**2. Literature Review**

The causes of policy uncertainty are failure of the government to clarify the direction and intensity of economic policy expectation, policy execution, and changes in policy position [4]. Economic uncertainty is difficult for enterprises to predict, which will enhance the external risks of business operations, and affects executives' cognition and behavioral decisions.

The existing literature measures the uncertainty of economic policy from the following three perspectives. The first type of literature measures the uncertainty of economic policy through the occurrence of external events, including major political events and changes in bureaucrats [5]. Since the occurrence of these events is not ongoing, their usage is subject to certain limitations. The second category uses the implied volatility of the stock market as the proxy variable of economic policy uncertainty. However, fluctuation in the financial market, which often lags behind, cannot reflect external economic policy uncertainty in real time. The third category of literature adopts the economic policy uncertainty index developed by Baker et al., based on the text analysis of newspapers. This method is authoritative, real-time and continuous, based on the reports of authoritative newspapers around the world. In this paper, we adopt the third type of measurement method.

At present, the research on the uncertainty of economic policy mostly focuses on corporate behavior, including corporate investment and financing, enterprise innovation, cash holdings [6–9], etc. The research related to economic policy uncertainty and executives mostly adopts the traits of executives as intermediaries or moderating variables to further study the impact of economic policy uncertainty on corporate behavior, for instance, their career records, including political background and financial experience, overconfidence, management governance [7,10–16], etc. Few scholars focus on the impact of economic policy uncertainty on executives' cognition and behavioral decisions. Based on the perspective of internal risk hedging, Rao [17] found that when the external uncertainty is high, the probability of executive turnover decreases. Wu [18] found that the uncertainty of economic policy is negatively correlated with executives' overconfidence. From the perspective of prospect theory, the uncertainty of economic policy comprises the uncertainties from policy change, policy execution, and the alterations of government positions. Facing external uncertainty, executives have uncertain expectations for the future of enterprises and themselves, which will lead to irrational bias in cognition and behavior choice, affecting their self-interest behaviors. At present, existing research seldom studies the relationship between economic policy uncertainty and executives' self-interest behavior, and related research needs to be further expanded.

According to the principal-agent theory, executives' self-interest behavior refers to the exploitation of their own rights and information asymmetry [19], in order to maximize their interests at the cost of shareholders and the enterprise, as illustrated by surging on-the-job consumption [20], seeking excess compensation [21], myopic behavior, cash flow manipulation [3], etc. In order to reflect the common behaviors of executives in listed companies, and present the explicit manifestations of their self-interest behavior, most scholars differentiate explicit self-interest behaviors from the implicit ones for quantitative research [1]. For explicit self-interest behavior, scholars commonly adopt excessive compensation [22,23], etc. With regard to implicit self-interest behavior, scholars use variables including excessive on-the-job consumption, management expenses, turnover of total assets [2,24–26], etc. Enterprises often take measures, such as supervision, reward, punishment, and incentive, to restrain the self-interest behavior of executives, and scholars mostly conduct research through the above related measures, including internal and external supervision, salary mechanism [27,28], etc. Change in the external macro-environment also affects executives' cognition and behavior choices. Executives will be passively restrained from self-interest behavior, or they may actively reduce such behaviors in exchange for stable income. The influence of economic uncertainty on executives' self-interest behavior needs to be further explored.

According to both the domestic and foreign literature, internal control reduces the asymmetry of internal and external information, strengthens internal supervision, plays an important role in reducing executive fraud [29] and preventing insider trading by executives [30], and exerts certain governance effects on both the implicit and explicit corruption of executives [31]. The above facts also lay a theoretical basis for choosing internal control as the moderating variable in this paper. With regard to the measurement of internal control quality, some scholars made a comprehensive evaluation through the five elements of internal control [32,33]. Scholars often adopt the internal control index of the DIB database to measure the quality of internal control [34,35].

By reviewing the existing literature, we can find that the research on the influencing factors of executives' self-interest behavior mostly focuses on corporate institutions, the strength of executives' power, etc., and seldom considers the influence of the external economic policy environment. Based on existing theories, negative cognitive theory induces executives to boost self-interest behaviors and gain immediate benefits under uncertain economic policies; however, based on the potential cost and risk, it is believed that due to the superposition effect of risks, executives are urged to restrain self-interest and tend to "protect themselves" against the risk of dismissal, thus reducing their self-interest behavior. However, the research on the uncertainty of economic policy focuses more on its impact on macroeconomic trends, corporate investment and financing, innovation and R&D, and financial market fluctuation. Macroeconomic policy and the fluctuation in economic fundamentals are the important foundations of enterprise behavior on the micro-level, and the uncertainty of economic policy will profoundly affect and change corporate behavior and decision-making. Under different degrees of policy uncertainty, executives' selfinterest behavior will be affected differently. In this paper, the macro-economic landscape is brought into the analysis framework of influencing factors of executives' self-interest behavior, and their self-interest behavior is refined into explicit and implicit categories. These two categories are quantitatively analyzed by adopting excessive compensation and on-the-job consumption, and the uncertainty of economic policy is adopted to analyze how the external environment affects executives' self-interest behavior, enriching the existing research results.

#### **3. Theoretical Analysis and Research Hypothesis**

This paper categorizes executive self-interest behaviors into explicit and implicit ones, and analyzes the influence of economic policy uncertainty on such behaviors. The explicit self-interest behavior of executives is exemplified by excessive compensation, and its implicit counterpart is measured by excessive on-the-job consumption.

On the one hand, at the corporate level, rising economic policy uncertainty amplifies the business risks of enterprises and exerts a negative impact on enterprise performance [36]. Changes in the economic environment will affect the survival and growth of enterprises. Rising economic policy uncertainty will make it difficult for management to predict the prospects of the market, as well as corporate financing and cash flow status in the future, making it more difficult to make decisions. In order to avert risks, C-suite often delays investment and lowers investment volume to alleviate the uncertainty, thus adversely affecting the performance of enterprises. Meanwhile, the financing of enterprises will also be affected by macroeconomic policies. Rising economic uncertainty will amplify instability in the future cash flow of enterprises and also aggravate the external financing challenges of enterprises. From the perspective of creditors such as banks, when economic policy is uncertain, the risk of loan default will rise, since it will be difficult to evaluate the credit of enterprises. Therefore, creditors will adopt a tight credit policy, raise the loan threshold, and reduce the loan amount, which pushes up the financing costs of enterprises and further undermines their development. Facing both internal and external difficulties, in order to maintain stable operation and ease operating pressure, enterprises will start to reduce expenses and compensation. On 2 June 2022, the State-owned Assets Supervision and Administration Commission (SASAC) issued the Notice on Further Implementing the

Tasks of Boosting Income and Reducing Expenditure of SOEs, which stipulated: "SOEs should strictly implement the linkage mechanism between total wages and profits, and the growth rate of total compensation shall not exceed that of total profit. SOEs with declining profits must cut total compensation." Therefore, when the uncertainty of economic policy is high, enterprises will face greater business risks, which will reduce C-suite enumeration, inhibiting excessive compensation of executives and their explicit self-interest behavior.

On the other hand, higher uncertainty of economic policy will lead to tougher employment. With rising external uncertainty, the turnover of executives will be more frequent, boosting the risk of dismissal [37]. Based on prospect theory, people tend to choose "safe returns" instead of "taking a chance". Even though self-interest behavior may bring some excess returns, if such behavior can be uncovered easily, the risk of turnover will also surge. Therefore, executives will suppress their explicit self-interest behavior to obtain "safe returns". Meanwhile, some executives choose to fulfill their social responsibility by taking the initiative to reduce salaries before ordinary employees. According to Vanke's 2021 annual report, due to the sharp decline in corporate performance, Yu Liang, chairman of the board of directors, voluntarily waived all bonuses in 2021 and reduced his compensation by nearly 90%. Eight directors, supervisors, and senior managers, including Yu Liang, reduced their salaries by half, totaling 24 million yuan. These executives not only fulfill their social responsibility, but also build good reputation and lay a solid foundation for their future career development. Therefore, when the uncertainty of economic policy is high, executives themselves will also choose to reduce their explicit self-interest behavior and excess remuneration.

However, executives' implicit self-interest, namely excessive on-the-job consumption, is affected differently by the uncertainty of economic policies. On-the-job consumption, also known as perquisite consumption or perk consumption, is the nonmonetary consumption spent by the managers, incurred when the manager is performing duties. On-the-job consumption is generally included in administrative expenses, which can be further divided into office allowance, travel expenses, correspondence expenses, etc. Although the "optimal" level of on-the-job consumption may motivate managers to perform well, excess on-the-job consumption may hurt firm value [38].

Managers increase their nonmonetary compensation to achieve self-utility maximization when the government supervision or other restrictions are weak [28]. With weak legal constraints and corporate governance mechanisms, on-the-job consumption has become an important part of management compensation in China, far more even than monetary compensation. Furthermore, on-the-job consumption is implicit, has no contractual constraints, and is largely determined by the top executives; executives are likely to deviate from the objective of maximizing stakeholder value and use on-the-job consumption to gain self-interest [39].

