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Barely three months into the new year and we are happy to announce a monumental milestone reached - 150 million downloads.
\n\nThis achievement solidifies IntechOpen’s place as a pioneer in Open Access publishing and the home to some of the most relevant scientific research available through Open Access.
\n\nWe are so proud to have worked with so many bright minds throughout the years who have helped us spread knowledge through the power of Open Access and we look forward to continuing to support some of the greatest thinkers of our day.
\n\nThank you for making IntechOpen your place of learning, sharing, and discovery, and here’s to 150 million more!
\n\n\n\n\n'}],latestNews:[{slug:"intechopen-supports-asapbio-s-new-initiative-publish-your-reviews-20220729",title:"IntechOpen Supports ASAPbio’s New Initiative Publish Your Reviews"},{slug:"webinar-introduction-to-open-science-wednesday-18-may-1-pm-cest-20220518",title:"Webinar: Introduction to Open Science | Wednesday 18 May, 1 PM CEST"},{slug:"step-in-the-right-direction-intechopen-launches-a-portfolio-of-open-science-journals-20220414",title:"Step in the Right Direction: IntechOpen Launches a Portfolio of Open Science Journals"},{slug:"let-s-meet-at-london-book-fair-5-7-april-2022-olympia-london-20220321",title:"Let’s meet at London Book Fair, 5-7 April 2022, Olympia London"},{slug:"50-books-published-as-part-of-intechopen-and-knowledge-unlatched-ku-collaboration-20220316",title:"50 Books published as part of IntechOpen and Knowledge Unlatched (KU) Collaboration"},{slug:"intechopen-joins-the-united-nations-sustainable-development-goals-publishers-compact-20221702",title:"IntechOpen joins the United Nations Sustainable Development Goals Publishers Compact"},{slug:"intechopen-signs-exclusive-representation-agreement-with-lsr-libros-servicios-y-representaciones-s-a-de-c-v-20211123",title:"IntechOpen Signs Exclusive Representation Agreement with LSR Libros Servicios y Representaciones S.A. de C.V"},{slug:"intechopen-expands-partnership-with-research4life-20211110",title:"IntechOpen Expands Partnership with Research4Life"}]},book:{item:{type:"book",id:"1281",leadTitle:null,fullTitle:"DNA Repair and Human Health",title:"DNA Repair and Human Health",subtitle:null,reviewType:"peer-reviewed",abstract:"Over the past decades, great advances have been made in understanding the cellular DNA repair pathways. At the same time, a wealth of descriptive knowledge of human diseases has been accumulated. Now, the basic research of the mechanisms of DNA repair is merging with clinical research, placing the action of the DNA repair pathways in the context of the whole organism. Such integrative approach enables understanding of the disease mechanisms and is invaluable in improving diagnostics and prevention, as well as designing better therapies. \nThis book highlights the central role of DNA repair in human health and well-being. The reviews presented here, contain detailed descriptions of DNA repair pathways, as well as analysis of a large body of evidence addressing links between DNA damage repair and human health. They will be of interest to a broad audience, from molecular biologists working on DNA repair in any model system, to medical researchers.",isbn:null,printIsbn:"978-953-307-612-6",pdfIsbn:"978-953-51-6533-0",doi:"10.5772/1750",price:169,priceEur:185,priceUsd:219,slug:"dna-repair-and-human-health",numberOfPages:808,isOpenForSubmission:!1,isInWos:null,isInBkci:!1,hash:"cc31f8578c9beb17ab7967da7f86b7f8",bookSignature:"Sonya Vengrova",publishedDate:"October 26th 2011",coverURL:"https://cdn.intechopen.com/books/images_new/1281.jpg",numberOfDownloads:76396,numberOfWosCitations:31,numberOfCrossrefCitations:17,numberOfCrossrefCitationsByBook:1,numberOfDimensionsCitations:41,numberOfDimensionsCitationsByBook:2,hasAltmetrics:0,numberOfTotalCitations:89,isAvailableForWebshopOrdering:!0,dateEndFirstStepPublish:"November 10th 2010",dateEndSecondStepPublish:"December 8th 2010",dateEndThirdStepPublish:"April 14th 2011",dateEndFourthStepPublish:"May 14th 2011",dateEndFifthStepPublish:"July 13th 2011",currentStepOfPublishingProcess:5,indexedIn:"1,2,3,4,5,6",editedByType:"Edited by",kuFlag:!1,featuredMarkup:null,editors:[{id:"66551",title:"Dr.",name:"Sonya",middleName:null,surname:"Vengrova",slug:"sonya-vengrova",fullName:"Sonya Vengrova",profilePictureURL:"https://mts.intechopen.com/storage/users/66551/images/1778_n.jpg",biography:"Dr. Sonya Vengrova did her undergraduate studies in the Moscow State University in Russia. During this period, she also did a research project at the National Cancer Institute, NIH, USA, and gained her Diploma from the Moscow State University in 2000. Subsequently, she went to the Rockefeller University in New York, USA, to work in the field of developmental genetics. She moved to the UK to start a PhD program at the Imperial College, London, UK in 2009, in the field of genome stability. The research was funded by the Marie Curie Cancer Care, and was carried out in the Marie Curie Research Institute, UK. Dr. Vengrova gained her PhD in 2004 and continued postdoctoral work at the Marie Curie Research Institute. In 2009, she moved to the University of Warwick, Coventry, UK, where she currently works as a Wellcome Trust research fellow on projects addressing different aspects of genome stability.",institutionString:null,position:null,outsideEditionCount:0,totalCites:0,totalAuthoredChapters:"0",totalChapterViews:"0",totalEditedBooks:"1",institution:{name:"University of Warwick",institutionURL:null,country:{name:"United Kingdom"}}}],equalEditorOne:null,equalEditorTwo:null,equalEditorThree:null,coeditorOne:null,coeditorTwo:null,coeditorThree:null,coeditorFour:null,coeditorFive:null,topics:[{id:"1050",title:"Molecular Genetics",slug:"medical-genetics-molecular-genetics"}],chapters:[{id:"22153",title:"DNA Repair, Human Diseases and Aging",doi:"10.5772/24565",slug:"dna-repair-human-diseases-and-aging",totalDownloads:4027,totalCrossrefCites:0,totalDimensionsCites:1,hasAltmetrics:0,abstract:null,signatures:"Vaidehi Krishnan, Baohua Liu and Zhongjun Zhou",downloadPdfUrl:"/chapter/pdf-download/22153",previewPdfUrl:"/chapter/pdf-preview/22153",authors:[{id:"58189",title:"Dr.",name:"Zhongjun",surname:"Zhou",slug:"zhongjun-zhou",fullName:"Zhongjun Zhou"},{id:"58224",title:"Dr.",name:"Baohua",surname:"Liu",slug:"baohua-liu",fullName:"Baohua Liu"},{id:"58225",title:"Dr.",name:"Vaidehi",surname:"Krishnan",slug:"vaidehi-krishnan",fullName:"Vaidehi Krishnan"}],corrections:null},{id:"22154",title:"Double Strand Break Signaling in Health and Diseases",doi:"10.5772/22148",slug:"double-strand-break-signaling-in-health-and-diseases",totalDownloads:2224,totalCrossrefCites:0,totalDimensionsCites:0,hasAltmetrics:0,abstract:null,signatures:"Marie-jo Halaby and Razqallah Hakem",downloadPdfUrl:"/chapter/pdf-download/22154",previewPdfUrl:"/chapter/pdf-preview/22154",authors:[{id:"46489",title:"Prof.",name:"Razq",surname:"Hakem",slug:"razq-hakem",fullName:"Razq Hakem"},{id:"58723",title:"Dr.",name:"Marie-Jo",surname:"Halaby",slug:"marie-jo-halaby",fullName:"Marie-Jo