Nominal chemical composition of aluminum-lithium alloy 2050-T84 (wt%) [7].
\\n\\n
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Barely three months into the new year and we are happy to announce a monumental milestone reached - 150 million downloads.
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DSSCs are emerged as a truly new class of energy conversion devices, which are representatives of the third generation solar technology. Mechanism of conversion of solar energy into electricity in these devices is quite peculiar. The achieved energy conversion efficiency in DSSCs is low, however, it has improved quickly in the last years. It is believed that DSSCs are still at the start of their development stage and will take a worthy place in the large-scale production for the future.',isbn:null,printIsbn:"978-953-307-735-2",pdfIsbn:"978-953-51-6075-5",doi:"10.5772/1757",price:159,priceEur:175,priceUsd:205,slug:"solar-cells-dye-sensitized-devices",numberOfPages:504,isOpenForSubmission:!1,isInWos:null,isInBkci:!1,hash:"05a255471069664ecf5fbf8778b92076",bookSignature:"Leonid A. 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Kosyachenko is professor of National University of Chernivtsi, Ukraine. After receiving his Doctor of Sciences Degree in Physics and Mathematics in 1983, he founded and became a head of Optoelectronics Department – the first department of this kind at Ukrainian universities. About twenty of his pupils have performed work to obtain the degrees of Candidate (Ph.D.) and Doctor of Sciences. His research interests have been in physics and technology of solar cells, semiconductor X-ray and γ-ray detectors, light-emitting and photosensitive devices. He is author (co-author) of several books and numerous scientific articles; presented reports at international scientific conferences and meetings in Germany, Italy, England, Japan, China, Greece, Spain, Belgium, Russia. He was the leader of several collaborative projects with the institutions of Russia, Belorussia and is one of the leaders of the long-term projects of the European Commission. Prof. L.A. 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Baptista and Joao Paulo Tardivo",coverURL:"https://cdn.intechopen.com/books/images_new/757.jpg",editedByType:"Edited by",editors:[{id:"85863",title:"Prof.",name:"Mauricio S.",surname:"Baptista",slug:"mauricio-s.-baptista",fullName:"Mauricio S. Baptista"}],productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}},{type:"book",id:"5501",title:"New Developments in the Pathogenesis of Rheumatoid Arthritis",subtitle:null,isOpenForSubmission:!1,hash:"857036a80d948539c72a88ea83aebf28",slug:"new-developments-in-the-pathogenesis-of-rheumatoid-arthritis",bookSignature:"Lazaros I. Sakkas",coverURL:"https://cdn.intechopen.com/books/images_new/5501.jpg",editedByType:"Edited by",editors:[{id:"49036",title:"Prof.",name:"Lazaros",surname:"Sakkas",slug:"lazaros-sakkas",fullName:"Lazaros Sakkas"}],productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}}]},chapter:{item:{type:"chapter",id:"46258",title:"Association Between HLA Gene Polymorphism and the Genetic Susceptibility of SARS Infection",doi:"10.5772/57561",slug:"association-between-hla-gene-polymorphism-and-the-genetic-susceptibility-of-sars-infection",body:'
Theoretically, any infectious disease with an infection source, transmission route, and susceptible population is able to infect any population. However, studies of human development history, especially those of infectious disease history, have clearly shown that ethnic and regional differences in susceptibility to some infectious diseases actually exist, even if their infection sources and transmission routes are the same. In terms of the 40 types of new infectious diseases that have occurred worldwide in the past 40 years, the epidemiology of some infectious diseases (including severe acute respiratory syndrome (SARS)) has been dominated by regional/territorial or ethnic oriented infections. Examples, along with the year of first occurrence, include:Ebola hemorrhagic fever caused by Ebola virus (1977), Legionnaires\' disease caused by
It is well known that the investigation of genetic predisposition is an important topic in modern medicine. It helps to clarify not only the fundamental reasons for patients’ individual differences but also the pathogenesis of many diseases. Better understanding of genetic predisposition can provide prevention and treatment strategies for the corresponding diseases, an especially important consideration for individualized disease prevention and treatment. Modern medical studies have shown that disease is a specific life process formed by interactions of environmental factors (external) and the human body (internal). Genetic factors are the major basis of an organism’s reactivity, including defensive immunity, the functional states of the nervous and endocrine systems, nutritional status, psychological factors, age, gender, etc. Among these numerous factors, genetic factors predominate because, besides external factors, immune responses and neuropsychological and endocrine functions are constrained by genetic factors. Even nutrition status is not based only on the quality and quantity of the exogenous nutrient supply. It is also influenced by digestion, absorption, and utilization functions controlled by genetic factors. Gender and age (an organism’s reactive characteristics at different ages) are even more determined by genetic factors. Therefore, organism reactivities determined by genetic factors have been collectively called genetic predisposition. Numerous studies have demonstrated that many severe diseases, such as cancer, atherosclerosis, coronary heart disease, diabetes, schizophrenia, and high blood pressure, have significant genetic predispositions. In addition, some infectious diseases caused by bacteria and viruses have significant individual genetic predispositions. The human immune and genetic system most closely related to genetic predisposition to disease is the major histocompatibility complex (MHC).
Human MHC is also named as human leucocyte antigens (HLA) system, which codes for the most polymorphic antigen system that is known. The correlation of HLA and human diseases has been studied for nearly 40 years. The rapid development of advanced technologies in modern molecular biology and their wide applications to HLA studies have effectively promoted studies of HLA mechanisms and their associations with disease, leading to significantly increased accuracy of disease association analysis. Many alleles have been identified as being primarily associated with certain aspects of diseases. For example, in autoimmune diseases, Hodgkin\'s disease and HLA-A1 have relative risk (RR) of 32. 0; congenital adrenal hyperplasia and HLA-B47 have relative risk of 15. 4; ankylosing arthritis and HLA-B27 have relative risk of 87. 4; Reiter\'s syndrome and HLA-B27 have relative risk of 37. 0; acute anterior uveitis and HLA-B27 have relative risk of 10. 4; psoriasis and HLA-Cw6 have relative risk of 13. 3, etc. In infectious diseases, Hepatitis B virus associated glomerulonephritis and HLA-DQB1*03 have relative risk of 12. 90; infection and development of AIDS are highly correlated with HLA-A29, HLA-B35, and B57; infection and development of flu are closely correlated with HLA-A2 antigen; hepatitis B is separately correlated with HLA-B13, B8, DR7, DR13; and infection and development of hepatitis C are closely correlated with HLA-DRB1*0402, DRB1*12 and DQB1*0301. Therefore, correlation studies of HLA and different diseases can help the identification and classification of diseases. The studies could also be treated as auxiliary diagnostic tools. While conducting such studies, researches could further clarify the relationships between diseases and genetic inheritance, provide genetic consulting services to specific families, detect HLA-linked disease genes, and, most importantly, provide early predictions and preventions of these diseases.