Higher uncertainty of economic policy leads to greater information asymmetry in enterprises; thus, the difficulties of internal and external supervision are also elevated, which facilitates executives to make use of their authority for on-the-job consumption and implicit self-interest behavior. Furthermore, as analyzed above, whether voluntary or forced, when the external uncertainty is high, the explicit remuneration of executives will decline. Therefore, executives are more inclined to use their authority to earn implicit benefits through on-the-job consumption to make up for salary loss. In addition, rising uncertainty of external economic policies often brings about greater financing difficulties for enterprises. In order to prevent capital chain rupture, enterprises tend to reduce investment while holding excess cash to cope with financial risks, which also provides opportunities for executives' invisible self-interest behavior.

In conclusion, concerning the impact of economic policy uncertainty on executives' self-interest behavior, this paper puts forward the following assumptions:

**Hypothesis 1 (H1a).** *Rising economic policy uncertainty will inhibit the explicit self-interest behavior of executives.*

**Hypothesis 1 (H1b).** *Rising economic policy uncertainty will encourage the implicit self-interest behavior of executives.*

Executives' responses to the fluctuation of external economic policy uncertainty are also influenced by the internal organizational structure and supervision system of their enterprises. Facing the uncertainty of the external macro-environment, enterprises need to improve internal control to better manage production and business activities and counter unknown risks. An effective internal control system can restrain executive opportunism, reduce information asymmetry, and alleviate the principal-agent problem between shareholders and C-suite, which is conducive to the long-term development of enterprises. "Internal environment", one of the five elements of internal control, requires enterprises to set up corresponding supervision mechanisms, establish sound organizational mechanisms, realize internal power checks and balances, avert "tyranny of the minority" and "insider control issue", and supervise the behavioral decisions of executives. Among the five elements of internal control, "Risk Assessment" requires enterprises to assess the possible risks in the future and formulate corresponding policies to prevent executives from speculating on the grounds of external risks. "Control activities" require enterprises to improve various management systems, better control the actual income and cost of each production and operation procedure, fix the loopholes of which C-suite may take advantage, and prevent their self-interest behaviors. "Information communication" encourages enterprises to reduce internal and external information asymmetry and improve the quality of information disclosure, which is conducive to the supervision of agents by stakeholders.

To sum up, this paper puts forward the following assumptions:

**Hypothesis 2 (H2a).** *Under economic policy uncertainty, effective internal control can enhance the inhibition of executives' explicit self-interest behavior.*

**Hypothesis 2 (H2b).** *Under economic policy uncertainty, effective internal control can weaken the facilitation of executives' explicit self-interest behavior.*

#### **4. Research Design**

#### *4.1. Data Sources and Sample Selection*

This paper adopts the data of A-share-listed companies in the Shanghai and Shenzhen stock exchanges from 2006 to 2021 as the research object, and has taken the following screening measures: (1) excluding the listed companies that were classified as ST and PT at the end of 2012 to 2021; (2) excluding listed companies in the financial sector; (3) excluding the listed companies that were forcibly delisted during the sample period; (4) eliminating the samples with missing observation values in the selected period; meanwhile, the continuous variables are winsorized at the top and bottom 1%. A total of 24484 observation samples were obtained after screening. The related data of explanatory and control variables in this paper were extracted from CSMAR, the economic policy uncertainty index of explanatory variables was sourced from the http://www.policyuncertainty. com/ website (accessed on 3 November 2022), and the internal control index of moderating variables was generated from the DIB database.

#### *4.2. Definition of Variables*

#### 4.2.1. Explanatory Variable

In this paper, the self-interest behavior of executives is regarded as the explanatory variable, which is divided into explicit and implicit self-interest behavior, measured by Csuite excessive compensation (OverPay) and excessive on-the-job consumption (UnPerks), respectively.

The detailed measurement of explicit self-interest behavior of executives-excessive compensation (OverPay) is as follows. In this paper, we adopt "the total compensation of top 3 executives" disclosed in the annual reports of A-share-listed companies in the Shanghai and Shenzhen stock exchanges as the data of executives' salaries, and the variables of C-suite compensation were obtained using a taking logarithm. Next, we drew from the practices of Core et al. [40], Luo et al. [41], etc. to measure the excessive compensation of executives. Firstly, Model (1) is regressed by years and industries using sample data to obtain the regression coefficient. Then, the estimated regression coefficient is multiplied by the factors that affect C-suite compensation, such as corporate scale and performance, to estimate the expected level of executive compensation; finally, according to Model (2), the actual C-suite compensation is subtracted from the expected C-suite compensation, and the difference is excessive compensation. The definitions of variables used in Model (1) are presented in Table 1.

$$Pay\_{i,t} = a\_0 + a\_1 Size\_{i,t} + a\_2 ROA\_{i,t} + a\_3 IA\_{i,t} + a\_4 Zone\_{i,t} + \sum Industry + \sum \text{Year} + \varepsilon\_{i,t} \tag{2}$$

$$OverPay = Pay\_{i,t} - Expected Pay\_{i,t} \tag{2}$$

**Table 1.** Definition table of overpay variables of executives.

The detailed measurement of implicit self-interest behavior of executives-excessive on-the-job consumption (UnPerks) is as follows. We draw from the research models of Quan et al. [42], Luo et al. [43], etc. and predict the normal on-the-job consumption of executives through the relevant corporate conditions of Model (3). The difference between actual and normal on-the-job consumption is abnormal on-the-job consumption. Among them, the C-suite on-the-job consumption is the balance of management expenses after deducting the total annual compensation, amortization of intangible assets, total provision for bad debts, and total provision for inventory depreciation. The definitions of variables used in Model (3) are presented in Table 2.

$$\frac{Pers\_{i,t}}{Aset\_{i,t-1}} = \beta\_0 + \beta\_1 \frac{1}{Aset\_{i,t-1}} + \beta\_2 \frac{Asal\varepsilon\_{i,t}}{Asset\_{i,t-1}} + \beta\_3 \frac{PPE\_{i,t}}{Asset\_{i,t-1}} + \beta\_4 \frac{Inventory\_{i,t}}{Asset\_{i,t-1}} + \beta\_5 LnEmployee\_{i,t} + \varepsilon\_{i,t} \tag{3}$$

$$
\Delta InPrks = Perks\_{i,t} - ExpectedPerks\_{i,t} \tag{4}
$$

**Table 2.** Definition table of excessive on-the-job consumption variables of executives.

#### 4.2.2. Explanatory Variables

The Economic Policy Uncertainty Index (EPU) of China is drawn from the website of http://www.policyuncertainty.com/ (accessed on 3 November 2022). From the newspapers People's Daily and Guangming Daily, Davis, Liu, and Sheng adopt the method of text analysis, counting articles related to economic policy uncertainty through scaling frequency, and formulating EPU after standardization treatment. At present, scholars at home and abroad use EPU when conducting research on economic policy uncertainty. This paper draws on the practice of Gu et al. [8]: the monthly data are arithmetically averaged, and then the logarithm is taken to obtain the explanatory variable EPU. Formula (5) provides more details.

$$EPL = LN \left( \frac{\sum \text{Economic policy uncertainty monthly}}{12} \right) \tag{5}$$

#### 4.2.3. Moderating Variables

In this paper, moderating variables are selected from the DIB internal control index, which is based on the five elements of internal control and granularly measures the internal control quality of listed companies. When the index is high, corporate internal control management activities are effective and the internal control system is sound. In this paper, we refer to the practices of Zhou et al. [44], etc., to establish an internal control moderating index after taking the logarithm of the internal control index.

#### 4.2.4. Control Variables

In this paper, the following indicators are selected as control variables, and the descriptions of each variable are illustrated in Table 3.

**Table 3.** Variable definition table.

#### *4.3. Model Setting*

#### 4.3.1. Economic Policy Uncertainty and Executives' Self-Interest Behavior

In order to validate the relationship between economic policy uncertainty and executives' self-interest behavior, this paper constructs the following econometric regression models. Model (6) is used to test the influence of economic policy uncertainty on executives' explicit self-interest behavior, so as to verify hypothesis H1a in this paper. According to H1a, *α*<sup>1</sup> of Model (6) should be significantly negative. Model (7) is used to test the influence of economic policy uncertainty on executives' implicit self-interest behavior, so as to verify hypothesis H1b in this paper. According to H1b, *β*<sup>1</sup> of Model (7) should be significantly positive.

$$OverPay = a\_0 + a\_1 EPL + a\_n \sum controls + \varepsilon\_{i,t} \tag{6}$$

$$Perk = \beta\_0 + \beta\_1 EPLI + \beta\_n \sum controls + \varepsilon\_{i,t} \tag{7}$$

#### 4.3.2. Moderating Role of Internal Control

Models (8) and (9) are used to test hypotheses H2a and H2b in this paper, respectively. By adding an interaction term including economic policy uncertainty and the internal control index to the regression equation, we can discuss the moderating function of internal control. Among them, in order to avoid the collinearity problem, in the interaction term of economic policy uncertainty and internal control index, the decentralized values of the two factors are multiplied.

$$OverPay = a\_0 + a\_1 EPL + a\_2 IC + a\_3 EPL \times IC + a\_n \sum controls + \varepsilon\_{i,t} \tag{8}$$

$$Park = \beta\_0 + \beta\_1 EPLI + \beta\_2 IC + \beta\_3 EPLI \times IC + \beta\_n \sum controls + \varepsilon\_{i,t} \tag{9}$$


Introductory Chapter: Vitamin D Deficiency

*Julia Fedotova*

## **1. Introduction**

Vitamin D (VD) is a unique bio-regulatory molecule as it can be synthesized in the skin in addition to its dietary sources [1, 2]. The well-studied function of VD is associated with its ability to regulate metabolic processes in skeletal tissue by affecting mineralization, maintaining a balance between the formation and resorption of bone tissue, thereby contributing to the prevention of osteoporosis and the occurrence of fractures [1–3].