Halaby"}],corrections:null},{id:"22155",title:"DNA Damage Repair and Cancer: The Role of RAD51 Protein and Its Genetic Variants",doi:"10.5772/23137",slug:"dna-damage-repair-and-cancer-the-role-of-rad51-protein-and-its-genetic-variants",totalDownloads:4320,totalCrossrefCites:3,totalDimensionsCites:4,hasAltmetrics:0,abstract:null,signatures:"Augusto Nogueira, Raquel Catarino and Rui Medeiros",downloadPdfUrl:"/chapter/pdf-download/22155",previewPdfUrl:"/chapter/pdf-preview/22155",authors:[{id:"50776",title:"Prof.",name:"Rui Manuel",surname:"de Medeiros Melo Silva",slug:"rui-manuel-de-medeiros-melo-silva",fullName:"Rui Manuel de Medeiros Melo Silva"},{id:"57116",title:"MSc.",name:"Augusto",surname:"Nogueira",slug:"augusto-nogueira",fullName:"Augusto Nogueira"},{id:"57117",title:"Prof.",name:"Raquel",surname:"Catarino",slug:"raquel-catarino",fullName:"Raquel Catarino"}],corrections:null},{id:"22156",title:"The Role of Error-Prone Alternative Non-Homologous End-Joining in Genomic Instability in Cancer",doi:"10.5772/24262",slug:"the-role-of-error-prone-alternative-non-homologous-end-joining-in-genomic-instability-in-cancer",totalDownloads:3149,totalCrossrefCites:2,totalDimensionsCites:5,hasAltmetrics:0,abstract:null,signatures:"Li Li, Carine Robert and Feyruz V. 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In 2016, she obtained a PhD in the field of cell therapy for cartilage repair from the University of Orléans as a French Ministry of Higher Education and Research fellow. Her expertise is cellular biology and histology applied in cell based tissue therapies, immunology and virology. 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In this chapter we shall focus on the needs that many researchers, scientists and even students have very often. When using commercial simulation software for numerical simulation of electromagnetic field we frequently encounter many insufficiencies which those software products have. Usually, main aim of computational software developers is to optimize and refine so called core of these programmes – EM field solver. After that CAD (Computer Assisted Design) and post processing parts of EM simulators are dealt with. Mainly this can be an issue with newer, short-time in development products but one’s own post processing using Matlab can be greatly beneficial even when using well established simulators of EM field. This is largely due to its flexibility which cannot be overcome by any EM field simulator.
Throughout this chapter we will show you many ways of post processing which we use in our research of EM field in industrial and medical applications (Vrba et al., 2008; Vydra et al., 2011) and in primary research of EM field around living cells and structures inside cell bodies (Cifra et al., 2011; Havelka et al., 2011).
We hope that this chapter will aid many researchers and students in the vast field of EM research. Here, we present our knowledge and tips which we have gathered through our studies and our research.
Generally, rough results we obtain using simulators of electromagnetic field - or from analytical solution of systems described by discrete elements - are in the form of complex vector components of intensity of electric and magnetic field (i.e. time dependent – periodical – components in the directions of coordinate axes). We process these results using Matlab and interpret them to draw conclusions. In this chapter we would like to present basic processing of rough data, calculation of specific absorption rate and other parameters in particular regions of simulation domain, visualization of results in many ways (pcolor, slices, histograms, multiple iso-surface, surf interpretation on various shapes according to specific task etc.). We will provide detailed examples with practical applications and explanation of advantages provided by presented solutions.
As mentioned above, in this chapter we suppose that we have obtained rough data from any numerical simulator of EM field and now we want to interpret them. First of all we should look at how the structure of this data looks like. To get the full understanding we shall briefly go through some EM field basics.
Electromagnetic Field can be described using well known Maxwell’s equations (for more information on Maxwell’s equations please refer to any book dealing with EM field theory).
Simply by solving those equations EM field can be completely described at all points of space and time. This leads us to complete description of EM field using only phasors of intensity of electric and magnetic field
We can see that this type of data can be extracted in form of matrices (multi-dimensional, e.g. 4D). Now, we shall look closer at those matrices.
As we mentioned in previous chapter, results from simulators of EM field are represented as matrices, which directly predestines them to be processed in Matlab, which is the perfect tool for matrix operations.
There is a sample of data obtained from simulation in the following table. It depicts x-component of vector of intensity of electric field [V/m] in y-axis section in a part of some model.
10 | 10 | 11 | 12 | 13 | 14 | 12 | 9 | 8 | 7 | |
10 | 10 | 11 | 12 | 13 | 14 | 11 | 10 | 9 | 8 | |
11 | 11 | 11 | 12 | 13 | 14 | 13 | 11 | 10 | 9 | |
12 | 12 | 12 | 12 | 13 | 14 | 13 | 12 | 11 | 10 | |
13 | 13 | 13 | 12 | 13 | 14 | 12 | 12 | 12 | 11 | |
14 | 14 | 13 | 13 | 13 | 14 | 13 | 13 | 13 | 12 | |
13 | 14 | 13 | 13 | 13 | 14 | 14 | 14 | 14 | 12 | |
13 | 14 | 14 | 14 | 14 | 14 | 15 | 15 | 14 | 13 | |
13 | 13 | 13 | 14 | 15 | 15 | 16 | 15 | 14 | 13 | |
12 | 13 | 13 | 14 | 14 | 15 | 15 | 15 | 14 | 13 |
X-component of vector of intensity of electric field [V/m]
Following graphical representation can help us shed some more light on the structure of data we obtained. These data are represented as four dimensional matrices (for phasors
Data structure
Generally we can describe phasors as follows.
Note: It may be necessary to convert data to suitable matrix form (e.g. rough data are in the form of a row vector with axial information for each element). We will look into it in the chapter 3.
Now that we know what our data source looks like we can simply process it to view the results and highlight some of their aspects according to our needs (see Table 2. for axial information).
Extraction of Axes (in our example)
In this section we are going to show some examples of how obtained data can be viewed, how to interpret those results, what type of projection should we use etc. We shall illustrate this on some practical examples of EM field applications.
As mentioned above we might obtain rough data in the form of a row vector. Let us illustrate this in this simple example. Our computational domain is 2 by 2 by 2 thus obtained row vector (x-component, apmlitude) has 8 elements. See Table 2.
1 | 2 | 1 | 2 | 1 | 2 | 1 | 2 | |
1 | 1 | 2 | 2 | 1 | 1 | 2 | 2 | |
1 | 1 | 1 | 1 | 2 | 2 | 2 | 2 | |
8 | 6 | 5 | 2 | 5 | 6 | 8 | 9 |
Amplitude of x-component of intensity of electric field [V/m]
From this we can extract axis. As long as we do not know the length of each axis we need to utilize this method to find actual axial data (see Figure 2.).
