*3.2. Gallium Oxide Thin-Film Growth*

Bulk devices and subsequent epitaxy of *β*-Ga2O3 layers could be provided by bulk growth, while high-quality epitaxial growth technologies are still required in order to study and fabricate more complex devices. Halide vapor phase epitaxy (HVPE), metal-organic vapor phase epitaxy (MOVPE), pulsed laser deposition (PLD), atomic layer deposition (ALD), molecular beam epitaxy (MBE), mist-chemical vapor deposition (CVD), and metalorganic chemical vapor deposition (MOCVD) are all involved in thin-film growth of Ga2O3.

Vapor phase epitaxy is a commercially promising technique for mass production of *β*-Ga2O3. Based on VPE, the halide vapor phase epitaxy (HVPE) method enables a growth rate as high as 250 µm/h [55] and the wafer size from 2 to 6 inches [56], it is thus a suitable technique for thick films with high purity for high voltage vertical switching devices. Furthermore, with the presence of chlorine catalyst in the growth chamber, this technique exhibits the growth of metastable phases of Ga2O3, such as α and *ε* [57]. The HVPE method suffers from a high level of roughness on the surface even at a relatively low growth rate [56,58]; an electrical mechanical [59] or a chemical mechanical [60] polishing can be employed to remove further deep surface pits formed during the growth. Leach et al. [61] reported a vast difference in surface morphology and XRD full-width half-maximum (FWMH), between sufficiently and insufficiently CMP polished (discriminated by the polishing times of the various polishing steps) *β*-Ga2O3 wafers grown by HVPE. Despite the poor morphology, the FWHM of the films grown on on-axis substrate were as narrow as 28 arcsec. Moreover, Murakami et al. [62] revealed that effective donor concentration without intentional doping could reach as low as 1013 cm−3 .

Metal-organic vapor phase epitaxy (MOVPE)can provide a highly scalable growth as its deposition areas are large. Triethylgallium (TEGa), trimethylgallium (TMGa), and O2are

most commonly the precursors for gallium and oxygen, respectively. The homoepitaxial growth of *β*-Ga2O3 by MOVPE can be strongly affected by substrate orientation. The growth rate is approximately 1.6–2.0 nm/min on the (100) plane, 0.65–1 µm/h on the (010) plane, and 1.6–4.3 nm/min on the (00-1) plane with miscut angles [63]. Recently, the growth rate can be elevated to 3.6 nm/min on the (100) plane [64] by tuning the growth pressure. A high-quality homoepitaxial growth on *β*-Ga2O3 the (100) with an FWMH of 43 arcsec has been reported by Gogova et al. [65]. The study of residual donor source is still in progress [66] while an electron concentration of 8 × 1019 cm−3 by Si-doping was realized by Baldini et al. [67], which is the highest doping level by this technique so far.

Pulsed laser deposition (PLD) has often been used for doped layers of Ga2O3 as it can transport materials from the target to the substrate stoichiometrically, thus the thickness of layers can be incisively controlled. It also has a relatively low operating temperature compared to other techniques. However, the quality of the materials deposited and the deposition rate are relatively low compared with other CVD and MBE methods. The roughness measured on the surface of Ga2O3 films had a root mean square between 1 and 7 nm [68–70].

A growth rate of 10.8 nm/min could be reached without oxygen, while it decreased to 6.5 nm/min by increasing oxygen pressure to 50 mbar [71]. Indeed, oxygen partial pressure and temperature are considered as the dominant parameters for properties of materials grown by the PLD [72]. The crystallinity was enhanced by increasing oxygen pressure at either low deposition temperature (250 ◦C [71]) or high deposition temperature (780 ◦C [68]). A higher oxygen partial pressure also leads to self-trapped holes at O1*s* and between two O2*s* sites [68], which could further act on the transport properties. Unlike the influence of oxygen pressure, a higher temperature does not always lead to a better film quality [73,74]. While, as expected, a higher annealing temperature could improve the crystallinity, as it helps the re-arrangement of Ga and O atoms to their optimal sites [75,76]. The highest *n*-type doping level achieved by the PLD is 1.7 × 1020 cm−3 by Si doping [69].

