**1.3.2 Intestinal parasites**

340 Type 1 Diabetes – Complications, Pathogenesis, and Alternative Treatments

A Norwegian study shows that children receive from 9% to 24% of their energy from added sugar in the diet, where a major part comes from soft drinks (Øverby et al., 2004). Despite the fact that the increase in intake of simple sugar (in the form of sweets and drinks) in ecological studies correlate with increasing incidence of T1D, only a couple of studies have attempted to investigate this at the individual level. In one study an association between sugar intake and T1D incidence was not found (Dahlquist et al., 1990), but in two more recent studies a correlation was found (Pundziute-Lycka et al., 2004; Benson et al., 2008). Both studies used a case-control design which is likely to suffer from recall bias. Prospective studies with proper registration of dietary habits are therefore needed. The role of diet at

A few studies have observed an association between high birth weight and increased risk of T1D (Stene et al., 2001), although the relation is not very strong, but overweight and obesity are increasing. Gestational diabetes in the mother is a risk factor for a high birth weight and gestational diabetes has increased the last decades. Today a considerable proportion of pregnant women have gestational diabetes. Gestational diabetes may be a consequence of increased body weight in connection with the increased insulin resistance following pregnancies in general. Data from the MIDIA study indicate that both the mothers Body Mass Index (BMI) before getting pregnant as well as high weight gain during pregnancy increase the risk for autoimmunity at an early age for the offspring (Rasmussen et al., 2009). Obesity during childhood is emerging as a possible risk factor for T1D (EURODIAB, 2002; Pundziute-Lycka et al., 2004), but further studies are needed, including to find what particular aspects of body size/obesity (such as inflammatory cytokines or other markers) are most relevant in this relation. Since all the potential relations described above have very important public health implications, the different factors need to be investigated in larger

The hygiene hypothesis states that the lack of exposure to parasites, symbiotic organisms and infectious agents in early childhood increases the susceptibility to allergic and autoimmune diseases (Zazdanbakhsh et al., 2001). Since humans have evolved coexisting in a shared environment with microbial agents throughout much of our evolutionary history, these agents might be necessary for the development of a balanced and regulated immune system (Stoll, 1947). The decline in non-specific infectious and microbial exposure in many populations is thus proposed to be the cause of the concomitant increase in atopic disorder over the past few decades (Bachlin & Degremont, 1997), and this hypothesis has been

The hygiene hypothesis is supported by epidemiological studies that show higher prevalence of autoimmune diseases in North America and Europe compared to South America and Africa, higher incidence associated with increased material wealth and higher risk for autoimmune diseases for third world immigrants to the industrialized countries (Herrström et al., 2001). There are also many studies showing that some infections and microbial agents reduce the incidence of autoimmune diabetes in experimental animals

extended to autoimmune diseases such as T1D (Kyronseppa, 1993).

**1.3.1 The hygiene hypothesis and epidemiology**

different ages in a child's life may also be important.

**1.2.6 Sugar**

**1.2.7 Overweight**

well-designed prospective studies.

**1.3 The hygiene hypothesis**

Since immunomodulatory effects of parasites have been reported (Samulsson & Ludvigsson, 2003), and there is evidence that infections protect against the development of allergic disorders, parasites become obvious and major candidates for the hygiene hypothesis. In 1947 it was reported that 40-60% of European children were positive for helminths (Horman et al., 2004), while in recent years only 5-23% are found positive (Strachan, 1989; Jones et al., 2000; Yazdanbakhsh et al., 2002; Cooke, 2009; Bach, 2002; Honeyman, 2005; van der Werf et al., 2007; Gibbon et al., 1997; Parslow et al., 2001; Pundziute-Lycka et al., 2003; Round & Mazmanian, 2009). The most prevalent of the helminths is Enterobius Vermicularis (pinworm) which is usually asymptomatic and each bout is self-limiting since the worms cannot reproduce within the gut. Most common of the water borne parasites are Cryptosporium and Giardia. While the genus Giardia comprises six species, more than 20 variants of Cryptosporium are known (Nygard et al., 2003).


**5. Conclusions**

Humans are the only species that can think of a living ecosystem. However, as the soteriological perspective in the Christian tradition is anthropocentric and other-worldly in orientation and emphasizes only individual repentance, therein lies a theological limitation that prevents Christians from actively contemplating human responsibility for nature and matter. The theological perspective of deep incarnation standing from the dialogue with new materialists emphasizes that we must have a firm response-ability for the entire planet because of our unique response-ability to this world. We must begin to think of the ethics of the planet, recognizing that its agents are members of a collective solidarity for the sake of a planetary community, which is constantly in flux. It requires that we form solidarity with nonhuman beings in order to embody the possibility of the "reworlding" of planetary humanism. This will lead to a symbiotic response-ability more deeply rooted in the biblical-theological ground. In this sense, Christians must immediately stop reckless anthropocentric practices such as development for development, factory-style livestock, and the way of life of mass production and consumption. In addition, human-centered ways of living that treat nonhuman beings simply as means for the progress of human

civilization should be changed. The pollution of the air, water, and soil that kills other living beings is in fact driving us to death, as well as this Anthropocene civilization. It means that our world must immediately undergo 're-worlding' from our earthen foundations. Such a 're-worlding' could mean ecological salvation.

Therefore, if earth bodies are affirmed in their myriad forms of entanglement in the planet, sensitively utilizing their capacity for mutual interdependence, our homeostatic balance of well-being can resonate with other forms of beings on the earth. This asks us to change the meaning of responsibility a human individual subject must take into response-ability, which allows us to empathize with each other. As many thinkers have expressed recently, there would be no final solutions but only the ongoing practice of being open to each other, and taking the risk of being vulnerable, so that we might use our ability to respond, our responsibility, to help awaken and breathe life into our new possibilities for living justly. We only remember that God created human beings with the divine image but forget that the earth is co-creating plants and vegetables. That is, God has the earth as a co-creator of living beings on the earth. The co-creativity that is also endowed to humans with the divine image is not only for humans but for the sake of all beings. This is the reason we need to consider the way we live with animals, plants, vegetables, and things, natural and artificial. Humanism is still significant for human responsibility, given that human beings are always already intertwined with everything on "Earth Planet". I still wish to emphasize human responsibility as an ability to respond to all beings, for only humans can imagine the not-yet in order to change the world.

**Funding:** This research is supported by the Research Fund of the Presbyterian University and Theological Seminary, Seoul, 2022.

