**Investigation of Optical Properties and Radiation Stability of TiO2 Powders before and after Modification by Nanopowders of Various Oxides** Investigation of Optical Properties and Radiation Stability of TiO2 Powders before and after Modification by Nanopowders of Various Oxides

DOI: 10.5772/intechopen.74073

Mikhail M. Mikhailov, Vitaly V. Neshchimenko, Semyon A. Yuryev and Alexey N. Sokolovskiy Mikhail M. Mikhailov, Vitaly V. Neshchimenko, Semyon A. Yuryev and Alexey N. Sokolovskiy

Additional information is available at the end of the chapter Additional information is available at the end of the chapter

http://dx.doi.org/10.5772/intechopen.74073

#### Abstract

The titanium dioxide powders are widely used as a pigment for coatings and paints, the important characteristics of which are reflectivity and stability to irradiation. The results of investigations of the optical properties and radiation stability of titanium dioxide powders before and after high-temperature modification with nanopowders are presented in this chapter. The diffuse reflection spectra of various titanium dioxide powders in the UV, visible, and near-IR ranges, and their change during irradiation by electrons with 30 keV energy and a different fluence in vacuum in situ were investigated: (1) TiO2 powders with particle size in the range 60–240 nm; (2) Microsized TiO2 powder (240 nm) modified by Al2O3, ZrO2, SiO2, TiO2, ZnO, MgO nanoparticles with grain size from 30 up to 60 nm; (3) Microsized TiO2 powder (260 nm) modified by SiO2 with the grain size of 12–14 nm at the temperature of 150, 400, and 800C. The reduction in reflectivity in entire spectrum with decrease in grain sizes of TiO2 nanopowders was established. Nanopowder with the grain size of 80 nm possesses the highest stability to irradiation. It was shown that the average grain size and specific surface of introduced nanoparticles effect noticeably on the radiation stability increase of titanium dioxide powders modified with nanoparticles of various oxides. The micro-sized TiO2 powder heating at temperature of 800о С is the factor which positively influences on the radiation stability.

Keywords: titanium dioxide, nanoparticles, optical properties, radiation stability, modification, irradiation, defects

© 2016 The Author(s). Licensee InTech. This chapter is distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0), which permits unrestricted use, distribution, and eproduction in any medium, provided the original work is properly cited. © 2018 The Author(s). Licensee IntechOpen. This chapter is distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


*5.3.1 STEM school experience and extra-curricular work*

The different atmosphere, school culture, curriculum, relationships and assessment systems at STEM school provided a new opportunity for the participants to unleash their STEM potential beyond expectation. Aida argued that the STEM school changed her view about education as not just "buildings where students go to learn subjects like math and science" to the view that education is "about changing our way of thinking." Alia considered her STEM experience as "a very good one that [she is] grateful for being part of it." She maintained how the STEM school experience made them "independent [learners] in terms of that we had to selflearn, think, collaborate, and create … and come to class prepared to present." In her opinion, this was "interesting as it was student centered and taught us teamwork." Along the same lines, Latifa considered her STEM experience as "the greatest thing that happened and will ever happen in my life and I'm not exaggerating." It helped her to become "a good learner and a researcher." She stressed the perspective that the things she learned in STEM school would not have been possible in any other place: "I learned teamwork…how to talk with different people who have different perspectives and everything literally everything …all that I learned in STEM school way practice and [with] teachers' guidance." The school as a boarding national

school was a mini cosmos. Through their experience with girls coming from "different parts of Egypt with different cultural backgrounds" in Aida's words, they gained a lot of experience dealing with people from different backgrounds which was "very helpful for her life in college in the United States."

Fareeda greatly valued her experiences at the STEM school. The teachers, in her view, were "like our parents" and "they were caring for us and tried to help us the most." She cited the example of the physics teacher when she talked to him about "her dream to be an engineer while [her] family wanted [her] to be a doctor', he advised her to 'follow [her] dream as [she] won't excel in a thing [she] doesn't like." Aida described the teachers as "very friendly even at the moments we made sit-ins and called for reforms to make our school better, they backed us." She went on to say, "they escorted us in our journeys outside the school looking for materials for our projects, and meeting with other experts in different places." She added, "they helped us to find new ways to get information, they used different teaching approaches like discussion." Latifa remembered how teachers were careful to warn students that "being different [as STEM students] does not mean being better than anyone else we're all good in our own unique ways." She maintained how the teachers used different teaching approaches: "some let us prepare materials and present them and they gave us comments and guided our discussions." Muneera also praised her teachers as supportive using "different strategies, but the majority helped us to be independent learners. I can depend on myself now at college if I don't understand something." In some classes, learning "was completely student centered where we did the entire presentation and the teacher was supervising us and only corrected us when there was something wrong."

However, all participants were concerned that "the teachers needed more training and professional support in STEM," especially with regard to assessment as "we were, not trained enough to answer the kind of questions we faced in the final exams." Latifa alluded to the need for teachers' readiness stating that "if teachers do not know or do not understand the [STEM] system, that would be a big problem for students because if students don't understand what the system is, teachers should know because they're supposed to teach students how to do things."

All of the girls valued the challenging and rigorous curriculum. For example, Aida stated, "the curriculum was so challenging with college level material" citing the different modes of assessment used at school as very conducive to learning. As a result of the challenging curriculum and assessment, Aida "had [knowledge] about nearly all the topics in my freshman year in classes like physics and calculus." Because of the college level content at the STEM school, Latifa was "tested out of calculus 1, 2, and 3 [because] most of these topics I covered in high school and also like physics one and two and chemistry one. I had all these topics [covered] in high school. Now I'm in physics 3 and I study some topics about waves and resonance and I remember how I used to watch videos explaining these topics in high school." She added that other things like "presentation skills and collaborative work [she learned at STEM school] were very helpful at college level." Alia noted that "the curriculum was very different from regular schools in Egypt and challenging." She found the college level material very helpful and shared that when she went to college, she "found many things especially physics and math I had covered in STEM school… and the way was taught it was special."

What was unique about the curriculum in Latifa's thought was the idea of not being restricted to text books; "you can understand the learning outcome from different references: the internet, teachers, colleagues." The curriculum at the STEM school was "more open" in Muneera's terms. She argued that "in subjects like biology and chemistry at the school I had the opportunity to dig deeper into the things I was interested in and I really appreciate that." That helped her a lot at university but

**99**

the capstone project."

*Gender Equity in STEM Education: The Case of an Egyptian Girls' School*

"this openness was not good all the time. In some cases, it was not very straightforward [clear]. The goals of the curriculum or what do we have to learn after studying

For the capstone, for instance, Muneera mentioned that "each group was required to submit the following: a prototype or model of their solution, a scientific poster of the whole project, the project portfolio, and do biweekly journal reflections." Alia also mentioned the capstone project as "pretty challenging but also very useful in terms of helping us to acquire more knowledge, research skills, such as problem solving and technical skills like for creating the prototype, not to mention enhancing presentation skills." Latifa thought that the capstone projects were "the biggest point of the learning in STEM I guess… how we were supposed to deal with real-world problems and like find practical solutions for them. That was big." This was initially challenging for her as she was not used to this approach to learning and

also that the teachers were learning this new system alongside the students.

In Aida's words, assessment was "different and difficult" with a "final exam each semester which accounted for 30% of the final grade where we worked collaboratively to solve one of the grand challenges of Egypt following the engineering design process." This was completely different from the mainstream secondary schools where grades were based solely on traditional final exams. Assessment, however, was challenging as it was completely different to traditional schools and "there were no direct questions because you have to think. You don't have to memorize …they were super challenging the first 2 years." Muneera described assessments as "checking understanding not checking memorization." Challenging as it was, assessment was more manageable and conducive to learning than "memorizing a book from cover to cover and then forget everything after the exam is over." Alia noted that the "assessments were different from the ones they had been used to, but we could eventually answer most of the questions." She found the college level material very helpful and shared that when she went to college, and "the way it was taught was special." As learning dose not only happen inside the school premises, out of school extra-curricular work was seen as an integral part of the STEM school experience. The school provided different civic engagement opportunities with several organizations that gave students opportunities to visit universities and research centers to discuss scientific and engineering ideas. Muneera, for instance, was interested in chemistry outside of school and she used to "interact with those responsible for the chemistry Olympiad. They were faculty from universities." In addition to her work in the capstone and extra effort needed to finalize projects she "visited a lot of universities and interacted with professors there." Fareeda viewed engaging in different out-of-school activities and field trips as one of the greatest assets of the STEM school. She described the International Science and Engineering Fair (ISEF) experience as the "best thing that happened" to her in the STEM school. She learned a lot from that experience, in addition to winning the first award and participating in the United States international competition and winning the third place in their category, she learned "group work, presentation skills," and how to defend her ideas "in front of Nobel laureates." Latifa described her participation in a programming camp as a great learning experience: and "in the second year of high school I participated in Intel ISEF competitions and science fairs with EEE science fairs with

The research work required of students at the STEM school also pushed them to seek support outside the school walls. Aida recounted, "when I was in school, I worked on a project with the physics department at the American University [in Cairo]. I also went to Cairo University, and different [other] universities for school [projects] that helped me understand how research is done in university." Aida thought that these activities were of great value in her college level studies. Alia

*DOI: http://dx.doi.org/10.5772/intechopen.87170*

this subject were not clear."

