participate regularly in sports outside school hours are less likely to be hypertensive [38]. Long-term low levels of cardiorespiratory fitness exhibited the highest levels of systolic blood pressure [39]. The combination of a family history of hypertension and cardiorespiratory fitness also showed a clear association with the increased risk of hypertension [40]. Interestingly, some studies set a different perspective on cardiorespiratory fitness and hypertension, somehow contradicting the above-mentioned associations. In one of them, physical activity was not associated with systolic blood pressure independently of adiposity, but there was a small independent association only with diastolic blood pressure [41]. Another study demonstrated that adolescents with overweight or obesity have a higher prevalence of higher blood pressure, regardless of cardiorespiratory fitness, suggesting that maintaining a normal body mass index protects against less favourable blood pressure [42]. Anyway, a study published two decades ago demonstrated that the level of cardiorespiratory fitness did not seem to be an important correlate of blood pressure variation across age groups and gender in schoolchildren [43].
Abnormal lipid profile is commonly known as a cardiovascular risk factor, sometimes associated with obesity, but in children, it can be the consequence of genetic defect leading to familial hypercholesterolemia also in lean children [44]. However, specific studies regarding familial hypercholesterolemia and cardiorespiratory fitness are lacking in the paediatric population. Overall, evidence supports an inverse association between cardiorespiratory fitness and dyslipidaemia with expected improvements in high-density lipoprotein cholesterol with exercise, which is the most consistent finding. The findings regarding the effects of exercise training on other lipid components have been variable, with both positive and null results, but in general demonstrate a reduction of total cholesterol and triglycerides with exercise training [45, 46]. Future studies in the paediatric population are needed to clarify the association between cardiorespiratory fitness change and dyslipidaemia [45].
Lower cardiorespiratory fitness, strength, and higher central adiposity were also highly predictive of higher levels of insulin resistance in children and adolescents without diabetes mellitus [47], however, at least in part, are mediated through obesity [48]. Nevertheless, increased muscle strength and cardiorespiratory fitness were associated with decreased insulin resistance and improved 𝛽-cell function among young in population studies [49, 50]. Cardiorespiratory fitness and muscular fitness in children are not only important in childhood but it was proven that they were inversely associated with measures of fasting insulin, insulin resistance, and 𝛽-cell function in adulthood [51].
In children with already developed diabetes mellitus, cardiorespiratory fitness might play an even more pivotal role. Independently of obesity, there was a significant inverse relationship between cardiorespiratory fitness and lipid profile components and systolic blood pressure in children with poorly controlled type 1 diabetes mellitus, indicating a favourable effect of increased cardiorespiratory fitness [52]. Additionally, youth with diabetes mellitus type 1 who are physically active, tend to have lower glycated haemoglobin and reduced insulin needs. Also, activity in adolescents at-risk for diabetes mellitus type 2 improves various measures of metabolism and body composition [53]. In children with diabetes mellitus type 2, lower levels of cardiorespiratory fitness were observed mostly due to physical inactivity [54]. People with diabetes mellitus type 2 have reduced cardiorespiratory fitness compared to healthy controls, with an association to increased cardiovascular morbidity and mortality. The mechanisms of lower cardiorespiratory fitness in children with diabetes mellitus type 2 are multifaceted and involve interrelated defects in insulin action, mitochondrial dysfunction, skeletal muscle microvasculature, and cardiac dysfunction [55]. In youth with diabetes mellitus type 2, left ventricular size is clearly related to physical fitness, which might counteract adverse effects of poor glycaemic control and, at least according to the study, right ventricular function [56]. Regular physical activity is an important component in the management of both diabetes mellitus type 1 and type 2, as it has the potential to improve glycaemic control, delay cardiovascular complications, and increase overall well-being [57].
Children with chronic kidney disease have lower cardiorespiratory fitness due to various reasons, one of the most important is reduced physical activity and increased sedentary lifestyle mainly due to the renal replacement therapy requirements (e.g. haemodialysis) [58]. Additionally, chronic kidney disease is associated with anaemia, effects of chronic uraemia, and metabolic acidosis on the heart and skeletal muscle, all contributing significantly to reduce physical activity [59]. Paediatric patients with chronic kidney disease are therefore significantly physically inactive, with less than 10% of the non-school time being physically active [60]. Additionally, children after kidney transplantation significantly gained fat weight [60, 61]. One of the reasons after transplantation might also be related to sirolimus effects on skeletal muscle [61]. Reduced cardiorespiratory fitness was strongly associated with the clustering of cardiovascular risk factors in these children [62].
