\\n\\n
More than half of the publishers listed alongside IntechOpen (18 out of 30) are Social Science and Humanities publishers. IntechOpen is an exception to this as a leader in not only Open Access content but Open Access content across all scientific disciplines, including Physical Sciences, Engineering and Technology, Health Sciences, Life Science, and Social Sciences and Humanities.
\\n\\nOur breakdown of titles published demonstrates this with 47% PET, 31% HS, 18% LS, and 4% SSH books published.
\\n\\n“Even though ItechOpen has shown the potential of sci-tech books using an OA approach,” other publishers “have shown little interest in OA books.”
\\n\\nAdditionally, each book published by IntechOpen contains original content and research findings.
\\n\\nWe are honored to be among such prestigious publishers and we hope to continue to spearhead that growth in our quest to promote Open Access as a true pioneer in OA book publishing.
\\n\\n\\n\\n
\\n"}]',published:!0,mainMedia:null},components:[{type:"htmlEditorComponent",content:'
Simba Information has released its Open Access Book Publishing 2020 - 2024 report and has again identified IntechOpen as the world’s largest Open Access book publisher by title count.
\n\nSimba Information is a leading provider for market intelligence and forecasts in the media and publishing industry. The report, published every year, provides an overview and financial outlook for the global professional e-book publishing market.
\n\nIntechOpen, De Gruyter, and Frontiers are the largest OA book publishers by title count, with IntechOpen coming in at first place with 5,101 OA books published, a good 1,782 titles ahead of the nearest competitor.
\n\nSince the first Open Access Book Publishing report published in 2016, IntechOpen has held the top stop each year.
\n\n\n\nMore than half of the publishers listed alongside IntechOpen (18 out of 30) are Social Science and Humanities publishers. IntechOpen is an exception to this as a leader in not only Open Access content but Open Access content across all scientific disciplines, including Physical Sciences, Engineering and Technology, Health Sciences, Life Science, and Social Sciences and Humanities.
\n\nOur breakdown of titles published demonstrates this with 47% PET, 31% HS, 18% LS, and 4% SSH books published.
\n\n“Even though ItechOpen has shown the potential of sci-tech books using an OA approach,” other publishers “have shown little interest in OA books.”
\n\nAdditionally, each book published by IntechOpen contains original content and research findings.
\n\nWe are honored to be among such prestigious publishers and we hope to continue to spearhead that growth in our quest to promote Open Access as a true pioneer in OA book publishing.
\n\n\n\n
\n'}],latestNews:[{slug:"intechopen-authors-included-in-the-highly-cited-researchers-list-for-2020-20210121",title:"IntechOpen Authors Included in the Highly Cited Researchers List for 2020"},{slug:"intechopen-maintains-position-as-the-world-s-largest-oa-book-publisher-20201218",title:"IntechOpen Maintains Position as the World’s Largest OA Book Publisher"},{slug:"all-intechopen-books-available-on-perlego-20201215",title:"All IntechOpen Books Available on Perlego"},{slug:"oiv-awards-recognizes-intechopen-s-editors-20201127",title:"OIV Awards Recognizes IntechOpen's Editors"},{slug:"intechopen-joins-crossref-s-initiative-for-open-abstracts-i4oa-to-boost-the-discovery-of-research-20201005",title:"IntechOpen joins Crossref's Initiative for Open Abstracts (I4OA) to Boost the Discovery of Research"},{slug:"intechopen-hits-milestone-5-000-open-access-books-published-20200908",title:"IntechOpen hits milestone: 5,000 Open Access books published!"},{slug:"intechopen-books-hosted-on-the-mathworks-book-program-20200819",title:"IntechOpen Books Hosted on the MathWorks Book Program"},{slug:"intechopen-s-chapter-awarded-the-guenther-von-pannewitz-preis-2020-20200715",title:"IntechOpen's Chapter Awarded the Günther-von-Pannewitz-Preis 2020"}]},book:{item:{type:"book",id:"466",leadTitle:null,fullTitle:"Carbon Nanotubes - Synthesis, Characterization, Applications",title:"Carbon Nanotubes",subtitle:"Synthesis, Characterization, Applications",reviewType:"peer-reviewed",abstract:"Carbon nanotubes are one of the most intriguing new materials with extraordinary properties being discovered in the last decade. The unique structure of carbon nanotubes provides nanotubes with extraordinary mechanical and electrical properties. The outstanding properties that these materials possess have opened new interesting researches areas in nanoscience and nanotechnology. Although nanotubes are very promising in a wide variety of fields, application of individual nanotubes for large scale production has been limited. The main roadblocks, which hinder its use, are limited understanding of its synthesis and electrical properties which lead to difficulty in structure control, existence of impurities, and poor processability. This book makes an attempt to provide indepth study and analysis of various synthesis methods, processing techniques and characterization of carbon nanotubes that will lead to the increased applications of carbon nanotubes.",isbn:null,printIsbn:"978-953-307-497-9",pdfIsbn:"978-953-51-4484-7",doi:"10.5772/978",price:159,priceEur:175,priceUsd:205,slug:"carbon-nanotubes-synthesis-characterization-applications",numberOfPages:530,isOpenForSubmission:!1,isInWos:1,hash:null,bookSignature:"Siva Yellampalli",publishedDate:"July 20th 2011",coverURL:"https://cdn.intechopen.com/books/images_new/466.jpg",numberOfDownloads:113652,numberOfWosCitations:182,numberOfCrossrefCitations:89,numberOfDimensionsCitations:191,hasAltmetrics:0,numberOfTotalCitations:462,isAvailableForWebshopOrdering:!0,dateEndFirstStepPublish:"October 12th 2010",dateEndSecondStepPublish:"November 9th 2010",dateEndThirdStepPublish:"March 16th 2011",dateEndFourthStepPublish:"April 15th 2011",dateEndFifthStepPublish:"June 14th 2011",currentStepOfPublishingProcess:5,indexedIn:"1,2,3,4,5,6,7,8",editedByType:"Edited by",kuFlag:!1,editors:[{id:"62863",title:"Dr.",name:"Siva",middleName:null,surname:"Yellampalli",slug:"siva-yellampalli",fullName:"Siva Yellampalli",profilePictureURL:"https://mts.intechopen.com/storage/users/62863/images/system/62863.jpg",biography:"Dr. Siva Yellampalli is currently working as a Professor of Practice, School of Engineering and Applied Sciences, SRM University AP, Amaravati. He obtained his MS and Ph.D from Louisiana State University. His main research interest is system level design for power optimization while his broader area of research encompasses different research fields such as VLSI, mixed signal circuits/systems development, MEMS, and CNT sensors. He has published a book in the area of mixed-signal design, edited two books on carbon nano tubes and one book on MEMS. He published 70 plus International Journal papers and IEEE Conference papers. In addition, he has delivered keynote speeches at International conferences held in Canada, Dubai and Spain including tutorials at various IEEE International Conferences. 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Inflammatory bowel disease (IBD) is a chronic, relapsing inflammatory condition of gastrointestinal tract with high incidence and prevalence in Western countries (North America, Europe, the highest in Scandinavia, and the United Kingdom) [1]. It is estimated that IBD affects 2.5–3 million people in Europe [2].