Note that actual axis arrangement can be different in your case (e.g. x and y axis arrangement may be commuted). Thus it is vital to get familiar with axial arrangement in your exporter from EM field simulator.
Furthermore, actualAxis vectors are underlined because they are growing on every loop iteration. Since axial vectors are not usually very long, this poses only mild concern. They cannot be preallocated because we generally do not know their actual length. If you are expecting very long axial vectors you may consider preallocating them safely longer than your expectations and then just using part of them which is non-zero (you may select this part of a vector using find – please refer to Matlab documentation).
Now that we know the length of each axial vector we may sort the vector of exported values and transform it to a matrix which will better represent three dimensional nature of our computational domain and will allow us to plot data with axial information. In this case we can very well utilize reshape which is built in Matlab.
MATRIX = reshape(vector_of_values,lenght(X),lenght(Y),lenght(Z))
Thanks to this process we now have every component of each vector (i.e.
First of all, we need to bear in mind that we have time-dependent data. The most basic process is to plot actual situation (distribution of intensity of electric or magnetic) at a given time, or amplitude of vector. (In some applications we may need to plot just one component of this vector. This is even simpler because then we can disregard following method.)
Phasor of intensity of electric or magnetic field can be represented by modulus and phase or real and imaginary part. We need to merge all the components of the vector and obtain real and imaginary part. This can be simply done (i.e. vector adding component matrices together). Then we have one matrix of complex numbers. We can choose specific time in which we need EM field to be plotted simply by adding <0,2π> to the phase of each vector and then we can plot real and imaginary modulus of the vector in specified time. Or we take just the amplitude of vectors and plot them.
It is very usual to plot RMS (i.e. Root Mean Square) value of vectors which is defined as follows.
This can be again obtained very simply from amplitude of intensity of electric field. (Note that this same procedure can be used also in the case of intensity of magnetic field
Now that we have three dimensional matrix of values of
In this section we shall extract data from a simulation which has setup according to the Figure 3. Please note that this is just an example without any practical use, it serves only as an illustration.
Model Setup and Its Voxel Representation (waveguide section with excitation probe at 2.45 GHz, voxels shown in section)
We simulated simple section of a waveguide (inner dimensions 100x50x200 mm) with one side shorted (there is an excitation probe in form of a cylinder in the distance of 17 mm from the shorted end) and the other side open (absorbing boundary condition – absorbs 99.9% of incident power). We extracted the data and plotted them using Matlab.
As you can see (Fig 4ab.) we used several colormaps which enable us to highlight different aspects in our results interpretation. Sometimes it is needed to have contrast colormap (jet, lines – for more information see Product Help of Matlab), at other circumstances you may need to use fine and moderate colormaps (hot, gray, bone, pink – for more information see Product Help of Matlab). In the fourth graph in Fig. 4 we used different shading – faceted. This enables us to highlight structure of computational grid. In many commercial simulators of EM field parts of a model need to be meshed finer than others (e.g. in our case the excitation probe needs to be meshed four times more than the rest of the waveguide to be voxeled sufficiently). In other examples we used shading interp to get more clear view.
a - (
We can also utilize custom colormaps. This can be exceptionally beneficial in applications where we need to find out where values are at some critical level or higher. We illustrated this feature in the first image in Fig. 4a. In Fig. 5. there is an Colormap Editor which can be accessed through: Figure – Edit – Figure Properties – Colormap pull-down menu – Custom.
In our example we set segment in the middle to black colour and segment next to it to white colour. This resulted in the graph as seen in Fig. 4a. For more information on colormaps please refer to the Product Help of Matlab.
Colormap Editor Window
Furthermore, we illustrated how real modulus of vector of intensity of electric field at phase 0° is interpreted using Matlab (second image in Fig. 4a.). This is the most basic interpretation of obtained data we can do.
Note that this kind of results interpretation is much more flexible than the interpretation allowed by post processing tools in commercial EM simulators. In the following example we shall show how to work with time dependency of phasors. Since the results of EM field simulator are extracted when the steady state is reached time dependency is reduced to angle of phasors depicting the field of vectors. Through the following method we can alter phase of those phasors and show real part and imaginary part through one period. The results can be seen in Fig. 6. Figure 7. shows example of data processing to achieve this.
Phase Shifted Data – real part of vector
Note: In many EM field simulators you may encounter various errors. Pay special attention to the data structure of your exported data since it may not be useful in the way we have shown here (e.g. real and imaginary parts are exported as absolute values so the vital information about phase is lost).
Note: In the part of the script (Fig. 7.) where lowerThan variable is used we are changing the range of values. Since there are parts of model where values of intensity of electric or magnetic field are very near to zero, minimum of these values in dB would be around -400 dB. This renders produced images useless (value range is huge but most of the relevant values are in the region <-50,0>). Using function find we identify indexes of elements with values lower than -50 dB and we replace those elements with value -50 dB. For more information on function find please refer to the Product Help of Matlab.
Note: In this example we use function subaxis which has similar usage as function subplot but allows users to set the layout of plots in the figure more accurately (options Padding, Spacing, Margin etc.). For more information on subaxis please see internet documentation.
In the following example we will go through one of many useful applications of EM simulators today – evaluation of hyperthermia cancer treatment. Generally, hyperthermia is a method through which tissue is overheated (usually using microwave energy) and cells die (principle of this method is that energy is focused into the cancerous tissue which is less perfused and thus it is more heated – temperature in treated area rises above levels that trigger cell apoptosis). For more information on microwave hyperthermia see for example (Vrba & Oppl., 2008).
Model of simulated experiment can be seen in Figure 8. In this example we use waveguide applicator which is fed by coaxial line ending in protruding inner wire which is located near the shorted end of the waveguide section. There is a horn aperture which helps focus microwave energy to the desired area.
Relatively complex and complicated structure of human body is replaced with so called “phantom” that represents simple muscle tissue. In the model there is a tumor located 1 cm below the surface of phantom. This tumor has the same dielectric parameters as the surrounding muscle tissue (usually the only difference in simulations between muscle tissue and tumorous tissue is in their perfusion, heat transfer rate and heat generation rate – generated heat in tumorous tissue is usually transferred slower than in physiological surrounding tissue).
Additionally there is a water bolus which serves as a coolant body protecting the surface tissue of patient and moving the maximum of temperature to the lower layers. In this example we use source at 434 MHz and the applicator is filled with water (required dimensions of the applicator are effectively lower and impedance matching between waveguide-bolus and body are much better). For more information on waveguide hyperthermia applicators please refer to (Vera et al., 2006).
In this simulation we again extract rough data from EM simulator and we process them further using Matlab. We again have intensity of electric and magnetic field defined in every element of the model. For effective analysis of the treatment we need to evaluate SAR (Specific Absorption Ratio) which describes how much power is absorbed in a weight unit [W/kg]. For more information on SAR see http://www.ets-lindgren.com/pdf/sar_lo.pdf.
Method of phase shifting results
To determine how SAR is distributed we need to use this formula.
As we see, in this case we can very well utilize
SAR is thus depending on RMS value of intensity of electric field, on conductivity of a material and on its density. We need to obtain those values somehow. In our case whole phantom has homogeneous density and electric conductivity thus we can only mask matrix of
Model of microwave hyperthermia at 434 MHz
Note: There are other options how to do that. For example some EM simulator allow users to export matrix of dielectric parameters of a model (this will produce similar matrix to our masking matrix).