Studies suggest that regular and early implementation of both aerobic and resistance exercise programs in persons with chronic kidney disease have positive effects on muscle function, exercise tolerance, and quality of life [59]. In children with a successful renal transplant, a weekly physical exercise of 3−5 hours significantly improved cardiorespiratory fitness and left ventricular mass [63].
In children with a congenital single kidney, physical activity improved aerobic capacity and exercise tolerance without increasing the risks of cardiovascular accidents [64], however, in the patients contact sports might be discouraged due to the increased risk of sport-related injury.
Children and also later adults, born prematurely, are likely to have poorer cardiorespiratory fitness, however, according to some studies, the poor cardiorespiratory outcome of a child born prematurely is not firmly established [65, 66]. In adults, exercise capacity was only modestly reduced and frequently with values within a normal range and was consistent with self-reported exercise capacity [67]. In addition, in children with abnormal lung function and structure, this did not impact the aerobic exercise capacity of preterm children at school age [68]. On the contrary, Welsh et al. demonstrated a significant reduction in peak oxygen consumption among prematurely born children but with no difference in physical activity [69]. Some subgroups of premature-born individuals might be at increased risk for reduced cardiorespiratory fitness, especially those with lower muscular fitness, which was more common among premature-born young adults [70]. Lowered muscle strength is associated also with neuromotor sequelae of premature birth [71]. Another risk factor for reduced exercise capacity is also a decreased ventricular size and mass that might be a consequence of prematurity [72]. Impaired heart rate recovery after maximal exercise might also play a role in poor cardiorespiratory fitness in some suggesting an impaired development of autonomic nervous function after preterm labour [73].
Babies, born prematurely, are a diverse group of patients with complications that depend on several factors, such as gestational age, associated comorbidities, prenatal factors, postnatal care, etc. Therefore, the studies are diverse and might contradict each other because the effect of premature birth depends on so many other factors. Anyway, children born prematurely do have a risk for lowered cardiorespiratory fitness and regular physical intervention is believed to produce better outcomes [65, 71].
Congenital heart disease may in a variety of ways adversely affect hemodynamic responses, usually produced during exercises, such as increased heart rate, preload, and heart contractility with decreased systemic vascular resistance and pulmonary vascular resistance [74]. Therefore, the consequences of cardiorespiratory fitness depend on the congenital defect itself and a proper evaluation is of pivotal importance to evaluate cardiac rehabilitation. Historically, children with congenital heart disease have been restricted from exercise, contributing to a sedentary lifestyle as well as increased cardiovascular risk factors. Given the large benefits and small risks of exercise in this population, guidelines have recently shifted towards exercise promotion [75]. In children, several tests to evaluate cardiorespiratory fitness might be used [74], however, the 6-minute walk test is quite common and was found to be a useful and reliable tool in the assessment and follow-up of functional capacity during rehabilitation programs [76]. Furthermore, exercise training is safe and beneficial for the vast majority of adults with congenital heart disease following appropriate screening [77, 78].
Exercise recommendations should be individualised based on functional parameters using a structured methodology to approach the evaluation, risk classification, and prescriptions of exercise and physical activity [75]. Participation in aerobic exercise significantly increased the quality of life in children with congenital heart disease [79].
Sleeping quality was also associated with cardiorespiratory fitness, not necessarily in children with high body mass index, as might be expected. Girls who were classified as fit were more likely to report better sleep quality compared to their unfit peers. Poor sleep quality was associated with lower cardiorespiratory fitness with no significant association with body mass index [80].
Not only obesity reduction, but improved cardiorespiratory fitness also positively affects psychosocial well-being, leading to improved self-esteem and reduced stress, further reducing cardiovascular risk. Cognitive function and cardiorespiratory fitness correlate significantly and are predictors of psychological well-being among school-aged children. In addition, students with a higher level of psychological well-being showed a higher cardiorespiratory fitness, concentration performance, and attention accuracy [81]. Cardiorespiratory fitness also had a small protective effect against developing depression [82]. Similarly, it was found that stress and depression can affect an individual’s level of physical activity and fitness, which may place them at risk of developing cardiovascular disease, confirming the role of increased physical activity in improving depression and reducing depression-related stress to improve cardiovascular risk [83].