Atomic layer deposition (ALD), initially called atomic layer epitaxy (ALE), is a sub-set of the chemical vapor deposition (CVD) technique based on self-saturation, sequential surface reactions. ALD is a more general deposition containing ALE and molecular layering (ML) techniques [77]. The highly controlled thickness of films and conformal coverage are the main advantages of ALD over other techniques, it also allows a relatively lower deposition temperature compared to MBE and CVD techniques and a lower growth rate (generally less than 0.1 nm/cycle). Sn-doped Ga2O3 grown by ALD was investigated by Siah et al. [78], however the concentration of Sn was estimated as 2 × 1020 cm−3 , with the free electrons determined to be 4 × 1018 cm−3 . This was due to the low growth temperature.

Thus, post-annealing is generally also required to improve the crystalline quality. Additionally, the temperature during growth depends mainly on the gallium precursor chosen [79,80]. Besides the conventional ALD, the plasma-enhanced atomic layer deposition (PEALD) further permits a lower deposition temperature and better Ga2O3film properties with very smooth surface roughness (<1 nm) [81–83].

Molecular beam epitaxy (MBE)suits research purposes better than commercial use, as it enables the growth of high structural quality *β*-Ga2O3 with a relatively low growth rate (<1 µm/h) and high production cost, while high voltage vertical devices often require thick drift regions (dozens of microns). The orientation of growth has been found to be one factor that influences the growth rate [84]. Mazzolini et al. [85] further demonstrated the growth rate of different orientations Γ(010) (2.3 nm/min) > Γ(001) > Γ(−201) > Γ(100) of Incatalyzed *β*-Ga2O3layers;this phenomenon was believed to be associated with the surface free energy related to the binding energy of the In ad-atom. Nepal et al. [86] reported a heteroepitaxial growth on SiC with (−402) having a relatively high FWMH (694 arcsec), which can be reduced to 30–60 arcsec by homoepitaxial growth [87]. The thin films grown by MBE also benefit a smooth surface with a roughness of less than 1 nm [88,89]. The densities of the threading dislocation etch pits was determined to be ~105 cm−2 for the film grown at 850 ◦C [89]. An electron concentration of 1020 cm−3 has been achieved by Sn doping [90].

Techniques based on chemical vapor deposition (CVD) have also been employed for the growth of Ga2O3. Scalability and mass production are the most advantageous characteristics of the mist-CVD technique, as it is a vacuum free, low-cost, and solutionprocessed approach. This technique is also often used for epitaxial growth of α-Ga2O3 on sapphire [91–94]. Morimoto et al. [94] also pointed out the facilities of mist-CVD for Ga2O3by F doping. Both homoepitaxial [95,96] and heteroepitaxial [97] growth of *β*-Ga2O3have been successfully performed. It is also worth noting that the FWMH of rocking curves was 39–91 arcsec for homoepitaxial growth with growth rate of 0.5–3.2 µm/h [96,98]. An electron concentration was measured as 5 × 1020 cm−3 by Sn doping [98].

The metal-organic chemical vapor deposition (MOCVD) technique uses Ga-based organic material as metal precursors, such as trimethylgallium (TMGa) and triethylgallium (TEGa), which usually leads to C-contamination of the as-grown film (relatively less carbon by using TEGa than TMGa). It is well-known that such contamination can be efficiently reduced by high growth temperature, and eliminated by post-annealing. Li et al. [99] reported a high-quality homoepitaxially grown film with FWMH and surface roughness of 21.6 arcsec and 0.68 nm, respectively. The growth rate is generally from several hundred nm/h [100,101] to10 µm/h [102–104]. This technique is also available for both *n*- and *p*-type dupability [24,105] (Figure 4).