**Institutional Review Board Statement:** Not applicable.

**Informed Consent Statement:** Not applicable.

**Data Availability Statement:** Not applicable.

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


**1. Introduction**

Structural damage is a typical defect in metallic structures and components that are exposed to deformations during the manufacturing process. Such undesired physical discontinuities imply quality level affectation of the final products and even the posterior performances when subjected to complex and cyclic loadings during their service. Thus, in the last years, a more comprehensive attention has been taken to nondestructive testing (NDT) methods in order to inspect the internal characteristics of metallic components for looking for internal defects or discontinuities.

In this regard, the use of conventional Acoustic Emission (AE) transducers has the advantages of moderate cost and easy implementation, and it allows the generation of specific waveforms with a known pulse shape. Although these methods provide satisfactory results, AE transducers also show some drawbacks including the low output power, that prevents such systems from being used remotely, low frequency bandwidth range, that makes necessary the use of arrays or ultrasonic

scanners increasing the system overall cost, small surface area, that prevents covering large object areas at once, and low spatial resolution in the excited volume. Ultrasonic transducers use waves with central frequencies ranging from fractions to multiples of MHz. AE analysis commonly relies on either of two schemes, pulseecho mode or pitch-catch mode. Pulse-echo mode is more useful in applications where it is required to use only one sensor for the send/receive signals. This has some limitations on some data acquisition speed and sensor's sensitivity and size. It is also hard to recognize the location of the defects at an angle. Hence, the defect should be vertically aligned with the sensor in order to catch it. The pitch-catch mode offers more flexibility to work in both transmission and reflection modes where it is possible to more deeply investigate the ultrasonic-material interaction at different levels inside the material and extract more data concerning the defect by taking measurements at different angles. However, this technique is more expensive as it requires the use of many sensors, and the data processing is slower [1–3]. The frequency of the ultrasonic signal used affects the sensitivity and resolution of the measured defect dimensions. At higher frequencies, smaller defects can be detected more accurately. However, increasing the frequency has a negative impact on wave propagation inside the material. In other words, higher frequencies travel closer to the surface. So, the portion of the waves that penetrate to the depth of the material is reduced, thus leading to weaker possibilities to catch deeply embedded defects. Most of the available ultrasonic NDT instruments use these types of conventional AE transducers. Typically, they analyze the ultrasonic pulse's Time of Flight (TOF) through the material under test (from the transducer to the receiver) in order to identify discontinuities in the structure corresponding to potential defects.

As an alternative, photonic approaches based on laser-induced ultrasonic and optical detection showed up as valuable competitors to the conventional ultrasonic techniques in the NDT field. These techniques offer the possibility of remote transmission and detection at a much higher resolution [4, 5]. The energy carried by a laser pulse incident on an isotropic specimen is rapidly absorbed into a shallow volume of the material and creates a localized heating, which results in a thermoelastic expansion of the material, inducing a stress wave that generates an acoustic pulse [2]. Such thermoelastic effect plays an important role in ultrasonic wave generation when the power density of the pulsed laser is lower than the ablation threshold of material. Ultrasonic waves mainly include longitudinal waves, shear waves, surface acoustic waves, and Lamb waves. Optical systems based on the laser technology can be used as well for the detection of transmitted and/or reflected acoustic waves. Several methods are implemented for this purpose. The vibration created by the acoustic wave at the surface can be optically detected using several approaches. They include optical interference techniques where a laser beam, reflected by the object surface, interferes with a reference beam. The interference fringes provide information about the crack's position and size. A Mach-Zehnder interferometer is the simplest example for how interference fringes are generated. The holographic interferometry technique is most commonly used for crack localization and flaw size determination [6]. It can detect very small details of the object under test. The optical approaches have important advantages such as the remote noncontact application, remote control, and generation of broadband frequency waves from kHz to GHz, high output power and the possibility to easily scan a larger object area at once. As an example of this performance, the work presented by Zhao et al. used this method for fatigue and subsurface crack detection [7]. Also, Erdahl discussed a valuable example of this approach to inspect multi-layered ceramic capacitors [8]. The main drawbacks of optical detection methods are their critical stability and the need for an anti-vibration setup in order to obtain reliable results, which make them very expensive and hard to apply to certain related fields.

**97**

*Wavelet Transform Applied to Internal Defect Detection by Means of Laser Ultrasound*

cies at certain time instants in the ultrasonic signal life time.

Considering the nature of the acoustic emission waves generated by the laser excitation, the detection of the TOF represents a challenge that is being currently attended to by the scientific community [12]. Although some studies have exhibited the potential of the WT to analyze acoustic emission signals, the analysis and interpretation of the resulting time-frequency maps under a laser-ultrasonic scheme is still a challenge, mainly with respect to the determination of the TOF, where the error minimization is highly important. In fact, the error in determining the TOF, due to the presence of defects in the material under inspection, could become a challenge due to inconsistencies in the analysis. In this regard, the wavelet transform capabilities and some of the most recent variants exported from other fields of

On the other side, it is difficult to control the acoustic pulse shape as this mainly depends on the optical beam absorption properties at the material surface.

In this regard, a third approach represented by a hybrid scheme, composed by laser-ultrasonics, is considered a good trade-off in order to take advantage of both strategies, that is, the advantages of the optical system for generating artificial acoustic emission waves, as well as using a conventional ultrasonic transducer for detection. This significantly shows interesting results that overcome the drawback of the other schemes. Laser-ultrasonics offers an alternative to conventional ultrasonic techniques in the field of NDT evaluation. It allows inspection at a far distance from the object allowing the remote investigation of the test specimen without the need for a direct contact. Additionally, this technique features a broader frequency bandwidth compared with the limited bandwidth of the conventional ultrasonic transducers. Practically speaking, laser-ultrasonics covers the majority of the ultrasonic bandwidth which is important for various applications involving material characterization [2]. Indeed, the potential of this hybrid sensing scheme, combined with performative signal processing techniques, results in a promising field of study. Many researchers have made efforts to investigate the features of laser-generated acoustic waves and got substantial research achievements. For example, Zhang et al. studied empirical mode decomposition (EMD) to analyze the ultrasonic signals captured from an object that suffers from a certain defect which is followed by the Fourier transform of the selected intrinsic mode functions (IMFs) extracted from the EMD [9]. Also, Li et al. studied the laser-generated ultrasonic wave frequency characteristics in order to analyze crack effects and extract them from their generated frequency components [2]. Dixon et al. used pulsed laser-generated ultrasonics and EMAT for detecting the crack position using the B-scan study in time and frequency domains [10]. Lee discussed the ultrasonic flaw signal and technique to extract features using the fast Fourier transform and discrete wavelet transform [11]. All these studies conclude that broadband frequency components appear in the ultrasonic waves generated by the laser impulse. The Fourier Transform (FT) is the simplest and most straight forward topology for separating the frequency's components and studying their responses individually. However, it has some drawbacks since it does not allow the visualization of the temporal fingerprints of those individual frequencies. This makes it harder to figure out which frequency component corresponds to the defect. That necessitates the use of a stronger technique as the Wavelet Transform (WT) in order to analyze these frequency components and extract only those that correspond to the defect under investigation. Thus, the WT shows what frequencies are present and their impact on the time domain. Hence, it is possible to distinguish temporal and spectral behaviors, both at a time. This property helps to get more specific information about the TOF of possible reflected signals from the material with defects. Higher frequencies travel faster and closer to the surface of the object under test, compared with the lower frequencies. The wavelet technique helps to visualize the propagated frequen-