Addressing cardiovascular fitness in children and adolescents could reduce future adiposity, improve other cardiovascular risk factors and thus be an important factor in improving health [16]. The main strategies for reducing cardiovascular risk and obesity remain physical exercise with a reduced sedentary lifestyle and an appropriate diet. Promoting health-related cardiorespiratory fitness in physical education proved to be an important contributor to improving cardiorespiratory fitness in children. Intensity, age, and weight status importantly affect cardiorespiratory fitness [84]. In children with obesity, regular exercise is even more important, and may not need to be vigorous; recreational programs are also effective and may encourage children to participate in physical activity and limit initial dropout. Three-month training programs in children with obesity led to decreased body mass index, waist circumference, decreased fat mass, blood glucose, homeostasis model assessment for insulin resistance, triglycerides, and systolic pressure before and after exercise [85].
A healthier diet in preschool and schoolchildren also led to lower adiposity levels, lower waist circumference, and increased cardiorespiratory fitness, making it a relevant modifiable factor in obesity management [86, 87].
The management of the whole family is of utmost importance because a parent\'s effect can have a significant impact on children\'s willingness and motivation to change their lifestyle [88]. Breastfeeding has also been positively associated with cardiorespiratory fitness, where breastfeeding for more than 6 months proved to have positive effects on cardiorespiratory fitness. Therefore, early nutrition may be a predictor for adolescence physical health and is of special importance to promoting healthier lifestyle in children as it is associated with higher cardiorespiratory fitness [89].
Intervention strategies aiming to reduce obesity and improve cardiorespiratory fitness in childhood might contribute to the prevention of metabolic syndrome in adulthood [90]. The process is schematically presented in Figure 1.
From regular physical activity and diet to decreased morbidity and mortality due to the cardiovascular diseases.
Cardiorespiratory fitness is declining in the paediatric population and is closely associated with increased cardiovascular risk. In children already having a cardiovascular risk factor present, it is important to determine cardiorespiratory fitness and if it is decreased, prompt physical intervention is warranted. Further research is needed to establish a standardised protocol of its measurement. Interventions include increased and customized physical activity along with a healthy diet. In children, breastfeeding could present an additional preventive factor.
The authors declare no conflict of interest.
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He is also Member of the Laboratory of genetic, animal and feed resource and member of Animal science Department of INAT. He graduated from Higher School of Agriculture of Mateur, University of Carthage, in 2002 and completed his masters in 2006. Dr. M’HAMDI completed his PhD thesis in Genetic welfare indicators of dairy cattle at Higher Institute of Agronomy of Chott-Meriem, University of Sousse, in 2011. 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Ms. Mehtab has published seven papers in international conferences and one of her papers has been accepted for publication in a reputable international journal. She has won the best paper awards in two prestigious international conferences – BAICONF 2019, and ICADCML 2021, organized in the Indian Institute of Management, Bangalore, India in December 2019, and SOA University, Bhubaneswar, India in January 2021. Besides, Ms. Mehtab has also published two book chapters in two books. Seven of her book chapters will be published in a volume shortly in 2021 by Cambridge Scholars’ Press, UK. Currently, she is working as the joint editor of two edited volumes on Time Series Analysis and Forecasting to be published in the first half of 2021 by an international house. Currently, she is working as a Data Scientist with an MNC in Delhi, India.",institutionString:"NSHM College of Management and Technology",institution:null},{id:"226240",title:"Dr.",name:"Andri Irfan",middleName:null,surname:"Rifai",slug:"andri-irfan-rifai",fullName:"Andri Irfan Rifai",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/226240/images/7412_n.jpg",biography:"Andri IRFAN is a Senior Lecturer of Civil Engineering and Planning. He completed the PhD at the Universitas Indonesia & Universidade do Minho with Sandwich Program Scholarship from the Directorate General of Higher Education and LPDP scholarship. He has been teaching for more than 19 years and much active to applied his knowledge in the project construction in Indonesia. His