**Figure 4.** Ga2O3 and related oxides have been demonstrated to exhibit some remarkable features, such as (**a**) ultra-high critical electric field, (**b**) potential bipolar operation due to its demonstrated *n*-type and *p*-type conductivity, (**c**) ultra-stable interfaces that may host a 2D electron gas, (**d**) extended transparency into the UV-A region for transparent conducting oxide (TCO) applications (tail state density is located deeper in the ultraviolet than conventional TCOs). Panel (**a**) adapted with permission from Chikoidze et al. [24] © 2022 Elsevier Ltd. All rights reserved. Panel (**b**) adapted with permission from Chikoidze et al. [106] Copyright © 2022, American Chemical Society. Panel (**c**) adapted with permission from Chikoidze et al. [107]. © 2022 Elsevier Ltd. All rights reserved. Panel (**d**) adapted with permission from Perez-Tomas et al. [108,109] © 2022 WILEY-VCH Verlag GmbH & Co. KGaA. Adapted with permission from [12] © 2021 COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE).


**4. Case Study**

In September 2006 the Government of Aragón and the Zaragoza City Council advanced the 'Zaragoza Plan for Sustainable Mobility', which led to the construction of the city's Tram Line 1 that was completed in 2013. The construction was controversial and in the following municipal elections, the political parties presented their proposals for improving transport in the city. Representatives of the main political parties (PSOE, PP and CHA) attended the university to explain their preferred alternative. The case study concerns a citizen participation project in a local community which contemplated alternatives put forward by the political parties during the municipal elections for the extension of the city tram network.

Eleven students (K = 11) from the 'Electronic-Government and Public Decisions' course of the Faculty of Economics and Business at the University of Zaragoza (Spain) were involved in its implementation.

There were 4 alternatives:

As the construction of Line 1 had a high economic cost, and the selection of any of first three alternatives assumes a significant investment, a fourth alternative (no cost) was included. The selection problem was solved using the Analytic Hierarchy Process [2]. The hierarchical model comprised four levels (the goal, 3 criteria, 9 attributes and 4 alternatives).

The results of the Investment Cost attribute have been used to illustrate the proposed methodology. The prior distribution parameters were c0 = 0.1, n0 = 1 and s20 = 0.0014 (corresponding to take σ2max = 0.35 and α = 0.05) and β = 0.05. The number of partitions was equal to the 678,570 that were processed in 98.84 s of CPU by a Toshiba Ultrabook KIRA with Intel (R) Core™ i7-4510U CPU @ 2.00GHz 2.60 GHz (64 bits) and 8 Gb of RAM.

The resulting number of groups was equal to five and the most probable composition was: **G**1 = {D1, D2, D3, D7}, **G**2 = {D4, D10}, **G**3 = {D5, D6}, **G**4 = {D9}, **G**5 = {D11}. The results obtained are shown in Tables 1–3. More specifically, Table 1 contains the posterior medians of the priorities of each alternative for each decision maker and each group. Table 2 shows the posterior probabilities that each alternative would be the most preferred, corresponding to the Pα distributions. Table 3 gives the probabilities for each ranking corresponding to the Pγ distributions. The values were calculated from (7)–(8) and (11)–(12), as described in Section 2.2, using S = 10,000 simulations.

So, for example, group G1 made up of decision makers D1, D2, D3 and D7, gives the highest priority (0.4502) to alternative A4, followed by the alternatives A2 (priority 0.3076), A3 (0.1518) and A1 (0.0879) (see Table 1). This ranking is also reflected by its Pα and Pγ distributions, which give the maximum posterior probabilities to the A4 alternative (97.31%, see Table 2) and the ranking 4231 (96.94%, see Table 3). Even though the individual opinion of D3 is different to the rest of the members of the group (their preferred alternative is A2 and the ranking is 2431), the consistency of the group G1 (0.2790) is good, being lower than the maximum level of inconsistency 0.35. This is due to the high priority of D3 for alternative A4 (0.2705) and the similarity of their priorities to alternatives A1 and A3 which means that G1 can be considered as a homogeneous group.