*DOI: http://dx.doi.org/10.5772/intechopen.84964*

### *Wavelet Transform Applied to Internal Defect Detection by Means of Laser Ultrasound DOI: http://dx.doi.org/10.5772/intechopen.84964*

On the other side, it is difficult to control the acoustic pulse shape as this mainly depends on the optical beam absorption properties at the material surface.

In this regard, a third approach represented by a hybrid scheme, composed by laser-ultrasonics, is considered a good trade-off in order to take advantage of both strategies, that is, the advantages of the optical system for generating artificial acoustic emission waves, as well as using a conventional ultrasonic transducer for detection. This significantly shows interesting results that overcome the drawback of the other schemes. Laser-ultrasonics offers an alternative to conventional ultrasonic techniques in the field of NDT evaluation. It allows inspection at a far distance from the object allowing the remote investigation of the test specimen without the need for a direct contact. Additionally, this technique features a broader frequency bandwidth compared with the limited bandwidth of the conventional ultrasonic transducers. Practically speaking, laser-ultrasonics covers the majority of the ultrasonic bandwidth which is important for various applications involving material characterization [2]. Indeed, the potential of this hybrid sensing scheme, combined with performative signal processing techniques, results in a promising field of study. Many researchers have made efforts to investigate the features of laser-generated acoustic waves and got substantial research achievements. For example, Zhang et al. studied empirical mode decomposition (EMD) to analyze the ultrasonic signals captured from an object that suffers from a certain defect which is followed by the Fourier transform of the selected intrinsic mode functions (IMFs) extracted from the EMD [9]. Also, Li et al. studied the laser-generated ultrasonic wave frequency characteristics in order to analyze crack effects and extract them from their generated frequency components [2]. Dixon et al. used pulsed laser-generated ultrasonics and EMAT for detecting the crack position using the B-scan study in time and frequency domains [10]. Lee discussed the ultrasonic flaw signal and technique to extract features using the fast Fourier transform and discrete wavelet transform [11]. All these studies conclude that broadband frequency components appear in the ultrasonic waves generated by the laser impulse. The Fourier Transform (FT) is the simplest and most straight forward topology for separating the frequency's components and studying their responses individually. However, it has some drawbacks since it does not allow the visualization of the temporal fingerprints of those individual frequencies. This makes it harder to figure out which frequency component corresponds to the defect. That necessitates the use of a stronger technique as the Wavelet Transform (WT) in order to analyze these frequency components and extract only those that correspond to the defect under investigation. Thus, the WT shows what frequencies are present and their impact on the time domain. Hence, it is possible to distinguish temporal and spectral behaviors, both at a time. This property helps to get more specific information about the TOF of possible reflected signals from the material with defects. Higher frequencies travel faster and closer to the surface of the object under test, compared with the lower frequencies. The wavelet technique helps to visualize the propagated frequencies at certain time instants in the ultrasonic signal life time.

Considering the nature of the acoustic emission waves generated by the laser excitation, the detection of the TOF represents a challenge that is being currently attended to by the scientific community [12]. Although some studies have exhibited the potential of the WT to analyze acoustic emission signals, the analysis and interpretation of the resulting time-frequency maps under a laser-ultrasonic scheme is still a challenge, mainly with respect to the determination of the TOF, where the error minimization is highly important. In fact, the error in determining the TOF, due to the presence of defects in the material under inspection, could become a challenge due to inconsistencies in the analysis. In this regard, the wavelet transform capabilities and some of the most recent variants exported from other fields of

*Wavelet Transform and Complexity*

scanners increasing the system overall cost, small surface area, that prevents covering large object areas at once, and low spatial resolution in the excited volume. Ultrasonic transducers use waves with central frequencies ranging from fractions to multiples of MHz. AE analysis commonly relies on either of two schemes, pulseecho mode or pitch-catch mode. Pulse-echo mode is more useful in applications where it is required to use only one sensor for the send/receive signals. This has some limitations on some data acquisition speed and sensor's sensitivity and size. It is also hard to recognize the location of the defects at an angle. Hence, the defect should be vertically aligned with the sensor in order to catch it. The pitch-catch mode offers more flexibility to work in both transmission and reflection modes where it is possible to more deeply investigate the ultrasonic-material interaction at different levels inside the material and extract more data concerning the defect by taking measurements at different angles. However, this technique is more expensive as it requires the use of many sensors, and the data processing is slower [1–3]. The frequency of the ultrasonic signal used affects the sensitivity and resolution of the measured defect dimensions. At higher frequencies, smaller defects can be detected more accurately. However, increasing the frequency has a negative impact on wave propagation inside the material. In other words, higher frequencies travel closer to the surface. So, the portion of the waves that penetrate to the depth of the material is reduced, thus leading to weaker possibilities to catch deeply embedded defects. Most of the available ultrasonic NDT instruments use these types of conventional AE transducers. Typically, they analyze the ultrasonic pulse's Time of Flight (TOF) through the material under test (from the transducer to the receiver) in order to identify discontinuities in the structure corresponding to potential defects.