#### *Gender Equity in STEM Education: The Case of an Egyptian Girls' School DOI: http://dx.doi.org/10.5772/intechopen.87170*

*Theorizing STEM Education in the 21st Century*

helpful for her life in college in the United States."

corrected us when there was something wrong."

and the way was taught it was special."

school was a mini cosmos. Through their experience with girls coming from "different parts of Egypt with different cultural backgrounds" in Aida's words, they gained a lot of experience dealing with people from different backgrounds which was "very

Fareeda greatly valued her experiences at the STEM school. The teachers, in her view, were "like our parents" and "they were caring for us and tried to help us the most." She cited the example of the physics teacher when she talked to him about "her dream to be an engineer while [her] family wanted [her] to be a doctor', he advised her to 'follow [her] dream as [she] won't excel in a thing [she] doesn't like." Aida described the teachers as "very friendly even at the moments we made sit-ins and called for reforms to make our school better, they backed us." She went on to say, "they escorted us in our journeys outside the school looking for materials for our projects, and meeting with other experts in different places." She added, "they helped us to find new ways to get information, they used different teaching approaches like discussion." Latifa remembered how teachers were careful to warn students that "being different [as STEM students] does not mean being better than anyone else we're all good in our own unique ways." She maintained how the teachers used different teaching approaches: "some let us prepare materials and present them and they gave us comments and guided our discussions." Muneera also praised her teachers as supportive using "different strategies, but the majority helped us to be independent learners. I can depend on myself now at college if I don't understand something." In some classes, learning "was completely student centered where we did the entire presentation and the teacher was supervising us and only

However, all participants were concerned that "the teachers needed more training and professional support in STEM," especially with regard to assessment as "we were, not trained enough to answer the kind of questions we faced in the final exams." Latifa alluded to the need for teachers' readiness stating that "if teachers do not know or do not understand the [STEM] system, that would be a big problem for students because if students don't understand what the system is, teachers should

All of the girls valued the challenging and rigorous curriculum. For example, Aida stated, "the curriculum was so challenging with college level material" citing the different modes of assessment used at school as very conducive to learning. As a result of the challenging curriculum and assessment, Aida "had [knowledge] about nearly all the topics in my freshman year in classes like physics and calculus." Because of the college level content at the STEM school, Latifa was "tested out of calculus 1, 2, and 3 [because] most of these topics I covered in high school and also like physics one and two and chemistry one. I had all these topics [covered] in high school. Now I'm in physics 3 and I study some topics about waves and resonance and I remember how I used to watch videos explaining these topics in high school." She added that other things like "presentation skills and collaborative work [she learned at STEM school] were very helpful at college level." Alia noted that "the curriculum was very different from regular schools in Egypt and challenging." She found the college level material very helpful and shared that when she went to college, she "found many things especially physics and math I had covered in STEM school…

What was unique about the curriculum in Latifa's thought was the idea of not being restricted to text books; "you can understand the learning outcome from different references: the internet, teachers, colleagues." The curriculum at the STEM school was "more open" in Muneera's terms. She argued that "in subjects like biology and chemistry at the school I had the opportunity to dig deeper into the things I was interested in and I really appreciate that." That helped her a lot at university but

know because they're supposed to teach students how to do things."

**98**

"this openness was not good all the time. In some cases, it was not very straightforward [clear]. The goals of the curriculum or what do we have to learn after studying this subject were not clear."

For the capstone, for instance, Muneera mentioned that "each group was required to submit the following: a prototype or model of their solution, a scientific poster of the whole project, the project portfolio, and do biweekly journal reflections." Alia also mentioned the capstone project as "pretty challenging but also very useful in terms of helping us to acquire more knowledge, research skills, such as problem solving and technical skills like for creating the prototype, not to mention enhancing presentation skills." Latifa thought that the capstone projects were "the biggest point of the learning in STEM I guess… how we were supposed to deal with real-world problems and like find practical solutions for them. That was big." This was initially challenging for her as she was not used to this approach to learning and also that the teachers were learning this new system alongside the students.

In Aida's words, assessment was "different and difficult" with a "final exam each semester which accounted for 30% of the final grade where we worked collaboratively to solve one of the grand challenges of Egypt following the engineering design process." This was completely different from the mainstream secondary schools where grades were based solely on traditional final exams. Assessment, however, was challenging as it was completely different to traditional schools and "there were no direct questions because you have to think. You don't have to memorize …they were super challenging the first 2 years." Muneera described assessments as "checking understanding not checking memorization." Challenging as it was, assessment was more manageable and conducive to learning than "memorizing a book from cover to cover and then forget everything after the exam is over." Alia noted that the "assessments were different from the ones they had been used to, but we could eventually answer most of the questions." She found the college level material very helpful and shared that when she went to college, and "the way it was taught was special."

As learning dose not only happen inside the school premises, out of school extra-curricular work was seen as an integral part of the STEM school experience. The school provided different civic engagement opportunities with several organizations that gave students opportunities to visit universities and research centers to discuss scientific and engineering ideas. Muneera, for instance, was interested in chemistry outside of school and she used to "interact with those responsible for the chemistry Olympiad. They were faculty from universities." In addition to her work in the capstone and extra effort needed to finalize projects she "visited a lot of universities and interacted with professors there." Fareeda viewed engaging in different out-of-school activities and field trips as one of the greatest assets of the STEM school. She described the International Science and Engineering Fair (ISEF) experience as the "best thing that happened" to her in the STEM school. She learned a lot from that experience, in addition to winning the first award and participating in the United States international competition and winning the third place in their category, she learned "group work, presentation skills," and how to defend her ideas "in front of Nobel laureates." Latifa described her participation in a programming camp as a great learning experience: and "in the second year of high school I participated in Intel ISEF competitions and science fairs with EEE science fairs with the capstone project."

The research work required of students at the STEM school also pushed them to seek support outside the school walls. Aida recounted, "when I was in school, I worked on a project with the physics department at the American University [in Cairo]. I also went to Cairo University, and different [other] universities for school [projects] that helped me understand how research is done in university." Aida thought that these activities were of great value in her college level studies. Alia

mentioned visits to "different universities and research centers and talking to professors about their projects" as reinforcing their STEM identity as they were "able to ask questions and discuss our work in a free way." Alia described the physical work they used to do build their projects prototypes; "in addition to engineers and professors who helped us in designing our [capstone projects] prototypes, we also sought the help of technicians like plumbers, carpenters, electricians to build certain parts of these prototypes."

Among the challenges faced by two of the participants (Muneera and Fareeda) was studying engineering while not being a mathematics major in high school. Muneera said it was a challenge at the very beginning but she added "I am doing very well in math now" and that the skills from the STEM school rather than content were the reason as, "now [at college] when I am stuck in anything, I can teach myself… I do not need someone to teach me…I can go find books or the internet, or any way to understand so I really think this was great from the school. I learned how to work in a group, though I speak different [foreign] language [with accent] I had the strong personality to face challenges… I had learned a lot how to deal with people." Alia argued that the experience at STEM school was invaluable in terms of helping them address any academic challenges because it helped her to be "an independent learner and know how to collaborate." On a personal level, she felt "it [STEM school experience] made me more confident and made my first years at college easier."

 The general rule is that starting from grade seven most schools are segregated except for a certain track called "distinguished public language schools" in which mathematics and science are taught in English. Fareeda was a staunch supporter for single sex STEM schools as long as "they provide quality education and have similar teachers [to our school] and [similar school] environment." She argued that the female students "felt more comfortable" and had "the chance to work together freely without pressures, to compete in the female way to excel." She concluded, "it was a great experience all over. We worked together in a friendly way." Aida thought that single sex schools are "good, but they need more planning." If she were to choose between a co-ed or a single sex school, she would "choose a single sex school because the friendly atmosphere developed at the school made the students closer to each other in a way you can't find in another school." Along the same lines, although Alia initially stated that she "did not have a preference" for single sex versus co-ed schools, she "would choose the single sex school just because we created a community in which we lived together as sisters, it was kind of empowering." Therefore, if she were given the choice, she "would definitely go for single sex schools."

On the other hand, when asked about the single sex learning experience, Latifa was vocal in resisting that type of schooling. She said, "I think it would be better if both sexes were in the same school because I believe that this system and the way of thinking will be more inclusive of the two ways of thinking [male and female]." Latifa posited the reason behind the fact that girls' school "was relatively better at getting like high grades, while they [boys] win more robotics competitions and programming and like the technology stuff" is due to "a natural difference between the two [genders] in terms of foci and interests."