research interest ranges from pavement management system to advanced data mining techniques for transportation engineering. He has published more than 50 papers in journals and 2 books.",institutionString:null,institution:{name:"Universitas Internasional Batam",country:{name:"Indonesia"}}},{id:"314576",title:"Dr.",name:"Ibai",middleName:null,surname:"Laña",slug:"ibai-lana",fullName:"Ibai Laña",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/314576/images/system/314576.jpg",biography:"Dr. Ibai Laña works at TECNALIA as a data analyst. He received his Ph.D. in Artificial Intelligence from the University of the Basque Country (UPV/EHU), Spain, in 2018. He is currently a senior researcher at TECNALIA. His research interests fall within the intersection of intelligent transportation systems, machine learning, traffic data analysis, and data science. He has dealt with urban traffic forecasting problems, applying machine learning models and evolutionary algorithms. He has experience in origin-destination matrix estimation or point of interest and trajectory detection. Working with large volumes of data has given him a good command of big data processing tools and NoSQL databases. He has also been a visiting scholar at the Knowledge Engineering and Discovery Research Institute, Auckland University of Technology.",institutionString:"TECNALIA Research & Innovation",institution:{name:"Tecnalia",country:{name:"Spain"}}},{id:"314575",title:"Dr.",name:"Jesus",middleName:null,surname:"L. Lobo",slug:"jesus-l.-lobo",fullName:"Jesus L. Lobo",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/314575/images/system/314575.png",biography:"Dr. Jesús López is currently based in Bilbao (Spain) working at TECNALIA as Artificial Intelligence Research Scientist. In most cases, a project idea or a new research line needs to be investigated to see if it is good enough to take into production or to focus on it. That is exactly what he does, diving into Machine Learning algorithms and technologies to help TECNALIA to decide whether something is great in theory or will actually impact on the product or processes of its projects. So, he is expert at framing experiments, developing hypotheses, and proving whether they’re true or not, in order to investigate fundamental problems with a longer time horizon. He is also able to design and develop PoCs and system prototypes in simulation. He has participated in several national and internacional R&D projects.\n\nAs another relevant part of his everyday research work, he usually publishes his findings in reputed scientific refereed journals and international conferences, occasionally acting as reviewer and Programme Commitee member. Concretely, since 2018 he has published 9 JCR (8 Q1) journal papers, 9 conference papers (e.g. ECML PKDD 2021), and he has co-edited a book. He is also active in popular science writing data science stories for reputed blogs (KDNuggets, TowardsDataScience, Naukas). Besides, he has recently embarked on mentoring programmes as mentor, and has also worked as data science trainer.",institutionString:"TECNALIA Research & Innovation",institution:{name:"Tecnalia",country:{name:"Spain"}}},{id:"103779",title:"Prof.",name:"Yalcin",middleName:null,surname:"Isler",slug:"yalcin-isler",fullName:"Yalcin Isler",position:null,profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bRyQ8QAK/Profile_Picture_1628834958734",biography:"Yalcin Isler (1971 - Burdur / Turkey) received the B.Sc. degree in the Department of Electrical and Electronics Engineering from Anadolu University, Eskisehir, Turkey, in 1993, the M.Sc. degree from the Department of Electronics and Communication Engineering, Suleyman Demirel University, Isparta, Turkey, in 1996, the Ph.D. degree from the Department of Electrical and Electronics Engineering, Dokuz Eylul University, Izmir, Turkey, in 2009, and the Competence of Associate Professorship from the Turkish Interuniversity Council in 2019.\n\nHe was Lecturer at Burdur Vocational School in Suleyman Demirel University (1993-2000, Burdur / Turkey), Software Engineer (2000-2002, Izmir / Turkey), Research Assistant in Bulent Ecevit University (2002-2003, Zonguldak / Turkey), Research Assistant in Dokuz Eylul University (2003-2010, Izmir / Turkey), Assistant Professor at the Department of Electrical and Electronics Engineering in Bulent Ecevit University (2010-2012, Zonguldak / Turkey), Assistant Professor at the Department of Biomedical Engineering in Izmir Katip Celebi University (2012-2019, Izmir / Turkey). He is an Associate Professor at the Department of Biomedical Engineering at Izmir Katip Celebi University, Izmir / Turkey, since 2019. In addition to academics, he has also founded Islerya Medical and Information Technologies Company, Izmir / Turkey, since 2017.