SARS virus is a recently discovered infectious pathogen that can cause severe human diseases, and, to date, we know little about it. Knowledge of its occurrence and development pattern remains limited, and studies of its pathogenesis, treatment, and prevention strategies remain limited. Considering that SARS displays significant regional/territorial and ethnic and individual specificity, and that the SARS-associated antigen epitopes are almost all related to HLA antigen recognition, as inferred by known SARS gene and protein sequences, we hypothesize that there is a close correlation between the occurrence of a SARS epidemic and the HLA system.
Previous studies demonstrated that although SARS-CoV and other known coronaviruses have less than 40%-50% homology in amino acid sequence, their structures and functions are similar to those of other known coronaviruses. The antisera of transmissible gastro-enteritis virus (TGEV), murine hepatitis virus (MHV), Feline infectious peritonitis virus (FIPV), and 229E human coronavirus can inhibit the growth of cultured SARS viruses. In the known OC43 and 229E coronavirus strains, HLA-A3. 1was shown by some studies to be the receptor of OC43 and aminopeptidase N (APN), also known as metalloproteinases or CD13, and the co-receptor of human coronavirus 229E and cats/pigs coronavirus. A recent study using molecular 3D structure simulation showed that CD13 also interacted with the S protein of SARS virus. Carcinoembryonic antigen (CEA) is the S protein receptor of human/rats coronavirus. The invasion, infection, and disease caused by OC43 must be accompanied by the presence and expression of HLA-A3. 1. The invasion, infection, and disease caused by coronavirus 229E must be accompanied by the presence and expression of aminopeptidase N. On the other hand, carcinoembryonic antigen may be the required co-receptor for many coronavirus infections. Theoretically, HLA-A3.1 is the susceptible gene of SARS coronavirus, and individuals without this susceptible gene are not easily affected or have resistance to the disease.
SARS is a highly contagious disease with high disease incidence and mortality rate. The limited diffusion mode based on East and Southeast Asian countries has indicated the existence of susceptible genes in these populations. This has been corroborated in numerous clinical case-control studies, but some other studies yielded opposite results. In the 2 months immediately following the last outbreak of SARS in Taiwan, Taiwan scholars recruited 658 employees from hospitals who had just experienced their initial or the most severe SARS infections to help the investigation of related infectious and genetic factors of SARS-CoV. They used an enzyme immunoassay to test the infections of SARS-CoV and then employed western blot analysis, antibody neutralization, and commercial SARS tests for verification. Risk evaluations were prepared through questionnaires and sequence-specific oligonucleotide probe analysis of the human leukocyte antigen (HLA) allele. The study showed that 3% (20/658) of the participants were positive. A female nurse with a subclinical case was identified. Identified risk factors of SARS-CoV infection included working in the same building, such as hospital emergency rooms and infection wards, direct nursing for SARS patients, and carrying the HLA-Cw*0801 allele. The SARS-CoV infection ratio of homozygous and heterozygous Cw*0801 carriers was 4. 4:1 (95% confidence interval, 1. 5-12. 9;
Another study in the Taiwan population also proved the correlation between HLA and SARS. The researchers used PCR-sequence specific oligonucleotides probe (SSOP) to study the genotyping of HLA type I and type II alleles. The study population included 37 suspected SARS cases (28 fever patients were excluded from SARS) and 101 non-infected medical staff who might have been exposed to SARS-CoV. Another control group contained 190 healthy, non-related Taiwanese people. Initially, during the analysis of SARS infected patients and the high-risk medical staff, the researchers found that HLA-B*4601 (OR = 2. 08,
Another study also showed that SARS infection was correlated with Chinese HLA. This study determined a strong correlation between SARS development and HLA-B*0703 (OR, 4. 08; 95% CI, 2. 03-8. 18;
Evidences of the SARS-HLA correlation has also been found in other Asian populations. In Vietnam 44 out of 62 SARS patients participated in a study. The control groups were 103 individuals who had contact with SARS patients and 50 individuals who had not. Compared with the control groups, HLA-DRB1*12 occurred more often in the SARS patient group (corrected
However, some studies resulted in the opposite conclusions. Xiong P,
Early in Feb. 2005 on an annual meeting of Association for the Advancement of Science (AAAS), an American microbiologist Kathryn Holmes, who had long been engaged in coronavirus researches, pointed out that it was not impossible to have another outbreak of severe acute respiratory syndrome (SARS) in the world like the one 2 years ago. The SARS-CoV used to spread in populations might only exist in laboratory samples. Her words shocked the world. It has been 10 years since the SARS pandemic. Many scholars conducted broad and indepth studies but have not achieved breakthroughs with respect to the origin of SARS CoV. On the contrary, the new influenza A virus (H1N1) that spread worldwide in April 2009 was studied thoroughly during the first 2 months of its spreading. It has 8 types of genes coming from 4 pedigrees and is very similar to the North American popular triple ligand swine H1N1 virus. Different from other viruses, there has been no SARS patient other than lab infections after the widespread infections in January 2004. SARS-CoV does not exist in nature or people now. Hence the natural SARS epidemic history has some extraordinary abnormalities. What are the reasons? The most important reason could be that there is no direct ancestor of SARS-CoV in nature. It had an “unusual evolution”. It is very likely that it was “unnaturally” introduced to populations, so it did not follow the normal epidemic transmission rules.
SARS-CoV has an unordinary phylogeny. It has a fast and obvious “reverse evolution. ”“Reverse evolution” is defined as “regaining the ancestor’s state” and is an evolution component that commonly exists in the biosphere, including microbial communities. In the long course of natural evolution, “reverse evolution” might be largely supplemental and it might coordinate “forward evolution” , acting as the twists and turns of mainstream evolution. However, the “reverse evolution” of SARS-CoV appears earlier and more powerfully, and it has more presence and lasts longer. In the early state of its epidemic, it had already lost the genes related to host adaptability (characteristic 29-ntORF8 gene) and presented “reverse evolution” of key amino acids on the virulence and transmission-related receptor’s binding site. The SARS-CoV outbreak in 2003-2004 in Guangzhou was phylogenetically closer to earlier viruses in the 2002-2003 epidemics than the later viruses. Under natural conditions, it is not possible that the adaptive evolution of Bt-SLCoV could have developed to the human level through carnivores in such a short time. Therefore, the only possible explanation is that SARS-CoV was produced through “unusual evolution (UE),” via processes such as like GM technology.
There have already been some debates about the technical maturity of transforming animal virus to human virus (for example, GM technology). However, it would be indisputable now, as in May and June 2012, a top international journal published 2 papers, which shocked the international natural science field in 2011 and clarified this problem by facts. However, according to some international information sources, in 2000 or earlier some scientists were studying or had already mastered these technologies at those early dates.
Therefore, Xu D
The investigation of the SARS in-out flow epidemic transmission network in mainland China shows that Beijing and Guangdong were the places where the exported cases and self-transmission cases were the most severe. Guangzhou was the origin of the transmission of SARS and the main import source of the early-stage regional cases of infection in most areas, but it did not cause significant radiation of transmission to its neighboring regions. Nevertheless, the in-out flow between Beijing and its neighboring regions did not start until the middle to late stages of the epidemic transmission. The transmission, however, was able to radiate significantly across regions. There have been no other cases reported among people and among animals except for laboratory infections and 4 mild infections reported in Guangzhou in December 2003 and January 2004. This is different from the trend of typical epidemic transmissions, and it is different from the correlation between the HLA gene polymorphism and SARS, as demonstrated by many studies. The HLA alleles that are closely related to the infection of SARS, such as B*4601, B*5401, Cw0801, and DRB1*0301, as found among populations from Taiwan, Hong Kong, and mainland China, are types of HLA alleles that are relatively common in the Chinese population. Why were only people in limited regions infected? Further, why did the transmission disappear rapidly?