IBD consist primarily of Crohn’s disease (CD) and ulcerative colitis (UC), which are distinguished by the location and the nature of the inflammation [3]. Patients with IBD experience many symptoms, such as abdominal pain, fever, vomiting, diarrhea, rectal bleeding, anemia, and weight loss, which have significant impact on their quality of life. Symptoms vary depending on the location and severity of inflammation and can be very painful and disruptive and in some cases even life-threatening (CD patients have 40% risk of mortality) [3].
IBD affects a young population, in the second and third decades of life or even in late adolescence [4]. The majority of patients with IBD progress to relapsing and chronic disease and need lifelong treatment and care. The health economic burden and permanent work disability in IBD are high in Europe with a total yearly direct healthcare cost of 4.6–5.6 billion Euros [2]. In recent years, the management of IBD has improved, due to the fact that the new treatments with anti-TNF drugs induce not only clinical remission but also a significant endoscopic improvement or even disappearance of the intestinal lesions [5, 6].
However, in the past two decades, clinical studies have shown that anti-TNF drugs are not always effective. Moreover, in some rare cases, anti-TNF drugs can even cause an aggravation of the disease. Therefore, this chapter aims to briefly summarize the detrimental role of TNF in the pathogenesis of IBD and to highlight the beneficial role of TNF, which is too often overlooked in the health and the disease.
Tumor necrosis factor (TNF, also known as TNFa, cachectin, or cachexin) was identified/named in 1975 by Carswell et al. who demonstrated that the serum of endotoxin-treated mice, rat, and rabbits, previously infected with Mycobacterium bovis strain Bacillus Calmette-Guerin caused hemorrhagic necrosis of various tumors in mice. They found that hemorrhagic necrosis of tumors in vivo was caused by so-called tumor necrosis factor (TNF) released from host cells, very likely macrophages, in response to injected endotoxin. They showed that both, a TNF-positive serum and endotoxin, were effective in causing necrosis of similar spectrum of transplanted tumors and at a similar phase of their growth. Moreover, a TNF-positive serum had cytotoxic effects on mouse and human tumor cells in vitro as well [7].
In 1985, human TNF was purified, characterized, and cloned, which enabled production of large quantities of a highly purified TNF protein for extensive investigations [8, 9]. Since recombinant TNF has shown antitumor activity in both transplantable murine tumors and human tumor xenografts, TNF was quickly launched into clinical trials as a potential anticancer agent. Recombinant human TNF has been tested in several phase I and phase II clinical trials in the 1980s and 1990s. However, the initial enthusiasm for the use of TNF as a systemic treatment has waned in the face of significant toxicities and a lack of evidence for therapeutic benefit. Systemic TNF treatment was found to cause dose-dependent toxicities such as fever, hypotension, and tachycardia [10, 11, 12].
Independently, other groups of researchers investigated metabolic basis for cachexia and endotoxin-induced septicemia and septic shock syndrome. Hypertriglyceridemia in animals injected with endotoxin was found to result from defective triglyceride clearance due to systemic suppression of the enzyme lipoprotein lipase. Finally, the substance responsible for specific suppression of lipoprotein lipase activity was identified and named cachectin [13, 14]. Interestingly, soon after the characterization of human TNF in 1985, it was recognized that the TNF and cachectin are the same single protein with the complex dual role [8, 9, 15].
Nevertheless, direct evidence that cachectin is a mediator of the pathology/septicemia induced by endotoxin was demonstrated by Beutler and colleagues [16, 17]. They showed that passive immunization with rabbit antiserum or purified Ig against murine TNF protected the mice from the lethal effect of the endotoxin lipopolysaccharide [16]. The same group then showed that injection of recombinant human TNF into rats in quantities similar to those produced endogenously in response to endotoxin caused hypotension, metabolic acidosis, hemoconcentration, and death of animals within minutes to hours. Thus, effects similar to those are induced by injection of endotoxin [17]. These observations led to the speculation that neutralization of TNF may be beneficial in life-threatening septicemia. Despite increased interest in the use of anti-TNF drugs for the treatment of sepsis, numerous clinical trials have showed only a small survival benefit (3.6%) [18]. The likely reason for the failure of anti-TNF drugs in sepsis can be found in the original animal study, where it was clearly demonstrated that neutralization of TNF was efficient in preventing death in mice only when administered before a very short time after the injection of endotoxin [16].
Nevertheless, the effort invested in the development of anti-TNF drugs, originally intended for the treatment of sepsis, enabled the use of anti-TNF therapy in the chronic inflammatory diseases, including IBD. However, the investigations and hopes regarding the use of anti-TNF drugs in sepsis and the use of TNF as an anticancer agent are still in progress [10, 19].
The first evidence showing a link between TNF and IBD were publications reporting that patients with IBD have increased levels of TNF in serum, stool, or mucosal biopsy specimens [20, 21, 22, 23]. However, the initial hopes for the use of TNF as a marker of IBD have waned when it was recognized that TNF can be increased also during infectious colitis [24] or TNF may even not be increased in patients with IBD [25] or TNF can be reduced in response to certain medication such as cyclosporine A [22, 26]. Nevertheless, a published reports about successful treatment of CD patients with TNF chimeric monoclonal antibodies (cA2 or infliximab) [27] established clear association of TNF involvement in the pathogenesis of IBD and caused extensive investigation of TNF role in IBD and production of various genetic models, including transgenic mice with persistent TNF overproduction in various tissues.