Now we should look into how to produce masking matrix efficiently. From our model we know that every element of the voxelized model is phantom if its value of y axis is higher than 120 mm (we can find out this in CAD part of EM simulator). We can prepare our three dimensional matrix of
An elegant way to find the index at y axis of element which has the value nearest to 120 mm (note that the value is not usually exactly 120 so if we looked for the exact match we would probably fail) is to use function min. Example of this method is as follows.
Example of finding the closest element position
In this example, we can illustrate one other useful feature of Matlab processing of EM simulator results. We can instantly normalize obtained results. Usually it is possible to extract actual power in the source which was simulated (e.g. 0.002496 W) and we can utilize this to obtain normalization coefficient. Power normalization coefficient is given by the following formula.
Covering Field of
Since this is the coefficient of power ratio we need to use coefficient of intensity of electric field ratio which is the square root of coefficient of power (see the equation below).
Simply by multiplying the matrix of data by this coefficient we obtain normalized data to the desired value of delivered power.
Now we can show several interpretations of results we obtained (Z section in the middle of the model). Thanks to Matlab’s flexibility and versatility we can highlight the results in the way that is far more efficient than by using post processing of the EM field simulator. In the following figures we show intensity of electric field and SAR in the treated area.
As you can see in figure 11. each colour scheme highlights different thing (as for the first three). In the fourth graph we used custom colormap to show some kind of a critical zone. In this example we expected that higher values of SAR than 1000 W/kg are considered to be dangerous in some regions (note that these critical limits differ significantly in every application – many factors contribute, e.g. vital or sensitive organs near the treated area etc.) and thus we highlighted the zone with higher values using bright red colour. This may be very important but commercial simulation software generally omits such option.
It may be also very useful to show obtained data only in the region of the tumour or to show values in form of several slices, semi-transparent layers or iso-surface view. Now we shall show how to prepare masking matrix for some simple geometrical objects representing tumours. For more information on the mentioned advanced techniques of results representation please see section 4. Advanced Viewing Techniques.
SAR [W/kg] in Different Colour Schemes (from left upper corner to right lower corner: hot, jet, lines, custom)
Very simple masking (i.e. when the region that needs to be masked is in the form of a cuboid) was shown in previous section. Now we should look into masking regions round in shape (i.e. spheres, ellipsoids and other common shapes that parts of model can be represented by).
Spheres are case of ellipsoid and we shall treat them as such. So our main aim now is to mask region generally in ellipsoidal form. Equation defining an ellipsoid (with its origin at
The graphical representation of a general ellipsoid can be seen in figure 12. There we can see that
Albeit there is a built-in function designed to generate ellipsoid (see the Product Help of Matlab) we shall show you an easy way which allows you to generate desired masking matrix (e.g. with values 0 or 1).
Representation of Ellipsoid (from left: scheme, tri-axial, oblate, prolate)
As you can see in Fig. 13. we simply utilized the formula representing ellipsoid and all elements whose coordinates meet the given restrictions are filled with ones. The other elements remain zero. Constants elementsX, elementsY or elementsZ define the length of axis of computational domain (i.e. actualAxisX and so on). Variables xc, yc and zc define centre of our ellipsoid.
Defining Ellipsoid in the Masking Matrix
Now we can simply use generated masking matrix and multiply every element of result matrix by according element of masking matrix. Then we can look how our results are interpreted in detailed view in the tumour.
From masked matrix of SAR we can also easily extract total power radiated to the tumorous region. Total power lost in the healthy tissue is than given by the difference between total power (in the case of perfectly matched source) and power lost in the tumour.
SAR [W/kg] in Tumour (from left: Y-slice, X-slice, Z-slice)
Note: In some cases it might be beneficial to set the colorbar range the same in all pictures (as shown in Fig. 14.). The simplest way to do this is to set value of [1,1] element of displayed matrix (i.e. a slice) to the maximum value of the whole three dimensional matrix (if needed, the minimum value should be set to element [max,max] of displayed matrix).
Additional information that we can obtain from masked result matrix is total absorbed power in the tumour. Since we know the dimensions of the tumour we can easily calculate its volume and use following formula.
The volume of standard ellipsoid is given as follows.
For example in our case tumour has volume only 8.37766e-6 m3. Information on total absorbed power may be very efficient way of preliminary evaluation for the treatment planning. Through this method we can determine power lost in any part of a simulated model. There may be some intricate volumes which are not as easily described as ellipsoid. Then we need to export their volume or masking matrix from the EM simulator (if possible).
We can determine the volume of such complicated shapes by summing elementary volumes of voxels representing those shapes. This may be unnecessary in some more advanced EM field simulators since they allow us to export model data in many suitable forms for Matlab processing. But the method presented in the following text is universal and can serve for better understanding of the model, its grid and working principals of EM simulations.
First of all we need to define which voxels are occupied by the model we want to evaluate. For this example we shall use our previously generated ellipsoid. As you can see in Fig. 14. generally grid of a simulation does not have to be symmetrical (i.e. voxels are not cubes but they are in the form of general cuboids). This means that each element may be representing different volume. We have our matrix of zeros and ones which we generated in Fig. 13. Now we need to apply this matrix to the actual coordinate system.
We can use built-in function meshgrid to produce three dimensional matrices which contain coordinates for specified element (for more information on function meshgrid please refer to the Product Help of Matlab). Now we can easily determine exact coordinates of elements occupied by our model (see Fig. 15.).
Determination of Coordinates of Model Elements
At this moment we need to get better understanding of how models are defined. Since the values (in this case ones) are located in the nodes of the grid not in the centers we need to determine how the model actually looks like. See the following figure for better understanding (2D-plane is used to illustrate).
As you can see there will be an error caused by this node to cell transformation. When the simulation grid is defined appropriately (i.e. it is fine enough) the error will be only marginal. If such error is unacceptable more advanced techniques of node to cell transformation should be used. But for purposes of this example this method is more than sufficient. For example, volume of previously defined ellipsoid determined voxel by voxel is 8.5302e-6 m3. This means that the relative error is 1.8 % (and this error includes error caused by voxelization itself – this means that node to cell transformation really brings only marginal error in simulations with fine grid).
In the Fig. 16. you can see that node to cell transformation can be done in a few (precisely 8) ways. We can easily determine which way is the most precise (i.e. [(A+1) – A] or [(A-1) – A] and its combinations with B and C). Since our model is voxelized symmetrically there is almost no difference between volumes computed accordingly to various node to cell transformations (ranging between 8.5302e-6 and 8.5304e-6).
Actual Model Dimensions
This section deals with some examples of advanced viewing of results that we have found useful during our work. As you have noticed, up to this point we have represented 3D results only in 2D graphs. This is because usually these 2D representations are clearer and easier to interpret. But for overviewing or demonstrational purposes we might need to show whole situation in 3D. For doing this we shall use multiple sections of a computational domain (slice or surf) and iso-surfaces.
We can display results in multiple 2D sections with variable transparency. This method of results visualization can give us much better overview of how a situation looks like.