As an alternative, photonic approaches based on laser-induced ultrasonic and optical detection showed up as valuable competitors to the conventional ultrasonic techniques in the NDT field. These techniques offer the possibility of remote transmission and detection at a much higher resolution [4, 5]. The energy carried by a laser pulse incident on an isotropic specimen is rapidly absorbed into a shallow volume of the material and creates a localized heating, which results in a thermoelastic expansion of the material, inducing a stress wave that generates an acoustic pulse [2]. Such thermoelastic effect plays an important role in ultrasonic wave generation when the power density of the pulsed laser is lower than the ablation threshold of material. Ultrasonic waves mainly include longitudinal waves, shear waves, surface acoustic waves, and Lamb waves. Optical systems based on the laser technology can be used as well for the detection of transmitted and/or reflected acoustic waves. Several methods are implemented for this purpose. The vibration created by the acoustic wave at the surface can be optically detected using several approaches. They include optical interference techniques where a laser beam, reflected by the object surface, interferes with a reference beam. The interference fringes provide information about the crack's position and size. A Mach-Zehnder interferometer is the simplest example for how interference fringes are generated. The holographic interferometry technique is most commonly used for crack localization and flaw size determination [6]. It can detect very small details of the object under test. The optical approaches have important advantages such as the remote noncontact application, remote control, and generation of broadband frequency waves from kHz to GHz, high output power and the possibility to easily scan a larger object area at once. As an example of this performance, the work presented by Zhao et al. used this method for fatigue and subsurface crack detection [7]. Also, Erdahl discussed a valuable example of this approach to inspect multi-layered ceramic capacitors [8]. The main drawbacks of optical detection methods are their critical stability and the need for an anti-vibration setup in order to obtain reliable results, which make them very expensive and hard to apply to certain related fields.

**96**

investigation, as the Synchrosqueezed Transform (ST), are considered. Thus, in this chapter, a defective metallic component for damage detection and visualization, through a laser-ultrasonic approach and detection of AE waves TOF, is studied. For this objective, the wavelet transform performance, as a time-frequency processing tool, and its results, are studied, compared with a promising variant called synchrosqueezed transform. This chapter is organized as follows: The theoretical basis and its suitability for the ultrasound processing of the wavelet transform and the synchrosqueezed transform are presented in Section 2. The materials and method, including the experimental setup, are explained in Section 3. The competency of the techniques and the experimental results are presented and discussed in Section 4. Finally, this chapter shows the conclusion dissemination in Section 5.


**4.2 Advance varietal trial-I (AVT-I)**

Based on superiority (5–10%) over the best performing check, superior entries will enter into the AVT-I from IVT. The number of tested entries in the AVT-I will be less than IVT. The plot size is large in AVT-I as compared to IVT, therefore data generated on yield and other ancillary traits will be more realistic, accurate and minimal chances of error. The number of testing locations should be more as compare to IVT in a given zone for more realistic data on yield and other economically important traits, varietal adaptation, biotic and abiotic tolerance, quality parameters, etc. National, zonal and local checks (which were used in IVT) shall be used for critical analysis along with the entries. During AVT-I, additional data on disease and or insect pest tolerance under artificial epiphytotic condition must be generated by the experts. Same as IVT, monitoring team would be deputed by the PC/PD at different growth stages of crop and observed data shall be submitted to the concerned PC/PD. Based on the performance of entry over the best performing check-in the respective zone, the superior entries would enter into the AVT-II.


Preface

Chapter 7 **An Introduction to Ensemble-Based Data Assimilation Method**

Youmin Tang, Zheqi Shen and Yanqiu Gao

Chapter 8 **Conditions for Optimality of Singular Controls in Dynamic**

Jenq-Lang Wu, Chee-Fai Yung and Tsu-Tian Lee

Chapter 9 **Simultaneous H ∞ Control for a Collection of Nonlinear Systems**

Lidia María Belmonte, Rafael Morales, Antonio Fernández-

Christos K. Volos, Hector E. Nistazakis, Ioannis M. Kyprianidis,

Chapter 12 **Synchronization Phenomena in Coupled Birkhoff-Shaw Chaotic**

**Systems Using Nonlinear Controllers 293**

Ioannis N. Stouboulos and George S. Tombras

Chapter 13 **Design of Dynamic Output Feedback Laws Based on Sums of**

Kenta Hoshino, Daisuke Sonoda and Jun Yoneyama

Chapter 14 **Could the Stock Return be a Leading Indicator of the Economic Growth in the Depression? Analysis Based on Nonlinear**

**Systems with Retarded Control 195** Misir J. Mardanov and Telman K. Melikov

**in the Earth Sciences 153**

**VI** Contents

**Section 2 Control and Applications of Nonlinear Dynamical Systems 193**

**in Strict-Feedback Form 227**

**Mechanical Systems 243** Le Anh Tuan and Soon-Geul Lee

**MIMO System 265**

Chapter 10 **Nonlinear Feedback Control of Underactuated**

Chapter 11 **Nonlinear Cascade-Based Control for a Twin Rotor**

Caballero and José Andrés Somolinos

**Squares of Polynomials 319**

**Dynamic Panel Model 337**

Lee Yuan-Ming and Wang Kuan-Min

This book is a research monograph to detail recent developments of nonlinear systems and control. The book selected a collection of nonlinear systems, which range from quantum me‐ chanics, chaotic systems to nonlinear dynamical systems such as unmanned vehicle plat‐ form and 3D crane system. More interestingly, the book covers not just scientific and engineering problems but also earth data assimilation and economic development model‐ ing, that is, from theories to applications in real-world issues. This book has a couple of ana‐ lytic tools for nonlinear control problems, such as feedback linearization, partial differential equation, Frobenius theorem, Lyapunov theory and its exponents, Nikiforov-Uvarov meth‐ od, eigenvalue/eigenvector, pseudocomposition (predictor-corrector), or stochastic methods including Kalman filtering. Many practical systems or natural phenomena are nonlinear, so from a scientist or engineer's perspective, we interpret the system and represent the system using scientific approaches, including physics-based analysis and chemical or social analy‐ sis, where the tools are basically mathematics. Then, they interpret the system characteristics and try to represent the system using scientific approaches to get comprehensive results of such nonlinear or complex systems. If the scientific structure and analysis are sound, the system or phenomenon may have unique solutions, or it would not be a surprise if no solu‐ tion exists nor any tools or solutions. During the last couple of decades, serious efforts using estimation and many control systems with those analysis tools have helped to solve many complex nonlinear systems. Here we would like to narrow down the contents to some non‐ linear dynamical systems and their controls.