It was clearly demonstrated that persistent systemic overproduction of TNF (TNF∆ARE/∆ARE mice) can cause severe systemic health problems in mice, such as severe chronic polyarthritis, profound inflammatory changes in the terminal ileum and occasionally in the proximal colon, hypoplastic thymus with atrophied and disorganized cortical and medullary areas, and occasional mild inflammation in the liver and lung. These alterations were first detected in homozygous mice between 1 and 4 weeks of their age. Heterozygous mice developed the same health problems but later in their life inflammatory arthritis at 6–8 weeks of age and severe inflammatory bowel disease extending into muscular layers of the bowel wall at 4–7 months of their age. Homozygous mice never exceeded the body weight of 3-week-old mice and died between 5 and 12 weeks of their age [28]. It was also demonstrated that chronic intestinal inflammation can be triggered by persistent local TNF overproduction. Mice homozygous for persistent overproduction of TNF in the intestinal epithelium (TNFi∆ARE/i∆ARE mice) developed chronic ileitis by the age of 16–20 weeks and had increased mucosal and systemic protein levels of TNF. No inflammation in other tissues was found. No histological signs of joint injury were observed. Heterozygous mice (TNFi∆ARE/+) develop only mild villous blunting with scarce inflammation (not significant) [29]. In addition, mice with persistent myeloid cell-specific TNF overproduction also developed symptoms of weight loss and ileitis by the age of 5 months (homo and heterozygous) but with more severe symptoms in the homozygous mice. Interestingly, mice with persistent T lymphocyte-specific TNF overproduction developed mild symptoms of IBD but only on homozygous background. On the other hand, mice with persistent B lymphocyte-specific TNF overproduction did not show any signs of IBD by the age of 15 months [30]. Results of numerous animal studies gave tacit confirmation that persistent systemic or local TNF overproduction is detrimental and responsible for intestinal inflammation, serious health problems, and even death [31].
The introduction of anti-TNF therapies in the 1998 affected the treatment of many chronic inflammatory disorders, including rheumatoid arthritis, ankylosing spondylitis, and IBD. Five therapeutic agents have been licensed in the USA and most other parts of the world. Randomized controlled trials demonstrated the efficacy and safety of induction and maintenance therapy for moderate-to-severe IBD. Subsequent studies have demonstrated that infliximab treatment results in a positive clinical response as well as in a significant endoscopic improvement, confirmed also by histological examination as a complete reduction in the inflammation infiltrate. The breakthrough in the treatment of patients with IBD with anti-TNF therapy has firmly established the dogma that TNF is a major cytokine in this disease [32, 33]. Anti-TNF drugs such as infliximab, adalimumab, and etanercept are nowadays commonly used in the treatment of a variety of inflammatory and autoimmune diseases (IBD, rheumatoid arthritis, psoriasis, psoriasiform arthritis, and ankylosing spondylitis). Nevertheless, with the increasing use and longer follow-up periods, more information about effectiveness and side effects of anti-TNF therapy in IBD has been published.
First reported/known adverse events of anti-TNF drugs were mainly immunogenicity leading to acute and delayed infusion reactions and loss of response, infectious complication, and concerns about tumor induction or progression [34, 35].
Today, after two decades of clinical experience with anti-TNF drugs and 2 million treated patients, it is widely known that around 30% of patients do not respond to anti-TNF therapy (primary nonresponders) and almost half of patients with initial response develop secondary loss of response within the first year. Among nonresponders, some may have low serum drug levels which could be explained by under-dosing or high drug clearance. Development of immunogenicity against the anti-TNF drugs is also associated with loss of response. In such cases, consideration of switch in anti-TNF drugs or dose escalation following loss of response may be an effective strategy [32]. However, some patients on anti-TNF drugs experience primary or secondary nonresponse despite adequate serum drug levels and the absence of neutralizing antibodies. Recently, it was proposed that such nonresponders may have upregulated other alternative inflammatory pathways independent of TNF [36]. Nevertheless, despite all complications and high costs of anti-TNF drugs, economic evaluation studies have shown that the benefit of anti-TNF drugs is still higher than the costs [37].
Susceptibility to infection and risk of malignancy has been a significant concern from the beginning of anti-TNF drug use. In the past, it was widely reported that anti-TNF therapy was associated with increased susceptibility to infections, particularly tuberculosis and hepatitis B. However, when it was recognized that anti-TNF drugs trigger the reactivation of latent infections [38], screening for tuberculosis and hepatitis B in clinical settings was implemented. Soon, reports about tuberculosis or hepatitis infections associated with anti-TNF therapy diminished [34]. Interestingly, recent publications report that anti-TNF therapy alone does not increase the risk of serious infection in IBD patients [39, 40]. Moreover, a systematic review (5528 patients) reported that the rate of serious infection was significantly lower among pediatric patients with IBD treated with anti-TNF than those treated with steroids or adults with IBD who received anti-TNF therapy [39]. In contrast, increasing number of reports about other untypical opportunistic infectious diseases, such as cytomegalovirus infection, histoplasmosis, aspergillosis appeared [34, 40]. Importantly, recent population-based study (190,694 patients with IBD) found that anti-TNF monotherapy was associated with increased risk of serious infection, mycobacterial infection, and bacterial infection but with decreased risk of opportunistic viral infection when compared with thiopurine monotherapy. However, when anti-TNF drugs are part of combination therapy with other immunosuppressive drugs, particularly thiopurines, the risk of serious infection and opportunistic infection increases [34, 41].
Anti-TNF drugs have been associated with the increased risk for malignancy [34]. In the past, few studies reported T-cell non-Hodgkin’s lymphoma or hepatosplenic T-cell lymphoma in IBD patients using anti-TNF drugs [42], while more recent studies found no association between anti-TNF drugs and hematologic malignancies. It was reported that the risk of lymphoma was no greater among children with IBD who received anti-TNF drugs than those treated with other IBD therapies or adults treated with anti-TNF drugs [39]. REFURBISH study found that the risk of T-cell non-Hodgkin’s lymphoma in IBD patients is increased with the use of combination anti-TNF and thiopurine therapy but not with the use of anti-TNF monotherapy [43]. However, recent cohort study of 189,289 patients with IBD reported that the use of thiopurine monotherapy or anti-TNF monotherapy in patients with IBD was associated with a small but statistically significant increased risk of lymphoma, and this risk was higher with combination therapy than with each of these treatments used alone [44].