Muneera said, "if I went back I would prefer mixed schools." She had a hard time adjusting to the coed nature of higher education.  Therefore, her ability to communicate with people from both sexes was affected by this long education experience. She explained "it was kind of the challenge when I came here. At the beginning I

**101**

*Gender Equity in STEM Education: The Case of an Egyptian Girls' School*

could not deal with guys. It was hard because I didn't have experience. I did not go somewhere else. I was all my life in that single sex school system." However, her experience in the STEM school pushed them "to build the environment where we're supporting each other and learning from each other as different people coming

From a cross-case perspective, a multilayered pattern of the supports and challenges [47] that impact gender equity in STEM education in the Egyptian context were delineated (see **Table 3**). The intersectional nature of the educational and sociological phenomena [41–43] is clearly reflected in the journey of the participants in this study. The participants endeavor towards STEM fulfillment reflects the power dynamics and relationships which are embedded in the structures and functions of society where society is structured by meanings, rules, convictions or habits adhered to by social beings [42, 45, 46]. As a result of the data analysis, the underlying mechanism of factors that support or impede girls' pursuit of STEM tracks show complexities of the phenomenon of creating gender equity, both broadly and especially in the Egyptian context. This is clearly manifested in the emerging themes from the data analysis (see **Table 3**). The intersectional pattern includes the impact of the power relationship of the socio-cultural, educational, and personal aspects. For instance, the existence of stereotype threats and biases [27] was salient in most of the participants' experiences. However, this was diminished by both factors at the personal and school levels epitomized in the girls' resilience and the supports they received through their experiences at the STEM school. The girls did not concede to family and social pressures; they pursued their own dreams. In their emancipation journey, they showed high degrees of persistence, self-efficacy, and resistance to the social norms and stereotype threats at the family level and the immediate social network [42, 45, 46]. In spite of the challenges they faced, the girls were able to navigate through this experience and benefit from it in their higher

In addition to the intersectional nature of the socio-cultural phenomenon of gender equity in STEM, these cases present a clear example of how gendered roles are created at both the social and family level [42, 45] and how they can be disrupted. One way to challenge such fossilized gender roles either explicitly or implicitly, especially in the absence of social collective effort, is through consolidating personal traits like self-efficacy and persistence [30, 31, 33]. This is apparent in girls' defiance to the commonly accepted stereotype that it is hard for girls to be engineers. There seemed to be a strong relationship between the degree of bias and the level of resistance on the part of the girls; in the cases where gender bias was explicitly reiterated, there was markedly higher degrees of resistance to such stereotype threats [27, 42]. However, to address gender inequity in STEM, more

The school and teachers provided additional support to the girls' personal resilience. All participants referred to factors at the school level that were effective in deepening their interest in STEM, especially engineering. At the curriculum level, one of the common features was rigor and challenge. Moreover, at the assessment level, participants agreed that assessments were not checking memorization; they were checking understanding which has helped them in their higher education institutions. Not only did the participants refer to the challenging curriculum but the way that curriculum was delivered. The primary support came from the girlfriendly pedagogies they encountered at school. They referred to quality teachers

work at the social level and at school level is required [6, 29, 34, 44].

*DOI: http://dx.doi.org/10.5772/intechopen.87170*

from different backgrounds."

education engineering institutions.

**6. Discussion**

could not deal with guys. It was hard because I didn't have experience. I did not go somewhere else. I was all my life in that single sex school system." However, her experience in the STEM school pushed them "to build the environment where we're supporting each other and learning from each other as different people coming from different backgrounds."


**Appendix A**

**Table A1.** Forecast model parameters distribution from 10,000 MCMC sampling for 2018, Anchorage sequence.

**Figure A1.** Plot of the magnitudes versus sequential numbers of the earthquakes in the study regions for the three sequences: (**a**) 3 November 2002, Mw 7.9 Denali (**b**) 23 January 2018, Mw 7.9 Kodiak (**c**) 30 November 2018, Mw 7.1 Anchorage. The corresponding times in days after each mainshock are depicted by doted vertical lines.

**Figure A2.** The log-log plot of the earthquake decay rates for: (**a**) the 2002, Mw 7.9 Denali sequence with *m* ≥ 3.0; (**b**) the 2018, Mw 7.9 Kodiak sequence with *m* ≥ 3.2 are presented as open squares. The blue solid lines are the corresponding fit of the OU law, Equation (5), to the aftershock sequences. The obtained parameters from the OU law, Equation (5), with the 95% confidence intervals are reported in the legends.

**Figure A3.** The aftershock sequence and corresponding earthquake magnitude for: (**a**) the 2002, Mw 7.9 Denali sequence with *m* ≥ 3.0; (**b**) the 2018, Mw 7.9 Kodiak sequence with *m* ≥ 3.2. The ETAS model fit, Equation (6), for the target time interval of [*Ts*, *Te*]=[0.06, 30] is plotted as a solid blue line, and the obtained set of parameters are reported with 95% confidence intervals. The OU law fit, Equation (5), is plotted as a black dashed line for comparison.

**Figure A4.** The model parameter estimation during the aftershock sequence of the 2018, Anchorage for all the events with magnitude 2.8 and greater. (**a**) The estimated *b*-value, Equation (1), (**b**) the parameters {*K*, *c*, *p*} of the OU law, Equation (5), and (**c**) the parameters {*A*, *c*, *p*, *α*} of the ETAS model, Equation (6). The error bars represent the 95% confidence intervals during the target time intervals, {1, 2, 3, 4, 5, 6, 7, 10, 14, 21, 30}, days after the mainshock.

**Figure A5.** The distribution of each parameter and the matrix plot of the pairs of the OU parameters that computed using the MCMC sampling for the 2018, Mw 7.1 Anchorage sequence with *m* ≥ 2.8.

**Figure A6.** The distribution of each parameter and the matrix plot of the pairs of the ETAS parameters computed using the MCMC sampling for the 2018, Mw 7.1 Anchorage sequence with *m* ≥ 2.8.

**Figure A7.** The probabilities to have the largest expected aftershocks to be larger than *m*ex ≥ 5.0, 6.0, 7.0 using the BPD, Equation (12), during a constant target time interval of [*Ts*, *Te*]=[0.06, 2] days and for the varying target time intervals. (**a**) The 3 November 2002, Mw 7.9 Denali sequence with *m* ≥ 3.0. (**b**) The 23 January 2018, Mw 7.9 Kodiak sequence with *m* ≥ 3.2. (**c**) The 30 November 2018, Mw 7.1 Anchorage sequence with *m* ≥ 2.8.

**Figure A8.** The comparison of the probabilities to have the largest expected aftershock during the target time interval of [*Ts*, *Te*]=[0.06, 2] days for the three sequences: (**a**) 3 November 2002, Mw 7.9 Denali (**b**) 23 January 2018, Mw 7.9 Kodiak (**c**) 30 November 2018, Mw 7.1 Anchorage. The blue triangles are computed using the BPD, Equation (12), with an earthquake decay rate given by the ETAS model, Equation (6). The purple squares are computed using BPD, Equation (12), with an earthquake decay rate given by OU law, Equation (5). The green circles give probabilities computed using the EVD, Equation (11). The aftershock magnitudes are modelled using Equation (3).

**Figure A9.** The number of forecasted and observed aftershocks in the forecasting time interval Δ*T* = [1, 2, 5, 7, 10, 14] days for (**a**) The 3 November 2002, Mw 7.9 Denali for *m* ≥ 3.0; (**b**) The 23 January 2018, Mw 7.9 Kodiak for *m* ≥ 3.2; (**c**) The 30 November 2018, Mw 7.1 Anchorage for *m* ≥ 2.8 by using the constant target time interval [*Ts*, *Te*]=[0.06, 2] days. The red squares show the average number of forecasted earthquakes using the ETAS model, Equation (6), and the black triangles illustrate the average number of forecasted earthquakes using OU law, Equation (5). The shading bands represent 95% confidence intervals. The blue circles represents the observed number of earthquakes in the forecast time interval.

**Figure A10.** The number of forecasted and observed aftershocks in the forecasting time interval Δ*T* = 7 days for the three sequences: (**a**) the 3 November 2002, Mw 7.9 Denali sequence for *m* ≥ 3.5; (**b**) the 23 January 2018, Mw 7.9 Kodiak sequence for *m* ≥ 3.5; (**c**) the 30 November 2018, Mw 7.1 Anchorage sequence for *m* ≥ 3.5. The red triangles show the average number of forecasted earthquakes using the ETAS model and the black squares illustrate the average number of forecasted earthquakes using OU law. The shading bands represent 95% confidence intervals. The blue circles represent the observed number of earthquakes in each forecasting time interval.