It can be also beneficial to use surface view as semi-transparent layers to view results in semi-masked way. Through this we can highlight some regions of model without completely blocking visual output from other regions. For example, in our case, we can use one surface view of
Figure 19. shows us how this graph is plotted and how transparencyMatrix is prepared.
Note that when using this type of transparency mapping maximum and minimum values must be present in transparencyMatrix (i.e. one edge of transparencyMatrix is set to 0 to denote the minimum value of transparency).
Sliced View of
Surface View of RMS|E| in [dB] (transparency of tumour region set to 1 – opaque, transparency of other regions set to 0.5 – semi-transparent; colormap – jet and lines)
Through this method we can produce much more intricate visualizations of results which are unseen in commercial EM simulators. For example we can mask results in uninteresting regions (immediate vicinity of power source etc.) almost entirely, semi-mask results in exposed tissue and left results in tumour unmasked, vital organs and other key regions of simulation domain. Note that masking results with transparency matrix does not alter presented values.
This may pose a problem when values around a power source are extreme and render the rest of results unclear. For this purpose you may consider utilizing simmilar approach as presented in Figure 7. Instead of finding values lower than some value you may find values higher than some reasonable value and lower all higher values to this level.
Many more possibilities are offered thanks to post processing of EM results in Matlab. As mentioned before, the greatest advantage is that it is extremely flexible and can meet very specific requirements which can arrise with various applications of EM field. In the following section we shall demonstrate some results obtained during our primary research of EM field of microtubules (nanostructures in living cells which serve as a crude frame of a cell and have other important roles in life cycle of a cell).
In this section we are going to show several results of EM field around microtubule. This structure is generally consisting of protofilaments which are polymerized tubulin heterodimers. Thirteen protofilaments bound together form a microtubule structure which resembles a long hollow tube (see Fig. 20).
Microtubule Structure Visualization
Tubulin heterodimers (i.e. basic building block of microtubules) are highly polar structures and provided some form of external energy (movement of microtubules, mechanical vibrations etc.) they may produce EM field around themselves (Pohl, 1981; Fröhlich, 1978).
In our work EM field simulations of microtubule model were entirely conducted using Matlab. Tubulin heterodimers were represented as vibrating elementary electrical dipoles (EED) and EM field was determined for each of these EEDs. Combining the results led to unravelling the EM field produced by these complicated structures at whole (Havelka, 2009).
For the purpose of this text we shall look at visualization of these results we used to present obtained EM field. Because microtubules are symmetrical structures we have found out that representing its field by iso-surface view is very clear and easy to interpret.
Sliced Semi-transparent View of Electric Field around Microtubule (see 4.1)
In the figure 23. you can see part of the code used to generate such visualization. More information on isosurface can be found in the Product Help of Matlab. In this particular example we wanted to view results in the form of several iso-surfaces. First of all we determined the range of data obtained through Matlab analysis of EM field around our sample microtubule.
Then we need to choose which values we want to be visualized as iso-surfaces (in this case, values range is extremely wide therefore we choose only exponents – 7, 5, 2). Then we need to find which positions at colour scale are lower than our actually viewed value (we generate the colour scale using function jet(length of colour scale)). Then we simply use function patch (to build 3D wire model of locations with desired values – i.e. 1e2, 1e5, 1e7) and we set its colour which we choose accordingly from our generated colour scheme.
Additionally you can choose lighting (particularly useful in this case is gouraud lighting which does not produce any glances on multiple iso-surfaces). It is also beneficial to use alpha which is lowered with each loop (to retain clarity of the visualization).
Iso-surface View of Electric Field around Microtubule [-] (A – rough data, B – iso-surface view from above, C – iso-surface view from enface, D – iso-surface view – general angle)
Last part is generating tiny triangle which is concealed in the middle of viewed data and contains the minimum and the maximum values which allows us to show colorbar appropriately for all the iso-surfaces.
In this work we have presented basic methods of how to process obtained rough data from commercial EM simulators or even process data from our own simulations done in Matlab. We show how Matlab processing can be greatly beneficial in highlighting results in many ways that are unseen in commercial EM simulators.
We present very simple way to modify data in the form suitable for further processing and then we illustrate how to view these data in ways highlighting specific aspects (i.e. values in specific regions (tumorous tissue), evaluation of treatment efficiency, utilization of Matlab in primary research, 3D viewing etc.). These innovative ways of combination of specialized software with researcher’s versatile tool, such as Matlab is, yield in very productive and efficient way of scientific exploration of the vast field of electromagnetism.
Generation of Iso-surface View of EM Field around Microtubule
The results that are obtained in our research of EM field around living cell help us understand crucial facts about this part of our lives which has to be truly discovered yet. Matlab in this instance allows us to visualize result so we can support or on the other hand disapprove many theories (e.g. transportation of particles around microtubule via EM field).
This research is supported by the Grant Agency of the Czech Republic by project 102/08/H081: "Non Standard Applications of Physical Fields" and by CTU project SGS12/071/OHK3/1T/13: “Advanced techniques in the processing of industrial materials and biopolymers using electromagnetic field - multi-frequency processing “. Further it is supported also by research program MSM6840770012: “Transdisciplinary Research in the Area of Biomedical Engineering II” of the CTU in Prague, sponsored by the Ministry of Education, Youth and Sports of the Czech Republic.