The study of Xu D
Supported by grants from the State Key Development Program for Basic Research of China (No.2003CB515509 and 2009CB522401) and from National Natural Scientific Foundation of China(No.81070450 and 30470751) to Dr. X.-Y.Z.
High strength heat hardening aluminum alloys are relevant for aeronautical applications due to their excellent interaction between chemical, physical and mechanical properties, and weight reduction. Such integration results in structures with maximum efficiency and fuel economy for aircraft in operation, based on this a large number of alloys has been developed in response. The aircraft industry is the symbols of technological generation and has developed improvements in structural integrity with the replacement of aluminum alloys, safer aircraft, and reduction of the costs of manufacturing, maintenance and operation. Therefore, this technological sector develops research for optimization of projects that result in lighter aircraft with the direct consequence in the fuel consumption and operationally more viable.
\nHighlighting of the substitution of structural and fuselage materials, the proposal for the manufacture of aluminum-lithium alloys showed up attractive, according to reference [1], the presence of lithium (Li) in aluminum (Al) alloys simultaneously increases the elastic limit and decreases density because every 1% Li the density is reduced by about 3% and the elastic limit increased by 6% thus, the Al-Cu-Li alloy 2050-T84 get up as a substitution attractive aluminum-magnesium-zinc alloy 7050-T7451.
\nThe improvement of aeronautical alloys induces the industry to produce materials with lower density and high strength, in this way the aluminum-copper-lithium alloys. The first generation, designated as 2020, was produced in the United States in the 1950s. The manufacture of these alloys was abandoned due to low ductility and poor fracture toughness. The second generation, composed of 2090, 2091 and 8090 alloys, was created as a proposal to improve the resistance to corrosion and its mechanical properties, however, it resulted in alloys with excessive anisotropy and low resistance to stress corrosion cracking. Recently, alloys of the third generation, composed of 2094, 2097, 2099, 2196, AA2197 and 2050 alloys, have been developed for military and aerospace applications and when compared Al-Li alloys of previous generations present high resistance to static and tolerance to damage [2].
\nThe resistance of corrosion of 2xxx series alloys is dependent on their chemical composition and the effect of their elements on the oxide layer. For practical applications, the presence of alloying elements such as Cu, Mg, Mn, Zn, Li, and Si have the purpose of increasing mechanical strength or specific resistance, however these elements form intermetallic particles or precipitated, which are harmful to the corrosion properties of the material, due to the formation of a thinner and more conductive oxide layer that allows the occurrence of cathodic reactions. Avoiding the appearance of these precipitates would be the most effective measure of preventing corrosion, however, the precipitates are important to increase the mechanical properties of the material [3].
\nThese alloys are fabricated by two processes: heat treatments and mechanical forming. Heat treatments perform considerable influence on the corrosive behavior of aluminum alloys as they may result in localized chemical effects and become the material resistant to localized corrosion. When there is no complete solubilization of the alloying elements, the result is a non-uniform microstructure that favors susceptibility to corrosion. The mechanical forming influences the grain morphology and the distribution of the constituent particles of the alloy. The deformation of the material can generate failures in atomic ordering and weaken the oxide layer, allowing localized corrosion [4].
\nThe common forms of corrosion in aluminum alloys are by pits and intergranular, the latter coming from the process of stress corrosion cracking (SCC) and occurs in the contours of grains resulting in poor mechanical properties and brittle fracture of the component when still subject to mechanical requests. The pitting corrosion occurs in isolated points on the metal surface and growth to the inside, often through the material [5].
\nThere are several researches about the behavior of the Al-Cu-Li 2050-T84 alloy, and the microstructural characteristics are presented using the transmission electron microscopy (TEM) technique that showed the presence of precipitates influencing the increase of the strength mechanical of the alloy, fracture toughness, fatigue and corrosion fatigue at room temperature (23°C), cryogenic (−60°C) and saline environment [6]. The corrosion evaluation was carried out with the potentiodynamic polarization tests and indicated that the alloy in question has a higher value of corrosion potential and pit, when compared to another Al-Li alloys, favoring the formation and growing of pits become pointed enough to results in stress concentration and a crack nucleation contributing directly to the fatigue life of aluminum alloys used in aircraft structures and can result in accelerated failure. However, the results obtained in air, salt spray at 3.5 and 5% NaCl and aqueous saline solution with 3.5% NaCl showed a clear difference in the region of the threshold, however, for the region of Paris independently of the environment, the FCG rates are quite similar.
\nAluminum alloys (Al) of the 2xxx series have Copper (Cu) and Lithium (Li) as the main alloying elements and require heat treatments of solubilization, precipitation and aging to improve your mechanical properties. Specifically, the Al-Cu-Li 2050 ternary alloy has density of 2.71 g∕cm3 [7] and presents precipitates responsible for the increase of mechanical strength as \n
Bright field STEM micrograph and respective (EDS) elemental mapping of Al-K, Mn-K, Mg-K, Cu-K and Zn-K in 2050-T84 alloy, showing the composition of precipitates at the grain boundaries (larger) and inside the grain (smaller) on a nanometric scale; bright field TEM micrograph [
The presence of S′ in the metal matrix restrains the movements of dislocations and promotes a homogeneous deformation and increases the strength of the alloy. According to Deng et al. [9], the presence of lithium (Li) favors the formation of free zones precipitate (FZP) in the grain boundary, Figure 2, which affects fracture properties, increasing the ductility of the material.
\nImagem de MET evidenciando a zona livre de precipitados da liga de alumio-lítio 2050-T84 [
Evaluating from corrosion, these properties are not suitable as other aluminum alloys, because under certain conditions they may favor intergranular corrosion and resulting of the embrittlement the material [10].
\nBy exposing aluminum alloys to the presence of alkaline factors or acidic factors such as chemical ions composed of chlorides or fluorides, e.g., their alumina oxide layer \n
Presence of precipitates such as \n
Nucleation: is tiny, rapid and leads to the formation of metastable pits due to adsorption of the aggressive ions on the metal surface followed by the rupture of the alumina oxide layer in the most susceptible regions;
Meta-stable formation: the growth is not fully established, however, is determined by the exposure of the free surface of the metal and by the geometry of the boundary defined during the breakage of the film passive oxide;
Stabilization: occurs after the formation of corrosion products at the entrance of the pits that holds the ions and after several days of exposure, they stop growing and are again passivated. However, if exposed to the medium again the growth of new pitting nucleation sites.
\nFigure 3 shows images obtained by SEM reveal the presence of pitting corrosion sites in 2050-T84 alloy when exposed to saline solution. This corrosion process occurred near precipitates and salt crystals deposited on the surface of a sample analyzed by the potentiodynamic polarization tests.