**Figure A11.** The obtained quantile scores from the M-test for the constant target time interval [*Ts*, *Te*]=[0.06, 2] days for (**a**) The 3 November 2002, Mw 7.9 Denali for *m* ≥ 3.0; (**b**) The 23 January 2018, Mw 7.9 Kodiak for *m* ≥ 3.2; (**c**) The 30 November 2018, Mw 7.1 Anchorage for *m* ≥ 2.8. The red triangles demonstrate the obtained quantile scores from the ETAS model, Equation (6), and the black squares illustrate the quantile scores of OU law, Equation (5). The blue dashed lines represent the 0.025th and 0.05th quantiles.


**About the Editor**

#### **Daniele Giansanti**

Dr. Giansanti has received: an MD in Electronic Engineering at Sapienza University, 1991, Rome; a PhD in Telecommunications and Microelectronics Engineering at Tor Vergata University, 1997, Rome; the Academic Specialization in Cognitive Psychology and Neural Networks at Sapienza University, Rome, 1997; and his Academic Specialization in Medical Physics at Sapienza University, Rome, 2005. Dr. Giansanti was in charge of the Design of VLSI Asics for DSP in the Civil Field (1991–1997) during his MD and PhD studies, and he served as CAE-CAD-CAM system manager and Design Engineer in the project of electronic systems (Boards and VLSI) for Warfare at Elettronica spa (1992–2000), one of the leaders in this military field. More importantly, he also conducts various research at ISS (the Italian NIH) (2000–today) in the following fields: (1) biomedical engineering and medical physics with the design and construction of wearable and portable devices (three national patents); (2) telemedicine and e-Health: technology assessments and the integration of new systems in the fields of tele-rehabilitation, domiciliary monitoring, digital pathology, and digital radiology; (3) Mhealth: recent interests in the fields of smartphone and tablet technology in health care, with particular focus on the opportunities and relevant problems of risks, abuse, and regulation; (4) acceptance and consensus in the use of robots for assistance and rehabilitation; (5) challenges and acceptance regarding the use of artificial intelligence in digital radiology and digital pathology; (6) cybersecurity in the health domain; and (7) technologies for frail and disabled people. He is a Professor at Sapienza and Catholic University in Rome, where he teaches several courses and is the tutor for several theses. He is a Board Editor and reviewer for several journals. He has 126 indexed publications on Scopus, more than 200 contributions as monographies and chapters, and contributes to congresses.


*Article* **Ontology-Based Process Modelling-with Examples of Physical Topologies**

**Heinz A Preisig**

> Department of Chemical Engineering, Norwegian University of Science and Technology, 7491 Trondheim, Norway<EMAIL_ADDRESS>
**Abstract:** Reductionism and splitting application domain into disciplines and identify the smallest required model-granules, termed "basic entity" combined with systematic construction of the behaviour equations for the basic entities, yields a systematic approach to process modelling. We do not aim toward a single modelling domain, but we enable to address specific application domains and object inheritance. We start with reductionism and demonstrate how the basic entities are depending on the targeted application domain. We use directed graphs to capture process models, and we introduce a new concept, which we call "tokens" that enables us to extend the context beyond physical systems. The network representation is hierarchical so as to capture complex systems. The interacting basic entities are defined in the leave nodes of the hierarchy, making the overall model the interacting networks in the leave nodes. Multi-disciplinary and multi-scale models result in a network of networks. We identify two distinct network communication ports, namely ports that exchange tokens and ports that transfer information of tokens in accumulators. An ontology captures the structural elements and the applicable rules and defines the syntax to establish the behaviour equations. Linking the behaviours to the basic entities defines the alphabet of a graphical language. We use this graphical language to represent processes, which has proven to be efficient and valuable. A set of three examples demonstrates the power of the graphical language. The Process Modelling framework (ProMo) implements the ontology-centred approach to process modelling and uses the graphical language to construct process models.

**Keywords:** model-based; computational engineering; process simulation; digital twin


**3.11 Production inventory**

Production industry focuses on stock valuation, stock management, and stock control. Production inventory used raw materials in production, the semifinished goods in the warehouse, and finished goods are ready to sell. The production system produces different types of products, and it is supplied into different warehouses. This system maintained a sufficient raw material in storage for smooth running of an *Advances in Inventory Control DOI: http://dx.doi.org/10.5772/intechopen.104387*

enterprise. This inventory needs to take practice for keeping enough stock on hand so the production process can run effectively.

Processing of each product type is carried out in lots of units, and finished lots are placed in the warehouse. Lot processing time is deterministic. Failures may occur during the production process when the production facility is busy. Times between failures are exponentially distributed with average units.

Production inventory is further classified into three inventories. There are raw materials, work-in process, and finished goods.

#### **3.12 Raw materials**

Raw materials can be commodities or components that are used in the production of goods and finished goods inventory. It can be classified as either direct materials or indirect materials. Material cost adds in production with the manufacturing overhead to calculate the raw materials inventory.

For example, automobile companies purchase various kinds of metals such as steel, aluminum, resins, copper, lead, and platinum from various suppliers that are used to make finished goods. i.e., cars. Flour is considered as indirect materials in bakery company to make finished products such as bread, pasta, crackers, many cakes, and many other foods are made using flour.

Raw materials include oil, lubricant, light bulbs, screws, nuts, bolts, etc., which are the examples of indirect raw materials.

#### **3.13 Work-in-process**

It is defined as the goods that are in different stages of production in production process. Products have been partially completed in the production cycle. Sometimes, products are waiting to be assembled and sold. Inventory level of work-in-progress should be kept as low as possible, which gives better returns to the industry. It can be avoided to lock up the capital of the enterprise.

#### **3.14 Finished goods**

Products are completely finished, which are ready for sale in the production process. That is, finished goods inventory is in stock that is available for customers to purchase. In production industry, the product is first made and then sold to the buyers or the received order is first, and then it is manufactured as per requirements with some specifications.


**1. Introduction**

The development of efficient fuel and its sustainability is the major topic of concern in the time of climate change and food insecurity. The generation of efficient sources of fuel and fiber delineates the ways for the development of sustainable sources of fuel. Biodiesel is an alternative to petroleum-based fuels derived from a variety of feedstocks; including vegetable oils, animal fats, and waste cooking oil [1]. At present, biodiesel is mainly produced from conventionally grown edible oils such as soybean, rapeseed, sunflower, and palm. The cost of biodiesel is the main obstacle to commercialization of the product [2, 3]. Biodiesel produced from edible oils is

currently not economically feasible. On the other hand, extensive use of edible oils for biodiesel production may lead to food crisis. The complexity is diverse in case of food and fuel crops, and raw material is derived from plant seed oils and animal fats and is a mixture of the alkyl esters of long-chain fatty acids, mainly produced by transesterification methodology [4]. The concentration of useful fatty acid is the basis of selection, and the utility of biodiesel can be increased by focusing on the traits related to direct production of oil and its quality.

Before focusing on the mitigation practices, other ways of dissection of traits can be done to improvise the genetic architecture of crop plants. The dissection of various properties relevant to biofuel development can be targeted. The physicochemical properties of biodiesel are very similar to those of petroleum diesel and, therefore, could be used as an alternative to diesel in conventional diesel engines without the need for any modifications [5]. In contrast to conventional fuels, other advantages of biodiesel include higher cetane number, flash point, and lubricity, absence of sulfur, and lower aromatics content compared with the petroleum diesel [6, 7]. The density, viscosity, cetane number, linolenic acid, methyl ester, polyunsaturated methyl esters, acid value, glycerides content come under the major parameters of physiochemical properties and are considered before making suitable mixture with commercial diesel [8, 9]. These parameters are of prime importance to study before subjecting oilseed crops to get biofuel. The quality and content of oil are also of basic and utmost important feature to observe and determination for fatty acid profile and important physiochemical properties [10]. Currently, the majority of the commercial production of biodiesel is dependent on oils derived from palm, soybean, and rapeseed by conventional methods. Changing the direction of biodiesel production from food crops to nonedible plants requires significant improvements in oil yield and quality of these plants as well as in their tolerance to biotic and abiotic stresses. As discussed throughout the present article, biotechnological interventions and genetic engineering approaches have shown great potentials to achieve these goals [11]. However, the application of such technologies in oil plants is at their starting points, and there is no commercial oil plant with enhanced oil content or composition yet; there are laboratory and pilot-scale samples though. Moreover, it is also necessary to thoroughly evaluate the potentials of genetic engineering technology in improving several other attributes of oil plants, i.e., environment adaptation, production cost, and economic feasibility in field scale [12]. Lack of the presence of superior genotypes as a base for genetic engineering especially for nonedible plants such as *Jatropha,* which is known as one of the most important to study but not implemented and proved as one of the drawbacks in pursuing this path [13]. Developing high-throughput tissue culture and transformation protocols for oil plants is also very important to produce a large number of primary GM lines. This is very critical for especially woody perennial trees. Most of the GM oil crops have been evaluated at laboratory or greenhouse levels, and it is not clear that their responses under field conditions are yet to be looked into [14]. It should be noted that genetic engineering methods might sometimes seem technically successful but would lead to commercial failures at large-scale production [15]. Identification and characterization of major genes involved in TAG biosynthesis pathway as well as in adaptation to biotic and abiotic stresses are also of grave importance [16]. In addition, it is necessary to carry out gene pyramiding programs to collect different agronomical traits in single superior genotypes of oil plants. This would help breeders to accelerate achieving superior genotypes suitable for commercial biodiesel production. Another challenge would be the biosafety issues related to GM oil plants, necessitating performing environmental and health risk assessments for such plants before commercial release.