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. With optimization of the conservative pelvic floor support during pregnancy, it is very promising to prevent PFD in later life of the women.",book:{id:"5937",slug:"obstetrics",title:"Obstetrics",fullTitle:"Obstetrics"},signatures:"Yu Chye Wah and Chew Heng Hai",authors:[{id:"202862",title:"Dr.",name:"Chye Wah",middleName:null,surname:"Yu",slug:"chye-wah-yu",fullName:"Chye Wah Yu"}]}],onlineFirstChaptersFilter:{topicId:"1067",limit:6,offset:0},onlineFirstChaptersCollection:[],onlineFirstChaptersTotal:0},preDownload:{success:null,errors:{}},subscriptionForm:{success:null,errors:{}},aboutIntechopen:{},privacyPolicy:{},peerReviewing:{},howOpenAccessPublishingWithIntechopenWorks:{},sponsorshipBooks:{sponsorshipBooks:[],offset:8,limit:8,total:0},allSeries:{pteSeriesList:[{id:"14",title:"Artificial Intelligence",numberOfPublishedBooks:9,numberOfPublishedChapters:90,numberOfOpenTopics:6,numberOfUpcomingTopics:0,issn:"2633-1403",doi:"10.5772/intechopen.79920",isOpenForSubmission:!0},{id:"7",title:"Biomedical Engineering",numberOfPublishedBooks:12,numberOfPublishedChapters:108,numberOfOpenTopics:3,numberOfUpcomingTopics:0,issn:"2631-5343",doi:"10.5772/intechopen.71985",isOpenForSubmission:!0}],lsSeriesList:[{id:"11",title:"Biochemistry",numberOfPublishedBooks:33,numberOfPublishedChapters:330,numberOfOpenTopics:4,numberOfUpcomingTopics:0,issn:"2632-0983",doi:"10.5772/intechopen.72877",isOpenForSubmission:!0},{id:"25",title:"Environmental Sciences",numberOfPublishedBooks:1,numberOfPublishedChapters:19,numberOfOpenTopics:4,numberOfUpcomingTopics:0,issn:"2754-6713",doi:"10.5772/intechopen.100362",isOpenForSubmission:!0},{id:"10",title:"Physiology",numberOfPublishedBooks:14,numberOfPublishedChapters:145,numberOfOpenTopics:4,numberOfUpcomingTopics:0,issn:"2631-8261",doi:"10.5772/intechopen.72796",isOpenForSubmission:!0}],hsSeriesList:[{id:"3",title:"Dentistry",numberOfPublishedBooks:9,numberOfPublishedChapters:141,numberOfOpenTopics:2,numberOfUpcomingTopics:0,issn:"2631-6218",doi:"10.5772/intechopen.71199",isOpenForSubmission:!0},{id:"6",title:"Infectious Diseases",numberOfPublishedBooks:13,numberOfPublishedChapters:124,numberOfOpenTopics:4,numberOfUpcomingTopics:0,issn:"2631-6188",doi:"10.5772/intechopen.71852",isOpenForSubmission:!0},{id:"13",title:"Veterinary Medicine and Science",numberOfPublishedBooks:11,numberOfPublishedChapters:112,numberOfOpenTopics:3,numberOfUpcomingTopics:0,issn:"2632-0517",doi:"10.5772/intechopen.73681",isOpenForSubmission:!0}],sshSeriesList:[{id:"22",title:"Business, Management and Economics",numberOfPublishedBooks:1,numberOfPublishedChapters:22,numberOfOpenTopics:3,numberOfUpcomingTopics:0,issn:"2753-894X",doi:"10.5772/intechopen.100359",isOpenForSubmission:!0},{id:"23",title:"Education and Human Development",numberOfPublishedBooks:0,numberOfPublishedChapters:12,numberOfOpenTopics:1,numberOfUpcomingTopics:1,issn:null,doi:"10.5772/intechopen.100360",isOpenForSubmission:!0},{id:"24",title:"Sustainable Development",numberOfPublishedBooks:1,numberOfPublishedChapters:19,numberOfOpenTopics:5,numberOfUpcomingTopics:0,issn:"2753-6580",doi:"10.5772/intechopen.100361",isOpenForSubmission:!0}],testimonialsList:[{id:"6",text:"It is great to work with the IntechOpen to produce a worthwhile collection of research that also becomes a great educational resource and guide for future research endeavors.",author:{id:"259298",name:"Edward",surname:"Narayan",institutionString:null,profilePictureURL:"https://mts.intechopen.com/storage/users/259298/images/system/259298.jpeg",slug:"edward-narayan",institution:{id:"3",name:"University of Queensland",country:{id:null,name:"Australia"}}}},{id:"13",text:"The collaboration with and support of the technical staff of IntechOpen is fantastic. The whole process of submitting an article and editing of the submitted article goes extremely smooth and fast, the number of reads and downloads of chapters is high, and the contributions are also frequently cited.",author:{id:"55578",name:"Antonio",surname:"Jurado-Navas",institutionString:null,profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bRisIQAS/Profile_Picture_1626166543950",slug:"antonio-jurado-navas",institution:{id:"720",name:"University of Malaga",country:{id:null,name:"Spain"}}}}]},series:{item:{id:"11",title:"Biochemistry",doi:"10.5772/intechopen.72877",issn:"2632-0983",scope:"Biochemistry, the study of chemical transformations occurring within living organisms, impacts all areas of life sciences, from molecular crystallography and genetics to ecology, medicine, and population biology. Biochemistry examines macromolecules - proteins, nucleic acids, carbohydrates, and lipids – and their building blocks, structures, functions, and interactions. Much of biochemistry is devoted to enzymes, proteins that catalyze chemical reactions, enzyme structures, mechanisms of action and their roles within cells. Biochemistry also studies small signaling molecules, coenzymes, inhibitors, vitamins, and hormones, which play roles in life processes. Biochemical experimentation, besides coopting classical chemistry methods, e.g., chromatography, adopted new techniques, e.g., X-ray diffraction, electron microscopy, NMR, radioisotopes, and developed sophisticated microbial genetic tools, e.g., auxotroph mutants and their revertants, fermentation, etc. More recently, biochemistry embraced the ‘big data’ omics systems. Initial biochemical studies have been exclusively analytic: dissecting, purifying, and examining individual components of a biological system; in the apt words of Efraim Racker (1913 –1991), “Don’t waste clean thinking on dirty enzymes.” Today, however, biochemistry is becoming more agglomerative and comprehensive, setting out to integrate and describe entirely particular biological systems. The ‘big data’ metabolomics can define the complement of small molecules, e.g., in a soil or biofilm sample; proteomics can distinguish all the comprising proteins, e.g., serum; metagenomics can identify all the genes in a complex environment, e.g., the bovine rumen. This Biochemistry Series will address the current research on biomolecules and the emerging trends with great promise.",coverUrl:"https://cdn.intechopen.com/series/covers/11.jpg",latestPublicationDate:"August 2nd, 2022",hasOnlineFirst:!0,numberOfPublishedBooks:33,editor:{id:"31610",title:"Dr.",name:"Miroslav",middleName:null,surname:"Blumenberg",slug:"miroslav-blumenberg",fullName:"Miroslav Blumenberg",profilePictureURL:"https://mts.intechopen.com/storage/users/31610/images/system/31610.jpg",biography:"Miroslav Blumenberg, Ph.D., was born in Subotica and received his BSc in Belgrade, Yugoslavia. He completed his Ph.D. at MIT in Organic Chemistry; he followed up his Ph.D. with two postdoctoral study periods at Stanford University. Since 1983, he has been a faculty member of the RO Perelman Department of Dermatology, NYU School of Medicine, where he is codirector of a training grant in cutaneous biology. Dr. Blumenberg’s research is focused on the epidermis, expression of keratin genes, transcription profiling, keratinocyte differentiation, inflammatory diseases and cancers, and most recently the effects of the microbiome on the skin. He has published more than 100 peer-reviewed research articles and graduated numerous Ph.D. and postdoctoral students.",institutionString:null,institution:{name:"New York University Langone Medical Center",institutionURL:null,country:{name:"United States of America"}}},editorTwo:null,editorThree:null},subseries:{paginationCount:4,paginationItems:[{id:"14",title:"Cell and Molecular Biology",coverUrl:"https://cdn.intechopen.com/series_topics/covers/14.jpg",isOpenForSubmission:!0,annualVolume:11410,editor:{id:"165627",title:"Dr.",name:"Rosa María",middleName:null,surname:"Martínez-Espinosa",slug:"rosa-maria-martinez-espinosa",fullName:"Rosa María Martínez-Espinosa",profilePictureURL:"https://mts.intechopen.com/storage/users/165627/images/system/165627.jpeg",biography:"Dr. Rosa María Martínez-Espinosa has been a Spanish Full Professor since 2020 (Biochemistry and Molecular Biology) and is currently Vice-President of International Relations and Cooperation development and leader of the research group 'Applied Biochemistry” (University of Alicante, Spain). Other positions she has held at the university include Vice-Dean of Master Programs, Vice-Dean of the Degree in Biology and Vice-Dean for Mobility and Enterprise and Engagement at the Faculty of Science (University of Alicante). She received her Bachelor in Biology in 1998 (University of Alicante) and her PhD in 2003 (Biochemistry, University of Alicante). She undertook post-doctoral research at the University of East Anglia (Norwich, U.K. 2004-2005; 2007-2008).