Solving nonlinear system is a daunting challenge, while analyzing nonlinear system is not easy because no universal solution is available, but the authors in this book have demon‐ strated what would be the system responses and behaviors in their fields, what would be the appropriate analysis tools, or how to get reasonable results in terms of convergence (re‐ gion of attraction)—those are the kinds of concerns they want to solve first. As the system goes more complicated or mixed, more analysis tools are needed to understand the system due to its mutual interaction or independent action. Furthermore, variables are getting big‐ ger, sophisticated, or specialized, and sometimes, only one of analytic tools is not sufficient to describe. Thanks to the development of hardware/software of electronics with faster com‐ puting technology, detailed analysis tools have been helping researchers or scientists to get more data or be able to solve higher-order, multidimensional, or more complex nonlinear control problems and real-world issues. Thus, nonlinear analysis tools, simulation, or exper‐ imental methods got to be advanced, extended to a wide and deep as well as quantitatively digitalized measurement system that helps to acquire more useful (visualized) data due to some phenomenal researchers. Hence, many nonlinear systems are resolved alongside the development of tools and control methods. On the other hand, linear system analysis and a set of tools such as linearization or partial differential equations are also used to analyze many nonlinear systems in a piecewise linear manner.

The book consists mainly of two parts as follows: the first section includes design, analysis, methods, and techniques of nonlinear system and the second section includes controls and applications of nonlinear systems. The following are brief outlines of each chapter.

In the first section, "Nonlinear Systems: Design, Analysis, and Estimation Methods," the au‐ thors in Chapter 1 present that quasilinearization technique can be simplified to partial dif‐ ferential equation (PDE) while decomposing time domain into smaller subintervals by applying spectral allocation method and extending up to boundaries with continuity condi‐ tion. In Chapter 2, the authors suggest an algorithm to find the change of coordinates and feedback for partial feedback linearization that are useful tools to convert nonlinear control system into partial linearization with feedback if the system has full rank and is involutive by Frobenius theorem. The authors in Chapter 3 investigate quantum characteristics of sin‐ gular potential of a particle using Nikiforov-Uvarov method and solved analytically the full wave functions with the evaluation of eigenfunctions with eigenvalues. Chapters 4 to 7 deal with estimation methods using Kalman filtering based on stochastic approach while solving nonlinear systems using iterative approach. The authors in Chapter 4 provide discrete-time nonlinear stochastic control problem solving iteratively using model-based optimal control by adding adjustable parameters to a continuous stirred-tank reactor model. In Chapter 5, the authors compare classical methods with multipoint iterative approaches such as compo‐ sition of known methods, weight function procedure, and pseudocomposition to solve non‐ linear systems. A couple of different iterative Kalman filtering algorithms with simulation examples is provided with two comparative studies in terms of state accuracies, estimation errors, and convergence where ISRCDKF provides the most improved state accuracies than the other techniques. A very thoughtful review of ensemble-based estimation methods is present in Chapter 7 where the authors provided many analyses, derivations, and discus‐ sions of Kalman filtering and particle filtering approaches. More importantly, the authors put more weights on those solutions to high dimensional systems in earth sciences where the novelty of this chapter lies in.

In the second section, "Control and Applications of Nonlinear Dynamical Systems," we have selected a couple of control approaches such as optimal, nonlinear, and output feed‐ back. These methods with analytic tools are applied to nonlinear dynamical systems to solve practical nonlinear control problems. In Chapter 8, the authors deal with optimal control problem with retarded control of singular situation in which they first optimize the condi‐ tions and obtain necessary conditions, design optimal solution, and then apply the control‐ ler to Legendre equation to demonstrate the results. The authors in Chapter 9 present simultaneous H-ꝏ control for nonlinear system under strict-feedback form, which is more challenging, but they used backstepping approach based on systematically control storage functions (CSF). Chapter 10 provides a control approach over three-dimensional overhead crane system using two separated subsystems, actuated and unactuated, in which the actu‐ ated subsystem is used to linearize nonlinear feedback states, whereas the unactuated sub‐ system is combined with the linear system. In Chapter 11, the authors develop dynamic model of twin-rotor helicopter, manufactured by Feedback Instruments Inc., which is a non‐ linear cascaded, coupled structure. They also developed its control algorithm, which carries out two electrical and mechanical parts and provided numerical results. In Chapter 12, the authors design a nonlinear controller to target antisynchronization/synchronization states

based on Birkhoff-Shaw nonautonomous chaotic coupled systems, and the stability of the systems is ensured by Lyapunov exponent theorem. With electronic circuit that models the coupling scheme, the authors are to verify the feasibility of their proposed design. Numeri‐ cal methods based on linear matrix inequalities (LMI) provide solutions to stabilization of nonlinear control problems in Chapter 13. With the design of output feedback laws based on the sum-of-squares (SoS) decomposition with state-dependent LMI, nonlinear polynomial systems can be stabilized via generalization as well as provide suitable analysis for stability through Lyapunov analysis. In the final chapter of this book, the authors try to analyze a practical nonlinear modeling problem. The authors examine thoroughly whether the stock return could be a leading indicator of economic growth in the depression period. In order to analyze nonlinear phenomena between economic development and stock return, a nonlin‐ ear dynamic data model is constructed with new current depth of recession indicator, espe‐ cially fluctuations of stock returns, which are highly correlated with economic activities. They propose that the stock return can considerably explain the economic growth in the re‐ cession period according to the country's development level and business cycle stages.

set of tools such as linearization or partial differential equations are also used to analyze

The book consists mainly of two parts as follows: the first section includes design, analysis, methods, and techniques of nonlinear system and the second section includes controls and

In the first section, "Nonlinear Systems: Design, Analysis, and Estimation Methods," the au‐ thors in Chapter 1 present that quasilinearization technique can be simplified to partial dif‐ ferential equation (PDE) while decomposing time domain into smaller subintervals by applying spectral allocation method and extending up to boundaries with continuity condi‐ tion. In Chapter 2, the authors suggest an algorithm to find the change of coordinates and feedback for partial feedback linearization that are useful tools to convert nonlinear control system into partial linearization with feedback if the system has full rank and is involutive by Frobenius theorem. The authors in Chapter 3 investigate quantum characteristics of sin‐ gular potential of a particle using Nikiforov-Uvarov method and solved analytically the full wave functions with the evaluation of eigenfunctions with eigenvalues. Chapters 4 to 7 deal with estimation methods using Kalman filtering based on stochastic approach while solving nonlinear systems using iterative approach. The authors in Chapter 4 provide discrete-time nonlinear stochastic control problem solving iteratively using model-based optimal control by adding adjustable parameters to a continuous stirred-tank reactor model. In Chapter 5, the authors compare classical methods with multipoint iterative approaches such as compo‐ sition of known methods, weight function procedure, and pseudocomposition to solve non‐ linear systems. A couple of different iterative Kalman filtering algorithms with simulation examples is provided with two comparative studies in terms of state accuracies, estimation errors, and convergence where ISRCDKF provides the most improved state accuracies than the other techniques. A very thoughtful review of ensemble-based estimation methods is present in Chapter 7 where the authors provided many analyses, derivations, and discus‐ sions of Kalman filtering and particle filtering approaches. More importantly, the authors put more weights on those solutions to high dimensional systems in earth sciences where