\n\nHis main research interests cover biomedical signal processing, pattern recognition, medical device design, programming, and embedded systems. He has many scientific papers and participated in several projects in these study fields. He was an IEEE Student Member (2009-2011) and IEEE Member (2011-2014) and has been IEEE Senior Member since 2014.",institutionString:null,institution:{name:"Izmir Kâtip Çelebi University",country:{name:"Turkey"}}},{id:"339677",title:"Dr.",name:"Mrinmoy",middleName:null,surname:"Roy",slug:"mrinmoy-roy",fullName:"Mrinmoy Roy",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/339677/images/16768_n.jpg",biography:"An accomplished Sales & Marketing professional with 12 years of cross-functional experience in well-known organisations such as CIPLA, LUPIN, GLENMARK, ASTRAZENECA across different segment of Sales & Marketing, International Business, Institutional Business, Product Management, Strategic Marketing of HIV, Oncology, Derma, Respiratory, Anti-Diabetic, Nutraceutical & Stomatological Product Portfolio and Generic as well as Chronic Critical Care Portfolio. A First Class MBA in International Business & Strategic Marketing, B.Pharm, D.Pharm, Google Certified Digital Marketing Professional. Qualified PhD Candidate in Operations and Management with special focus on Artificial Intelligence and Machine Learning adoption, analysis and use in Healthcare, Hospital & Pharma Domain. Seasoned with diverse therapy area of Pharmaceutical Sales & Marketing ranging from generating revenue through generating prescriptions, launching new products, and making them big brands with continuous strategy execution at the Physician and Patients level. Moved from Sales to Marketing and Business Development for 3.5 years in South East Asian Market operating from Manila, Philippines. Came back to India and handled and developed Brands such as Gluconorm, Lupisulin, Supracal, Absolut Woman, Hemozink, Fabiflu (For COVID 19), and many more. In my previous assignment I used to develop and execute strategies on Sales & Marketing, Commercialization & Business Development for Institution and Corporate Hospital Business portfolio of Oncology Therapy Area for AstraZeneca Pharma India Ltd. Being a Research Scholar and Student of ‘Operations Research & Management: Artificial Intelligence’ I published several pioneer research papers and book chapters on the same in Internationally reputed journals and Books indexed in Scopus, Springer and Ei Compendex, Google Scholar etc. Currently, I am launching PGDM Pharmaceutical Management Program in IIHMR Bangalore and spearheading the course curriculum and structure of the same. I am interested in Collaboration for Healthcare Innovation, Pharma AI Innovation, Future trend in Marketing and Management with incubation on Healthcare, Healthcare IT startups, AI-ML Modelling and Healthcare Algorithm based training module development. I am also an affiliated member of the Institute of Management Consultant of India, looking forward to Healthcare, Healthcare IT and Innovation, Pharma and Hospital Management Consulting works.",institutionString:null,institution:{name:"Lovely Professional University",country:{name:"India"}}},{id:"310576",title:"Prof.",name:"Erick Giovani",middleName:null,surname:"Sperandio Nascimento",slug:"erick-giovani-sperandio-nascimento",fullName:"Erick Giovani Sperandio Nascimento",position:null,profilePictureURL:"https://intech-files.s3.amazonaws.com/0033Y00002pDKxDQAW/ProfilePicture%202022-06-20%2019%3A57%3A24.788",biography:"Prof. Erick Sperandio is the Lead Researcher and professor of Artificial Intelligence (AI) at SENAI CIMATEC, Bahia, Brazil, also working with Computational Modeling (CM) and HPC. He holds a PhD in Environmental Engineering in the area of Atmospheric Computational Modeling, a Master in Informatics in the field of Computational Intelligence and Graduated in Computer Science from UFES. He currently coordinates, leads and participates in R&D projects in the areas of AI, computational modeling and supercomputing applied to different areas such as Oil and Gas, Health, Advanced Manufacturing, Renewable Energies and Atmospheric Sciences, advising undergraduate, master's and doctoral students. He is the Lead Researcher at SENAI CIMATEC's Reference Center on Artificial Intelligence. In addition, he is a Certified Instructor and University Ambassador of the NVIDIA Deep Learning Institute (DLI) in the areas of Deep Learning, Computer Vision, Natural Language Processing and Recommender Systems, and Principal Investigator of the NVIDIA/CIMATEC AI Joint Lab, the first in Latin America within the NVIDIA AI Technology Center (NVAITC) worldwide program. He also works as a researcher at the Supercomputing Center for Industrial Innovation (CS2i) and at the SENAI Institute of Innovation for Automation (ISI Automação), both from SENAI CIMATEC. He is a member and vice-coordinator of the Basic Board of Scientific-Technological