\nHer multidisciplinary research focuses on investigating archaea and their potential applications in biotechnology. She has an H-index of 21. She has authored one patent and has published more than 70 indexed papers and around 60 book chapters.\nShe has contributed to more than 150 national and international meetings during the last 15 years. Her research interests include archaea metabolism, enzymes purification and characterization, gene regulation, carotenoids and bioplastics production, antioxidant\ncompounds, waste water treatments, and brines bioremediation.\nRosa María’s other roles include editorial board member for several journals related\nto biochemistry, reviewer for more than 60 journals (biochemistry, molecular biology, biotechnology, chemistry and microbiology) and president of several organizing committees in international meetings related to the N-cycle or respiratory processes.",institutionString:null,institution:{name:"University of Alicante",institutionURL:null,country:{name:"Spain"}}},editorTwo:null,editorThree:null},{id:"15",title:"Chemical Biology",coverUrl:"https://cdn.intechopen.com/series_topics/covers/15.jpg",isOpenForSubmission:!0,annualVolume:11411,editor:{id:"441442",title:"Dr.",name:"Şükrü",middleName:null,surname:"Beydemir",slug:"sukru-beydemir",fullName:"Şükrü Beydemir",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0033Y00003GsUoIQAV/Profile_Picture_1634557147521",biography:"Dr. Şükrü Beydemir obtained a BSc in Chemistry in 1995 from Yüzüncü Yıl University, MSc in Biochemistry in 1998, and PhD in Biochemistry in 2002 from Atatürk University, Turkey. He performed post-doctoral studies at Max-Planck Institute, Germany, and University of Florence, Italy in addition to making several scientific visits abroad. He currently works as a Full Professor of Biochemistry in the Faculty of Pharmacy, Anadolu University, Turkey. Dr. Beydemir has published over a hundred scientific papers spanning protein biochemistry, enzymology and medicinal chemistry, reviews, book chapters and presented several conferences to scientists worldwide. He has received numerous publication awards from various international scientific councils. He serves in the Editorial Board of several international journals. Dr. Beydemir is also Rector of Bilecik Şeyh Edebali University, Turkey.",institutionString:null,institution:{name:"Anadolu University",institutionURL:null,country:{name:"Turkey"}}},editorTwo:{id:"13652",title:"Prof.",name:"Deniz",middleName:null,surname:"Ekinci",slug:"deniz-ekinci",fullName:"Deniz Ekinci",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002aYLT1QAO/Profile_Picture_1634557223079",biography:"Dr. Deniz Ekinci obtained a BSc in Chemistry in 2004, MSc in Biochemistry in 2006, and PhD in Biochemistry in 2009 from Atatürk University, Turkey. He studied at Stetson University, USA, in 2007-2008 and at the Max Planck Institute of Molecular Cell Biology and Genetics, Germany, in 2009-2010. Dr. Ekinci currently works as a Full Professor of Biochemistry in the Faculty of Agriculture and is the Head of the Enzyme and Microbial Biotechnology Division, Ondokuz Mayıs University, Turkey. He is a member of the Turkish Biochemical Society, American Chemical Society, and German Genetics society. Dr. Ekinci published around ninety scientific papers, reviews and book chapters, and presented several conferences to scientists. He has received numerous publication awards from several scientific councils. Dr. Ekinci serves as the Editor in Chief of four international books and is involved in the Editorial Board of several international journals.",institutionString:null,institution:{name:"Ondokuz Mayıs University",institutionURL:null,country:{name:"Turkey"}}},editorThree:null},{id:"17",title:"Metabolism",coverUrl:"https://cdn.intechopen.com/series_topics/covers/17.jpg",isOpenForSubmission:!0,annualVolume:11413,editor:{id:"138626",title:"Dr.",name:"Yannis",middleName:null,surname:"Karamanos",slug:"yannis-karamanos",fullName:"Yannis Karamanos",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002g6Jv2QAE/Profile_Picture_1629356660984",biography:"Yannis Karamanos, born in Greece in 1953, completed his pre-graduate studies at the Université Pierre et Marie Curie, Paris, then his Masters and Doctoral degree at the Université de Lille (1983). He was associate professor at the University of Limoges (1987) before becoming full professor of biochemistry at the Université d’Artois (1996). He worked on the structure-function relationships of glycoconjugates and his main project was the investigations on the biological roles of the de-N-glycosylation enzymes (Endo-N-acetyl-β-D-glucosaminidase and peptide-N4-(N-acetyl-β-glucosaminyl) asparagine amidase). From 2002 he contributes to the understanding of the Blood-brain barrier functioning using proteomics approaches. He has published more than 70 papers. His teaching areas are energy metabolism and regulation, integration and organ specialization and metabolic adaptation.",institutionString:null,institution:{name:"Artois University",institutionURL:null,country:{name:"France"}}},editorTwo:null,editorThree:null},{id:"18",title:"Proteomics",coverUrl:"https://cdn.intechopen.com/series_topics/covers/18.jpg",isOpenForSubmission:!0,annualVolume:11414,editor:{id:"200689",title:"Prof.",name:"Paolo",middleName:null,surname:"Iadarola",slug:"paolo-iadarola",fullName:"Paolo Iadarola",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bSCl8QAG/Profile_Picture_1623568118342",biography:"Paolo Iadarola graduated with a degree in Chemistry from the University of Pavia (Italy) in July 1972. He then worked as an Assistant Professor at the Faculty of Science of the same University until 1984. In 1985, Prof. Iadarola became Associate Professor at the Department of Biology and Biotechnologies of the University of Pavia and retired in October 2017. Since then, he has been working as an Adjunct Professor in the same Department at the University of Pavia. His research activity during the first years was primarily focused on the purification and structural characterization of enzymes from animal and plant sources. During this period, Prof. Iadarola familiarized himself with the conventional techniques used in column chromatography, spectrophotometry, manual Edman degradation, and electrophoresis). Since 1995, he has been working on: i) the determination in biological fluids (serum, urine, bronchoalveolar lavage, sputum) of proteolytic activities involved in the degradation processes of connective tissue matrix, and ii) on the identification of biological markers of lung diseases. In this context, he has developed and validated new methodologies (e.g., Capillary Electrophoresis coupled to Laser-Induced Fluorescence, CE-LIF) whose application enabled him to determine both the amounts of biochemical markers (Desmosines) in urine/serum of patients affected by Chronic Obstructive Pulmonary Disease (COPD) and the activity of proteolytic enzymes (Human Neutrophil Elastase, Cathepsin G, Pseudomonas aeruginosa elastase) in sputa of these patients. More recently, Prof. Iadarola was involved in developing techniques such as two-dimensional electrophoresis coupled to liquid chromatography/mass spectrometry (2DE-LC/MS) for the proteomic analysis of biological fluids aimed at the identification of potential biomarkers of different lung diseases. He is the author of about 150 publications (According to Scopus: H-Index: 23; Total citations: 1568- According to WOS: H-Index: 20; Total Citations: 1296) of peer-reviewed international journals. He is a Consultant Reviewer for several journals, including the Journal of Chromatography A, Journal of Chromatography B, Plos ONE, Proteomes, International Journal of Molecular Science, Biotech, Electrophoresis, and others. He is