In the second section, "Control and Applications of Nonlinear Dynamical Systems," we have selected a couple of control approaches such as optimal, nonlinear, and output feed‐ back. These methods with analytic tools are applied to nonlinear dynamical systems to solve practical nonlinear control problems. In Chapter 8, the authors deal with optimal control problem with retarded control of singular situation in which they first optimize the condi‐ tions and obtain necessary conditions, design optimal solution, and then apply the control‐ ler to Legendre equation to demonstrate the results. The authors in Chapter 9 present simultaneous H-ꝏ control for nonlinear system under strict-feedback form, which is more challenging, but they used backstepping approach based on systematically control storage functions (CSF). Chapter 10 provides a control approach over three-dimensional overhead crane system using two separated subsystems, actuated and unactuated, in which the actu‐ ated subsystem is used to linearize nonlinear feedback states, whereas the unactuated sub‐ system is combined with the linear system. In Chapter 11, the authors develop dynamic model of twin-rotor helicopter, manufactured by Feedback Instruments Inc., which is a non‐ linear cascaded, coupled structure. They also developed its control algorithm, which carries out two electrical and mechanical parts and provided numerical results. In Chapter 12, the authors design a nonlinear controller to target antisynchronization/synchronization states

applications of nonlinear systems. The following are brief outlines of each chapter.

many nonlinear systems in a piecewise linear manner.

VIII Preface

the novelty of this chapter lies in.

Hence, this book is the culmination of their research and efforts. I hope it will be a good reference for the researchers and that it could provide good insights to obtain the solution for practical problems. Also it is an honor to edit these phenomenal papers. Special thanks go to InTechOpen for the opportunity and Edi Lipović, the Publishing Process Manager.

#### **Dongbin Lee, Ph.D.**

Assistant Professor/Director of Oregon Tech Robotics Lab, Adviser to Oregon Tech Unmanned Systems Club MMET Dept, Oregon Institute of Technology (Oregon Tech), Klamath Falls, Oregon, United States of America

**Nonlinear Systems: Design, Analysis, and Estimation Methods**

## **Solving Nonlinear Parabolic Partial Differential Equations Using Multidomain Bivariate Spectral Collocation Method Solving Nonlinear Parabolic Partial Differential Equations Using Multidomain Bivariate Spectral Collocation Method**

Motsa Sandile Sydney, Samuel Felix Mutua and Shateyi Stanford Shateyi Stanford

Motsa Sandile Sydney, Samuel Felix Mutua and

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

http://dx.doi.org/10.5772/64600

#### **Abstract**

In this study we introduce the multidomain bivariate spectral collocation method for solving nonlinear parabolic partial differential equations (PDEs) that are defined over large time intervals. The main idea is to reduce the size of the computational domain at each subinterval to ensure that very accurate results are obtained within shorter computational time when the spectral collocation method is applied. The proposed method is based on applying the quasi-linearization technique to simplify the nonlinear partial differential equation (PDE) first. The time domain is decomposed into smaller nonoverlapping subintervals. Discretization is then performed on both time and space variables using spectral collocation. The approximate solution of the PDE is obtained by solving the resulting linear matrix system at each subinterval independently. When the solution in the first subinterval has been computed, the continuity condition is used to obtain the initial guess in subsequent subintervals. The solutions at different subintervals are matched together along a common boundary. The examples chosen for numerical experimentation include the Burger's-Fisher equation, the Fitzhugh-Nagumo equation and the Burger's-Huxley equation. To demonstrate the accuracy and the effectiveness of the proposed method, the computational time and the error analysis of the chosen illustrative examples are presented in the tables.

**Keywords:** bivariate interpolation, spectral collocation, quasi-linearisation, multi-domain approach, non-linear evolution PDEs

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


**Blessings and Curses: Exploring the Experiences of New Mothers during the COVID-19 Pandemic**

**Phillip Joy 1,\*, Megan Aston 2, Sheri Price 2, Meaghan Sim 2, Rachel Ollivier 2, Britney Benoit 3, Neda Akbari-Nassaji 4 and Damilola Iduye 2**

Received: 25 November 2020; Accepted: 15 December 2020; Published: 21 December 2020

**Abstract:** The aim of this study was to explore the postpartum experiences of new parents during the COVID-19 pandemic. The postpartum period can be a time of significant transition, both positive and negative, for parents as they navigate new relationships with their babies and shifts in family dynamics. Physical distancing requirements mandated by public health orders during the COVID-19 pandemic had the potential to create even more stress for parents with a newborn. Examining personal experiences would provide health care professionals with information to help guide support during significant isolation. Feminist poststructuralism guided the qualitative research process. Sixty-eight new mothers completed an open-ended on-line survey. Responses were analyzed using discourse analysis to examine the beliefs, values, and practices of the participants relating to their family experiences during the pandemic period. It was found that pandemic isolation was a time of complexity with both 'blessings and curses'. Participants reported that it was a time for family bonding and enjoyment of being a new parent without the usual expectations. It was also a time of missed opportunities as they were not able to share milestones and memories with extended family. Caring for a newborn during the COVID-19 pandemic where complex contradictions were constructed by competing social discourses created difficult dichotomies for families. In acknowledging the complex experiences of mothers during COVID-19 isolation, nurses and midwives can come to understand and help new parents to focus on the blessings of this time while acknowledging the curses.

**Keywords:** family; bonding; COVID-19; mother; post-partum


**Chapter 11**

Conditional Variances. Economics

[22] Bollerslev, T., R.F. Engle, and J.M. Wooldridge (1998). A Capital Asset Pricing Model with Time Varying Variance. Journal of Political Economy,

*Linear and Non-Linear Financial Econometrics - Theory and Practice*

[32] Alles, Lakshman, and Louis Murray (2001). An Examination of Returns and Volatility Patterns on the Irish Equity Market. Applied Financial Economics,

[33] Bollerslev, T. (1986). Generalized

Autoregressive Conditional Heteroscedasticity. Journal of Econometrics, 31, 307-327.