VD comes in two major forms, D2 and D3, with D3 being the most prominent. Both forms can be sourced from food, D2 from plants and mushrooms while D3 can be found in fish oil [2–4]. However, the majority of the body's VD is synthesized de novo in the skin after exposure to ultraviolet B radiation such as sunlight [2, 5].

Earlier studies have suggested that a serum level of VD should range around 40–60 ng/l lowers the risks of developing different diseases, as well as an all-cause lower mortality [1, 2]. A daily intake or production of 4000–6000 international units is required to sustain these levels [2]. While it is possible to produce the required levels of VD through 2 times in a week sun exposure for 10–30 minutes, many patients are unable to produce that much because of issues related to the environment, health and socioeconomic reasons [1, 2].

That is why, it is recommended for healthy adults at risk for VD deficiency to supplement with 1500–2000 IU with an upper limit of 10.000 IU a day orally [1, 2]. A correlation between very low VD3 levels and numerous diseases and a correlation between an impact of VD levels and normal functioning of the whole organism have well-established [1].

## **2. COVID-19 era and Vitamin D deficiency**

VD is postulated to impact innate and adaptive immunological responses [6]. Low concentrations of VD are associated to elevated autoimmunity and increased susceptibility to virus diseases [6, 7]. The implication of VD in the protective mechanisms against respiratory tract infections by COVID-19 has been reported [7]. VD produces anti-microbial peptides secretion, especially cathelicidins and defensins, thereby resulting in the replication rate of viruses and pro-inflammatory cytokines levels. Supplementation of VD in patients with COVID-19 for treatment has been made in human studies [6, 7]. Beneficial effects of VD to protect the incidence of influenza A are associated with very low VD levels due to lack of sunlight exposure [7]. VD might

help in preventing influenza by preventing a cytokine storm in the influenza state, reducing the production of IL-1 and IL-6 [7, 8]. Recently, low VD levels are linked with elevated IL-6 levels in patients with the human immunodeficiency virus disease [9].

As mentioned, VD has multiple effects on the immune system. Many studies have therefore looked into whether VD status and VD supplementation could lower the risk of contracting acute respiratory infections in general, also in some another pandemic like COVID-19 in the future.

## **3. Summary**

Overall, VD deficiency might affect the treatment response and remission rate in different population with numerous disorders. We do not exactly know the precise mechanisms how VD deficiency might implicate in many disorders. However, we must take into account that patients with VD deficiency can be resistant to available therapeutic options, which poses a major therapeutic challenge to health experts. Thus, it is possible to suggest that VD deficiency is likely a driving factor for the development of a whole number of severe diseases.

The following recommendations can be made:

New technologies might offer ways to treat patients with various disorders in a association with VD deficiency more effectively.

*Introductory Chapter: Vitamin D Deficiency DOI: http://dx.doi.org/10.5772/intechopen.110556*

## **Author details**

Julia Fedotova Laboratory of Neuroendocrinology, Pavlov Institute of Physiology RAS, Saint Petersburg, Russia

\*Address all correspondence to<EMAIL_ADDRESS>
© 2023 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.

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Section 2


**Author details**

John J. McGlone\*, Edgar O. Aviles-Rosa, Courtney Archer, Meyer M. Wilson, Karlee D. Jones, Elaina M. Matthews, Amanda A. Gonzalez and Erica Reyes Laboratory of Animal Behavior, Physiology and Welfare, Texas Tech University, Lubbock, TX, USA

\*Address all correspondence to<EMAIL_ADDRESS>
© 2020 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.

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**4. Conclusions**

In this work, a polymeric precursor was modified using variations of steam activation methods to prepare APHSs with high specific surface area and a mesopore-rich structure. The specific surface area and specific capacitance of the physical APHS samples was up to 2240 m2/g and 136 F/g, respectively.

The activation condition (time and temperature) affected the pore structure of APHS. During the initial increase of the activation time, micropores with narrow PSD were formed by oxidation of amorphous areas or small crystallites. As the activation time increased, the oxidation of crystallites increased, leading to increased specific surface areas and mesopore volume. As the activation time increased further, the oxidation of crystallites increased, leading to increased micropore and mesopore volume. With additional extension of the activation time, the pores that initially developed started to deepen, enlarge, and perhaps merge, resulting in the observed increase in the average pore width. When the activation temperature increased from 900 to 1000 ◦C, the oxidation rate of APHS was found to increase about twice. As a result, at the activation temperature of 1000 ◦C, APHS exhibited broad PSD curves and wide pore diameter.

The specific capacitance was significantly dependent on the pore size distribution according to activation conditions. It was confirmed that the correlation between the specific capacitance in 1M TEABF4/PC and the pore characteristics of the APHS was determined by pores of diameter 1.5–2.5 nm. The specific capacitance of APHS-9-4 was higher than that of APHS-10-2, which had the highest specific surface area and mesopore volume. These results suggest that the pore structure of APHS-9-4 is better optimized than is the pore structure of APHS-10-2 in 1M TEABF4/PC. In conclusion, APHS, created using the physical activation method, exhibited better specific capacitance than did MSP20 created using the chemical activation method.

**Author Contributions:** Conceptualization, S.-J.P. and B.-J.K.; methodology, S.-J.P. and B.-J.K.; validation, K.-H.A., S.-J.P. and B.-J.K.; formal analysis, H.-M.L. and B.-J.K.; investigation, K.-H.A.; resources, K.-H.A. and B.-J.K.; data curation, H.-M.L.; writing—original draft preparation, H.-M.L.; writing—review and editing, B.-J.K.; visualization, B.-J.K.; supervision, B.-J.K.; project administration, B.-J.K.; funding acquisition, B.-J.K.

**Funding:** This research was supported by the Nano·Material Technology Development Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Science and ICT (Project no. 2018M3A7B9086636). This research was financially supported by the Ministry of SMEs and Startups (MSS), Korea, under the "Regional Specialized Industry Development Program (P0003187)" supervised by the Korea Institute for Advancement of Technology (KIAT).

**Conflicts of Interest:** The authors declare no conflict of interest.


*Article* **Circuit-Based Electrothermal Simulation of Multicellular SiC Power MOSFETs Using FANTASTIC**

### **Vincenzo d'Alessandro 1,\*, Lorenzo Codecasa 2, Antonio Pio Catalano 1 and Ciro Scognamillo 1**

Received: 26 June 2020; Accepted: 30 August 2020; Published: 3 September 2020

**Abstract:** This paper discusses the benefits of an advanced highly-efficient approach to static and dynamic electrothermal simulations of multicellular silicon carbide (SiC) power MOSFETs. The strategy is based on a fully circuital representation of the device, which is discretized into an assigned number of individual cells, high enough to analyze temperature and current nonuniformities over the active area. The cells are described with subcircuits implementing a simple transistor model that accounts for the utmost influence of the traps at the SiC/SiO2 interface. The power-temperature feedback is emulated with an equivalent network corresponding to a compact thermal model automatically generated by the FANTASTIC tool from an accurate 3D mesh of the component under test. The resulting macrocircuit can be solved by any SPICE-like simulation program with low computational burden and rare occurrence of convergence issues.

**Keywords:** electrothermal (ET) simulation; finite-element method (FEM); model-order reduction (MOR); multicellular power MOSFET; silicon carbide (SiC)


**IMMUNOTHERAPY - MYTHS, REALITY, IDEAS, FUTURE**

Edited by **Krassimir Metodiev**

#### **Immunotherapy - Myths, Reality, Ideas, Future**

http://dx.doi.org/10.5772/63291 Edited by Krassimir Metodiev

#### **Contributors**

Atanas Arnaudov, Danilo Di Bona, Maria Stefania Leto-Barone, Simona La Piana, Gabriele Di Lorenzo, Viola Heinzelmann, Marcus Vetter, Yehia Mohamed, Michael Browning, Ronwyn Irene Van Eeden, Bernardo Rapoport, Norbert Lukan, Janio Santurio, Barbara Ostrov, Robert Cameron, Raymond Wong, Astrid Holzinger, Hinrich Abken, Helena Villanueva, Fernando Pastor, Mario M. Soldevilla, Gheorghita Isvoranu, Juliana Miranda, Jair Cunha Junior, Deise Silva, Ernesto Taketomi, Neli Mitkova Ermenlieva, Gabriela Tsankova, Tatina Todorova, Lisa Sedger, Tsveteslava Veselinova Veselinova Ignatova-Ivanova, Krassimir Metodiev, Igor Resnick

#### **© The Editor(s) and the Author(s) 2017**

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#### **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 Croatia, 2017 by INTECH d.o.o. eBook (PDF) Published by IN TECH d.o.o. Place and year of publication of eBook (PDF): Rijeka, 2019. IntechOpen is the global imprint of IN TECH d.o.o. Printed in Croatia

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*3.1. Discrimination of HF Structures, Distribution of HSPG and GPC1 Using IR Spectral Imaging Analysis*

Anagen, catagen, and telogen HFs were individually isolated and maintained in culture for one day (A1, C1, and T1, respectively) or three days (A3, C3, and T3, respectively) before analysis. The white light image in Figure 2A shows a section of a HF and its different structures: germinative matrix (1), differentiation zone (2), IRS (3), ORS (4), and hair shaft (5). OCT is indicated by number 6.