From the tables, it can be observed that the compositions of the groups are very much determined by their similarity to the most preferred alternative. The decision makers from groups **G**1 and **G**3 mostly prefer the alternative A4, those from group **G**2 prefer alternative A1, those from **G**3 prefer alternative A3 and those from **G**4 prefer alternative A2 (see Tables 1 and 2). However, groups **G**1 and **G**3 differ in the rankings (see Table 3). The decision makers from the group **G**1 tend to prefer the 4231 ranking, while those from the group **G**3 prefer 4123. Nevertheless, preferences within each group are not completely homogeneous; in group **G**1, decision-maker D3 shows a greater preference for alternative A2. This

opinion is shared with decision maker D11 of group **G**4, although it assigns a priority 0.2705 to alternative A4 that justifies its inclusion in group **G**1. Something similar happens in group **G**3, in which decision maker D5 shows a greater preference for alternative A1, although it assigns a non-negligible priority (0.3613) to alternative A4 and to the ranking 4123, hence its inclusion in group **G**3.

The consistency levels of the actors and most of the groups are acceptable (<0.35). The only exception is G3 whose consistency is estimated as 0.4071, but with a 95% credibility interval [0.20, 1.43] that does not reject the consistency hypothesis σ2(G3) ≤ 0.35.

The ambiguities of the opinions are revealed if we analyse the partitions selected by Occam's window with the smaller number of groups, included in Table 4 and Figure 2. Figure 2 incorporates, in each node, the groups of decision makers that are classified together in all the selected partitions and includes a link between two nodes if their components are classified together in some of the partitions. Most of the decision makers are linked because of their preferences for alternatives A2 and A4, the latter being the alternative which most decision makers support. Only D4, D9 and D10 are isolated because of their preferences for alternatives A1 (D4 and D10) and A3 (D9).

**Table 1.** Priorities and consistency for each decision maker and each group.

in**bold** the highest priority.

**Table 2.** Alpha distributions for each decision maker and each group.

in **bold** the probabilities higher than 20%.

**Table 3.** Gamma distributions for each decision maker (Di) and each group (Gj) (probabilities higher than 20% are in bold).

There are 4 homogeneous groups: {D1, D2, D7} that prefer alternative A4 and the ranking 4231; {D5, D6} position alternatives A2 and A3 in the last places and they show a non-negligible preference for A4; {D4, D10} prefer alternative A1 and put A3 in last place; decision maker {D9} prefers A3. Decision makers D3, D8, D11 are in more intermediate and ambiguous positions. In the case of D3, this is due to the greater preference for A2 (shared with D11) and the non-negligible preference for A4 (which places them close to the group {D1, D2, D7}). In the case of D8, the intermediate position is due to their preferences for A4 and A2, in that order, which places them close to the group {D1, D2, D7}, as well as to the rejection of A3, which places them close to the group {D5, D6}.

In order to achieve as broad an agreement as possible, alternative A4 could be suggested, given that a majority of decision makers (in groups G1 and G3) showed a preference for it. The negotiation should be aimed at convincing decision makers D4, D9, D10 and D11.

With regards to the practical implications of the Bayesian procedure proposed in this work, it is worth mentioning that, as in AHP, these applications are numerous, especially in matters of strategic planning where the number of actors is not usually very high.

**Table 4.** Partitions selected by the Occam window.

† The ratio calculates the quotient of the posterior probability for the most probable model and that for the model corresponding to each partition.

**Figure 2.** Relations of opinions existing in D.


*<IP_ADDRESS>. Temperature ramp tests*

**Figure 9** shows the thermograms obtained in the DMA for the PP matrix and its biocomposites. In these graphs the values of the storage modulus (E'), loss modulus (E"), and tan delta are shown. Neat PP tan delta plot shows two relaxations located near 6°C (β relaxation or Tg) and 60°C (α relaxation) [35]. It is also observed that the values of E´ are temperature dependent. At 25°C the value of E´ is 2708 MPa, while at 75°C, this value is 1199 MPa, which represents a decrease of 55%.

In the tan delta plot of the biocomposite PP-Bag (**Figure 10**), a Tg of 5.3°C is observed, while the α relaxation increased 17.5°C compared to the neat PP. Also, E'values at 25°C is 2454 MPa,

**Figure 8.** Strain sweep test curves for neat PP at 0, 30, and 60°C.

**Figure 9.** Dynamic mechanical analysis (DMA) curves of neat PP.

**Figure 10.** Dynamic mechanical analysis (DMA) curves of PP-Bag biocomposite.

while at 75°C, this value is 1169 MPa. E'values' decrease in this temperature range was 52%. This result shows that the addition of bagasse fiber improves the stability of the storage module of the PP matrix with the temperature. The increase in the value of α relaxation and the stability of E´ with the temperature was also observed in biocomposites PP-Bag + NaOH and PP-Bag + NaOH+Silanes (**Figures 11** and **12**).