[34] Engle, R., and V. Ng (1993). Measuring and Testing the Impact of News on Volatility. Journal of Finance,

[36] Pagan and Sabau (1987)

"An Examination of Returns and Volatility Patterns on the Irish Equity Market," Applied Financial Economics,

[38] Diebold, F. (1986). Temporal Aggregation of ARCH Processes and the Distribution of Asset Returns. Special Studies Paper 200, Fedeml Reserve Board, Division of Research and Statistics, Washington, D.C.

[35] Glosten, L., R. Jagannathan, and D. Runkle (1993). Relationship between the Expected Value and Volatility of the Nominal Excess Returns on Stocks. Journal of Finance, 48, 1779-1802.

[37] Alles, Lakshman, and Louis Murray,

11(2),137-146.

48, 1749-1778.

1 1, no. 2 (2001)

[23] Engle, R.F., and J. Patton (2001). What Good is a Volatility Model?. NYU

[24] R.F. Engle, "New Frontiers for ARCH Models," J. of Applied

[25] Engle, R., and V. Ng (1991). Measuring and Testing the Impact of News on Volatility. University of

Econometrics, Vol. 17, pp 425-46, 2002

[26] Cutler, D.M., J.M. Poterb, and L.H. Summer (1991). Speculative Dynamics. Review of Economic Studies, 58, 529-

[27] Lo, A.W., and A.C. MacKinlay (1988). Stock Market Prices do not Follow Random Walk: Evidence from a Simple Specification Test. levies' of

[28] Nelson, D.B. (1991). Conditional Heteroscedasticity in Asset Returns: A New Approach. Econometrica, 59, 347-

[29] Engle, R. (2002). Introduction: in ARCH Selected Reading. Advanced Texts in Econometrics (Oxford

[30] Breusch, T.S., and A.R. Pagan

[31] Wooldridge, Jeffery M. (2003). Introductory Econometrics. A Modern Approach (Mason, Ohio: South-

(1979). A Simple Test for Heteroskedasticity and Random Coefficient Variations. Econometrica,

Western Publishing).

Financial Studies, 1, 41-66.

Stern School of Business.

California, San Diego.

546.

370.

University Press).

50, 987-1007.

**204**

Letters, 50, 197-203.

96, l16-131.


**Preface to "Combining Sensors and Multibody Models for Applications in Vehicles, Machines, Robots and Humans"**

Measuring and simulating sensors and physical models represent two ways of obtaining information from a dynamical system. Each of them has advantages and disadvantages, but the combination of both leads to more consistent results. This general idea can be particularized to mobile mechanical systems, also known as multibody systems. In this type of system, with popular examples including vehicles, machines, robots and humans, there is a tradition of using simplified models along with sensors to estimate the states, inputs and/or parameters of the system. However, in the last decade, research activity has been devoted to substituting the simplified models with detailed multibody models, which can be useful in some applications. Therefore, the aim of this Special Issue has been to gather contributions that illustrate the interest in this recent trend.

> **Javier Cuadrado, Miguel A. Naya** *Editors*


**Author details**

Peter Kusch

*Gas Chromatography - Derivatization, Sample Preparation, Application*

mer blends, biopolymers, and natural resins [3].

**2. Multidimensional gas chromatography**

used extensively over the last 30 years as a complementary analytical tool used to characterize the structure of synthetic organic polymers and copolymers, poly-

Developed by Phillips and coworker at the Southern Illinois University (USA) in the early 1990s, comprehensive multidimensional GC (GC × GC or 2D GC) is a powerful technique for samples containing very large numbers of compounds of interest and also for samples which exhibit high chemical complexity. This technique can be used to separate very complex mixtures, such as those found in the petrochemical, environmental, and food and fragrance industries [4–6]. The method uses two capillary columns, typically of very different polarities, installed in series with a modulator in between. The first column is in principle nonpolar or low polar, and the second column is polar. The length of the first column might typically be 20–30 m, the inner diameter 0.25 mm, and the film thickness 0.25 μm. The second column is typically shorter (1–2 m), the inner diameter is narrower (0.1 mm), and the stationary phase is thinner (0.1 μm), to allow for faster separations. The entire assembly is located inside the GC oven [6]. The modulator collects effluent from the first column for a fraction of the time equal to peak width. The modulator focuses the material collected from each cut into a very narrow band through flow compression. It introduces the bands sequentially onto the second column, resulting in additional separation for each band injected onto the second column [4–9]. The most common data transformation is the construction of a 2D representation, in which one axis represents the separation on the first column (first dimension), and the other axis represents the secondary column separation (second dimension). Therefore, the look of GC × GC chromatograms appears completely different from conventional GC chromatogram showing a two-dimensional plane where analyte spots are scattered about [7, 8]. A contour plot, using elevation lines or color coding, represents the signal intensity. 2D GC data are primarily used for

*2D GC plot of a refinery stream boiling at diesel temperature range. The scale indicates the relative signal*

*intensity. Figure reprinted from Ref. [10] with permission from ACS.*

**4**

**Figure 1.**

Department of Applied Natural Sciences, Bonn-Rhein-Sieg University of Applied Sciences, Rheinbach, Germany

\*Address all correspondence to<EMAIL_ADDRESS>
© 2018 The Author(s). Licensee IntechOpen. This chapter is distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/ by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


2.2.3. *Time Lag Method*

Independent of the method described in Section 2.2.2, the propagation direction of NLIWs was estimated using the distance between two locations of the NLIW front observed at different times, with the assumption that the NLIWs propagate across the two measurement locations with an angle orthogonal to the constant phase lines at a constant speed (Figure 2a,c). The observed propagation speed was estimated by dividing the distance between the two locations *Dobs* by the arrival time lag *Tobs*, for example, *cobs* = *Dobs Tobs* . Then, *cKdV*.*iw* was calculated from *cobs* and angular difference *θtl* = |*φobs* − *φtl*| between *φobs* (direction from the first measurement location to the second measurement location) and the propagation direction of NLIWs *φtl* as

$$c\_{\rm KdV.iw} = c\_{\rm obs} \cos(\theta\_{l\rm l}) = \frac{D\_{\rm obs}}{T\_{\rm obs}} \cos(|\phi\_{\rm obs} - \phi\_{\rm ll}|). \tag{16}$$

Finally, the *φtl* was obtained from Equation (16) as

$$\phi\_{tl} = \phi\_{obs} \pm \cos^{-1}\left(\frac{c\_{KdV,iw}T\_{obs}}{D\_{obs}}\right). \tag{17}$$

The propagation direction estimated using the method described above (*time lag* method) also has an angular ambiguity caused by the sign of the arccosine part. Thus, a physically reasonable direction is selected. The *φtl* and *φobs* are angles in degrees measured counter-clockwise from the east.