**Figure 2.** PCA analysis of spectra from specific hair follicle regions. (**A**) White light image of a hair follicle. Five hair follicle structures were analyzed: 1, germinative matrix; 2, differentiation zone of the matrix; 3, IRS; 4, ORS; 5, hair shaft. The number 6 corresponds to OCT. (**B**) Pixel spectrum representative of each structure and OCT. (**C**,**D**) PCA score plot performed on normalized mean spectra of the above regions in the 1800–900 cm−1 (**C**) or 1350–1190 cm−1 (**D**) range and carried out on anagen A1/A3, catagen C1/C3, and telogen T1/T3 hair follicles. Ellipses represent the 95% confidence intervals.

3.1.1. Different Structures of the Hair Follicle are Discriminated by IR Spectral Imaging Analysis Based on the Variation of GAGs and Their Sulfation

The whole section was analyzed by IRSI and representative spectra of the HF structures are illustrated in Figure 2B. These spectra represent the means calculated from a small zone from each HF structure (indicated by 1 to 5). For comparison, the mean spectrum of OCT was also represented (6). The analysis of the GAG spectral profiles in the different HF structures was performed by PCA first in the 1800–900 cm−1 spectral range (Figure 2C) corresponding to the proteins and PGs and then in the 1350–1190 cm−1 spectral range (Figure 2D), focusing on sulfated GAGs. Figure 2C shows the PCA score plot built with the principal components PC1 and PC3 carrying 58.4% and 13.3% of the total explained variance, respectively. This score plot revealed five structural groups distributed in three well-differentiated zones. The first zone was composed of an overlap of the germinative matrix (group 1) and the differentiation zone (group 2). This overlap can be explained by the fact that the matrix cells of the differentiation zone are the result of differentiation of the progenitor cells present in the germinative matrix derived from stem cells of SHG [36–39]. They therefore share similar characteristics, such as proteins and polysaccharides, explaining their similarity. The second zone is constituted by the ORS (group 4), the third—by the hair shaft zones of HFs (group 5). It can be noted that the IRS structure (group 3) lies between the ORS and the hair shaft zones. Interestingly, IRS histologically separates the hair shaft from the ORS, which corroborates spectral data.

Figure 2D shows the PCA score plot built with the principal components PC1 and PC2 carrying 94.4% and 3.9% of the total explained variance, respectively. The PCA performed in the sulfated GAG absorption range (1350–1190 cm−1 ) succeeded to precisely discriminate the germinative matrix structure (group 1) from the four other groups and, in particular, from the differentiation zone (group 2), in contrast with the overlap observed in Figure 2C. The other structures (differentiation zone, IRS, ORS, and hair shaft) were not clearly separated using sulfated GAG spectral signatures. Interestingly, different groups obtained by this PCA reflect the scheme of differentiation of the multipotent HF cells [36–39]. Indeed, the progenitor hair cells present in the germinative matrix provide, on the one hand, the ORS cells and, on the other hand, the transit-amplifying cells of the differentiation zone that will differentiate into IRS and hair shaft cells.

The PCA results shown in Figure 2C,D allowed discriminating several features of the HFs, the germinative matrix, the differentiation zone, the ORS, the IRS, and the hair shaft, by the contribution of proteins, PGs, GAGs, and sulfated GAGs. The biochemical spectral information is confirmed by the loading vectors shown in the region of 1800–900 cm−1 (Figure S1A) and in the region of 1350–1190 cm−1 (Figure S1B). The sulfate group vibrations of GAGs are mainly represented by the IR absorption band centered at 1248 cm−1 . This peak is assigned an antisymmetric stretching S=O vibrations as we have previously reported [29]. This discrimination is in agreement with the difference in PG composition in the different parts of HFs observed by immunostaining or immunofluorescence [21,22,40]. Moreover, the IRSI technique does not require any staining or chemicals while keeping good discrimination of histological structures.

3.1.2. Focus on GPC1 Distribution in Hair Follicles by Spectral Imaging Analysis and Immunohistochemistry

In order to better understand the contribution of HSPGs in the differences observed by the PCA in the spectral range corresponding to PGs/GAGs and sulfated GAGs, a correlation image was computed with a spectrum of standard HS. This analysis permitted obtaining a representative image of the HS contribution in the section of HFs. As shown in Figure 3, the coefficient of HS contribution was most important in the ORS. The IRS displayed a good correlation with HS. The germinative matrix structure presented a low correlation with HS, while the differentiation zone and the hair shaft did not correlate with the HS. This result correlates well with HS distribution in the HFs obtained by immunohistochemistry reported by Malgouries et al., where several HSPGs were found in the ORS part of HFs [21,40].

**Figure 3.** Characterization of hair follicle structures by different imaging approaches. From left to right: white light image, HS- and GPC1-correlated IR images, and immunohistochemical labeling of GPC1 (green) counterstained with the Evans blue dye (red). CTS, connective tissue sheath; IRS, inner root sheath; ORS, outer root sheath. Arrowheads indicate high level of correlation. Scale bar: 100 µm.

A correlation image was also created with a representative spectrum of GPC1. The coefficient of GPC1 contribution is most important in the differentiation zone (Figure 3). The hair shaft, the ORS, and the germinative matrix also presented a good correlation with GPC1, but not the IRS. The GPC1 correlation map is confirmed by the GPC1 green labeling obtained by immunohistochemistry of HFs. These results obtained by the IRSI technique demonstrate its ability to discriminate at the molecular scale in a comparable manner to immunohistochemistry without any labeling.

These results support the PCA analyses carried out on the different HF structures. The use of both HS and GPC1 correlation mapping may partly explain the discrimination potential of the PCA analyses.


**Author details**

Rania Djemal\*, Moez Hanin and Chantal Ebel Plant Physiology and Functional Genomics Research Unit, Institute of Biotechnology of Sfax, University of Sfax, Sfax, Tunisia

\*Address all correspondence to<EMAIL_ADDRESS>
© 2023 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.

*Control of Plant Responses to Salt Stress: Significance of Auxin and Brassinosteroids DOI: http://dx.doi.org/10.5772/intechopen.111449*


3. Solution to the EOM

The general solution to the high voltage transmission line equation of motion was derived using Euler-Bernoulli equation. The particular solution to the equation of motion was derived using a product of two functions. The two functions were first separated using the principle of variable separation as expressed in Eq. (14) [19]:

$$Y(\mathbf{x}, t) = \mathbf{X}(\mathbf{x}) T(t) \tag{14}$$

Where X xð Þ is the normalized function representing the mode shape of the equation of motion. The normalized function ensures that orthogonality condition was satisfied in the derivation of the EOM model solution. Applying the normalized function in the EOM yields Eqs. (15) and (16):

$$EI\stackrel{\textstyle \longrightarrow \textstyle \longrightarrow}{X}(\mathbf{x}) - S\stackrel{\textstyle \longrightarrow}{X}(\mathbf{x}) - \omega^2 \rho AX(\mathbf{x}) = \mathbf{0} \tag{15}$$

$$
\ddot{T}(t) + \omega^2 T(t) = 0\tag{16}
$$

==== == d4y d2y d2 € y Where X x x T tðÞ¼ and ω2 ð Þ¼ ð Þ ¼ is a constant that equates x and t. Assuming dx4, X dx2, dt2 that X xð Þ ¼ ZeΨx , the model is expressed in Eq. (17) as:

$$\mathcal{Z}e^{\Psi \mathbf{x}} \left( EI\Psi^4 - S\Psi^2 - \rho A\omega^2 \right) = 0 \tag{17}$$

� � Considering that ZeΨx ¼6 0, hence EIΨ4 � SΨ2 þ rAω2 ¼ 0. The general solution of the Euler-Bernoulli equation which represents the solution to the equation of the motion of the transmission line is expressed in Eqs. (18) and (19) as [9]:

$$
\Omega^2, \Psi^2 = -\frac{(-\mathbf{S}) \pm \sqrt{\mathbf{S}^2 - 4(\mathbf{E}\mathbf{I})(-\rho A \omega^2)}}{2\mathbf{E}\mathbf{I}}\tag{18}
$$

$$
\Omega, \Psi = (\pm) \sqrt{\frac{S \pm \sqrt{S^2 + 4EI(\rho A \omega^2)}}{2EI}} \tag{19}
$$

The values of Ω and Ψ represents the general solution of the equation of motion. The practical implication of the derived solution is that it represents the transverse vibration of the high voltage transmission line. The derived solution has infinite number of solutions and the solution is indexed to accommodate all the possible solutions from the model. The indexed solution is expressed in Eqs. (20) and (21) as:

$$
\Omega\_n = \sqrt{\frac{S}{2EI} + \sqrt{\frac{S^2}{\left(2EI\right)^2} + m\_L \frac{\left(2\pi f\_n\right)^2}{EI}}} \tag{20}
$$

$$\Psi\_n = \sqrt{-\frac{S}{2EI} + \sqrt{\frac{S^2}{\left(2EI\right)^2} + m\_L \frac{\left(2\pi f\_n\right)^2}{EI}}}\tag{21}$$