This would include evaluation of GM plants risks related to gene flow and potential negative effects on non-target organisms as well as the risks of potential negative effects on human and animal health.


**4. Information optical method for modeling aero-optical imaging**

#### **4.1 Angular spectrum propagation model**

**Figure 18** depicts the propagation of the angular frequency spectrum of plane wave. As to the optical wave, the complex amplitude of the plane wave is expressed by

**Figure 18.** *The angular spectrum propagation of plane wave in uniform optical media.*

$$\begin{split} U(\mathbf{r},t) &= a \exp\left(ik \cdot \mathbf{r}\right) \\ &= a \exp\left[ik(\mathbf{x}\cos a + \mathbf{y}\cos \beta + \mathbf{z}\cos \gamma)\right] \end{split} \tag{21}$$

where *a* is the constant amplitude; cos ð Þ *α*, cos *β*, cos *γ* denotes the direction cosine; *k* ¼ 2*π=λ* is the wave vector [30].

The angular frequency spectrum is just the 2-D Fourier transformation of the complex amplitude of optical wave. Given that a monochromatic light injects the X-Y plane along with the direction of Z axis, its angular spectrum can be expressed as

$$A\left(f\_{\mathbf{x}}, f\_{\mathbf{y}}, z\right) = \iint U(\mathbf{x}, \mathbf{y}, z) \exp\left[-i2\pi \left(\mathbf{x}f\_{\mathbf{x}} + \mathbf{y}f\_{\mathbf{y}}\right)\right] d\mathbf{x}d\mathbf{y} \tag{22}$$

where *U x*ð Þ , *y*, *z* is the complex amplitude distribution. On the other hand, the inverse Fourier transform of the angular spectrum is a complex amplitude distribution. Here, the transmission of aerial optics through the flow fields can be seen as the transmission of each spectrum. Each plane wave spectrum in ð Þ *x*, *y*, 0 is denoted by *A*0 *f x*, *f y*, 0 � �, and each spectrum in ð Þ *x*, *y*, *z* is denoted by *A*0 *f x*, *f y*, *z* � �, where *f x* ¼ cos *α λ* , *f y* ¼ cos *β λ* . According to the Helmholtz scalar equation, angular spectrum propagation function can be obtained as

$$A\_1(\frac{\cos a}{\lambda}, \frac{\cos \beta}{\lambda}, z) = A\_0\left(\frac{\cos a}{\lambda}, \frac{\cos \beta}{\lambda}, 0\right) \exp\left(j kz\sqrt{1 - \cos^2 a - \cos^2 \beta}\right) \tag{23}$$

which describes the propagation between the two parallel planes. As a matter of fact, a transfer function of frequency filtering is obtained by

$$\begin{aligned} H\_c \left( f\_x, f\_y \right) &= \frac{A \left( f\_x, f\_y \right)}{A\_0 \left( f\_x, f\_y \right)} \\ &= \left\{ \begin{array}{l} ikz \left[ ikz \sqrt{1 - \left( \left. \left. f\_x \right)^2 - \left( \left. \left. f\_y \right)^2 \right| \right. \right. \right]} & f\_x \right.^2 + f\_y \right.^2 < \frac{1}{\lambda^2} \\ & 0 & \text{others} \end{array} \tag{24}$$

The model of aero-optical imaging proposed in this chapter is inspired by the above analysis. Hence, the aero-optical transmission is translated into spatial filtering with limited bandwidth of the lights.

#### **4.2 Linear filter model of aero-optical imaging**

The light source described in this chapter may be too far away from the built-in detector, causing the output wave to appear as a plane wave. Therefore, the transmission of light at hypersonic speed can be considered as the transmission of plane waves. The term "diffraction" is conveniently described by Sommerfeld as " any deviation of light rays from rectilinear paths that cannot be interpreted as reflection or

*Perspective Chapter: Computational Modeling for Predicting the Optical Distortions… DOI: http://dx.doi.org/10.5772/intechopen.106591*

refraction.". Furthermore, the results obtained from the scalar diffraction theory approximate the real effect if the wavelength is smaller than the diffraction aperture and the observation point is far from the diffraction aperture [31]. The supersonic flow field transmission process considering the above discussion, aero-optics transmission can be seen as a scalar diffraction problem, so angular spectrum propagation can be used for aero-optics research.

From the point of view of information optics, each cubic grid can be seen as an optical system that composes any optical filtering system that characterizes the flow fields. After these considerations, the supersonic flow fields can be divided into 63 � 63 � 79 optical filtration subsystems, which are serially connected in the negative direction along the Z axis. **Figure 19** maps a sketch of the plane optical wave through CFD cubic grids.

**Figure 20** shows the structure of one cubic CFD grid. Each cubic grid has eight points with the determined index of refraction. The following equation gives out the characteristic parameter *ni oc* of the cubic optical filtering system.

$$n^i\_{\
oc} = \frac{(n\_1 + n\_2 + \dots + n\_8)}{8} \tag{25}$$

where *i* is the order number of the optical filtering system (*i* ¼ 63 � 63 � 79). One of these serial systems is described in **Figure 21**. *Hi f x*, *f y*, *zi* denotes the transfer

**Figure 19.** *The sketch map of CFD cubic grids.*

**Figure 20.** *The distribution of CFD grid points in one cubic optic system.*

**Figure 21.** *The diagram of serially connected systems representing the transmission of angle spectrum.*

function of the *i*th optical system, which can be gained through Eq. (23) based on angular spectrum propagation model.

In the frequency domain, the output of such serially linear filtering system can be obtained through

$$A\_i(f\_{\,\,x}, f\_{\,\,y}, z\_i) = A\_0\left(f\_{\,\,x}, f\_{\,\,y}, \mathbf{0}\right) H\_1 H\_2 \cdots H\_i \tag{26}$$

However, Eq. (23) is actually called as coherence transfer function (CTF). As to aero-optics, it should be viewed as a noncoherent imaging system, which is a linear system concerning on the distribution of light intensity. To the noncoherent imaging system, optical transfer function (OTF) is utilized for the study of light propagation. The OTF can be derived from CTF through the following equation

$$H(u,v) = \frac{H\_{\epsilon}(u,v) \otimes H\_{\epsilon}(u,v)}{\int \int\_{-\infty}^{\infty} |H\_{\epsilon}(a,\ \beta)| da d\beta} \tag{27}$$

where CTF is ½ �¼ *hc*ð Þ *x*, *y Hc*ð Þ *u*, *v* , *u* ¼ *f x*,*v* ¼ *f y* and OTF is ½ �¼ *h x*ð Þ , *y H u*ð Þ , *v* . Thus, OTF of the flow fields is equal to the 2D Fourier transformation of the pointspread function (PSF, *PSF* ¼ *h x*ð Þ , *y* ) of light intensity distributions. Relationship between the input light intensity distribution *Io*ð Þ *x*, *y* and output light intensity distribution *I x*ð Þ , *y* is obtained by

$$\mathbb{E}[I\_o(\mathbf{x},\ \mathcal{y})] \cdot \mathbb{E}[h(\mathbf{x},\ \mathcal{y})] = \mathbb{E}[I(\mathbf{x},\ \mathcal{y})] \tag{28}$$

where *I x*ð Þ¼ , *y* j j *U x*ð Þ , *y* 2 is the light intensity distribution.