Advice and Evaluation, in the area of Innovation, of the Foundation for Research Support of the State of Bahia (FAPESB). He serves as Technology Transfer Coordinator and one of the Principal Investigators at the National Applied Research Center in Artificial Intelligence (CPA-IA) of SENAI CIMATEC, focusing on Industry, being one of the six CPA-IA in Brazil approved by MCTI / FAPESP / CGI.br. He also participates as one of the representatives of Brazil in the BRICS Innovation Collaboration Working Group on HPC, ICT and AI. He is the coordinator of the Work Group of the Axis 5 - Workforce and Training - of the Brazilian Strategy for Artificial Intelligence (EBIA), and member of the MCTI/EMBRAPII AI Innovation Network Training Committee. He is the coordinator, by SENAI CIMATEC, of the Artificial Intelligence Reference Network of the State of Bahia (REDE BAH.IA). He leads the working group of experts representing Brazil in the Global Partnership on Artificial Intelligence (GPAI), on the theme \"AI and the Pandemic Response\".",institutionString:"Manufacturing and Technology Integrated Campus – SENAI CIMATEC",institution:null},{id:"1063",title:"Prof.",name:"Constantin",middleName:null,surname:"Volosencu",slug:"constantin-volosencu",fullName:"Constantin Volosencu",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/1063/images/system/1063.png",biography:"Prof. Dr. Constantin Voloşencu graduated as an engineer from\nPolitehnica University of Timișoara, Romania, where he also\nobtained a doctorate degree. He is currently a full professor in\nthe Department of Automation and Applied Informatics at the\nsame university. Dr. Voloşencu is the author of ten books, seven\nbook chapters, and more than 160 papers published in journals\nand conference proceedings. He has also edited twelve books and\nhas twenty-seven patents to his name. He is a manager of research grants, editor in\nchief and member of international journal editorial boards, a former plenary speaker, a member of scientific committees, and chair at international conferences. His\nresearch is in the fields of control systems, control of electric drives, fuzzy control\nsystems, neural network applications, fault detection and diagnosis, sensor network\napplications, monitoring of distributed parameter systems, and power ultrasound\napplications. He has developed automation equipment for machine tools, spooling\nmachines, high-power ultrasound processes, and more.",institutionString:"Polytechnic University of Timişoara",institution:{name:"Polytechnic University of Timişoara",country:{name:"Romania"}}},{id:"221364",title:"Dr.",name:"Eneko",middleName:null,surname:"Osaba",slug:"eneko-osaba",fullName:"Eneko Osaba",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/221364/images/system/221364.jpg",biography:"Dr. Eneko Osaba works at TECNALIA as a senior researcher. He obtained his Ph.D. in Artificial Intelligence in 2015. He has participated in more than twenty-five local and European research projects, and in the publication of more than 130 papers. He has performed several stays at universities in the United Kingdom, Italy, and Malta. Dr. Osaba has served as a program committee member in more than forty international conferences and participated in organizing activities in more than ten international conferences. He is a member of the editorial board of the International Journal of Artificial Intelligence, Data in Brief, and Journal of Advanced Transportation. He is also a guest editor for the Journal of Computational Science, Neurocomputing, Swarm, and Evolutionary Computation and IEEE ITS Magazine.",institutionString:"TECNALIA Research & Innovation",institution:{name:"Tecnalia",country:{name:"Spain"}}},{id:"275829",title:"Dr.",name:"Esther",middleName:null,surname:"Villar-Rodriguez",slug:"esther-villar-rodriguez",fullName:"Esther Villar-Rodriguez",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/275829/images/system/275829.jpg",biography:"Dr. Esther Villar obtained a Ph.D. in Information and Communication Technologies from the University of Alcalá, Spain, in 2015. She obtained a degree in Computer Science from the University of Deusto, Spain, in 2010, and an MSc in Computer Languages and Systems from the National University of Distance Education, Spain, in 2012. Her areas of interest and knowledge include natural language processing (NLP), detection of impersonation in social networks, semantic web, and machine learning. Dr. Esther Villar made several contributions at conferences and publishing in various journals in those fields. Currently, she is working within the OPTIMA (Optimization Modeling & Analytics) business of TECNALIA’s ICT Division as a data scientist in projects related to the prediction and optimization of management and industrial processes (resource planning, energy efficiency, etc).",institutionString:"TECNALIA Research & Innovation",institution:{name:"Tecnalia",country:{name:"Spain"}}},{id:"49813",title:"Dr.",name:"Javier",middleName:null,surname:"Del Ser",slug:"javier-del-ser",fullName:"Javier Del Ser",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/49813/images/system/49813.png",biography:"Prof. Dr. Javier Del Ser received his first PhD in Telecommunication Engineering (Cum Laude) from the University of Navarra, Spain, in 2006, and a second PhD in Computational Intelligence (Summa Cum Laude) from the University of Alcala, Spain, in 2013. He is currently a principal researcher in data analytics and optimisation at TECNALIA (Spain), a visiting fellow at the Basque Center for Applied Mathematics (BCAM) and a part-time lecturer at the University of the Basque Country (UPV/EHU). His research interests gravitate on the use of descriptive, prescriptive and predictive algorithms for data mining and optimization in a diverse range of application fields such as Energy, Transport, Telecommunications, Health and Industry, among others. In these fields he has published more than 240 articles, co-supervised 8 Ph.D. theses, edited 6 books, coauthored 7 patents and participated/led more than 40 research projects. He is a Senior Member of the IEEE, and a recipient of the Biscay Talent prize for his academic career.",institutionString:"Tecnalia Research & Innovation",institution:null},{id:"278948",title:"Dr.",name:"Carlos Pedro",middleName:null,surname:"Gonçalves",slug:"carlos-pedro-goncalves",fullName:"Carlos Pedro Gonçalves",position:null,profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bRcmyQAC/Profile_Picture_1564224512145",biography:'Carlos Pedro Gonçalves (PhD) is an Associate Professor at Lusophone University of Humanities and Technologies and a researcher on Complexity Sciences, Quantum Technologies, Artificial Intelligence, Strategic Studies, Studies in Intelligence and Security, FinTech and Financial Risk Modeling. He is also a progammer with programming experience in:\n\nA) Quantum Computing using Qiskit Python module and IBM Quantum Experience Platform, with software developed on the simulation of Quantum Artificial Neural Networks and Quantum Cybersecurity;\n\nB) Artificial Intelligence and Machine learning programming in Python;\n\nC) Artificial Intelligence, Multiagent Systems Modeling and System Dynamics Modeling in Netlogo, with models developed in the areas of Chaos Theory, Econophysics, Artificial Intelligence, Classical and Quantum Complex Systems Science, with the Econophysics models having been cited worldwide and incorporated in PhD programs by different Universities.\n\nReceived an Arctic Code Vault Contributor status by GitHub, due to having developed open source software preserved in the \\"Arctic Code Vault\\" for future generations (https://archiveprogram.github.com/arctic-vault/), with the Strategy Analyzer A.I. module for decision making support (based on his PhD thesis, used in his Classes on Decision Making and in Strategic Intelligence Consulting Activities) and QNeural Python Quantum Neural Network simulator also preserved in the \\"Arctic Code Vault\\", for access to these software modules see: https://github.com/cpgoncalves. He is also a peer reviewer with outsanding review status from Elsevier journals, including Physica A, Neurocomputing and Engineering Applications of Artificial Intelligence. Science CV available at: https://www.cienciavitae.pt//pt/8E1C-A8B3-78C5 and ORCID: https://orcid.org/0000-0002-0298-3974',institutionString:"University of Lisbon",institution:{name:"Universidade Lusófona",country:{name:"Portugal"}}},{id:"241400",title:"Prof.",name:"Mohammed",middleName:null,surname:"Bsiss",slug:"mohammed-bsiss",fullName:"Mohammed Bsiss",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/241400/images/8062_n.jpg",biography:null,institutionString:null,institution:null},{id:"276128",title:"Dr.",name:"Hira",middleName:null,surname:"Fatima",slug:"hira-fatima",fullName:"Hira Fatima",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/276128/images/14420_n.jpg",biography:"Dr. Hira Fatima\nAssistant Professor\nDepartment of Mathematics\nInstitute of Applied Science\nMangalayatan University, Aligarh\nMobile: no : 8532041179\nhirafatima2014@gmal.com\n\nDr. Hira Fatima has received his Ph.D. degree in pure Mathematics from Aligarh Muslim University, Aligarh India. Currently working as an Assistant Professor in the Department of Mathematics, Institute of Applied Science, Mangalayatan University, Aligarh. She taught so many courses of Mathematics of UG and PG level. Her research Area of Expertise is Functional Analysis & Sequence Spaces. She has been working on Ideal Convergence of double sequence. She has published 17 research papers in National and International Journals including Cogent Mathematics, Filomat, Journal of Intelligent and Fuzzy Systems, Advances in Difference Equations, Journal