\nImages of 2050-T84 surface alloy by scanning electron microscopy after the potentiodynamic polarization tests. In (a) shows pits and salt crystals in corrosion process, in (b) detail of pit.
With corrosion evaluation criteria, the addition of lithium is very harmful because this element is highly reactive and additions of about 3% in aluminum causes changes in pitting potential \n
This corrosive behavior can be investigated by Evans diagram, obtained through potentiodynamic polarization tests, which provides values for potential corrosion \n
Corrosion fatigue is the term used to denote the damage and failure of components subjected to cyclic loading in a brittle environmental resulting from the interaction between plastic deformation and localized chemical or electrochemical reactions [3, 4, 5]. Aluminum alloys have relatively low corrosion resistance if exposed to NaCl salt spray due to the presence of precipitates from heat treatments, which have less corrosion resistance than the matrix. When there is remaking of these precipitates in the grain boundaries there is an increase in susceptibility to intergranular corrosion. Avoiding the emergence of these precipitates would be the most effective measure of preventing corrosion, however, they are important in enhancing the monotonic mechanical properties of the material [3]. For the reduction of damage caused by the environment, materials less susceptible to corrosion of the environment or the application of surface protection processes such as paints and galvanizing should be used.
\nIn addition to the development complexity of the corrosion fatigue testing methodology, the fatigue crack growth presents adverse behavior in some moments. The crack increases rapidly and in others, cases remain at the same length for hours or even days [3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13]. Interpretation for the fast growth crack, due to the embrittlement of metal alloys subjected to corrosion fatigue, is based on the mechanism of hydrogen embrittlement. Such mechanisms occur due to the reduction of hydrogen particles and the adsorption of atoms at critical locations such as pits, voids between the crack walls and towards the crack tip. Hydrogen atoms, even at room temperature, may be interstitially lodged in the metal crystal or even in grain boundaries, resulting in drastically reducing the toughness and ductility of the material [13].
\nAccording to the reference [14] hydrogen induces the appearance of delayed fractures as a consequence of the appearance of numerous surface cracks, which are nucleated throughout the process of leaving hydrogen in the gaseous form of the material. Thus, the FCG rate is accelerated due to the action of hydrogen embrittlement and the presence of oxides that alter the crack closure mechanism.
\nThe plastic deformation at the crack tip causes the oxide layer to break down by exposing the free surface to the corrosive environments and allows for pit. The interior of the pit is more anodic than the rest of the material and in this way the corrosion proceeds to the interior making the pit pointed enough to produce intense concentration of tension and to initiate a crack. If the layer of the repassivation reaction does not occur, the propagation of the crack is continuous [15].
\nAdversely, there is a possibility that some oxide residue caused by corrosion or salt crystals deposited in front of the crack will deform plasticize the crack tip [16] and with the decrease of the cyclic load the crack tip will not move, it is very thin and closed with a very small radius, as shown in Figure 4, and with increased static loading the crack opens elastically and becomes blunting. Under these conditions if the stress at the crack tip is less than or equal to the fracture stress, the crack will not propagate. The final result of the crack propagation rate is due to competition among all of these factors discussed [6].
\nSchematic illustration of the wedging effect mechanism induced by corrosion products [
During the fatigue corrosion tests, the crack growth is controlled by the maximum stress intensity factor \n
The action of chemical elements at the crack tip was studied by Wang [16] in corrosion fatigue tests with 3.5% NaCl in aluminum alloys. The authors verified there was a variation of the stress intensity factor at the threshold and increase in the fatigue crack growth rate (da/dN) and also concluded that the ratio between stresses has an influence in the region close to the threshold and as the ratio increases, the variation of the factor of intensity decreases.
\nThe material of this study is an aluminum-lithium alloy 2050 with the T84 heat treatment indicates that it was obtained through the solubilization steps with the temperature between 480 and 540°C, cold rolling, stress relief and natural aging hardening as shown in Ref. [7] and the chemical composition described in Table 1.
\nLi | \nCu | \nMg | \nMn | \nZr | \nAg | \nSi | \nTi | \nCr | \nFe | \nNi | \nZn | \nAl | \n
---|---|---|---|---|---|---|---|---|---|---|---|---|
0.87 | \n3.54 | \n0.31 | \n0.37 | \n0.08 | \n0.37 | \n0.03 | \n0.03 | \n0.06 | \n30* | \n0.02 | \n<1* | \nBase | \n
Nominal chemical composition of aluminum-lithium alloy 2050-T84 (wt%) [7].
*ppm ? part per million
This material it was provided as plate with 800 × 550 × 50 mm from which they were extracted specimens for potentiodynamic polarization, tensile, thoughness, fatigue and corrosion fatigue tests. Potentiodynamic polarization performed in triplicate followed the ASTM G61 [18] standard and the measurements were made in the range −1.2 to −0.2 V with a potential sweep rate of \n
Tensile tests were carried out according to the ASTM E8/E8M [19] standard, using 05 specimens removed longitudinally to the sheet rolling direction, see Figure 5. The fracture thoughness were carried out according to the ASTM E399 [20] standard in in MTS servo-hydraulic testing machine, with the clip gage to measure the crack size using the compliance technique and specimens with C(T) geometry removed at direction TL and LT, thickness (B) 25.4 mm and geometry and dimensions shown in Figure 6. Both tests were conducted at 23 and −60°C at a chamber with liquid nitrogen.
\nDimensions in millimeter of specimens to tensile test at room and cryogenics temperatures.
Geometry and dimensions of specimens to fracture toughness tests at room and cryogenics temperatures (thickness (B) 25.4 mm).
Fatigue crack growth and corrosion fatigue were performed in air with a frequency of 15 Hz, 3.5 and 5% NaCl salt spray and with 3.5% NaCl aqueous saline solution. Specimens with C(T) geometry and extracts in the LT direction according to the specifications of ASTM E399 [20], thickness (B) 12.5 mm were tested in a MTS servo-hydraulic machine, according to the specifications of ASTM E647 [21], with sinusoidal waveform, extensometry and load ratio \n
Where da/dN: fatigue crack growth rates, C: constant, \n
The corrosion fatigue tests in 3.5 and 5% salt spray were conducted with C(T) specimens, see Figure 6, mounted inside fog cell coupled to a salt spray generation and conditioning device consisting of an air compressor, a reservoir of saline solution and nebulizer. Figure 7(a) shows the test specimen whose flow rate was 0.084 ml/s. The threshold values for air and salt spray tests were estimated from a linear regression of the fatigue crack growth rate curve as a function of the variation of the stress intensity factor \n
Fatigue crack growth specimens mounted for testing. In (a) for tests in salt spray with 3.5 and 5% NaCl (thickness (B) 12.5 mm). In (b) for tests in aqueous solution with 3.5% NaCl (thickness (B) 6 mm).
Results of potentiodynamic polarization shown in Figure 8(a) and from the curve shown in Figure 8(b) the \n
Potentiodynamic polarization plots obtained for aluminum-lithium in (a) corrosion potential; in (b) pitting potential.