**Figure 13** shows the summary of the temperature sweep tests for biocomposites. The tan delta graphics show that there are no significant changes in the Tg of the biocomposites compared to the PP matrix. The values of Tg range between 3.7°C and 6.5°C. Also, these graphs show a reinforcing effect in the PP-bag biocomposite. Tan delta values varied 19.8% compared to the PP matrix. In the case of biocomposite PP-Bag + NaOH, this variation was 32.64% while in the

**Figure 12.** Dynamic mechanical analysis (DMA) curves of PP-Bag + NaOH+Silane biocomposite.

**Figure 11.** Dynamic mechanical analysis (DMA) curves of PP-Bag + NaOH biocomposite.

Biocomposites from Colombian Sugarcane Bagasse with Polypropylene: Mechanical, Thermal…

http://dx.doi.org/10.5772/intechopen.80753

143

biocomposite PP-Bag + NaOH+ Silane was 32.95%.

Biocomposites from Colombian Sugarcane Bagasse with Polypropylene: Mechanical, Thermal… http://dx.doi.org/10.5772/intechopen.80753 143

**Figure 11.** Dynamic mechanical analysis (DMA) curves of PP-Bag + NaOH biocomposite.

**Figure 9.** Dynamic mechanical analysis (DMA) curves of neat PP.

142 Characterizations of Some Composite Materials

**Figure 10.** Dynamic mechanical analysis (DMA) curves of PP-Bag biocomposite.

PP-Bag + NaOH+Silanes (**Figures 11** and **12**).

while at 75°C, this value is 1169 MPa. E'values' decrease in this temperature range was 52%. This result shows that the addition of bagasse fiber improves the stability of the storage module of the PP matrix with the temperature. The increase in the value of α relaxation and the stability of E´ with the temperature was also observed in biocomposites PP-Bag + NaOH and

**Figure 12.** Dynamic mechanical analysis (DMA) curves of PP-Bag + NaOH+Silane biocomposite.

**Figure 13** shows the summary of the temperature sweep tests for biocomposites. The tan delta graphics show that there are no significant changes in the Tg of the biocomposites compared to the PP matrix. The values of Tg range between 3.7°C and 6.5°C. Also, these graphs show a reinforcing effect in the PP-bag biocomposite. Tan delta values varied 19.8% compared to the PP matrix. In the case of biocomposite PP-Bag + NaOH, this variation was 32.64% while in the biocomposite PP-Bag + NaOH+ Silane was 32.95%.

**Figure 13.** Dynamic mechanical analysis (DMA) curves of neat PP and its composites.

With temperature increase, a second peak is observed around 60°C for neat PP. This peak can be related to an alpha transition. In the case of biocomposites, this alpha transition can be spotted at higher temperatures. This suggests that the service temperature of the biocomposites with alkaline and silanized treatments would allow a better performance of the material. In this experiment observed that the addition of silane to bagasse does not generate an improvement in the viscoelastic properties compared to the alkalinization treatment. It is emphasized that the alkalization treatment generates an improvement against the damping. This improvement can be positive for biocomposite applications that require an enhanced mechanical performance against stresses produced by bending loads.

#### *3.2.3. Thermal characterization*


**5. Color conversion phosphors**

Commercial, industrial, and residential lighting are promptly shifting towards a phosphor-converted white light system. The most preferred way to generate white light from LEDs/LDs is to use phosphors that have the ability to absorb the high energy (short wavelength) photons and down-convert them into lower energy (longer wavelength) ones. The chemical composition of phosphor plays an essential role in display, SSL, and VLC. In the 19th century, phosphor's name arose as a generic term for a material that glows in the dark. Phosphor is a kind of photoluminescent material that emits visible light when exposed to certain radiation. The luminescence process of the phosphor is shown in **Figure 5(a)**.