of Mathematical Analysis, Journal of Mathematical & Computer Science etc. She has also reviewed few research papers for the and international journals. She is a member of Indian Mathematical Society.",institutionString:null,institution:null},{id:"414880",title:"Dr.",name:"Maryam",middleName:null,surname:"Vatankhah",slug:"maryam-vatankhah",fullName:"Maryam Vatankhah",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"Borough of Manhattan Community College",country:{name:"United States of America"}}},{id:"414879",title:"Prof.",name:"Mohammad-Reza",middleName:null,surname:"Akbarzadeh-Totonchi",slug:"mohammad-reza-akbarzadeh-totonchi",fullName:"Mohammad-Reza Akbarzadeh-Totonchi",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"Ferdowsi University of Mashhad",country:{name:"Iran"}}},{id:"414878",title:"Prof.",name:"Reza",middleName:null,surname:"Fazel-Rezai",slug:"reza-fazel-rezai",fullName:"Reza Fazel-Rezai",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"American Public University System",country:{name:"United States of America"}}},{id:"302698",title:"Dr.",name:"Yao",middleName:null,surname:"Shan",slug:"yao-shan",fullName:"Yao Shan",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"Dalian University of Technology",country:{name:"China"}}},{id:"125911",title:"Prof.",name:"Jia-Ching",middleName:null,surname:"Wang",slug:"jia-ching-wang",fullName:"Jia-Ching Wang",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"National Central University",country:{name:"Taiwan"}}},{id:"357085",title:"Mr.",name:"P. Mohan",middleName:null,surname:"Anand",slug:"p.-mohan-anand",fullName:"P. Mohan Anand",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"Indian Institute of Technology Kanpur",country:{name:"India"}}},{id:"356696",title:"Ph.D. Student",name:"P.V.",middleName:null,surname:"Sai Charan",slug:"p.v.-sai-charan",fullName:"P.V. Sai Charan",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"Indian Institute of Technology Kanpur",country:{name:"India"}}},{id:"357086",title:"Prof.",name:"Sandeep K.",middleName:null,surname:"Shukla",slug:"sandeep-k.-shukla",fullName:"Sandeep K. Shukla",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"Indian Institute of Technology Kanpur",country:{name:"India"}}},{id:"356823",title:"MSc.",name:"Seonghee",middleName:null,surname:"Min",slug:"seonghee-min",fullName:"Seonghee Min",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"Daegu University",country:{name:"Korea, South"}}},{id:"353307",title:"Prof.",name:"Yoosoo",middleName:null,surname:"Oh",slug:"yoosoo-oh",fullName:"Yoosoo Oh",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:"Yoosoo Oh received his Bachelor's degree in the Department of Electronics and Engineering from Kyungpook National University in 2002. He obtained his Master’s degree in the Department of Information and Communications from Gwangju Institute of Science and Technology (GIST) in 2003. In 2010, he received his Ph.D. degree in the School of Information and Mechatronics from GIST. In the meantime, he was an executed team leader at Culture Technology Institute, GIST, 2010-2012. In 2011, he worked at Lancaster University, the UK as a visiting scholar. In September 2012, he joined Daegu University, where he is currently an associate professor in the School of ICT Conver, Daegu University. Also, he served as the Board of Directors of KSIIS since 2019, and HCI Korea since 2016. From 2017~2019, he worked as a center director of the Mixed Reality Convergence Research Center at Daegu University. From 2015-2017, He worked as a director in the Enterprise Supporting Office of LINC Project Group, Daegu University. His research interests include Activity Fusion & Reasoning, Machine Learning, Context-aware Middleware, Human-Computer Interaction, etc.",institutionString:null,institution:{name:"Daegu Gyeongbuk Institute of Science and Technology",country:{name:"Korea, South"}}},{id:"262719",title:"Dr.",name:"Esma",middleName:null,surname:"Ergüner Özkoç",slug:"esma-erguner-ozkoc",fullName:"Esma Ergüner Özkoç",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"Başkent University",country:{name:"Turkey"}}},{id:"346530",title:"Dr.",name:"Ibrahim",middleName:null,surname:"Kaya",slug:"ibrahim-kaya",fullName:"Ibrahim Kaya",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"Izmir Kâtip Çelebi University",country:{name:"Turkey"}}},{id:"419199",title:"Dr.",name:"Qun",middleName:null,surname:"Yang",slug:"qun-yang",fullName:"Qun Yang",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"University of Auckland",country:{name:"New Zealand"}}}]}},subseries:{item:{id:"95",type:"subseries",title:"Urban Planning and Environmental Management",keywords:"Circular economy, Contingency planning and response to disasters, Ecosystem services, Integrated urban water management, Nature-based solutions, Sustainable urban development, Urban green spaces",scope:"