Alloy | \n\n | \nLog | \n\n | \n
---|---|---|---|
2050-T84 | \n−0.6581 | \n−3.963 | \n−0.601 | \n
2198-T851 | \n−0.667 | \n−2.711 | \n−0.587 | \n
Results obtained of potentiodynamic polarization for aluminum-lithium alloys 2198 T851 and 2050 T84.
Evaluating the results of \n
Tensile and thoughness properties of alloy 2050-T84.
Presence of precipitates \n
Evaluation of the mechanical and tenacity behavior of high strength aluminum alloys is performed according to the types of stresses requested and operating temperature because they are materials used in structures of vehicles, pipelines, pressure vessels, aircraft fuselage and reservoir of storage hydrogen and oxygen liquids that are mechanically requested at ambient and/or cryogenic temperatures as described by reference [11]. Such applications are possible because of their low density, high specific strength, non-magnetism, stable microstructure, high elastic limit, and ductility retention.
\nMechanical behavior and fracture toughness of the 2050-T84 alloy at the air at 23°C and cryogenic at −60°C are shown in Figure 9. Results showed no significant difference with temperature variation and can be attributed to the retention of ductility at cryogenic temperatures due to the face-centered cubic crystal structure (FCC) and the and the freezing of impurities with low melting point and rich in hydrogen (H), sodium (Na) and potassium (K), dispersed in the Al matrix [15].
\nInfluence of temperature on fracture toughness \n
The plots are shown in Figure 10 and was determined the coefficient found by the extension of the straight line as shown Table 3. Evaluating the threshold \n
da/dN × Δ
Condition | \nParis | \nR2\n | \n\n\n | \n
---|---|---|---|
Air | \n\n\n | \n0.99 | \n2.92 | \n
Salt spray 3.5% | \n\n\n | \n0.99 | \n4.85 | \n
Salt spray 5% | \n\n\n | \n0.99 | \n3.35 | \n
Aqueous solution | \n\n\n | \n0.97 | \n— | \n
Aluminum-lithium’s constant C and m for the Paris-Erdogan equation and threshold.
Lowest threshold value was found with the test conducted in air. This is due to the common factors influencing the crack closure, such as the induction of plasticity, the formation of oxides in front of the crack and/or the roughness generated on the fracture surface, due to the severity of the loading. The curve obtained with a salt spray of 3.5% NaCl presented a higher threshold indicating a significant influence of the action of the oxides residues or salt crystals deposited on the surface of the crack that possibly induced the plastic deformation and avoided the embrittlement action of the fog. Considering that the 5% NaCl test curve accelerates discretely from the region close to the threshold, is possible that hydrogen embrittlement and anodic dissolution acted preferentially in the crack growth process, forming surface oxides and increasing the fatigue crack growth rate in the Paris region by reducing the threshold values.
\nIn these conditions the fracture micromechanism occurred due to the movement of the slip bands that favored the rupture of the oxide layer and the surface of the metal was exposed to the saline solution making it anodic, whereas the regions adjacent to the sliding became cathodic forming an electrochemistry heaped load that, together with hydrogen embrittlement, accelerated crack growth and resulted in a lower threshold. Although no threshold result was obtained with tests conducted in aqueous saline solution, the final result of the crack propagation rate in this region is due to the competition between hydrogen embrittlement and the plasticity induced by crystals of salt and oxides, therefore it is a very complex micromechanism.
\nAccording to Wang [16], when the corrosion occurs simultaneously with fatigue loading, is expected to result in reduced material properties due to slip bands on the material, grain handling, free surface corrosion at the crack tip and crack closure, however, this did not occur with the 2050-T84 alloy. These results show that there is a clear difference of the threshold region when the tests were conducted in salt spray, however, for the Paris region regardless of the environment, the rates of FCG are quite similar. For Moreto et al. [6] this behavior occurs for two reasons, the first is related to the process of crack growth being purely mechanical because, a short time of interaction with the environment and the second reason is based on the concepts of crack closure, which when fully opened, the corrosion products formed within the crack lead to contact between the surfaces by raising the crack closing tension intensity factor.
\nThe 2050-T84 alloy with additional lithium was developed to have improved mechanical properties to be applied to aircraft structural components. The results of potentiodynamic potential shows that this alloy requires less amount of energy yielded for rupture of the oxide layer, however, once corrosion is started its evolution is rapid. Corrosion process occurred near precipitates \n
Fatigue corrosion behavior of this material indicates that the competition between hydrogen embrittlement and the plasticity induced by salt crystals and cracking tip oxides are beneficial for FCG. This behavior occurs for to process of crack growth being purely mechanical and the corrosion products formed within the crack lead to contact between the surfaces by raising the crack closing tension intensity factor.
\nThe authors would like to thanks CAPES for the financial support, EMBRAER supply the material and the Department of Materials, São Carlos School of Engineering, University of São Paulo for the use of the experimental facilities.
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Teguete, Y. Traore, A. Sissoko, M. Y. Djire, A. Thera, T. Dolo, N. Mounkoro, M. Traore and A. Dolo",authors:[{id:"87496",title:"Dr.",name:"Ibrahima",middleName:null,surname:"Teguete",slug:"ibrahima-teguete",fullName:"Ibrahima Teguete"}]},{id:"27121",doi:"10.5772/27439",title:"Clinical Risk Factors for Preterm Birth",slug:"clinical-risk-factors-for-preterm-birth",totalDownloads:8765,totalCrossrefCites:9,totalDimensionsCites:19,abstract:null,book:{id:"776",slug:"preterm-birth-mother-and-child",title:"Preterm Birth",fullTitle:"Preterm Birth - Mother and Child"},signatures:"Ifeoma Offiah, Keelin O’Donoghue and Louise Kenny",authors:[{id:"68552",title:"Dr.",name:"Ifeoma",middleName:null,surname:"Offiah",slug:"ifeoma-offiah",fullName:"Ifeoma Offiah"},{id:"70166",title:"Prof.",name:"Louise",middleName:null,surname:"Kenny",slug:"louise-kenny",fullName:"Louise Kenny"},{id:"74717",title:"Dr.",name:"Keelin",middleName:null,surname:"O'Donoghue",slug:"keelin-o'donoghue",fullName:"Keelin O'Donoghue"}]},{id:"27122",doi:"10.5772/27539",title:"Psychobiological Stress and Preterm Birth",slug:"psychobiological-stress-and-preterm-birth",totalDownloads:2997,totalCrossrefCites:2,totalDimensionsCites:14,abstract:null,book:{id:"776",slug:"preterm-birth-mother-and-child",title:"Preterm Birth",fullTitle:"Preterm Birth - Mother and Child"},signatures:"Curt A. Sandman, Elysia P. Davis and Laura M. Glynn",authors:[{id:"70534",title:"Prof.",name:"Curt",middleName:null,surname:"Sandman",slug:"curt-sandman",fullName:"Curt