*Blue Laser Diode-Based Visible Light Communication and Solid-State Lighting DOI: http://dx.doi.org/10.5772/intechopen.100106*

**Figure 5.** *(a) The luminescence process of phosphor. (b) Jablonski diagram of downconversion luminescence process.*

The luminescence process occurs when the activator absorbs the radiant energy and goes to a higher energy state. As the excited state is unstable, the excited photon emits absorbed energy in the relaxation state and falls back to a lower energy state. The Jablonski diagram of the downconversion phosphor luminescence process is shown in **Figure 5(b)**.

The properties associated with ideal phosphor are color quality, CRI, thermal stability, emission spectrum, photoluminescent lifetime, etc. Recent studies have highlighted that phosphor-based white light quality depends on photoluminescent material, size, composition, and arrangement with the package. The absorption rate depends on the crystal structure, particle size, and particle size distribution of phosphor. The difference between the spectral position of the peak of absorption and emission spectra is called stock shift, expressed in wavelength. The extent of the stock shift depends on the characteristic of phosphor. During the illumination process, the phosphor cannot absorb all excitation energy; some of the energy is reflected or transmitted. The most absorbed energy will be released in the form of light, and the rest of the energy may be converted into heat; therefore, in this process, emitted energy is always less than the absorbed energy, and thus the wavelength of excitation light is always shorter than that of emitted light. The phosphor's efficiency depends on how much relaxation (loss of energy) occurs during activation and emission.

Phosphors are increasingly utilized in lighting devices, such as compact fluorescent lamps, LEDs, and LDs. Nowadays, phosphors are using everywhere and extensive research have been carried out to find proper color conversion phosphors. The color conversion phosphor that can be excited by the blue or ultraviolet laser diode is shown in the **Table 2**.


ADHD - From Etiology to Comorbidity

*Edited by Hojka Gregorič Kumperščak*

Published in London, United Kingdom

### *Supporting open minds since 2005*

ADHD - From Etiology to Comorbidity http://dx.doi.org/10.5772/intechopen.87283 Edited by Hojka Gregorič Kumperščak

#### Contributors

Hojka Gregoric Kumperscak, Clay Brites, Anja Plemenitaš Ilješ, Juan Carlos López, Annabel Jiménez-Soto, Juan Pedro Vargas, Estrella Díaz, Danijela Krgović, Marija Burgić Radmanović, Sanela Burgić

#### © The Editor(s) and the Author(s) 2021

The rights of the editor(s) and the author(s) have been asserted in accordance with the Copyright, Designs and Patents Act 1988. All rights to the book as a whole are reserved by INTECHOPEN LIMITED. The book as a whole (compilation) cannot be reproduced, distributed or used for commercial or non-commercial purposes without INTECHOPEN LIMITED's written permission. Enquiries concerning the use of the book should be directed to INTECHOPEN LIMITED rights and permissions department (permissions@intechopen.com).

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Individual chapters of this publication are distributed under the terms of the Creative Commons Attribution 3.0 Unported License which permits commercial use, distribution and reproduction of the individual chapters, provided the original author(s) and source publication are appropriately acknowledged. If so indicated, certain images may not be included under the Creative Commons license. In such cases users will need to obtain permission from the license holder to reproduce the material. More details and guidelines concerning content reuse and adaptation can be found at http://www.intechopen.com/copyright-policy.html.

#### Notice

Statements and opinions expressed in the chapters are these of the individual contributors and not necessarily those of the editors or publisher. No responsibility is accepted for the accuracy of information contained in the published chapters. The publisher assumes no responsibility for any damage or injury to persons or property arising out of the use of any materials, instructions, methods or ideas contained in the book.