Through the above theoretical analysis, a discrete OTF matrix 63 � 63 could be acquired. In other words, PSF can be gained for the spatial filtering of image. The relationship between PSF and the light intensity distributions is satisfied by

$$I(\mathbf{x}, \boldsymbol{y}) = I\_o(\mathbf{x}, \boldsymbol{y}) \* h(\mathbf{x}, \boldsymbol{y}) \tag{29}$$

Here, the transmission of right incident light through the supersonic flow fields is considered. And position of the image centroid can be calculated by

$$\mathbf{x}\_{\varepsilon} = \frac{\sum\_{i} i \cdot I(i, j)}{\sum\_{i} \sum\_{j} I(i, j)}, \mathbf{y}\_{\varepsilon} = \frac{\sum\_{j} j \cdot I(i, j)}{\sum\_{i} \sum\_{j} I(i, j)} \tag{30}$$

where ð Þ *i*, *j* is the coordinate of the corresponding image pixel at the image coordinate, and *I i*ð Þ , *j* is the corresponding pixel value. Thus, the centroid shift of the degraded image can be evaluated through,

*Perspective Chapter: Computational Modeling for Predicting the Optical Distortions… DOI: http://dx.doi.org/10.5772/intechopen.106591*

$$
\Delta \mathbf{x} = \mathbf{x}'\_c - \mathbf{x}''\_c,\\
\Delta \mathbf{y} = \mathbf{y}'\_c - \mathbf{y}''\_c \tag{31}
$$

where *x*0 *c*, *y*0 � � *c* , *xo c*, *yo c* � � are respectively the centroids of the degraded image and original image. To estimate the total aberrations induced by the flow fields, Euclidean distance (ED) of image shift is used for an implicit assessment through

$$\mathbf{r}\_{\rm ED} = \sqrt{\left(\mathbf{x'} - \mathbf{x}\right)^2 + \left(\mathbf{y'} - \mathbf{y}\right)^2} \tag{32}$$

#### **4.3 Simulation results**

Digital images of aircraft obtained from the Internet are used to simulate aerooptical images. To study the shift of image centroid without considering the effect of temporal integration on the image, only snapshots were numerically investigated. **Figure 22** shows the original image. **Figures 23**–**25** show the degradation results of a supersonic flow fields with the same Mach number (Ma = 7) and height of 30, 35 and 40 km, respectively. **Figures 23** and **26** show the results when the height is 30 km and the Mach numbers are 7 and 5, respectively. **Table 1** shows the results of calculating the shifts of image centroid. Although the evaluation method cannot calculate the total

**Figure 22.** *The original image.*

**Figure 23.** *The aero-optically degraded image (H = 30 km, Ma = 7).*

**Figure 24.** *The aero-optically degraded image (H = 35 km, Ma = 7).*

**Figure 25.** *The aero-optically degraded image (H = 40 km, Ma = 7).*

### **Figure 26.** *The aero-optically degraded image (H = 30 km, Ma = 5).*

aero-optical distortion, the validity of the proposed model of the aero-optical imaging method based on optical information can be easily verified.

It must qualitatively satisfy the aero-optical effect of light propagation in a supersonic flow fields. That is, at the same Mach number, the lower the height, the stronger *Perspective Chapter: Computational Modeling for Predicting the Optical Distortions… DOI: http://dx.doi.org/10.5772/intechopen.106591*

#### **Table 2.**

*Image centroid shifts related to the original image.*

the aero-optical effect. The higher the Mach number at the same height, the stronger the optical effect of air. The image is blurred and the centroid shift is larger in the quantitative analysis.

Furthermore, from the results in **Table 2**, it can be seen that the Mach number in the aero-optical images has a greater weight than the flight altitude. That is, the compressive effect of the flow fields by the flight speed compared with atmospheric density at different altitudes is a key factor influencing the change in the density field. Through the above analysis, the simulation results are consistent with the basic facts of the aero-optic effect.


Open Access This chapter is licensed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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## **Author Index**

#### **A**

Abdulla, Parosh Aziz I-588 Abdulla, Parosh I-105 Aggarwal, Saksham I-666 Agrawal, Sakshi II-588 Albert, Elvira I-448 Aljaafari, Fatimah II-541 Amir, Guy I-607 Anand, Ashwani II-211 Andreotti, Bruno I-367 Apinis, Kalmer II-453 Atig, Mohamad Faouzi I-588 Atig, Mohamed Faouzi I-105 Avigad, Jeremy II-74 Ayaziová, Paulína II-523

#### **B**

Bach, Jakob I-407 Bajwa, Ali I-308 Balachander, Mrudula II-309 Banerjee, Anindya II-133 Barbosa, Haniel I-367 Barrau, Florian II-3 Barth, Max II-577 Bassan, Shahaf I-187 Batz, Kevin II-410 Bentkamp, Alexander II-74 Beutner, Raven I-145 Beyer, Dirk II-152, II-495 Biere, Armin I-426 Blanchette, Jasmin II-111 Bonakdarpour, Borzoo I-29, I-66 Bouma, Jelle II-19 Bruyère, Véronique I-271

#### **C**

Cadilhac, Michaël II-192 Chadha, Rohit I-308

Chakraborty, Supratik II-588 Chalupa, Marek II-535 Chatterjee, Krishnendu I-3 Chen, Mingshuai II-410 Chien, Po-Chun II-152 Chimdyalwar, Bharti II-588 Chin, Wei-Ngan I-569 Cimatti, Alessandro II-3 Cooper, Martin C. I-167 Cordeiro, Lucas C. II-541 Corfini, Sara II-3 Correas, Jesús I-448 Corsi, Davide I-607 Cortes, João II-55 Cristoforetti, Luca II-3

#### **D**

Darke, Priyanka II-588 de Gouw, Stijn II-19 de la Banda, Alejandro Stuckey I-666 de Pol, Jaco van II-353 Deligiannis, Pantazis II-433 Denis, Xavier II-93 Di Natale, Marco II-3 Dietsch, Daniel II-577, II-582 Dimitrova, Rayna II-251 Doveri, Kyveli I-290 Duan, Zhenhua II-571

#### **E**

Erhard, Julian II-547 Ernst, Gidon II-559 Etman, L. F. P. II-44 Eugster, Patrick I-126

#### **F**

Fang, Wenji II-11 Farinelli, Alessandro I-607

© The Editor(s) (if applicable) and The Author(s) 2023 S. Sankaranarayanan and N. Sharygina (Eds.): TACAS 2023, LNCS 13993, pp. 705–708, 2023. https://doi.org/10.1007/978-3-031-30823-9

706 Author Index

Fedyukovich, Grigory II-270 Fichtner, Leonard II-577 Filiot, Emmanuel II-309 Finkbeiner, Bernd I-29, I-145 Fokkink, W. J. II-44 Fuchs, Tobias I-407 Furbach, Florian I-588

#### **G**

Ganty, Pierre I-290 Godbole, Adwait A. I-588 Goorden, M. A. II-44 Gordillo, Pablo I-448 Griggio, Alberto II-3 Guo, Xingwu I-208 Gupta, Ashutosh I-105 Gutierrez, Julian I-666

#### **H**

Hadži-Ðoki´c, Luka I-290 Hahn, Ernst Moritz I-527 Hamza, Ameer II-270 Harel, David I-607 Hartmanns, Arnd I-469 Havlena, Vojtˇech I-249 Heim, Philippe II-251 Heisinger, Maximilian I-426 Heizmann, Matthias II-577, II-582 Hendi, Yacoub G. I-588 Hendriks, D. II-44 Henzinger, Thomas A. I-3, II-535 Herasimau, Andrei II-473 Heule, Marijn J. H. I-329, I-348, I-389 Hoenicke, Jochen II-577 Hofkamp, A. T. II-44 Hsu, Tzu-Han I-29, I-66 Huang, Xuanxiang I-167 Hussein, Soha II-553

#### **I**

Iser, Markus I-407

#### **J**

Jaber, Nouraldin II-289 Jacobs, Swen II-289 Jakobsen, Anna Blume II-353 Jansen, Nils I-508 Jongmans, Sung-Shik II-19

Jourdan, Jacques-Henri II-93 Junges, Sebastian I-469, I-508, II-410

#### **K**

Kaminski, Benjamin Lucien II-410 Karmarkar, Hrishikesh II-594 Katoen, Joost-Pieter II-391, II-410 Katz, Guy I-187, I-208, I-607 Kiesl-Reiter, Benjamin I-329, I-348 Klumpp, Dominik II-577, II-582 Kobayashi, Naoki I-227 Kokologiannakis, Michalis I-85 Konnov, Igor I-126 Korovin, Konstantin I-647 Kovács, Laura I-647 Krishna, S. I-105 Krishna, Shankara N.  I-271 , II-192 Perez, Mateo I-527 Pietsch, Manuel II-547 Planes, Jordi I-167 Podelski, Andreas II-577 , II-582 Pu, Geguang II-36 Purser, David I-47

#### **Q**

Quatmann, Tim I-469

#### **R**

Raskin, Jean-François II-309 Raszyk, Martin II-473 Reeves, Joseph E.  I-348, II-553 Wies, Thomas I-628 Wijs, Anton I-684

Winkler, Tobias II-391 Wojtczak, Dominik I-527 Wolff, Sebastian I-628 Wu, Minchao I-227

#### **X**

Xiao, Shengping II-36 Xing, Hengrui II-571

#### **Y**

Yan, Qiuchen II-553 Yang, Jiyu II-571 Yang, Luke I-666 Yang, Zuchao II-571 Yeduru, Prasanth II-594 Yerushalmi, Raz I-607 Yuan, Simon II-473

#### **Z**

Zhang, Chengyu II-36 Zhang, Hongce II-11 Zhang, Min I-208 Zhang, Minjian I-308 Zhang, Yueling I-208 Zhou, Ziwei I-208 Zhu, He II-229 Žikeli´c, Ðor de I-3


**5.5 GP IIb/IIIa inhibitors**

The platelet glycoprotein (GP) IIb/IIIa complex receptor antagonists block activity at the fibrinogen binding site on platelet (Colwell & Nesto, 2003). These agents are useful in type 2 diabetes patients with acute coronary syndrome and in those undergoing percutaneous coronary interventions (Colwell & Nesto, 2003). These agents are administered intravenously with a rapid onset of action and short half-life (Natarajan et al., 2008). Numerous studies have been performed comparing various GP IIb/IIIa inhibitors. Currently, three different GP IIb/IIIa inhibitors (abciximab, eptifibatide, and tirofiban) are approved for clinical use. This group of drugs was mainly study for secondary prevention of CVD in diabetes patients. Evidence from three trials revealed that among 1,262 diabetes patients, use of these agents was associated with reduction in mortality from 4.5% to 2.5% (p=0.031) (Bhatt et al., 2000). In another meta-analysis of six large trials, with 6,458 patients with diabetes and acute coronary syndromes, GP IIb/IIIa inhibitor therapy was associated with a significant mortality reduction at 30 days, from 6.2% to 4.6% CI(0.59-0.92, p=0.007) (Roffi et al., 2001). Nonetheless, the role of GP IIb/IIIa inhibitors in primary prevention of CVD in type 2 diabetes mellitus has not been justified; therefore it is not recommended for this purpose.