Where ωn ¼ 2πf and for n ¼ 1, 2, 3, …. n

In Eqs. (22)–(24), the infinite natural frequencies of the power conductor were derived while considering that the mode shape is the same as a pinned-pinned beam eigenfunction model with no external force. Hence,

$$Y\_n(\mathbf{x}, t) = \sin \frac{n \pi \mathbf{x}}{l} \cos \omega\_n t \tag{22}$$

$$EI\left(\frac{n\pi\pi}{l}\right)^4 \sin\frac{n\pi\pi}{l} \cos\omega\_n t - S\left(-\frac{n\pi}{l}\right)^2 \sin\frac{n\pi\pi}{l} \cos\omega\_n t + \rho A(-\omega\_n) \sin\frac{n\pi x}{l} \cos\omega\_n t = 0\tag{23}$$

$$\sin\frac{n\pi x}{l}\cos\omega\_n t \left[\frac{EI}{\rho A} \left(\frac{n\pi}{l}\right)^4 + \frac{S}{\rho A} \left(\frac{n\pi}{l}\right)^2 - \omega\_n^2\right] = 0\tag{24}$$

The natural frequency of the power conductor in rad/s is expressed in Eqs. (25) and (26) as:

$$
\omega\_n^2 = \left(\frac{n\pi\tau}{l}\right)^2 \frac{S}{A\rho} + \left(\frac{n\pi\tau}{l}\right)^4 \frac{EI}{A\rho} \tag{25}
$$

$$
\omega\_n = \sqrt{\left(\frac{n\pi}{L}\right)^2 \frac{S}{m\_L} \left[1 + \left(\frac{n\pi}{L}\right)^2 \frac{EI}{S}\right]}\tag{26}
$$

The natural frequency in Hz is expressed in Eq. (27) as:

$$F\_n = \frac{1}{2\pi} \sqrt{\left(\frac{n\pi}{L}\right)^2 \frac{S}{m\iota} \left[1 + \left(\frac{n\pi}{L}\right)^2 \frac{EI}{S}\right]}\tag{27}$$


**2.5 Software validation of particle–wall collision**

In this paper, the ABAQUS software is used to simulate the particle–wall collision process, and it is compared with the numerical results by using the DEFEM. The ABAQUS is a finite element software applied to engineering simulation, which can simulate the stress and strain of large structures. This paper simulates the collision process between a spherical particle and the wall using the ABAQUS. The particle with a diameter of 0.05 m vertically hit the wall at a velocity of 0.5 m/s. The elastic modulus of the particles is 0.02 GPa, and the Poisson's ratio is 0.3. The elastic modulus of the wall is 2 GPa, and the Poisson's ratio is 0.3. After the contact force of particles is counted, the simulation results of ABAQUS and DEFEM are compared, as shown in **Figure 3**(**a**). It can be observed that the changing trend of the two results is the same, and the numerical value is similar. The contact force of the two numerical methods is re-zero near 0.003 seconds. In addition, the displacement of particles during collision and rebound is tracked, as shown in **Figure 3**(**b**). The results obtained by the two methods are in good agreement. It can be seen from these two results that the simulation results of the DEFEM are consistent with those of the ABAQUS.

*DEFEM Method and Its Application in Pebble Flows DOI: http://dx.doi.org/10.5772/intechopen.109347*

**Figure 2.** *Schematic diagram of the simulation process of the DEFEM.*

**Figure 3.**

*(a) Comparison of the results of DEFEM and ABAQUS software for contact force of the particle; (b) comparison of DEFEM and ABAQUS software for the displacement of the particle.*

Compared with the DEM, one of the advantages of the DEFEM is to calculate the dynamic deformation displacement and stress distribution of particles. It shows the comparison of deformation displacement calculated using the ABAQUS and the DEFEM, as shown in **Figure 4**. It can be observed that the distribution of the two methods is similar. The black vector in **Figure 4**(**b**) represents the deformation displacement at the grid node of the particle. Due to the collision between particles and the wall, the deformation near the wall is greater than that away from the wall, which also conforms to the relevant physical law.

#### **Figure 4.**

*(a) Static deformation displacement distribution calculated by ABAQUS software; (b) dynamic deformation displacement distribution calculated by the DEFEM (black vector represents the deformation displacement of nodes).*

**Figure 5.**

As shown in **Figure 5**, the static stress distribution of the particle calculated using the ABAQUS software has the same variation trend as the dynamic stress distribution calculated by the DEFEM, but there are some differences in values. Because the FEM is used to solve the problem in the ABAQUS software, it is considered that the contact force between particles only exists at the contact point. As shown in **Figure 5**(**b**), face contact is selected in the DEFEM. The multiple EDEs cover the boundary of particles. Therefore, the contact between particles can be transformed into the contact between EDEs, involving multiple nodes. The judgment and simulation process of the contact force are different between the two methods, so the stress distribution calculated by the two methods is different, but these differences are acceptable within the allowable error range.

Through the comparison between the ABAQUS software and the DEFEM, it can be observed that the DEFEM can well track the contact force, stress distribution, and movement in the process of particle collision, which also proves the accuracy of the DEFEM.


*Editorial* **The Artificial Intelligence in Digital Pathology and Digital Radiology: Where Are We?**

#### **Daniele Giansanti**

Centre Tisp, Istituto Superiore di Sanità, Via Regina Elena 299, 00161 Roma, Italy<EMAIL_ADDRESS>Tel.: +39-06-4990-2701

#### **1. The Digital Radiology and Digital Pathology**

Thanks to the incredible changes promoted by Information and Communication Technology (ICT) conveyed today by *electronic-health* (*eHealth*) and *mobile-health* (*mHealth*), many new applications of both organ and cellular diagnostics are now possible. Today, in the era of digitalization, we prefer to speak specifically about the prospects of *digital radiology* and *digital pathology*.

The first one includes the use of diagnostic imaging tools for organs and/or body functions based on systems compatible with *Digital Imaging and COmmunications in Medicine* (DICOM), or as it is commonly said, *DICOM-compliant*. In particular, *digital radiology* (DR) includes not only those instruments whose image formation processes are based on the interaction fields that use ionizing radiation, but also instruments of different types such as, for example, those instruments based on ultrasound (ultrasound) or magnetic fields [1,2] (nuclear magnetic resonance).

The second one, *digital pathology* (DP) includes the use of digital processes related to instrumentation for cellular diagnostics, mainly (but not only) in two forms: histological and cytological [3,4]. We can also speak of *digital histology* and *digital cytology* as the two major components of the DP, however, the DP also includes other processes for digitizing information in a biomedical laboratory such as by way of non-exhaustive example such as those relating to the integration of cytometric reports.

#### **2. General Actual Developments of** *Digital Radiology***,** *Digital Pathology***, and the Artificial Intelligence**

Of course, a detailed analysis of the perspectives of the DR and the DP would deserve two separate treatments. However, in light of the objective of this contribution, brief considerations of a fundamental nature are reported. In recent years, the DR has opened up both to new forms of construction and/or reconstruction applications of artificial reality and artificial intelligence (also related).

As far as artificial reality is concerned, we are seeing more and more applications of augmented and/or virtual reality. For example, in [5,6], they are some available ones that use the DICOM file from computed tomography) and/or magnetic resonance imaging to return to the surgeon on support augmented reality viewers during an operation (as for a fighter pilot), for example, the exact placement of blood vessels or a nerve. Virtual reality applications in the so-called virtual colonoscopy or in all those endo-cavitary diagnostic applications, where it is possible to create a real virtual journey (thanks to the processing of *voxels* starting from the file saved in DICOM), are now routine. This possibility of processing *voxels* to create environments of artificial reality also finds wide application today in the two sectors of three-dimensional reconstruction (3D) and simulation and training in surgery. In fact, by processing the *voxels*, it is possible to transform the DICOM file into a file of the standard format for the 3D printing called stereolithography (STL) and to print models of organs and tissues (e.g., bones). For example, it is now routine to print skeletal parts to design replacement bioengineering parts. An example of such applications can be found

**Citation:** Giansanti, D. The Artificial Intelligence in Digital Pathology and Digital Radiology: Where Are We? *Healthcare* **2021**, *9*, 30. https:// doi.org/10.3390/healthcare9010030

Received: 25 December 2020 Accepted: 28 December 2020 Published: 31 December 2020

**Publisher's Note:** MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations.

**Copyright:** © 2020 by the author. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https:// creativecommons.org/licenses/by/ 4.0/).

in the treatment of pelvic fractures caused by osteoporosis or bone cancer: the 3D model of the pelvis is printed and then bioengineering grafts are designed with biomaterials on the same model. As for simulation and training in surgery, it is now possible to use technologies for augmented and virtual reality combined with systems for restoring the perception of force, called force-feedback. Therefore, the system will give a perception of force-feedback associated, for example, with the liver to the surgeon who trains in liver surgery. Furthermore, *Artificial Intelligence* (AI) is bursting into the world of the DR and is affecting many scholars both in the world of technologies and bioethics. These scholars are interested both in the potential of feature recognition, automatic recognition, and quality control, but also in the limitations and related problems and the new applications in the fields described above and the related research activities [7–9]. Surely, the evolutions of digitalization processes in the world of the DP [3,4] are taking place at a slower rate than in the world of DR, especially because the DP has not adapted to the DICOM standard (DICOM WSI in this case) with the same readiness as the DR. However, it has been shown how digitization processes in this area [4–6] can favor the decision processes and the training, which uses a very strong component of *mHealth* in environments where training is based on smartphone viewers to which the image is sent from a centralized digital microscope. Furthermore, artificial reality can certainly be of support by providing tools to navigate around cellular and/or tissue elements. Furthermore, the AI, as discussed for the DR, is breaking into the world of the DP, and also in this case affecting many scholars both in the world of innovative technologies [10] and bioethics.