Knowledge about immune diseases secondary to TNF target therapy is relatively new. Until 2007, altogether 233 cases of immune diseases secondary to TNF targeted therapy were reported [45]. Nowadays, increasing number of various paradoxical reactions is published such as psoriasiform skin lesions, uveitis, ileitis or colitis, joint manifestations, vasculitis and autoimmune disease (lupus and myositis), and sarcoidosis-like lesions. There are currently no predictors of their occurrence, and the optimal clinical management is still a matter of debate. Mostly paradoxical reactions are poorly described, and their prevalence and pathogenesis are not known. Therefore, it is important to be aware of all possible side effects of TNF therapy to properly inform the patient about potential side effects of anti-TNF therapy before the treatment.
Psoriasis or psoriasiform skin lesions are one of the most frequently reported paradoxical reactions. Until November 2008, altogether 120 cases of psoriasis in patients treated with anti-TNF drugs were published. Among them 18 cases were found in patients with IBD (15%) [46]. Nowadays, increasing number of studies has shown that psoriasis can develop in IBD patients (adults or children) without any history of psoriasis and independent of the type of anti-TNF drugs [46, 47, 48]. However, in IBD patients with a history of psoriasis, anti-TNF treatment may trigger reappearance (3/21) [47] or exacerbation of the psoriasis (2/18) [46, 48].
Retrospective cohort (917) reported that 29% patients undergoing anti-TNF therapy (infliximab) developed skin lesions such as psoriasiform eczema, xerosis cutis, palmoplantar pustulosis, and psoriasis. The average time from the start of TNF therapy to the onset of skin lesions varied from 14.3 weeks [46] to 2 years [46, 47, 48]. In most patients psoriatic lesions were effectively treated with topical steroids, and in patients with severe psoriasis or patients without response to topical therapy, anti-TNF therapy was discontinued [47]. In another study in almost half of patients changed their initial anti-TNF agent despite conventional skin-directed therapies, and one-third of patients discontinued all anti-TNF therapy [48].
Lichenoid drug reaction in association with anti-TNF therapy was also reported. Until 2015, only seven cases were reported in association with anti-TNF drugs. Oral lichen planus occurred between 8 weeks and 6 months after anti-TNF therapy. Outcome was mainly favorable with improvement or recovery with or without cessation of the TNF blocker. Authors recommend a careful monitoring for oral manifestations in IBD patients treated with TNF inhibitors. OLP is thought to be mediated by dendritic cells and T cells [49].
Patients treated with anti-TNF therapy (i.e., etanercept, adalimumab, and infliximab) can develop sarcoidosis-like lesions. Until 2017, altogether 90 cases were reported, 6 cases in IBD patients. Median duration between initiation of anti-TNF therapy and diagnosis was 22.5 months (range 1–84 months). Most frequently affected organs were lungs, skin, and eyes [50].
Patients with IBD developed new onset arthritis or synovitis after 2.5 ± 1.6 years of successful anti-TNF treatment. The onset of paradoxical arthritis appeared when IBD patients were in clinical and endoscopic remission but with signs of histologically diagnosed subclinical inflammation. The inhibition of inflammatory pathways alternative to TNF (IL12/1L23) may be an effective therapeutic option for severe paradoxical articular manifestations [51].
The lupus-like syndrome can be observed in 0.5–1% of patients treated with anti-TNF drugs and appears independent of the type of anti-TNF drugs. Most patients develop fatigue or fever, musculoskeletal or skin symptoms, or serositis, a rarely major organ disease. The symptoms resolve after discontinuation of TNF therapy [52, 53].
Soon after the identification of TNF and production of recombinant TNF, it was recognized that the biological effects of TNF may be both injurious and beneficial. TNF can have a direct cytostatic and cytotoxic effect on human tumor cells, as well as a variety of immunomodulatory effects on various immune effector cells, including neutrophils, macrophages, and T cells. It can have a number of anti-infective and metabolic effects [54].
Today, in the era of anti-TNF drugs, the beneficial role of TNF is often in the shadow and is highlighted only after the appearance of a new adverse effect of anti-TNF drugs in clinical use.
Experimental studies have shown that TNF has important role in maintaining intestinal integrity [55]. If infection or injury occurs, TNF is rapidly released to promote the acute-phase inflammatory response (i.e., IL1, IL6-production of pro-inflammatory cytokine cascade) and to trigger the localized accumulation of leukocytes. Endothelial cells respond to TNF by releasing chemokines (IL-8, MCP-1, IP-10) and adhesion molecules (E-selectin, ICAM-1, VCAM-1). Collectively, these solubles and cell surface molecules lead to the recruitment of distinct populations of leukocytes to sites of infection/injury to eliminate the initial cause of cell injury, clear out necrotic cells and tissues damaged from the original insult and the inflammatory process, and initiate tissue repair. Indirectly, TNF also contribute to increased local blood flow and vascular permeability and regulation of coagulation. TNF increases mediators such as prostaglandins and platelet-activating factor [56].
However, in case of chronic TNF deprivation, intestinal barrier is more sensitive to infection and injury. Mice with TNF deprivation (caused by anti-TNF drugs or target mutations) failed to resist L. monocytogenes infections and died few days after the infection [57]. Mice deficient in TNF or TNFR1 are highly susceptible to Mycobacterium and Staphylococcus infection as well [54, 59]. It was found that TNF deprivation caused delayed elimination of bacterium from the spleens and livers. However the effect was dose and time dependent. The worst results were observed when anti-TNF drug was given between days 0 and 2 of infection [57].
TNF has also important role in maintaining and protecting epithelial cells from toxic injury. For instance, DSS, a toxic agent that damages the intestinal epithelia, induce development of an acute inflammation in mice, which usually resolves in a few weeks. However, when mice have blocked production of TNF (induced by deletion of TNF gene or anti-TNF drugs), the inflammation in the intestine becomes devastating and life-threatening [58].
All these studies demonstrate that homeostatic concentrations of TNF have important protective role against intestinal injury. However, homeostatic concentrations of TNF are also important for effective innate and adaptive immune responses. It was found that mice genetically deficient in TNF completely lack splenic primary B-cell follicles and cannot form organized follicular dendritic cell networks and germinal centers [59]. Thus, chronic TNF deprivation may cause disturbances in innate and adaptive immunity. TNF is an important regulator of macrophage function required to control infection and can also contribute to containment of the disease by promoting migration of immune cells and granuloma formation at sites of infection. In case of tuberculosis, an intracellular pathogen, formation of granulomas and walling off the bacteria by macrophages and T cell (central memory T cells (CCR7+CD27+) and effector memory T cells (CCR7−CD27−)), is thus one of the protective mechanisms to control tuberculosis infection. In latency, infection is contained in a nondividing state within macrophages. However, anti-TNF therapy disturbs the physiological TNF-mediated immunoinflammatory responses and causes disease reactivation or dissemination seen in patients receiving TNF blockade [38].