Sandman"},{id:"74174",title:"Prof.",name:"Laura",middleName:null,surname:"Glynn",slug:"laura-glynn",fullName:"Laura Glynn"},{id:"74177",title:"Prof.",name:"Elysia",middleName:null,surname:"Davis",slug:"elysia-davis",fullName:"Elysia Davis"}]},{id:"22230",doi:"10.5772/21555",title:"Tubal Damage, Infertility and Tubal Ectopic Pregnancy: Chlamydia trachomatis and Other Microbial Aetiologies",slug:"tubal-damage-infertility-and-tubal-ectopic-pregnancy-chlamydia-trachomatis-and-other-microbial-aetio",totalDownloads:5569,totalCrossrefCites:3,totalDimensionsCites:9,abstract:null,book:{id:"233",slug:"ectopic-pregnancy-modern-diagnosis-and-management",title:"Ectopic Pregnancy",fullTitle:"Ectopic Pregnancy - Modern Diagnosis and Management"},signatures:"Louise M. Hafner and Elise S. Pelzer",authors:[{id:"43697",title:"Prof.",name:"Louise",middleName:null,surname:"Hafner",slug:"louise-hafner",fullName:"Louise Hafner"},{id:"43707",title:"Ms.",name:"Elise",middleName:null,surname:"Pelzer",slug:"elise-pelzer",fullName:"Elise Pelzer"}]},{id:"62277",doi:"10.5772/intechopen.79361",title:"Basic Antenatal Care Approach to Antenatal Care Service Provision",slug:"basic-antenatal-care-approach-to-antenatal-care-service-provision",totalDownloads:2999,totalCrossrefCites:6,totalDimensionsCites:9,abstract:"Globally, antenatal care is advocated as the cornerstone for reducing children’s deaths and improving maternal health. The basic antenatal care approach is used in the public health institutions in South Africa to provide healthcare services to the pregnant women. The basic antenatal care approach is a modified version of the focused antenatal care approach that was recommended by researchers during 2001 and adopted by the World Health Organisation in 2002 following realisation that traditional antenatal care programmes that were meant for developed countries were poorly implemented and largely ineffective when used in developing countries. The basic antenatal care approach is listed as one of the priority interventions for reducing maternal and child mortality in the country and is recommended as the minimum level of antenatal care that every pregnant woman should receive. Every site where pregnant women make contact with healthcare services should provide antenatal care services daily using this approach so that the first antenatal care visit consultation takes place as soon as the pregnancy has been confirmed or the very first time that a pregnant woman visits a health facility. The introductions of the basic antenatal care approach have been a positive milestone for South Africa.",book:{id:"7259",slug:"selected-topics-in-midwifery-care",title:"Selected Topics in Midwifery Care",fullTitle:"Selected Topics in Midwifery Care"},signatures:"Thembelihle Sylvia Patience Ngxongo",authors:[{id:"243711",title:"Dr.",name:"Thembelihle Sylvia Patience",middleName:null,surname:"Ngxongo",slug:"thembelihle-sylvia-patience-ngxongo",fullName:"Thembelihle Sylvia Patience Ngxongo"}]}],mostDownloadedChaptersLast30Days:[{id:"57672",title:"Ectopic Pregnancy: Diagnosis, Prevention and Management",slug:"ectopic-pregnancy-diagnosis-prevention-and-management",totalDownloads:2716,totalCrossrefCites:0,totalDimensionsCites:3,abstract:"An ectopic pregnancy (EP) falls within the area of the gynecological emergency and/or reproductive management of women, which is the implantation of fertilized ovum outside the endometrial cavity. The etiology of EP concentrated mainly on factor causes delayed transport of the fertilized ovum through the fallopian tube (favors implantation in tubal mucosa), thus giving rise to EP. This chapter describes the causes, diagnosis, prevention and the guidelines to improve the management of women who may have an EP, a major gynecological emergency that is a cause of morbidity or even mortality of women in first trimester. Three types of EP are diagnosed: tubal, cervical and ovarian; tubal is the main type. Identification of the signs and symptoms of acute and chronic EP in women, involving classical clinical trials or other symptoms common to early pregnancy, as well as evaluating the most important congenital and acquired factors related with EP, were discussed. Explanation of the most accurate methods used to diagnose the pregnancy including serum beta hCG and progesterone levels, medical history, ultrasonography, pregnancy tests and laparoscopy was also clarified. The evaluation of the most effective management tools of EP, including methotrexate administration and surgery (laparotomy and laparoscopy), was obviously explained.",book:{id:"5937",slug:"obstetrics",title:"Obstetrics",fullTitle:"Obstetrics"},signatures:"Talal Anwer Abdulkareem and Sajeda Mahdi Eidan",authors:[{id:"201127",title:"Prof.",name:"Talal",middleName:"Anwer",surname:"Abdulkareem",slug:"talal-abdulkareem",fullName:"Talal Abdulkareem"}]},{id:"56365",title:"Massive Postpartum Hemorrhage: Protocol and Red Code",slug:"massive-postpartum-hemorrhage-protocol-and-red-code",totalDownloads:2513,totalCrossrefCites:1,totalDimensionsCites:1,abstract:"Postpartum hemorrhage (PPH) is the leading cause of maternal death. In developing countries, approximately 8% of maternal death is caused by PPH. Protocols should provide a standardized approach to evaluate and monitor the patients. A standard protocol must be recognized by the institution and must be accepted and known by all team members. Additionally, it is important to have a massive obstetric hemorrhage protocol (red code) for those patients with an important bleeding who require blood products available as soon as possible. In the red code activation protocol there are several key points to consider: the management algorithm must be known and accepted by all team members, a clear and effective communication between the team must be established and all the participants must know the role they play. Massive obstetric hemorrhage has a multidisciplinary implication: obstetricians, anesthesiologists, pediatricians, midwife, nurses, auxiliary staff, and laboratory blood bank staff. The active participation of the multidisciplinary team in simulations before the protocols implementation facilitates the evaluation of critical points and subsequent changes before their final application, the assessment of the adequacy of circuits and infrastructure, as well as a better protocols compliance.",book:{id:"5937",slug:"obstetrics",title:"Obstetrics",fullTitle:"Obstetrics"},signatures:"Jaume Miñano Masip, Laura Almeida Toledano, Sílvia Ferrero\nMartínez and María Dolores Gómez Roig",authors:[{id:"202446",title:"Ph.D.",name:"Maria Dolores",middleName:null,surname:"Gómez Roig",slug:"maria-dolores-gomez-roig",fullName:"Maria Dolores Gómez Roig"},{id:"202447",title:"Dr.",name:"Jaume",middleName:null,surname:"Miñano Masip",slug:"jaume-minano-masip",fullName:"Jaume Miñano Masip"},{id:"202448",title:"Dr.",name:"Laura",middleName:null,surname:"Almeida",slug:"laura-almeida",fullName:"Laura Almeida"},{id:"202449",title:"Dr.",name:"Silvia",middleName:null,surname:"Ferrero",slug:"silvia-ferrero",fullName:"Silvia Ferrero"}]},{id:"56677",title:"Ovarian Cancer and Pregnancy",slug:"ovarian-cancer-and-pregnancy",totalDownloads:1713,totalCrossrefCites:0,totalDimensionsCites:0,abstract:"The annual incidence rate of cancer is estimated to be