#### **3. What Future Awaits Us for Artificial Intelligence in Digital Radiology and Digital Pathology?**

Recent advances in AI have led to the conclusion that artificial intelligence could be very useful in DR very soon in routine applications [7]. Researchers have developed *deep learning neural networks* that can identify pathologies in radiological images such as bone fractures and potentially cancerous lesions [8,9]. The *deep learning* is advancing rapidly, and is a much better technology than previous approaches to medical imaging, however, the best systems currently live up to human performance and are used only in research environments. Radiological practice would certainly benefit from systems capable of rapidly reading and interpreting multiple images because the number of images has increased much faster in the last decade than the number of radiologists. It is evident that in DR, the amount of work is very high, so every solution able to reduce it could be welcome, decreasing the costs and improving the process. Like other AI systems, systems used in radiology perform individual tasks and are trained and used for specific image recognition tasks. However, thousands of activities are needed to fully identify all potential outcomes in medical images, and only some of these can be performed by the AI today. In addition, image interpretation work includes only a few of the tasks performed by radiologists. They also consult with other doctors for diagnosis and treatment, treat diseases, perform image-guided medical interventions, tailor the exam on the patient's needs, discuss outcomes, activities, and procedures with patients and many other activities. *Therefore, in DR it is important to understand what the role of AI is and the help it can provide us.* Scientists in DP benefit from combining histopathological data obtained, analyzed, and shared with other sources of clinical data such as that obtained from *omics, historical clinical data*, and *demographic data*. However, it is difficult to integrate the data collected in different formats that do not combine in a useful way [3,4]. For example, medical records are mostly kept in an unstructured text format. AI is helping to integrate information from these multiple sources [5,6,10]. Natural language processing, a branch of AI, is being used, for example, to extract pertinent details from written notes from the entire slide representation. Methodologies of AI are being developed to help integrate data from all sources, not just imaging. In addition, AI is being used to help decrease the errors that are made in diagnostic pathology. Before the birth of DP, the diagnosis from tissue samples always rested on the competence of medical professionals. AI can try to reduce the error rate in the diagnostic processes.

#### **4. What Are the Aspects to Be Explored and to Deepen?**

It is clear that AI, albeit with a different speed, is making a major breakthrough in both DR and DP.

In both sectors:

This incredible development involves many scholars both from the world of technologies and bioethics. These scholars are interested in both the potential in applications of AI in feature recognition, diagnostics, automatic recognition, integration in the new processes including the quality control, but also to the limits and the related problems. It is important to face and contribute to this, which has a broad spectrum ranging from the continuous innovation aspects including the recent ones correlated to the Covid-19 pandemic up to the problem of the last "yard" of the AI, depending on the acceptance of all actors from the health operators up to the patients.

**Conflicts of Interest:** The authors declare no conflict of interest.

#### **References**


**Coding, Modulation, and Detection for Power-Efficient Low-Complexity Receivers in Impulse-Radio Ultra-Wideband Transmission Systems**

Andreas Schenk and Robert F.H. Fischer

Additional information is available at the end of the chapter

http://dx.doi.org/10.5772/53261


**3.1 Cognitive development**

Adolescence is a sensitive and critical period for both normal and maladaptive patterns of development. This period was formerly described as the time of transition from concrete operational thinking to formal logical (abstract) thinking, including development in reasoning and judgment.

New perspectives emphasize that adolescent thinking is a function of social, emotional, and cognitive processes (Steinberg, 2005). There is growing evidence that the brain continues to mature throughout adolescence and into early adulthood (Gogtay et al., 2004). During this period, brain, behavioral, and cognitive development systems mature at different rates, causing adolescence to be a period of increased vulnerability and adjustment.

Two issues are especially relevant to understanding adolescent psychological development. First, brain development in this period is mostly in regions that have an important role in regulation of behavior and emotion and to the perception and evaluation of risk and reward. Significant changes include myelination and synaptic pruning, which increase the efficiency of information processing and enhance transmission of brain messages (Paus, 2005). Areas associated with more basic functions, including the motor and sensory areas,

Reproductive health also varies across regions. Adolescent females are less likely to use contraceptives than adult women, and adolescent mothers are more at risk of developing complications related to pregnancy than adult mothers (Nugent, 2005). An adolescent mother is also more likely to drop out of school and be less educated than an adolescent female who has not become pregnant. Marital age has increased in many parts of the world, yet in some regions, child marriage (marriage by 18 years) continues to occur and is largely driven by 'poverty, parental concerns about premarital sex and pregnancy, and other

Because of these differences, a pediatrician's approach to the psychosocial history of an adolescent needs to be tailored to meet the needs of different regions/countries. Although we recognize each country, and sometimes different parts within the same country, may have their own unique issues, it is impossible to address matters of every single country. For this reason, in this chapter, we have decided to focus on some regions of the world and give an example of one country per region, though keeping in mind that this may not apply to

Many changes occur during adolescence, the most obvious being the physical ones. Pediatric and other medical references tend to focus on these physical changes, and this information is readily available. For this reason, the physical changes that occur during puberty and adolescence will not be discussed here. Rather, the focus will be on the other developmental changes that occur: the cognitive and emotional changes. These develop more insidiously and health care providers may be less familiar with them. In addition, healthcare providers may be deceived by the physical appearances of adolescents which are

Adolescence is a sensitive and critical period for both normal and maladaptive patterns of development. This period was formerly described as the time of transition from concrete operational thinking to formal logical (abstract) thinking, including development in

New perspectives emphasize that adolescent thinking is a function of social, emotional, and cognitive processes (Steinberg, 2005). There is growing evidence that the brain continues to mature throughout adolescence and into early adulthood (Gogtay et al., 2004). During this period, brain, behavioral, and cognitive development systems mature at different rates,

Two issues are especially relevant to understanding adolescent psychological development. First, brain development in this period is mostly in regions that have an important role in regulation of behavior and emotion and to the perception and evaluation of risk and reward. Significant changes include myelination and synaptic pruning, which increase the efficiency of information processing and enhance transmission of brain messages (Paus, 2005). Areas associated with more basic functions, including the motor and sensory areas,

economic and cultural reasons' (Nugent, 2005).

every single country within the same region.

**3.1 Cognitive development**

reasoning and judgment.

**3. Developmental changes that occur during adolescence**

not necessarily proportionate to their cognitive and/or emotional development.

causing adolescence to be a period of increased vulnerability and adjustment.

mature in the early teen years, while the prefrontal cortex, the reasoning area of the brain and an important area for controlling impulses, emotions and executive functioning, appears to reach adult dimension in the early 20s, with girls developing earlier than boys (Geidd et al., 1999; Gogtay et al., 2004; Luna et al., 2010). Executive functions include the ability to inhibit impulses, weigh consequences of decisions, prioritize, strategize, long-term planning, decision-making, self-evaluation, self-regulation, and the coordination of affect and cognition. Second, changes in arousal and motivation brought on by pubertal maturation precede the development of regulatory competence (Blakemore et al., 2010). The brain's reward center, the ventral striatum, also is more active during adolescence than in adulthood.

This creates a gap between the adolescent's affective experience and the ability to regulate arousal and motivation. While the adolescent brain continues to strengthen its connections between reasoning and emotion related regions, each adolescent progresses at varying rates in developing their ability to think and their own view of the world.

Adolescent thinking becomes more multidimensional and they are better to contemplate hypothetical situations and the relationship between varied actions or decisions and outcomes, but decision-making remains susceptible to emotions.

Adolescent cognitive development can be characterized into 3 stages: early, middle, and late (Cromer, 2011; Radzik et al., 2007).

In early adolescence, the use of formal logical operations is mainly focused on schoolwork and in home environments. This includes questioning authority and societal standards. There is development of enhanced ability to verbalize thoughts and views, starting with those related to their life. These include choices regarding engaging in sports, peer groups, dress, and parental rules that adolescents think should be changed. At this stage, they may be unable to perceive long-term outcomes of current decision-making.

In middle adolescence, more complex thinking processes are used. The focus expands to include more philosophical and futuristic concerns. Middle adolescents tend to question and analyze more extensively in order to form their own code of ethics, identity, and possible future goals, which may begin to influence relationships with others. They may perceive future implications, but may not apply it in decision-making.

In late adolescence, complex thinking processes are used to focus on less self-centered concepts as well as personal decision-making. Adolescents may think about more global concepts such as justice, history, politics, and patriotism. They develop idealistic views on specific topics or concerns and may debate and develop intolerance of opposing views. They tend to focus on making career decisions and think about their emerging role in society. At this stage, they are able to think things through independently and weigh consequences before making decisions. Table 1 summarizes the cognitive changes that occur during adolescence.