It is interesting that increased susceptibility to infection and a slightly increased risk for malignancy have been expected side effects of anti-TNF drugs and have been confirmed in clinical practice. However, the observation that anti-TNF drug could lead to aggravation of preexisiting autoimmune diseases or onset of a new inflammatory diseases was not expected. Although numerous experimental studies have shown complex role of TNF in the innate and adaptive immunity [60], only paradoxical side effects of anti-TNF drugs clearly demonstrated that the maintenance of homeostatic TNF concentrations is important for normal function of organism. Recently, it was confirmed that paradoxical psoriasis is caused due to the TNF deprivation. Namely, in normal condition a production of type I IFN by plasmacytoid dendritic cells (pDC) is downregulated by TNF. In case of TNF deprivation (caused by anti-TNF drugs), production of IFN by pDC is not regulated anymore. The resulting type I interferon overexpression is responsible for the skin phenotype of paradoxical psoriasis, which, unlike classical psoriasis, is independent of T cells [61].
Although our understanding of TNF has increased considerably over the past two decades, novel finding is well in line with what had been predicted from previous mouse studies. However, the observation that anti-TNF drugs could lead to aggravation of preexisiting diseases or onset of a new inflammatory diseases was not expected. Nevertheless, paradoxical reaction appears independently of the underlying disease or the type of anti-TNF drugs used and regresses upon discontinuation of therapy, which suggests that paradoxical reactions really are a side effect of TNF blockade and not de novo disease. Thus, paradoxical reactions can once again remind us that TNF physiologically possess various beneficial roles, and thus the maintenance of homeostatic TNF concentrations is important for normal function of an organism.
This work was in part supported by ARRS (Slovenian Research Agency, P3-054).
Authors declare that no financial interest or conflict of interests exists.
Classic smart home, internet of things, cloud computing and rule-based event processing, are the building blocks of our proposed advanced smart home integrated compound. Each component contributes its core attributes and technologies to the proposed composition. IoT contributes the internet connection and remote management of mobile appliances, incorporated with a variety of sensors. Sensors may be attached to home related appliances, such as air-conditioning, lights and other environmental devices. And so, it embeds computer intelligence into home devices to provide ways to measure home conditions and monitor home appliances’ functionality. Cloud computing provides scalable computing power, storage space and applications, for developing, maintaining, running home services, and accessing home devices anywhere at anytime. The rule-based event processing system provides the control and orchestration of the entire advanced smart home composition.
Combining technologies in order to generate a best of breed product, already appear in recent literature in various ways. Christos Stergioua et al. [1] merge cloud computing and IoT to show how the cloud computing technology improves the functionality of the IoT. Majid Al-Kuwari [2] focus on embedded IoT for using analyzed data to remotely execute commands of home appliances in a smart home. Trisha Datta et al. [3] propose a privacy-preserving library to embed traffic shaping in home appliances. Jian Mao et al. [4] enhance machine learning algorithms to play a role in the security in a smart home ecosystem. Faisal Saeed et al. [5] propose using sensors to sense and provide in real-time, fire detection with high accuracy.
In this chapter we explain the integration of classic smart home, IoT and cloud computing. Starting by analyzing the basics of smart home, IoT, cloud computing and event processing systems. We discuss their complementarity and synergy, detailing what is currently driving to their integration. We also discuss what is already available in terms of platforms, and projects implementing the smart home, cloud and IoT paradigm. From the connectivity perspective, the added IoT appliances and the cloud, are connected to the internet and in this context also to the home local area network. These connections complement the overall setup to a complete unified and interconnected composition with extended processing power, powerful 3rd party tools, comprehensive applications and an extensive storage space.
In the rest of this chapter we elaborate on each of the four components. In Section 1, we describe the classic smart home, in Section 2, we introduce the internet of things [IoT], in Section 3, we outline cloud computing and in Section 4, we present the event processing module. In Section 5, we describe the composition of an advanced smart home, incorporating these four components. In Section 6, we provide some practical information and relevant selection considerations, for building a practical advanced smart home implementation. In Section 7, we describe our experiment introducing three examples presenting the essence of our integrated proposal. Finally, we identify open issues and future directions in the future of advanced smart home components and applications.
Smart home is the residential extension of building automation and involves the control and automation of all its embedded technology. It defines a residence that has appliances, lighting, heating, air conditioning, TVs, computers, entertainment systems, big home appliances such as washers/dryers and refrigerators/freezers, security and camera systems capable of communicating with each other and being controlled remotely by a time schedule, phone, mobile or internet. These systems consist of switches and sensors connected to a central hub controlled by the home resident using wall-mounted terminal or mobile unit connected to internet cloud services.
Smart home provides, security, energy efficiency, low operating costs and convenience. Installation of smart products provide convenience and savings of time, money and energy. Such systems are adaptive and adjustable to meet the ongoing changing needs of the home residents. In most cases its infrastructure is flexible enough to integrate with a wide range of devices from different providers and standards.
The basic architecture enables measuring home conditions, process instrumented data, utilizing microcontroller-enabled sensors for measuring home conditions and actuators for monitoring home embedded devices.
The popularity and penetration of the smart home concept is growing in a good pace, as it became part of the modernization and reduction of cost trends. This is achieved by embedding the capability to maintain a centralized event log, execute machine learning processes to provide main cost elements, saving recommendations and other useful reports.
A typical smart home is equipped with a set of sensors for measuring home conditions, such as: temperature, humidity, light and proximity. Each sensor is dedicated to capture one or more measurement. Temperature and humidity may be measured by one sensor, other sensors calculate the light ratio for a given area and the distance from it to each object exposed to it. All sensors allow storing the data and visualizing it so that the user can view it anywhere and anytime. To do so, it includes a signal processer, a communication interface and a host on a cloud infrastructure.