more than 11,000 patients in the U.K. in the age group of 15–40 years, which corresponds to 4% of all cancer patients. The diagnosis of cancer is followed by devastating consequences for the patients and their families in this age group. Although the treatment of cancer is of crucial significance, it should also examine the impact of the disease on fertility at the time of the diagnosis and the damages caused from the surgical treatment, chemotherapy, or radiotherapy. The gynecological cancer, especially the diagnosis of ovarian cancer, the prevention, and treatment, as well as the fertility preservation in young women, represent the gold standard for all gynecologists. The crucial disadvantage remains the difficulty in primary diagnosis of ovarian cancer and the coexistence with pregnancy, focusing on the fertility preservation and maintaining pregnancy. In the absence of large perspective randomized trials and cohort studies, the therapeutic mapping and optimal management of these patients are difficult. In order to establish detailed guidelines, it is necessary to ensure surgical mapping depending on the cancer staging and the quality of life of the patients.",book:{id:"5937",slug:"obstetrics",title:"Obstetrics",fullTitle:"Obstetrics"},signatures:"Chrisostomos Sofoudis",authors:[{id:"173802",title:"Dr.",name:"Chrisostomos",middleName:null,surname:"Sofoudis",slug:"chrisostomos-sofoudis",fullName:"Chrisostomos Sofoudis"}]},{id:"65495",title:"Improving Maternal Health: The Safe Childbirth Checklist as a Tool for Reducing Maternal Mortality and Morbidity",slug:"improving-maternal-health-the-safe-childbirth-checklist-as-a-tool-for-reducing-maternal-mortality-an",totalDownloads:2222,totalCrossrefCites:1,totalDimensionsCites:4,abstract:"Ensuring healthy lives and promoting the well-being for all at all ages is essential to sustainable development. The UN’s adoption of the sustainable development goals (SDGs) in September 2015 reaffirmed the reduction of maternal and newborn mortality as global priorities in the coming decade. The World Health Organisation Safe Childbirth Checklist has been developed to ensure the delivery of essential maternal and perinatal care practices. The Safe Childbirth Checklist aims to help frontline health workers to prevent avoidable childbirth-related mortality and morbidity. The Checklist addresses the major causes of maternal death (haemorrhage, infection, obstructed labour and hypertensive disorders), intrapartum-related stillbirths (inadequate intrapartum care), and neonatal deaths (birth asphyxia, infection and complications related to prematurity). Successful completion of checklist items by healthcare workers will help keep the woman and baby safe as the checklist catalogues a core set of practices that are proven to reduce maternal and newborn harm. The practices described in the checklist items should be conducted at every birth. This chapter utilises experiences gained in Cameroon, Ghana, Nigeria and Zambia during the Pfizer Independent Grant for Learning and Change supported Medical Women’s Association of Nigeria Improving Maternal Health in sub-Saharan Africa project to describe the checklist and how it can be used to deliver lifesaving midwifery care and enhance maternal health.",book:{id:"7259",slug:"selected-topics-in-midwifery-care",title:"Selected Topics in Midwifery Care",fullTitle:"Selected Topics in Midwifery Care"},signatures:"Julius Dohbit, Vetty Agala, Pamela Chinwa-Banda, Betty Anane-\nFenin, Omosivie Maduka, Ufuoma Edewor, Ibimonye Porbeni, Fru\nAngwafo and Rosemary Ogu",authors:[{id:"213063",title:"Prof.",name:"Rosemary",middleName:null,surname:"Ogu",slug:"rosemary-ogu",fullName:"Rosemary Ogu"},{id:"241001",title:"Dr.",name:"Pamela",middleName:"Chirwa",surname:"Banda",slug:"pamela-banda",fullName:"Pamela Banda"},{id:"259772",title:"Dr.",name:"Vetty",middleName:null,surname:"Agala",slug:"vetty-agala",fullName:"Vetty Agala"},{id:"270792",title:"Prof.",name:"Fru",middleName:null,surname:"Angwafo",slug:"fru-angwafo",fullName:"Fru Angwafo"},{id:"270799",title:"Dr.",name:"Julius",middleName:null,surname:"Dohbit Sama",slug:"julius-dohbit-sama",fullName:"Julius Dohbit Sama"},{id:"270802",title:"Dr.",name:"Betty",middleName:null,surname:"Anane-Fenin",slug:"betty-anane-fenin",fullName:"Betty Anane-Fenin"},{id:"270803",title:"Dr.",name:"Ufuoma",middleName:null,surname:"Edewor",slug:"ufuoma-edewor",fullName:"Ufuoma Edewor"},{id:"273872",title:"Dr.",name:"Ibimonye",middleName:null,surname:"Porbeni",slug:"ibimonye-porbeni",fullName:"Ibimonye Porbeni"},{id:"273875",title:"Dr.",name:"Omosivie",middleName:null,surname:"Maduka",slug:"omosivie-maduka",fullName:"Omosivie Maduka"}]},{id:"56985",title:"Pelvic Floor Support",slug:"pelvic-floor-support",totalDownloads:3337,totalCrossrefCites:1,totalDimensionsCites:1,abstract:"Pelvic floor muscle can be weakened by pregnancy and birth trauma and this contributes to sagging of pelvic floor, and may lead to pelvic floor disorder (PFD). There are various forms of pelvic floor support available in modern medicine, each has its own therapeutic logic behind its use. The noninvasive mechanical device bowel aid provides conservative support to supplement current obstetric management to improve outcome of management of pregnancy related problem like hemorrhoid and anal fissure. 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He has both an MS and Ph.D. in Biomedical Engineering. He was previously a research scientist at the University of California Los Angeles (UCLA) and visiting professor and researcher at the University of North Dakota. He is currently working in artificial intelligence and its applications in medical signal processing. In addition, he is using digital signal processing in medical imaging and speech processing. Dr. Asadpour has developed brain-computer interfacing algorithms and has published books, book chapters, and several journal and conference papers in this field and other areas of intelligent signal processing. He has also designed medical devices, including a laser Doppler monitoring system.",institutionString:"Kaiser Permanente Southern California",institution:null},{id:"169608",title:"Prof.",name:"Marian",middleName:null,surname:"Găiceanu",slug:"marian-gaiceanu",fullName:"Marian Găiceanu",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/169608/images/system/169608.png",biography:"Prof. Dr. Marian Gaiceanu graduated from the Naval and Electrical Engineering Faculty, Dunarea de Jos University of Galati, Romania, in 1997. He received a Ph.D. (Magna Cum Laude) in Electrical Engineering in 2002. Since 2017, Dr. Gaiceanu has been a Ph.D. supervisor for students in Electrical Engineering. He has been employed at Dunarea de Jos University of Galati since 1996, where he is currently a professor. 