*3.3.3. Erythropoietin*

(DME) [5]. Several studies have shown marked increases of VEGF in vitreous and vitreous compared to plasma concentration in DME and PDR patients [19, 36–46]. Treatments that target VEGF have been proven highly effective in treating DR. VEGF antibodies, which were originally used for cancer treatments, such as bevacizumab and its correlate ranibizumab have been used effectively. These have also been tested in several small trials which showed improved vision in DR patients, demonstrating the involvement of VEGF in the

Brzović-Šarić also demonstrated a significant difference between vitreous VEGF values in nondiabetic patients with eye disorders and PDR patients [25]. Loukovaara et al. state that VEGF is a major factor in PDR development and found significant increases of VEGF levels in the vitreous of DR patients (465.1 ± 1470.2 pg/mL) compared to control patients (40.3 ± 165.8 pg/mL) [37]. Our study found a mean level of VEGF in vitreous of patients with PDR of 0.356 + 0.60 pg/mL [26]. Yoshimura et al. found that there was significantly elevated VEGF in PDR patients, but not in DME patients [47]. The increased levels of VEGF expression in patients with diabetic retinopathy was mainly produced by Muller glial cells. Experiments in diabetic mice, demonstrated that conditional knockout of VEGF in Muller cells effectively blocked the increase in retinal VEGF expression [48]. Lange and co-workers suggest that oxygen tension levels were positively correlated with vitreous VEGF levels, and oxygen tension levels at the posterior pole were increased in PDR patients [49]. The vitreous levels of VEGF will decrease in the most

severe stage of PDR, when there is a transition from angiogenesis to fibrosis [50].

Angiopoietins are a group of proteins with the role of regulating vascular development and angiogenesis. Two types of angiopoietins, angiopoietin-1 and angiopoietin-2, contribute to the maintenance of retinal vasculature. The former exerts a stabilizing effect on vessels, organizing and limiting the angiogenesis response, while the latter exhibits angiogenic activity if VEGF is present, but promotes endothelial cell death and vascular regression in the absence of VEGF. The ratio between these two angiopoietins represents the inflammatory process in the cell. Fiedler et al. state that hypoxia/ischemia activates endothelial cells upregulating angiopoientin-2 thus lowering the angiopoientin-1/angiopoientin-2 ratio [37, 51]. A recent publication by Loukovaara et al. demonstrates significant correlation between intravitreal concentrations of Ang-2 with MMP-9, VEGF, EPO and TGFb1 levels in diabetic eyes undergoing vitrectomy, indicating its role in retinal tissue neovascularization in PDR patients. The study shows a slight increase in angiopoietin-1 from the control group (19.1 ± 25.4 pg/mL) to the study group (25.6 ± 27.1 pg/mL), and a great increase in angiopoietin-2 from the control group (43.0 ± 60.9 pg/mL) to the study group (317.1 ± 419.1 pg/mL), thus lowering the angiopoietin-1/angiopoietin-2 ratio in study group. The plasma value of angiopoietin-1 is similar in both groups, but the plasma value of angiopoietin-2 is increased from the control group (2623.4 ± 2142.0 pg/mL) compared to the study group (5690.4 ± 8064.7 pg/mL) [36, 37, 52]. Several studies state that angiopoietin-1 can be used for the prevention and treatment of diabetic retinopathy by its ability to suppress VEGF

pathophysiology of PDR [5, 36].

76 Early Events in Diabetic Retinopathy and Intervention Strategies

*3.3.2. Angiopoietin*

expression in diabetic retina [53].

Erythropoietin (EPO) is a glycoprotein cytokine that acts as a major regulator of erythropoiesis. Besides erythropoiesis, several studies state that erythropoietin has a neuroprotective and angiogenic effect in brain and retina. Production of EPO in serum and vitreous is mainly caused by hypoxia [54–57]. EPO is found in many organs, including kidney, liver, brain, and retina [55]. The angiogenic effect of EPO is a potential equivalent to VEGF, and has been suspected as an important factor in the angiogenesis of PDR [56]. Watanabe et al. showed that vitreous EPO levels of PDR patients are significantly higher (464.0 mlU/mL) compared to non-diabetic patients (36.5 mlU/mL). They also found that EPO levels are higher with active as compared to quiescent PDR [54]. These are consistent with Katsura et al., who also reported increases of vitreous EPO levels in PDR patients compared to controls [55]. Cristina et al. found that EPO levels in vitreous fluid are significantly higher (326 mU/mL) compared to serum EPO (11.2 mU/mL) in PDR patients [56]. This shows that intraocular production is responsible for the high concentration of erythropoietin found in the vitreous fluid of retinal degeneration patients [54, 56, 57]. Garci et al. found increased vitreous EPO concentrations in DME patients (430 mU/mL) compared to control patients (25 mU/mL) [57]. Treatment involving the erythropoietin blockade is likely to be beneficial, but may worsen the disease due to the decrease of its neuroprotective function [54].


**7. Conclusion**

**Figure 4.** An active lifestyle enhances physical activity and decreases sedentary behaviors (Cardozo et al., unpublished

Valkeinen et al. (2006) examined the EMG activity after a 21 week strength training period in elderly woman with fibromyalgia. The EMG activity of the right vastus lateralis and vastus medialis muscles was recorded during maximal isometric leg extensions, and the results were expressed as the mean integrated EMG activity. There was a large increase in the maximal force and EMG activity of the muscles, indicating that strength training for elderly people can increase neuromuscular functional performance. Hakkinen et al. (2001) examined neuromus‐ cular adaptations in middle-aged and older men and women during a resistance training period of 6 months. The EMG activity during the unilateral extension actions of the knee muscles was recorded from the agonist muscles vastus lateralis and vastus medialis and from the biceps femoris. The EMG signal was collected at 1000Hz, full wave rectified and integrated. The results show that there were increases in the EMG integrated magnitude of the agonist muscle during isometric and concentric leg extensions at maximal voluntary contraction in older women after training. This finding may be related to changes in the muscle activation

data).

122 Electrodiagnosis in New Frontiers of Clinical Research

This chapter presents a global understanding of age-related neuromuscular alterations, such as weakness and fatigue, and the use of EMG parameters in their identification. Neuromus‐ cular adaptations due to aging influence the ability of the elderly to maintain the capacity to perform daily activities and to modulate their postural control. Additionally, physical activity can improve neuromuscular functional ability in older people.


**d.** Particle Characteristics

Particles can be characterized by their composition and crystallographic phase, as well as by their size, density, and shape. The particle composition can have a dramatic impact on the amount of incorporation obtained for a particular bath composition. For instance three times more TiO2 than A12O3 has reportedly been incorporated into a Ni matrix, under the same deposition conditions. The particle size also effects on the amount of co-deposited particles in the composite coatings. For example when the particle size in the electrolyte increases then amount of adsorbed ions on the surface increases, which leads to the increase in the migration velocity of the particles and also results in a higher columbic force of attraction, leads to increase in the amount of the particles. But the density of particles in the coating decreases as the particle size in the electrolyte increases [25]*.*

The electrode/particle interaction will be affected by the particle properties, such as material type, shape, size, surface charge, concentration, and dispersion in the bath. The co-deposition of nano-sized particles produces a composite coating with a much higher hardness than that achieved with micron-sized particles. The smaller the particle, the more difficult the codeposition into the metal matrix due to the high tendency of agglomeration. In addition, the smaller the particle size, the greater the effect of colloidal properties (van der Waals, electro‐ static, and solvent interaction forces) [24].