Creates the cloud service for managing home appliances which will be hosted on a cloud infrastructure. The managing service allows the user, controlling the outputs of smart actuators associated with home appliances, such as such as lamps and fans. Smart actuators are devices, such as valves and switches, which perform actions such as turning things on or off or adjusting an operational system. Actuators provides a variety of functionalities, such as on/off valve service, positioning to percentage open, modulating to control changes on flow conditions, emergency shutdown (ESD). To activate an actuator, a digital write command is issued to the actuator.
Home access technologies are commonly used for public access doors. A common system uses a database with the identification attributes of authorized people. When a person is approaching the access control system, the person’s identification attributes are collected instantly and compared to the database. If it matches the database data, the access is allowed, otherwise, the access is denied. For a wide distributed institute, we may employ cloud services for centrally collecting persons’ data and processing it. Some use magnetic or proximity identification cards, other use face recognition systems, finger print and RFID.
In an example implementation, an RFID card and an RFID reader have been used. Every authorized person has an RFID card. The person scanned the card via RFID reader located near the door. The scanned ID has been sent via the internet to the cloud system. The system posted the ID to the controlling service which compares the scanned ID against the authorized IDs in the database.
To enable all of the above described activities and data management, the system is composed of the following components, as described in Figure 1.
Sensors to collect internal and external home data and measure home conditions. These sensors are connected to the home itself and to the attached-to-home devices. These sensors are not internet of things sensors, which are attached to home appliances. The sensors’ data is collected and continually transferred via the local network, to the smart home server.
Processors for performing local and integrated actions. It may also be connected to the cloud for applications requiring extended resources. The sensors’ data is then processed by the local server processes.
A collection of software components wrapped as APIs, allowing external applications execute it, given it follows the pre-defined parameters format. Such an API can process sensors data or manage necessary actions.
Actuators to provision and execute commands in the server or other control devices. It translates the required activity to the command syntax; the device can execute. During processing the received sensors’ data, the task checks if any rule became true. In such case the system may launch a command to the proper device processor.
Database to store the processed data collected from the sensors [and cloud services]. It will also be used for data analysis, data presentation and visualization. The processed data is saved in the attached database for future use.
Smart home paradigm with optional cloud connectivity.
The internet of things (IoT) paradigm refers to devices connected to the internet. Devices are objects such as sensors and actuators, equipped with a telecommunication interface, a processing unit, limited storage and software applications. It enables the integration of objects into the internet, establishing the interaction between people and devices among devices. The key technology of IoT includes radio frequency identification (RFID), sensor technology and intelligence technology. RFID is the foundation and networking core of the construction of IoT. Its processing and communication capabilities along with unique algorithms allows the integration of a variety of elements to operate as an integrated unit but at the same time allow easy addition and removal of components with minimum impact, making IoT robust but flexible to absorb changes in the environment and user preferences. To minimize bandwidth usage, it is using JSON, a lightweight version of XML, for inter components and external messaging.
Cloud computing is a shared pool of computing resources ready to provide a variety of computing services in different levels, from basic infrastructure to most sophisticated application services, easily allocated and released with minimal efforts or service provider interaction [6, 7]. In practice, it manages computing, storage, and communication resources that are shared by multiple users in a virtualized and isolated environment. Figure 2 depicts the overall cloud paradigm.
Cloud computing paradigm.
IoT and smart home can benefit from the wide resources and functionalities of cloud to compensate its limitation in storage, processing, communication, support in pick demand, backup and recovery. For example, cloud can support IoT service management and fulfillment and execute complementary applications using the data produced by it. Smart home can be condensed and focus just on the basic and critical functions and so minimize the local home resources and rely on the cloud capabilities and resources. Smart home and IoT will focus on data collection, basic processing, and transmission to the cloud for further processing. To cope with security challenges, cloud may be private for highly secured data and public for the rest.
IoT, smart home and cloud computing are not just a merge of technologies. But rather, a balance between local and central computing along with optimization of resources consumption. A computing task can be either executed on the IoT and smart home devices or outsourced to the cloud. Where to compute depends on the overhead tradeoffs, data availability, data dependency, amount of data transportation, communications dependency and security considerations. On the one hand, the triple computing model involving the cloud, IoT and smart home, should minimize the entire system cost, usually with more focus on reducing resource consumptions at home. On the other hand, an IoT and smart home computing service model, should improve IoT users to fulfill their demand when using cloud applications and address complex problems arising from the new IoT, smart home and cloud service model.
Some examples of healthcare services provided by cloud and IoT integration: properly managing information, sharing electronic healthcare records enable high-quality medical services, managing healthcare sensor data, makes mobile devices suited for health data delivery, security, privacy, and reliability, by enhancing medical data security and service availability and redundancy and assisted-living services in real-time, and cloud execution of multimedia-based health services.
Smart home and IoT are rich with sensors, which generate massive data flows in the form of messages or events. Processing this data is above the capacity of a human being’s capabilities [8, 9, 10]. Hence, event processing systems have been developed and used to respond faster to classified events. In this section, we focus on rule management systems which can sense and evaluate events to respond to changes in values or interrupts. The user can define event-triggered rule and to control the proper delivery of services. A rule is composed of event conditions, event pattern and correlation-related information which can be combined for modeling complex situations. It was implemented in a typical smart home and proved its suitability for a service-oriented system.
The system can process large amounts of events, execute functions to monitor, navigate and optimize processes in real-time. It discovers and analyzes anomalies or exceptions and creates reactive/proactive responses, such as warnings and preventing damage actions. Situations are modeled by a user-friendly modeling interface for event-triggered rules. When required, it breaks them down into simple, understandable elements. The proposed model can be seamlessly integrated into the distributed and service-oriented event processing platform.
The evaluation process is triggered by events delivering the most recent state and information from the relevant environment. The outcome is a decision graph representing the rule. It can break down complex situations to simple conditions, and combine them with each other, composing complex conditions. The output is a response event raised when a rule fires. The fired events may be used as input for other rules for further evaluation. Event patterns are discovered when multiple events occur and match a pre-defined pattern. Due to the graphical model and modular approach for constructing rules, rules can be easily adapted to domain changes. New event conditions or event patterns can be added or removed from the rule model. Rules are executed by event services, which supply the rule engine with events and process the evaluation result. To ensure the availability of suitable processing resources, the system can run in a distributed mode, on multiple machines and facilitate the integration with external systems, as well. The definition of relationships and dependencies among events that are relevant for the rule processing, are performed using sequence sets, generated by the rule engine. The rule engine constructs sequences of events relevant to a specific rule condition to allow associating events by their context data. Rules automatically perform actions in response when stated conditions hold. Actions generate response events, which trigger response activities. Event patterns can match temporal event sequences, allowing the description of home situations where the occurrences of events are relevant. For example, when the door is kept open too long.