First published in London, United Kingdom, 2021 by IntechOpen IntechOpen is the global imprint of INTECHOPEN LIMITED, registered in England and Wales, registration number: 11086078, 5 Princes Gate Court, London, SW7 2QJ, United Kingdom Printed in Croatia

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ADHD - From Etiology to Comorbidity Edited by Hojka Gregorič Kumperščak p. cm. Print ISBN 978-1-83962-475-9 Online ISBN 978-1-83962-495-7 eBook (PDF) ISBN 978-1-83962-496-4


**2.1 Signal conditioning modules (HCPL-788J)**

232 Electrical Generation and Distribution Systems and Power Quality Disturbances

phase or a 3-phase voltage measurement supported by the power quality monitoring hardware. When working in different places, we can establish the network in various sites and connect via the Ethernet network from a single PC or laptop. The network has the capability to send from the board site to the PC or laptop with high speed up to 100 megabit per second (Mb/s). Nevertheless, it is easy to monitor the power quality monitoring system

This chapter is organized as follow: Section 2 is the architecture of the power quality monitoring being composed of 2 sets of ARM7 microcontroller boards, 3 signal conditioning modules, external memory board and energy measurement board. Section 3 is the embedded software design with the details of sampling concept, power quality monitoring concept, data frames, configuration data and Ethernet packet structures. Section 4 is the application software to interface the power quality monitoring hardware. Section 5 is the experimental results which are displaying the fault signals from AC lines while being on operation or being done after. Section 6 is the conclusion from the research with the future

The architecture of the power quality monitoring system is planned for specific purposes which are to detect, to store, to download and to display the fault signals while being on operation or being done later on. The main structures are divided into 5 circuit boards. The block diagram of the architecture of the power quality monitoring system is shown in

Fig. 1. Block diagram of the architecture of the power quality monitoring system

via the Ethernet network from PC or laptop.

**2. Architecture of the power quality monitoring system**

work suggestion.

Fig. 1.

There are actually 3 signal conditioning modules with 3 HCPL-788J integrated circuits for measuring the voltage of the three-phase AC lines in order to send the attenuated AC voltage to the waveform sampling board which the ADUC7024 microcontroller is embedded in. The 3 signal conditioning modules have used the same electronic circuit. The signal conditioning circuit is shown in Fig. 2.

Fig. 2. The circuit of the signal conditioning module

#### **2.2 The voltage and frequency measurement and fault detection board (ADE7758)**

This board is the key part of monitoring system of fault detection which refers to sags and overvoltages. In this chapter, ADE7758 integrated circuit has been chosen to operate because of its suitable qualification to detect the fault signals in time. The circuit of the board is shown in Fig. 3.


**8. Conclusions**

*H. pylori* infection significantly increases the risk for CVDs including atherosclerosis, HTN, CHD, cerebrovascular disease, and peripheral arterial diseases especially in younger patients (< 65 years old). *H. pylori* infection significantly impairs vascular endothelial function through multiple mechanisms including increased ROS production and oxidative stress, inflammation, decreased NO formation, modification of the expression of cytokines and miRNAs, interruption of lipid and glucose metabolisms, and exosomes-mediated pathways as shown in **Figure 4**. Endothelial dysfunction associated with *H. pylori* infection is reversible in both animal model and human subjects if the infection could be eliminated in a timely fashion (within one year of infection for human subjects and 6 months for mice). Accumulating data suggests that *H. pylori* infection is an additional risk factor for endothelial dysfunction and CVDs. Screening young male population for *H. pylori* infection once a year and treating accordingly could be an effective approach for early prevention of CVDs especially premature atherosclerosis associated with *H. pylori* infection.

#### **Figure 4.**

*Schematic illustration of the mechanism on endothelial dysfunction and atherosclerosis associated with*  H. pylori *infection. It is proposed that* H. pylori *infection could impair endothelial function through exosomemediated mechanisms. CagA protein is only from CagA+* H. pylori*, and could serve as an ideal tracking molecule for exosome trafficking in vivo. CagA<sup>+</sup>* H. pylori *translocate CagA protein into gastric epithelial cells (GES-1). CagA-containing exosomes are released into circulation from GES-1, then enter into endothelial cells, leading to endothelial dysfunction.* H. pylori *Infection could also decrease endothelial function through increased production of reactive oxygen species, oxidative stress, and inflammation, decreased cellular nitric oxide formation, modification of the expression of cytokines and miRNAs, and interruption of lipid and glucose metabolisms. [adopted and modified from (47) with permission].*

Helicobacter pylori *Infection and Endothelial Dysfunction DOI: http://dx.doi.org/10.5772/intechopen.97260*