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He is also a member of the editorial boards of the Journal of Electrical Engineering, Electronics, Control and Computer Science and Sustainability. Dr. Gaiceanu has been General Chairman of the IEEE International Symposium on Electrical and Electronics Engineering in the last six editions.",institutionString:'"Dunarea de Jos" University of Galati',institution:{name:'"Dunarea de Jos" University of Galati',country:{name:"Romania"}}},{id:"4519",title:"Prof.",name:"Jaydip",middleName:null,surname:"Sen",slug:"jaydip-sen",fullName:"Jaydip Sen",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/4519/images/system/4519.jpeg",biography:"Jaydip Sen is associated with Praxis Business School, Kolkata, India, as a professor in the Department of Data Science. His research areas include security and privacy issues in computing and communication, intrusion detection systems, machine learning, deep learning, and artificial intelligence in the financial domain. 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He has been listed among the top 2% of scientists in the world for the last three consecutive years, 2019 to 2021 as per studies conducted by the Stanford University, USA.",institutionString:"Praxis Business School",institution:null},{id:"320071",title:"Dr.",name:"Sidra",middleName:null,surname:"Mehtab",slug:"sidra-mehtab",fullName:"Sidra Mehtab",position:null,profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0033Y00002v6KHoQAM/Profile_Picture_1584512086360",biography:"Sidra Mehtab has completed her BS with honors in Physics from Calcutta University, India in 2018. She has done MS in Data Science and Analytics from Maulana Abul Kalam Azad University of Technology (MAKAUT), Kolkata, India in 2020. Her research areas include Econometrics, Time Series Analysis, Machine Learning, Deep Learning, Artificial Intelligence, and Computer and Network Security with a particular focus on Cyber Security Analytics. 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:{name:"Association for Computing Machinery",country:{name:"United States of America"}}},{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:'"Politechnica" University Timişoara',institution:null},{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:{name:"Tecnalia",country:{name:"Spain"}}},{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:"426586",title:"Dr.",name:"Oladunni A.",middleName:null,surname:"Daramola",slug:"oladunni-a.-daramola",fullName:"Oladunni A. Daramola",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"Federal University of Technology",country:{name:"Nigeria"}}},{id:"357014",title:"Prof.",name:"Leon",middleName:null,surname:"Bobrowski",slug:"leon-bobrowski",fullName:"Leon Bobrowski",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"Bialystok University of Technology",country:{name:"Poland"}}},{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:"354126",title:"Dr.",name:"Setiawan",middleName:null,surname:"Hadi",slug:"setiawan-hadi",fullName:"Setiawan Hadi",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"Padjadjaran University",country:{name:"Indonesia"}}},{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:"332603",title:"Prof.",name:"Kumar S.",middleName:null,surname:"Ray",slug:"kumar-s.-ray",fullName:"Kumar S. Ray",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"Indian Statistical Institute",country:{name:"India"}}},{id:"415409",title:"Prof.",name:"Maghsoud",middleName:null,surname:"Amiri",slug:"maghsoud-amiri",fullName:"Maghsoud Amiri",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"Allameh Tabataba'i University",country:{name:"Iran"}}},{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"}}}]}},subseries:{item:{id:"1",type:"subseries",title:"Oral Health",keywords:"Oral Health, Dental Care, Diagnosis, Diagnostic Imaging, Early Diagnosis, Oral Cancer, Conservative Treatment, Epidemiology, Comprehensive Dental Care, Complementary Therapies, Holistic Health",scope:"\r\n\tThis topic aims to provide a comprehensive overview of the latest trends in Oral Health based on recent scientific evidence. Subjects will include an overview of oral diseases and infections, systemic diseases affecting the oral cavity, prevention, diagnosis, treatment, epidemiology, as well as current clinical recommendations for the management of oral, dental, and periodontal diseases.
",coverUrl:"https://cdn.intechopen.com/series_topics/covers/1.jpg",hasOnlineFirst:!0,hasPublishedBooks:!0,annualVolume:11397,editor:{id:"173955",title:"Prof.",name:"Sandra",middleName:null,surname:"Marinho",slug:"sandra-marinho",fullName:"Sandra Marinho",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bRGYMQA4/Profile_Picture_2022-06-01T13:22:41.png",biography:"Dr. Sandra A. Marinho is an Associate Professor and Brazilian researcher at the State University of Paraíba (Universidade Estadual da Paraíba- UEPB), Campus VIII, located in Araruna, state of Paraíba since 2011. She holds a degree in Dentistry from the Federal University of Alfenas (UNIFAL), while her specialization and professional improvement in Stomatology took place at Hospital Heliopolis (São Paulo, SP). Her qualifications are: a specialist in Dental Imaging and Radiology, Master in Dentistry (Periodontics) from the University of São Paulo (FORP-USP, Ribeirão Preto, SP), and Doctor (Ph.D.) in Dentistry (Stomatology Clinic) from Hospital São Lucas of the Pontifical Catholic University of Rio Grande do Sul (HSL-PUCRS, Porto Alegre, RS). She held a postdoctoral internship at the Federal University from Jequitinhonha and Mucuri Valleys (UFVJM, Diamantina, MG). She is currently a member of the Brazilian Society for Dental Research (SBPqO) and the Brazilian Society of Stomatology and Pathology (SOBEP). Dr. Marinho's experience in Dentistry mainly covers the following subjects: oral diagnosis, oral radiology; oral medicine; lesions and oral infections; oral pathology, laser therapy and epidemiological studies.",institutionString:null,institution:{name:"State University of Paraíba",institutionURL:null,country:{name:"Brazil"}}},editorTwo:null,editorThree:null,series:{id:"3",title:"Dentistry",doi:"10.5772/intechopen.71199",issn:"2631-6218"},editorialBoard:[{id:"267724",title:"Prof.",name:"Febronia",middleName:null,surname:"Kahabuka",slug:"febronia-kahabuka",fullName:"Febronia Kahabuka",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bRZpJQAW/Profile_Picture_2022-06-27T12:00:42.JPG",institutionString:"Muhimbili University of Health and Allied Sciences, Tanzania",institution:{name:"Muhimbili University of Health and Allied Sciences",institutionURL:null,country:{name:"Tanzania"}}},{id:"70530",title:"Dr.",name:"Márcio",middleName:"Campos",surname:"Oliveira",slug:"marcio-oliveira",fullName:"Márcio Oliveira",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bRm0AQAS/Profile_Picture_2022-08-01T12:34:46.jpg",institutionString:null,institution:{name:"State University of Feira de Santana",institutionURL:null,country:{name:"Brazil"}}}]},onlineFirstChapters:{paginationCount:26,paginationItems:[{id:"83087",title:"Role of Cellular Responses in Periodontal Tissue Destruction",doi:"10.5772/intechopen.106645",signatures:"Nam Cong-Nhat Huynh",slug:"role-of-cellular-responses-in-periodontal-tissue-destruction",totalDownloads:8,totalCrossrefCites:0,totalDimensionsCites:0,authors:null,book:{title:"Periodontology - New Insights",coverURL:"https://cdn.intechopen.com/books/images_new/11566.jpg",subseries:{id:"1",title:"Oral Health"}}},{id:"82654",title:"Atraumatic Restorative Treatment: More than a Minimally Invasive Approach?",doi:"10.5772/intechopen.105623",signatures:"Manal A. 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