The following challenges are known with this model: structure for the processed events and data, configuration of services and adapters for processing steps, including their input and output parameters, interfaces to external systems for sensing data and for responding by executing transactions, structure for the processed events and data, data transformations, data analysis and persistence. It allows to model which events should be processed by the rule service and how the response events should be forwarded to other event services. The process is simple: data is collected and received from adapters which forward events to event services that consume them. Initially the events are enriched to prepare the event data for the rule processing. For example, the response events are sent to a service for sending notifications to a call agent, or to services which transmit event delay notifications and event updates back to the event management system.
Event processing is concerned with real-time capturing and managing pre-defined events. It starts from managing the receptors of events right from the event occurrence, even identification, data collection, process association and activation of the response action. To allow rapid and flexible event handling, an event processing language is used, which allows fast configuration of the resources required to handle the expected sequence of activities per event type. It is composed of two modules, ESP and CEP. ESP efficiently handles the event, analyzes it and selects the appropriate occurrence. CEP handles aggregated events. Event languages describe complex event-types applied over the event log.
In some cases, rules relate to discrepancies in a sequence of events in a workflow. In such cases, it is mandatory to precisely understand the workflow and its associated events. To overcome this, we propose a reverse engineering process to automatically rediscover the workflows from the events log collected over time, assuming these events are ordered, and each event refers to one task being executed for a single case. The rediscovering process can be used to validate workflow sequences by measuring the discrepancies between prescriptive models and actual process executions. The rediscovery process consists of the following three steps: (1) construction of the dependency/frequency table. (2) Induction of dependency/frequency graphs. (3) Generating WF-nets from D/F-graphs.
In this section, we focus on the integration of smart home, IoT and cloud computing to define a new computing paradigm. We can find in the literature section [11, 12, 13, 14] surveys and research work on smart home, IoT and cloud computing separately, emphasizing their unique properties, features, technologies, and drawbacks. However, our approach is the opposite. We are looking at the synergy among these three concepts and searching for ways to integrate them into a new comprehensive paradigm, utilizing its common underlying concepts as well as its unique attributes, to allow the execution of new processes, which could not be processed otherwise.
Figure 3 depicts the advanced smart-home main components and their inter-connectivity. On the left block, the smart home environment, we can see the typical devices connected to a local area network [LAN]. This enables the communication among the devices and outside of it. Connected to the LAN is a server and its database. The server controls the devices, logs its activities, provides reports, answers queries and executes the appropriate commands. For more comprehensive or common tasks, the smart home server, transfers data to the cloud and remotely activate tasks in it using APIs, application programming interface processes. In addition, IoT home appliances are connected to the internet and to the LAN, and so expands smart home to include IoT. The connection to the internet allows the end user, resident, to communicate with the smart home to get current information and remotely activate tasks.
Advanced smart home—integrating smart home, IoT and cloud computing.
To demonstrate the benefits of the advanced smart home, we use RSA, a robust asymmetric cryptography algorithm, which generates a public and private key and encrypts/decrypts messages. Using the public key, everyone can encrypt a message, but only these who hold the private key can decrypt the sent message. Generating the keys and encrypting/decrypting messages, involves extensive calculations, which require considerable memory space and processing power. Therefore, it is usually processed on powerful computers built to cope with the required resources. However, due to its limited resources, running RSA in an IoT device is almost impossible, and so, it opens a security gap in the Internet, where attackers may easily utilize. To cope with it, we combine the power of the local smart home processors to compute some RSA calculations and forward more complicated computing tasks to be processed in the cloud. The results will then be transferred back to the IoT sensor to be compiled and assembled together, to generate the RSA encryption/decryption code, and so close the mentioned IoT security gap. This example demonstrates the data flow among the advanced smart home components. Where, each component performs its own stack of operations to generate its unique output. However, in case of complicated and long tasks it will split the task to sub tasks to be executed by more powerful components. Referring to the RSA example, the IoT device initiates the need to generate an encryption key and so, sends a request message to the RSA application, running in the smart home computer. The smart home computer then asks the “prime numbers generation” application running on cloud, to provide p and q prime numbers. Once p and q are accepted, the encryption code is generated. In a later stage, an IoT device issues a request to the smart home computer to encrypt a message, using the recent generated RSA encryption key. The encrypted message is then transferred back to the IoT device for further execution. A similar scenario may be in the opposite direction, when an IoT device gets a message it may request the smart home to decrypt it.
To summarize, the RSA scenarios depict the utilization of the strength of the cloud computing power, the smart home secured computing capabilities and at the end the limited power of the IoT device. It proves that without this automatic cooperation, RSA would not be able to be executed at the IoT level.
A more practical example is where several detached appliances, such as an oven, a slow cooker and a pan on the gas stove top, are active in fulfilling the resident request. The resident is getting an urgent phone call and leaves home immediately, without shutting off the active appliances. In case the relevant IoTs have been tuned to automatically shut down based on a predefined rule, it will be taken care at the IoT level. Otherwise, the smart home realizes the resident has left home [the home door has been opened and then locked, the garage has been opened, the resident’s car left, the main gate was opened and then closed, no one was at home] and will shut down all active devices classified as risk in case of absence. It will send an appropriate message to the mailing list defined for such an occasion.
Smart home has three components: hardware, software and communication protocols. It has a wide variety of applications for the digital consumer. Some of the areas of home automation led IoT enabled connectivity, such as: lighting control, gardening, safety and security, air quality, water-quality monitoring, voice assistants, switches, locks, energy and water meters.
Advanced smart home components include: IoT sensors, gateways, protocols, firmware, cloud computing, databases, middleware and gateways. IoT cloud can be divided into a platform-as-a-service (PaaS) and infrastructure-as-a-service (IaaS). Figure 4 demonstrates the main components of the proposed advanced smart home and the connection and data flow among its components.
Advanced smart home composition.
The smart home application updates the home database in the cloud to allow remote people access it and get the latest status of the home. A typical IoT platform contains: device security and authentication, message brokers and message queuing, device administration, protocols, data collection, visualization, analysis capabilities, integration with other web services, scalability, APIs for real-time information flow and open source libraries. IoT sensors for home automation are known by their sensing capabilities, such as: temperature, lux, water level, air composition, surveillance video cameras, voice/sound, pressure, humidity, accelerometers, infrared, vibrations and ultrasonic. Some of the most commonly used smart home sensors are temperature sensors, most are digital sensors, but some are analog and can be extremely accurate. Lux sensors measure the luminosity. Water level ultrasonic sensors.