**3. ROS production in seeds**

In plants, transport chain of electrons toward oxygen can potentially generate ROS. Seeds represent a particular case in this regard. During germination, the seed metabolic activity vary dramatically, meanwhile the sources of ROS in seeds also vary considerably [13, 39–45]. The mitochondrial respiratory chain is one of the major sources of ROS; electron leakage from the transport chain generates superoxide, and subsequently H2 O2 , by dismutation of the former. During germination, respiratory activity increased and production of ROS enhanced [6, 14, 46, 47]. Another source of ROS is peroxisomes. Peroxisomes divided into: glyoxysomes (oily seeds), peroxisomes of photosynthetic tissues, nodule peroxisomes (*Fabaceae* nodules) and gerontosomes (senescing tissues) [14, 27, 46–50]. In glyoxysomes, lipid reserves of oily seeds are converted into sugars during the first stages of seedling development [49–51]. During this lipid oxidation process H2 O2 is produced. In peroxisomal matrix, xanthine is also oxidized into uric acid by xanthine oxidase resulting with the production of superoxide [49–51]. Catalase (H2 O2 eliminating enzyme) is localized in peroxisomes [49–52]. Production of nitric oxide (NO), (a free radical and also an important cellular signaling compound in plants) also takes place in peroxisomes [48, 51–54]. NADPH oxidases of the cell membrane are another sources of ROS in plants, these enzymes transfer electrons from cytoplasmic NADPH to oxygen, producing superoxide radical and its dismutating product H2 O2 . NADPH oxidases are increased during plant infections [28, 29], in plant growth processes [55], and under severe abiotic stress conditions [56]. Enhanced activity of NADPH oxidase is reported in ABA induced generation of ROS under water stress [57, 58]. During biotic stress cell wall peroxidases and amine oxidases are induced leading to the formation of H2 O2 in the apoplast [59]. As a result, mitochondria and peroxisomes are the major sources of ROS in nonquiescent seeds, during seed development and germination. Aquaporins and peroxiporins (transmembrane proteins) are shown to play roles in the transport of H2 O2 in vegetative tissues [56, 60], but the mobility of ROS in seeds has not yet been documented. Finally, lipid oxidation can generate ROS that could be trapped in seed tissues [16, 61].


*2.2. Enzymatic and Mechanical Treatments*

The softwood pulp was beaten in a PFI mill at 4000 revolutions under a refining intensity of 3.33 N/mm (ISO 5264-2) followed by an enzymatic treatment. The enzymatic treatment was performed according to the method described by Morais et al. [12]. The treatment was carried out at a consistency of 4% at pH 7 at 40 ◦C with continuous mechanical agitation to ensure an efficient mass transfer for 60 min and 30 mg of enzyme/g of pulp.


*Edited by Georgios Tsoulfas*

Liver cirrhosis and its complications affect millions of patients of all ages around the globe and present treating physicians with perplexing problems, given the variety of etiologies and the critical nature of hepatic physiology. This book is a collection of chapters offering the distilled knowledge of various worldwide experts in hepatic surgery and hepatic physiology. The various debates that are presented regarding the diagnosis and treatment of liver cirrhosis and its significant complications, in addition to the most up-to-date information regarding molecular aspects, provide the reader with the full spectrum of knowledge in this challenging and continuously evolving field.

ISBN 978-1-78923-885-3

Liver Cirrhosis - Debates and Current Challenges

Published in London, UK © 2019 IntechOpen © Johanna Poetsch / iStock


**Structured Approaches to General Inverse Eigenvalue Problems**

Patrick Dumond and Natalie Baddour

Additional information is available at the end of the chapter

http://dx.doi.org/10.5772/62284

## **Abstract**

[24] Rainwater, G., Tokman, M.: A new class of split exponential propagation iterative methods of Runge-Kutta type (sEPIRK) for semilinear systems of ODEs. *J. Comp.*

[25] Tokman, M.: A new class of exponential propagation iterative methods of Runge-Kutta

[26] Richardson, M., Lambers, J. V.: Krylov subspace spectral methods for polar and

*Phys.* 269 (2014) 40–60.

26 Applied Linear Algebra in Action

type (EPIRK). *J. Comp. Phys.* 230 (2011) 8762–8778.

cylindrical geometries. In preparation.

An inverse eigenvalue problem is one where a set or subset of (generalized) eigenval‐ ues is specified and the matrices that generate it are sought. Many methods for solving inverse eigenvalue problems are only applicable to matrices of a specific type. In this chapter, two recently proposed methods for structured (direct) solutions of inverse eigenvalue problems are presented. The presented methods are not restricted to matrices of a specific type and are thus applicable to matrices of all types. For the first method, the Cayley–Hamilton theorem is developed for the generalized eigenvalue vibration problem. For a given (desired) frequency spectrum, many solutions are possible. Hence, a discussion of the required information and suggestions for including structural constraints are given. An algorithm for solving the inverse eigenvalue problem using the generalized Cayley– Hamilton theorem is then demonstrated. An algorithm for solving partially described systems is also specified. The Cayley–Hamilton theorem algorithm is shown to be a good tool for solving inverse generalized eigenvalue problems. Examples of application of the method are given. A second method, referred to as the inverse eigenvalue determinant method, is also introduced. This method provides another direct approach to the reconstruction of the matrices of the generalized eigenvalue problem, given knowledge of its eigenvalues and various physical parameters. As for the first method, there are no restrictions on the type of matrices allowed for the inverse problem. Examples of application of the method are also given, including application-oriented examples.

**Keywords:** Inverse problems, Eigenvalue problems, Inverse eigenvalue problems, In‐ verse spectrum, Inverse vibrations problems

© 2016 The Author(s). Licensee InTech. This chapter is distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


**5. Conclusions**

In the present article, the vibration characteristics of a radial turbine bladed disc of a marine engine turbocharger were investigated. Starting with the analysis of structural dynamic properties of cyclic symmetry components, basic procedures were transferred to special problems of bladed discs of marine turbocharger radial turbines and expanded. In particular, the assignment of individual peaks in the measured transmission functions to the corresponding mode shapes was performed using a carefully designed FE model, without the need to apply an expensive scanning vibrometer. In addition, the distribution of the strain energy between the disc and the blade calculated by the FE model is a next parameter that allows the systematic assessment each of the large number of modal shapes present in this complicated structure. The mode shapes with predominant strain energy in the blade are thus referred to as blade-dominated. Depending on the criterion of distribution of the strain energy among the blades and the disc, some modes can be called mixed. The transfer functions shown above also record these mixed modes such as matching peaks, but their e ffect on blade stress is not significant. Disc dominant modes do not occur in the examined frequency range of the analysed marine engine turbocharger radial turbine. The reason for this is the massive disc and the rigid connection of the blades to them.

Based on the results of the measurements described above, it was possible to create a 3D mistuned FE model of the turbine bladed disc. Creation of this model is based on individual adaptation of the modulus of elasticity to individual blades using optimization algorithms. The vibration behaviour of the real bladed discs can be achieved with su fficient accuracy by such 3D models, unlike methods that are based on the use of substructures and do not describe the frequency splitting due to mistuning with the necessary accuracy. Since the description of the optimization algorithm and the creation of the 3D model of the mistuned turbine wheel would go far beyond the possible size of this article, this topic will be the subject of a separate publication.

With regard to industrial application, it should be noted that an improvement in manufacturing accuracy is only conditionally recommended, since increasing the manufacturing accuracy of the blades would entail unacceptable financial costs. Rather, it is important to determine the inclination of individual vibration modes in order to tend large increases in stress. It should be noted that large stress increases are always accompanied by strongly localised modes. However, strongly localised mode shapes can only occur if the tuned bladed disc system has a su fficient number of node diameter vibrations in a relative frequency proximity. These cases can be identified already in the early stages of development if a suitable FE blade disc model is used. Together with the described e ffective mistuning identification method of integrated bladed discs, the development of new marine engine turbochargers can be significantly accelerated. Another added value of the method is the possibility of its relatively easy automation, both in terms of measurement and its subsequent processing and evaluation. The turbocharger manufacturer can thus obtain complete statistical information on the parameters of the blade discs in relation to the mistuning caused by various influences in the production process.

**Author Contributions:** Conceptualization, V.P.; methodology, V.P. and P.K.; software, P.K. and O.F.; validation, P.K. and A.L.; writing—review and editing, V.P. and P.K. All authors have read and agreed to the published version of the manuscript.

**Funding:** The authors gratefully acknowledge funding from the Specific research on BUT FSI-S-20-6267.

**Acknowledgments:** The authors thank the Brno University of Technology for support. **Conflicts of Interest:** The authors declare no conflict of interest.


**Acknowledgements**

The author would like to thank Professor Dr. Dobrila Stanković Djordjević, Dean of the Faculty of the Medicine and Professor Dr. Nebojsa Djordjević, Chairman of Department of Surgery, Faculty of the Medicine, University of Nis, Nis, Serbia for constructive support; his teacher of surgery Professor Dr. Miroslav Jeremic for helping generously.