also Associate Editor of Biotech.",institutionString:null,institution:{name:"University of Pavia",institutionURL:null,country:{name:"Italy"}}},editorTwo:{id:"201414",title:"Dr.",name:"Simona",middleName:null,surname:"Viglio",slug:"simona-viglio",fullName:"Simona Viglio",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bRKDHQA4/Profile_Picture_1630402531487",biography:"Simona Viglio is an Associate Professor of Biochemistry at the Department of Molecular Medicine at the University of Pavia. She has been working since 1995 on the determination of proteolytic enzymes involved in the degradation process of connective tissue matrix and on the identification of biological markers of lung diseases. She gained considerable experience in developing and validating new methodologies whose applications allowed her to determine both the amount of biomarkers (Desmosine and Isodesmosine) in the urine of patients affected by COPD, and the activity of proteolytic enzymes (HNE, Cathepsin G, Pseudomonas aeruginosa elastase) in the sputa of these patients. Simona Viglio was also involved in research dealing with the supplementation of amino acids in patients with brain injury and chronic heart failure. She is presently engaged in the development of 2-DE and LC-MS techniques for the study of proteomics in biological fluids. The aim of this research is the identification of potential biomarkers of lung diseases. She is an author of about 90 publications (According to Scopus: H-Index: 23; According to WOS: H-Index: 20) on peer-reviewed journals, a member of the “Società Italiana di Biochimica e Biologia Molecolare,“ and a Consultant Reviewer for International Journal of Molecular Science, Journal of Chromatography A, COPD, Plos ONE and Nutritional Neuroscience.",institutionString:null,institution:{name:"University of Pavia",institutionURL:null,country:{name:"Italy"}}},editorThree:null}]},overviewPageOFChapters:{paginationCount:49,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:"83073",title:"Dental and Orofacial Trauma Impacts on Oral-Health-Related—Quality of Life in Children: Low- and Middle-Income Countries",doi:"10.5772/intechopen.105845",signatures:"Yolanda Malele-Kolisa, Nazia Khan, Mpho P. 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She graduated from Gazi University Faculty of Dentistry, Ankara, Turkey in 2000. \r\nLater she received her Ph.D. degree from the Oral Diagnosis and Radiology Department; which was recently renamed as Oral and Dentomaxillofacial Radiology, from the same university. \r\nShe is working as a full-time Associate Professor and is a lecturer and an academic researcher. \r\nHer expertise areas are dental caries, cancer, dental fear and anxiety, gag reflex in dentistry, oral medicine, and dentomaxillofacial radiology.",institutionString:"Gazi University",institution:{name:"Gazi University",institutionURL:null,country:{name:"Turkey"}}}]},{type:"book",id:"7139",title:"Current Approaches in Orthodontics",subtitle:null,coverURL:"https://cdn.intechopen.com/books/images_new/7139.jpg",slug:"current-approaches-in-orthodontics",publishedDate:"April 10th 2019",editedByType:"Edited by",bookSignature:"Belma Işık Aslan and Fatma Deniz Uzuner",hash:"2c77384eeb748cf05a898d65b9dcb48a",volumeInSeries:2,fullTitle:"Current Approaches in Orthodontics",editors:[{id:"42847",title:"Dr.",name:"Belma",middleName:null,surname:"Işik Aslan",slug:"belma-isik-aslan",fullName:"Belma Işik Aslan",profilePictureURL:"https://mts.intechopen.com/storage/users/42847/images/system/42847.jpg",biography:"Dr. Belma IşIk Aslan was born in 1976 in Ankara-TURKEY. After graduating from TED Ankara College in 1994, she attended to Gazi University, Faculty of Dentistry in Ankara. She completed her PhD in orthodontic education at Gazi University between 1999-2005. Dr. Işık Aslan stayed at the Providence Hospital Craniofacial Institude and Reconstructive Surgery in Michigan, USA for three months as an observer. She worked as a specialist doctor at Gazi University, Dentistry Faculty, Department of Orthodontics between 2005-2014. She was appointed as associate professor in January, 2014 and as professor in 2021. Dr. Işık Aslan still works as an instructor at the same faculty. She has published a total of 35 articles, 10 book chapters, 39 conference proceedings both internationally and nationally. Also she was the academic editor of the international book 'Current Advances in Orthodontics'. She is a member of the Turkish Orthodontic Society and Turkish Cleft Lip and Palate Society. She is married and has 2 children. 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Prof. Hüsnü Yavuzyılmaz, he continued his studies with Prof. Dr. Gürbüz Öztürk of Istanbul University Faculty of Dentistry Department of Prosthodontics, this time on Gnatology. He attended training programs on occlusion, neurology, neurophysiology, EMG, radiology and biostatistics. In 1982, he presented his PhD thesis \\Gerber and Lauritzen Occlusion Analysis Techniques: Diagnosis Values,\\ at Istanbul University School of Dentistry, Department of Prosthodontics. As he was also working with Prof. Senih Çalıkkocaoğlu on The Physiology of Chewing at the same time, Gözler has written a chapter in Çalıkkocaoğlu\\'s book \\Complete Prostheses\\ entitled \\The Place of Neuromuscular Mechanism in Prosthetic Dentistry.\\ The book was published five times since by the Istanbul University Publications. Having presented in various conferences about occlusion analysis until 1998, Dr. Gözler has also decided to use the T-Scan II occlusion analysis method. Having been personally trained by Dr. Robert Kerstein on this method, Dr. Gözler has been lecturing on the T-Scan Occlusion Analysis Method in conferences both in Turkey and abroad. Dr. Gözler has various articles and presentations on Digital Occlusion Analysis methods. 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Dr. Al Ostwani is an assistant professor and faculty member at IUST University since 2014. \nDuring his academic experience, he has received several awards including the scientific research award from the Union of Arab Universities, the Syrian gold medal and the international gold medal for invention and creativity. Dr. Al Ostwani is a Member of the International Association of Dental Traumatology and the Syrian Society for Research and Preventive Dentistry since 2017. 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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. Dr. Gaiceanu is a member of the National Council for Attesting Titles, Diplomas and Certificates, an expert of the Executive Agency for Higher Education, Research Funding, and a member of the Senate of the Dunarea de Jos University of Galati. He has been the head of the Integrated Energy Conversion Systems and Advanced Control of Complex Processes Research Center, Romania, since 2016. He has conducted several projects in power converter systems for electrical drives, power quality, PEM and SOFC fuel cell power converters for utilities, electric vehicles, and marine applications with the Department of Regulation and Control, SIEI S.pA. (2002–2004) and the Polytechnic University of Turin, Italy (2002–2004, 2006–2007). He is a member of the Institute of Electrical and Electronics Engineers (IEEE) and cofounder-member of the IEEE Power Electronics Romanian Chapter. He is a guest editor at Energies and an academic book editor for IntechOpen. 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. He has more than 200 publications in reputed international journals, refereed conference proceedings, and 20 book chapters in books published by internationally renowned publishing houses, such as Springer, CRC press, IGI Global, etc. Currently, he is serving on the editorial board of the prestigious journal Frontiers in Communications and Networks and in the technical program committees of a number of high-ranked international conferences organized by the IEEE, USA, and the ACM, USA. 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. 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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.
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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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