Float level sensors offer a more precise measurement capability to IoT developers. Air composition sensors are used by developers to measure specific components in the air: CO monitoring, hydrogen gas levels measuring, nitrogen oxide measure, hazardous gas levels. Most of them have a heating time, which means that it requires a certain time before presenting accurate values. It relies on detecting gas components on a surface only after the surface is heated enough, values start to show up. Video cameras for surveillance and analytics. A range of cameras, with a high-speed connection. Using Raspberry Pi processor is recommended as its camera module is very efficient due to its flex connector, connected directly to the board.
Sound detectors are widely used for monitoring purposes, detecting sounds and acting accordingly. Some can even detect ultra-low levels of noise, and fine tune among various noise levels.
Humidity sensors sense the humidity levels in the air for smart homes. Its accuracy and precision depend on the sensor design and placement. Certain sensors like the DHT22, built for rapid prototyping, will always perform poorly when compared to high-quality sensors like HIH6100. For open spaces, the distribution around the sensor is expected to be uniform requiring fewer corrective actions for the right calibration.
Smart home communication protocols: bluetooth, Wi-Fi, or GSM. Bluetooth smart or low energy wireless protocols with mesh capabilities and data encryption algorithms. Zigbee is mesh networked, low power radio frequency-based protocol for IoT. X10 protocol that utilizes powerline wiring for signaling and control. Insteon, wireless and wireline communication. Z-wave specializes in secured home automation. UPB, uses existing power lines. Thread, a royalty-free protocol for smart home automation. ANT, an ultra-low-power protocol for building low-powered sensors with a mesh distribution capability. The preferred protocols are bluetooth low energy, Z-wave, Zigbee, and thread. Considerations for incorporating a gateway may include: cloud connectivity, supported protocols, customization complexity and prototyping support. Home control is composed of the following: state machine, event bus, service log and timer.
Modularity: enables the bundle concept, runtime dynamics, software components can be managed at runtime, service orientation, manage dependencies among bundles, life cycle layer: controls the life cycle of the bundles, service layers: defines a dynamic model of communication between various modules, actual services: this is the application layer. Security layer: optional, leverages Java 2 security architecture and manages permissions from different modules.
OpenHAB is a framework, combining home automation and IoT gateway for smart homes. Its features: rules engine, logging mechanism and UI abstraction. Automation rules that focus on time, mood, or ambiance, easy configuration, common supported hardware:
Domoticz architecture: very few people know about the architecture of Domoticz, making it extremely difficult to build applications on it without taking unnecessary risks in building the product itself. For example, the entire design of general architecture feels a little weird when you look at the concept of a sensor to control to an actuator. Building advanced applications with Domoticz can be done using OO based languages.
Deployment of blockchain into home networks can easily be done with Raspberry Pi. A blockchain secured layer between devices and gateways can be implemented without a massive revamp of the existing code base. Blockchain is a technology that will play a role in the future to reassure them with revolutionary and new business models like dynamic renting for Airbnb.
We can find in the literature and practical reports, many implementations of various integrations among part of the main three building blocks, smart home, IoT and cloud computing. For example, refer to [12–14]. In this section we outline three implementations, which clearly demonstrate the need and the benefits of interconnecting or integrating all three components, as illustrated in Figure 5. Each component is numbered, 1–6. In the left side, we describe for each implementation, the sequence of messages/commands among components, from left to right and from bottom up. Take for example the third implementation, a control task constantly runing at the home server (2) discovers the fact that all residents left home and automatically, initiates actuators to shut down all IoT appliances (3), then it issues messages to the relevant users/residents, updating them about the situation and the applied actions it took (6).
Advanced smart home implementations chart.
The use of (i) in the implementations explanation, corresponds to the circled numbers in Figure 5.
First step is deploying water sensors under every reasonable potential leak source and an automated master water valve sensor for the whole house, which now means the house is considered as an IoT.
In case the water sensor detects a leak of water (3), it sends an event to the hub (2), which triggers the “turn valve off” application. The home control application then sends a “turn off” command to all IoT (3) appliances defined as sensitive to water stopping and then sends the “turn off” command to the main water valve (1). An update message is sent via the messaging system to these appearing in the notification list (6). This setup helps defending against scenarios where the source of the water is from the house plumbing. The underlying configuration assumes an integration via messages and commands between the smart home and the IoT control system. It demonstrates the dependency and the resulting benefits of combining smart home and IoT.
Most houses already have the typical collection of smoke detectors (1), but there is no bridge to send data from the sensor to a smart home hub. Connecting these sensors to a smart home app (2), enables a comprehensive smoke detection system. It is further expanded to notify the elevator sensor to block the use of it due to fire condition (1), and so, it is even further expanded to any IoT sensor (3), who may be activated due to the detected smoke alert.
In [5] they designed a wireless sensor network for early detection of house fires. They simulated a fire in a smart home using the fire dynamics simulator and a language program. The simulation results showed that the system detects fire early.
Consider the scenario where you leave home while some of the appliances are still on. In case your absence is long enough, some of the appliances may over heat and are about to blowout. To avoid such situations, we connect all IoT appliances’ sensors to the home application (2), so that when all leave home it will automatically adjust all the appliances’ sensors accordingly (3), to avoid damages. Note that the indication of an empty home is generated by the Smart Home application, while the “on” indication of the appliance, is generated by IoT. Hence, this scenario is possible due to the integration between smart home and IoT systems.
In this chapter we described the integration of three loosely coupled components, smart home, Iot, and cloud computing. To orchestrate and timely manage the vast data flow in an efficient and balanced way, utilizing the strengths of each component we propose a centralized real time event processing application.
We describe the advantages and benefits of each standalone component and its possible complements, which may be achieved by integrating it with the other components providing new benefits raised from the whole compound system. Since these components are still at its development stage, the integration among them may change and provide a robust paradigm that generates a new generation of infrastructure and applications.
As we follow-up on the progress of each component and its corresponding impact on the integrated compound, we will constantly consider additional components to be added, resulting with new service models and applications.
IntechOpen's Authorship Policy is based on ICMJE criteria for authorship. An Author, one must:
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