Understanding cognitive development during this period is helpful in understanding age differences in judgment and decision-making, risk-taking, sensation-seeking, and also why adolescence can be a time of increased risk for the onset of a wide range of emotional and behavioral problems, including depression, violent delinquency, and substance abuse.

Adolescent Psychosocial Developmentand Evaluation: Global Perspectives 185

Adolescence has been quaintly described as "that awkward period between sexual maturation and the attainment of adult roles and responsibilities"(Dahl, 2004). It is a time of great change with concurrent but asynchronous physical, cognitive, and emotional development. Although most adolescents progress through this phase unscathed with gradual, appropriate changes, some may experience significant challenges. Adolescents experience many changes in how they interact with their family, peers, society, and themselves (Choudhoury et al., 2006). They move from an idealistic opinion of parents during childhood, into increased conformity to peer group expectations and values, to the development of their own personal values and principles as they progress through early, middle, and late adolescence (B. Newman & P. Newman, 1999). This movement mirrors a shift in emotional support from family to peers and then to self and intimate partners. This is not to say there is or should be separation from the family, as healthy emotional development is highly dependent on continued positive interaction with parents throughout (Larson & Brown, 2007). However, there is gradual change until parents and the adolescent or young adult accept their individual roles and are able to share and challenge each others'

As previously mentioned, emotional and cognitive development are inextricably linked as brain development progresses throughout adolescence into early adulthood. Cognition has a significant impact on expression of emotions, and conversely emotion and situational contexts have a significant impact on adolescents' behavioral choices (Steinberg, 2005). Emotional development during adolescence involves learning to recognize and master the control of emotions experienced so as to facilitate functioning within expected societal norms. Emotions serve many important functions including motivating positive behavior, achieving goals, providing information about self, and facilitating relationships, including intimacy (Larson & Brown, 2007). It involves self-discovery and self-characterization to acquire a specific role in society which is facilitated by the enhanced abstract thought acquired during adolescence. There is evidence to support an association between cognitive maturation and increased regulation of emotional behavior; however it has been proposed that these changes are non-linear unlike development during childhood and adulthood (Casey et al., 2010). The subcortical limbic system -including the amygdala is important in the processing of emotions and emotional responses to social stimuli, whereas the prefrontal cortex is responsible for the cognitive control or regulation of emotional behavior. An "Imbalance Model" has been put forward that proposes that an imbalance between the development of these two systems may be related to the development of psychopathology (Casey et al., 2010). Sensitivity to rewards seems to peak in adolescence and may have a positive impact, such as academic or athletic achievements or negative influence with thrill seeking through use of substances or other high-risk behaviors. This incentive response suggests behaviors may be defined from a motivational perspective, and the dorsal and ventral striata which receive input from the cerebral cortex have been found to be involved in these responses (Somerville & Casey, 2010). There is also a significant association between the pubertal stage of maturation and affective measures including sensation-seeking, sex and sexual arousal, emotional sensitivity, and sleep, with sensation-seeking peaking in

**3.2 Emotional development**

personal views and beliefs in a healthy way.

middle adolescence (Steinberg, 2005).

Table 1. Cognitive and emotional developmental changes that occur during adolescence

#### **3.2 Emotional development**

184 Complementary Pediatrics

used

Emergence of formal logical operations

Focus on personal

decisions, demonstrated in schoolwork and

environments

May be unable to perceive long-term outcomes of current decision-

home

making

support

of same sex interaction

Increasing awareness of a wider range of emotions begins

Peers are an increasingly important source of

Increased closeness

Increased need for privacy with increased interest in personal physical appearance and body image

**Cognitive development**

**Emotional development** **Early adolescence Middle adolescence Late adolescence**

Complex thinking processes used

Focus on less selfcentered concepts as well as personal decision-making

Able to think things

independently and weigh consequences before making decisions

Adolescent – parent communication improves

Increased autonomy from parents

Improved cognitive

emotional responses

control over

Increased confidence in personal beliefs and ability to express

them

through

Focus expands to include more philosophical and futuristic concerns

May perceive future implications of actions, but may not apply it in decision-

Increased conflict with parents as peer group interest peaks

Increased experience of a wide range of

Cognitive control over emotional responses limited

Sensation seeking at its peak with

increased risk taking

Increased sexual arousal with increased sexual activity and experimentation

behavior

Table 1. Cognitive and emotional developmental changes that occur during adolescence

making

emotions

More complex thinking processes

Adolescence has been quaintly described as "that awkward period between sexual maturation and the attainment of adult roles and responsibilities"(Dahl, 2004). It is a time of great change with concurrent but asynchronous physical, cognitive, and emotional development. Although most adolescents progress through this phase unscathed with gradual, appropriate changes, some may experience significant challenges. Adolescents experience many changes in how they interact with their family, peers, society, and themselves (Choudhoury et al., 2006). They move from an idealistic opinion of parents during childhood, into increased conformity to peer group expectations and values, to the development of their own personal values and principles as they progress through early, middle, and late adolescence (B. Newman & P. Newman, 1999). This movement mirrors a shift in emotional support from family to peers and then to self and intimate partners. This is not to say there is or should be separation from the family, as healthy emotional development is highly dependent on continued positive interaction with parents throughout (Larson & Brown, 2007). However, there is gradual change until parents and the adolescent or young adult accept their individual roles and are able to share and challenge each others' personal views and beliefs in a healthy way.

As previously mentioned, emotional and cognitive development are inextricably linked as brain development progresses throughout adolescence into early adulthood. Cognition has a significant impact on expression of emotions, and conversely emotion and situational contexts have a significant impact on adolescents' behavioral choices (Steinberg, 2005). Emotional development during adolescence involves learning to recognize and master the control of emotions experienced so as to facilitate functioning within expected societal norms. Emotions serve many important functions including motivating positive behavior, achieving goals, providing information about self, and facilitating relationships, including intimacy (Larson & Brown, 2007). It involves self-discovery and self-characterization to acquire a specific role in society which is facilitated by the enhanced abstract thought acquired during adolescence. There is evidence to support an association between cognitive maturation and increased regulation of emotional behavior; however it has been proposed that these changes are non-linear unlike development during childhood and adulthood (Casey et al., 2010). The subcortical limbic system -including the amygdala is important in the processing of emotions and emotional responses to social stimuli, whereas the prefrontal cortex is responsible for the cognitive control or regulation of emotional behavior. An "Imbalance Model" has been put forward that proposes that an imbalance between the development of these two systems may be related to the development of psychopathology (Casey et al., 2010). Sensitivity to rewards seems to peak in adolescence and may have a positive impact, such as academic or athletic achievements or negative influence with thrill seeking through use of substances or other high-risk behaviors. This incentive response suggests behaviors may be defined from a motivational perspective, and the dorsal and ventral striata which receive input from the cerebral cortex have been found to be involved in these responses (Somerville & Casey, 2010). There is also a significant association between the pubertal stage of maturation and affective measures including sensation-seeking, sex and sexual arousal, emotional sensitivity, and sleep, with sensation-seeking peaking in middle adolescence (Steinberg, 2005).

Adolescent Psychosocial Developmentand Evaluation: Global Perspectives 187

Within all this diversity is a need to discuss basic psychosocial issues with children,

• *Home*: The vast majority of North American adolescents live with at least one parent. Careful questioning will elicit the family constellation, which may include grandparents, step-parents, siblings and step-siblings, and unrelated friends. Some young people may see a pet as being a member of the family. Questions must be asked in a way that allows for the teen to disclose that they are homeless, have difficult relationships, or have a non-traditional family, such as one with two fathers or two

• *Education*: Throughout North America, there is mandatory schooling, usually until age 16. Most young people continue through secondary education, which is usually grade 12 or age 18. Urban areas, particularly in the United States, have high rates of students who do not complete high school. If one asks a young person what their school performance is like, they all know that the correct answer is "fine" or "OK". Specific questions about marks, the level of the courses they are taking (with much variation in terms of level of

schooling offered), how much school they miss, and career goals are all important. • *Eating*: Eating disorders are prevalent in North America, resulting in young people being both underweight and overweight. The current focus in schools and health systems on obesity focuses on the importance of being thin, which may be a trigger for anorexia nervosa or bulimia. More and more, eating disorders are being diagnosed in pre-adolescents, often associated with significant anxiety or anxiety disorders. Poverty is strongly associated with childhood obesity, with less nutritious foods being available

and limited opportunities for safe exercise for those living in inner cities.

for boys and girls within a family.

• *Activities*: Some North American adolescents are extremely active as athletes, volunteers, or workers. Working more than 16 hours a week often interferes with scholastic achievement. Some places require volunteer work for students to graduate from high school. Direct questions about screen time are essential, with many young people spending 5 or more hours a day in front of a computer or TV screen. Many are unaware of the dangers of revealing personal information on the internet to a legion of "friends" they have never met. Peer relationships should also be addressed, including questions about how the young person spends their lunchtime, if they see their friends outside of school, whether their parents allow them to have friends outside their religious or cultural group, and if there are discrepancies in the rules about friendship

• *Adherence*: Chronic health conditions are not uncommon in North America, with adolescents surviving with conditions that were previously fatal. Adolescents have many reasons for not taking medications—their family might not be able to afford them, they may see them as a sign that they are different from their friends, a chaotic household does not lend itself to the organization needed to be adherent, and mental health issues can interfere with the ability to regularly take medication. Medications that affect physical appearance, such as steroids, can be quite problematic for young people. Questions need to be asked in a sensitive manner without making assumptions

about adherence and the importance placed on medications within a family. • *Drugs*: Most drugs are readily available to North American youth. Alcohol is the most common substance used by youth, followed by marijuana and tobacco. Young people may respond well to being asked about drugs in their environment first, such as asking, "At your school, do students tend to drink more or take drugs?" You can then go on to

adolescents, and youth. The original HEADS acronym now has many variations.

mothers.

High intensity emotions may also have a significant impact on adolescents' thought processes and by extension to their behavioral choices – these have been referred to as 'hot' and 'cold' cognitions (Dahl, 2004; Somerville & Casey, 2010). 'Hot cognitions' refer to thinking amidst high intensity emotions and often result in poor decision-making. 'Cold cognitions' refer to thoughts in a state of calm, more commonly resulting in appropriate decision-making. This may explain why the adolescent who is usually even-keeled may, under certain 'hot' circumstances, make an otherwise unexpected poor decision.

Healthy emotional development is a key developmental task for adolescents who are learning to negotiate increasingly complex and ambiguous social interactions and utilize lessons learned from previous experiences to assist in determining future choices. Discordance during this time of development may serve as the root of psychopathology. Adolescents who fail to learn how to modify their own emotions may become impulsive with progression to delinquent behavior or may become alienated both from peers and family, leading to parental conflict, relationship challenges, and an increased risk of depression, substance abuse, and suicide risk.


**3.4 Device fabrication of 2D-perovskite films**

The finite preparation methods of 2D-perovskite films are different from the multiple preparation methods of 3D-perovskite films. *One-step spin-coating methods* are the most used to prepare 2D-perovskite films [75]. In this method, organics and metal halides are dissolved in solvents, e.g., DMF or (DMSO/GBL(1/1)) on substrates. By adjusting the ratio of the precursors, the dimension of perovskite is changed. 2D-perovskite films in both n-i-p and p-i-n structures are fabricated using one-step spin-coating methods as (PEA)2(MA)n − 1PbnI3n + 1, (BA)2(MA)n − 1PbnI3n + 1 and (PEI)2(MA)n − 1PbnI3n + 1 [65, 76, 77]. The *fast deposition-crystallization procedure* was also introduced to fabricate 2D-perovskite by dropping antisolvent, e.g., chlorobenzene, during the spin-coating process. It is shown, homogeneous nuclei are formed immediately and grow up slowly. Finally, dense and uniform films are obtained without oversize grains that may destroy the morphology [78]. The preferred *hot-cast method* was introduced for (BA)2(MA)3Pb4I13 films on PEDOT:PSS substrate [66]. The FTO/PEDOT:PSS substrate was heated before the precursor solution was spin-coated on it. **Figure 8** shows the photograph of (BA)2(MA)3Pb4I13 films that were prepared on substrates with different hot-cast temperatures from room temperature (R.T.) to 150°C. The films became dark and shiny with lower

#### **Figure 8.**

*(a) The (BA)2(MA)3Pb4I13 films cast from room temperature (R.T.) to 150°C, (b) GIXRD spectra, (c, d) AFM images, and (e, f) SEM images of films prepared by traditional room-temperature-cast method. Reprinted with permission from Ref. [66].*

pinhole density with rising temperature, resulting in high-efficiency devices. The inorganic layers in 2D-perovskite films prepared by the hot-cast method have a preferential orientation vertical to the substrate with excellent crystallinity and few carrier traps, which favors the charge transport.

*Another solution vapor annealing method* was used to prepare high-quality (PEA)2PbBr4 nanosheets at room temperature as an emitting layer for LEDs [79]. Using a precursor solution of DMF comprising PEABr and PbBr2 (2/1) was spincoated on the top of the ITO/PEDOT:PSS substrate and the productive sample was placed face down on the edge of a glass dish without contacting it. In the following step, the dish was transferred into a lidded beaker filled with DMF to form a closed space with DMF vapor at 30°C for several minutes before the DMF vapor diffused under the (PEA)2PbI4 film and contacted with it. The film was removed out into open air rapidly and heated at 100°C for 10 min while turning into purple. By using DMF vapor annealing, the small and compact (PEA)2PbI4 perovskite grains was recrystallized into sized nanosheets equally distributed on the substrate, which has larger grain size, higher crystallinity, and higher P.L. intensity (higher photoluminescence quantum yield (PLQY) due to the quantum confinement), comparing with unprocessed films. The nanosheet-LEDs showed a longer P.L. lifetime (much longer than the 3D-perovskite MAPbI3). They exhibited a small leak of current and low turn-on voltage, the external quantum efficiency (EQE) was 20 times higher than poly-LEDs.

*Sequential deposition method* The sequential deposition is used to prepare a sequential dipping process and sequential spin-coating of 2D-perovskite films [80]. The dipping process was used to fabricate quasi-2D and quasi 3D-perovskite films with spin-coating (IC2H4NH3)2PbI4 layers on mp-TiO2 substrates [81]. It is observed, immersing the films into MAI solution with a specific concentration for different times (1–5 min), transferring the films into cleaning fluid (2 mL isopropanol mixed with 10 mL methylbenzene) to remove the MAI residual. With increasing dipping time, MA+ cations in solution passed through (IC2H4NH3)2PbI4 films and increased inorganic PbI4 layers' thickness. Then, the nanoparticles regularly grew up and interconnected with each other in film morphology (uniform films without

**173**

*Mixed 2D-3D Halide Perovskite Solar Cells DOI: http://dx.doi.org/10.5772/intechopen.97684*

formed, with migrating PEA<sup>+</sup>

**3.5 Layer orientation**

residuals), leading to sharper diffraction peaks. In the previous studies, ITO/NiOx/ mixed-dimensional perovskite/PCBM/bis-C60/Ag devices were prepared using the sequential spin-coating method with mixed-cations perovskite FAxPEA1 − xPbI3 as the active layer [81]. With observing, a PbI2 layer was spin-coated on NiOx substrate, followed by the PEAxFA1 − xI solution loaded on it for 15 s before spin-coating. After thermal treatment, the mixed-cations FAxPEA1 − xPbI3 perovskite films were

3D-perovskite FAPbI3 to form quasi 3D- rather than quasi 2D-perovskite at room temperature. This self-assembly organic shell could prevent perovskite crystals from ambient moisture and passivated the surface defects to enhance the device performance and quasi 3D-perovskite's stability (the transition energy transformed from black phase to yellow phase). In summary, the 2D-perovskite films were commonly fabricated using one-step spin-coating method (simple process and low cost), with small-n members contrary to their 3D-counterparts but increasing "n" showed pre- or post-treatment is necessary such as hot-cast, antisolvent or solution vapor annealing processes for better crystallization. On the other hand, sequential deposition was used for obtaining efficient charge collection and extraction, dense and uniform films (due to the superior PbI2 framework for crystal growth). In sequential spin-coating, the large cations were not likely to enter into the lattice but pack on the surface of 3D-perovskite grains, forming a quasi 3D-structure. For future large-scale fabrication, the solution process was not enough for high-quality. Still, doctor blading, pressure-processing method, and so on were more appropriate as long as high-quality crystal is needed [82]. Melt processing is another innovative technique with an excellent quality. It was implemented in 2017 to fabricate lead iodide based 2D-perovskites using PEA derivatives [83]. Although it had not been used for device fabrication yet, however it is a promising one that it exhibits high phase purity, crystallinity, and potential crystal orientation control under ambient

air, but its disadvantage is the used toxic solvents in processing.

The device performance has been enhanced using the vertical alignment of the inorganic sheets of the 2D-perovskites concerning the substrate. The vertically oriented inorganic slabs provided a direct pathway for charge transport between layers, whereas the bulky organic separators act as electrical insulators hindering out-of-plane conduction of charges [63]. 2D single-layered (n = 1) halide perovskites have shown to align horizontally to the substrate on which they were grown. When "n" was greater than 1, competition arose between horizontal and vertical to the perovskite layers alignment (caused by BA and MA cations). When n = 1–4, it was found that the devices with n ≥ 3 had a better performance than lower "n", as shown in previous studies [84, 85]. It showed that for BA2MA3Pb4I13, the nucleation process and film growth orientation occurred at the liquid-air interface rather than at the liquid–liquid or liquid–substrate interfaces (since surface tension made nucleation and growth at the liquid-air interface more favorable) and that the initial nuclei are oriented in vertical configuration [86]. With increasing "n", the probability of obtaining an n-homogeneous-film decreased, giving rise to a mixture of a 3D-like dominant phase with some 2D-perovskite phases. Finally, films with n = 5–10 tend to align perpendicular to the substrate **(Figure 9**) [87]. This crystal orientation was examined using a scanning electron microscope (SEM), X-ray diffraction (XRD), and grazing incidence wide-angle X-ray scattering (GIWAXS) tests. XRD spectra of (BA)2(MA)n − 1PbnI3n + 1 (n = 1, 2, 3, 4, ∞), with (n = 1) showed (00 k) peaks implying the preferential growth along (110) direction, in (n = 2), (0 k0) reflections occurred in addition to (111) and (222) in

cations to lattice surfaces and grain boundaries of