**About the Editor**

**Hari Prasad Devkota** completed his Bachelor of Pharmaceutical Sciences (B. Pharm.) from Pokhara University, Nepal in 2005. After working at the same institute as a Teaching Associate till 2007, he received Japanese Government (MEXT) Scholarship and entered the Graduate School of Pharmaceutical Sciences, Kumamoto University, Japan in 2007, and completed his Master's and PhD in Pharmaceutical Sciences in 2010 and 2013, respectively. He was working as Postdoctoral Fellow in Kumamoto University (2013–2014) with the support from Takeda Science Foundation (TSF), Japan. Since 2014, he has been working as Assistant Professor at Kumamoto University. His main research interests are plant-based bioactive natural products, functional foods and ethnopharmacology. To date, he has authored more than 130 publications including original research articles, review articles, books and book chapters. He is actively involved in the research on medicinal plants from Asia and Africa for their ethnopharmacological surveys, chemical constituents and pharmacological activities.


**2. Exposure of fish to mycotoxins**

Fish production in aquaculture has increased rapidly over the previous decades. Consequently, increasing numbers of fish have to be fed in aquaculture, which requires an increasing amount of fish feed. Since the global availability of fishmeal, which is a major ingredient in fish feed, is limited, cereals are common alternatives. Based on recent estimations, it has been determined that fishmeal is still a major component in fish feed in Europe [1], despite the fact that its percentage in commercial feeds has decreased over the last decades. The disadvantage of plant-based ingredients is that there is a higher probability of them being contaminated with mycotoxins. The second most prominent feed ingredient in aquaculture feeds in

Europe is wheat flour [1], followed by soybean products. Other feed ingredients are often present in fish feeds at average percentages of less than 10%, and these ingredients may also contain considerable amounts of mycotoxins. One example of such a problematic feed ingredient may be distillers' grain with solubles (DDGS) [1, 2].

The most important mycotoxins in feed ingredients in terms of risk to fish and consumers, since they are either known to be toxic and/or occur at high concentrations, include aflatoxin B1 (AFB1), deoxynivalenol (DON), nivalenol (NIV), zearalenone (ZEN), ochratoxin A (OTA), T-2 toxin (T2), fumonisin B1 (FB1), moniliformin (MON), enniatins (ENNs), and beauvericin (BEA). Nevertheless, there are a number of reasons why mycotoxin contamination levels in feed ingredients can vary widely, for example, different fungal species or strains often grow on specific feed ingredients. Especially, high OTA levels have been found in corn (up to 1850 μg/kg, [3]), followed by wheat (up to 1024 μg/kg, [4]), soybean, and sunflower products (up to 350 and 240 μg/kg, respectively, [3]). Furthermore, *Fusarium* mycotoxins can contaminate peas and soybeans [5], and FB1 can be found in significant amounts in corn [6].

The occurrence of mycotoxins in feed ingredients is also known to vary as a result of climate effects and differences in the distribution of various fungal species and strains that have differing abilities to form toxins [7–9]. The problem with mycotoxin contamination in feed ingredients is thought to have increased as a result of climate changes and the shipping of commodities on a global scale, which has led to the worldwide distribution of many fungal species, often resulting in higher contamination in cereals [9–11]. However, the presence of mycotoxins in feed ingredients does not mean that these substances will also be present in compounded animal feeds, since a number of mycotoxins have been reported to possess different degrees of stability when thermally processed and extruded [12]. Furthermore, the processing of feed ingredients, which includes cleaning, sorting, milling, and the application of thermal processes, also influences the mycotoxin load in the final products [13–16]. Nevertheless, the extent of the reduction in mycotoxin contamination during these procedures differs widely for each mycotoxin [15, 17–20]. Generally, mycotoxins that are most stable and widely distributed and, in most cases, occur at high concentrations in certain feed ingredients are problematic for fish production. Two mycotoxins that are already problematic at relatively low concentrations in fish feeds and will be reviewed in the section on fish toxicity are AFB1 and OTA due to their high toxicity.

The most prominent member of the fumonisins in naturally contaminated animal feeds is FB1 [21], which often occurs at high concentrations in feed ingredients (e.g., [22, 23]). However, since fumonisins are relatively unstable and easily affected by feed production processes, they are assumed to be less problematic than other mycotoxins. Nonetheless, feed processing may yield mycotoxin metabolites, in some cases resulting in increased toxicity [24].

ZEN is a mycotoxin that commonly occurs after crops have been infected have been infected with *Fusarium* species in the field, but this toxin can also develop during the storage of the cereals [25, 26]. ZEN contamination appears to be common in commercial fish feeds [27, 28], which raises concerns about the effects of chronic exposure to this mycotoxin, since besides exhibiting toxic characteristics, it is also a potent natural estrogen [29].

The trichothecenes include some very important mycotoxins, such as T-2 toxin, DON, and NIV. Recent research has focused on DON since it is known for its high prevalence and incidence in feed ingredients and animal feeds in Europe [30]. However, *Fusarium* fungi are also known to produce some less commonly described mycotoxins, known as emerging mycotoxins, which include BEA, ENNs, and MON [31, 32]. Although ENNs and BEA have been reported to be extremely prevalent in cereals [33], there has not been enough detailed research into their presence in feed components, compounded animal feeds, or farmed animals that have been exposed

**19**

*Food Safety: The Risk of Mycotoxin Contamination in Fish*

the levels present in commercial fish feeds remain unknown.

to these mycotoxins. The other important *Fusarium*-related mycotoxin is MON. Up to 1.2 mg/kg MON has been detected in feeds for higher vertebrates [34], whereas

As mentioned above, mycotoxin contamination often occurs on crop fields, but improper storage of feed ingredients and feeds also contributes to the final toxin levels in fish diets. Toxin production depends on the fungi's ability to produce certain chemical compounds as well as environmental factors, such as physical, chemical, and biological factors [35]. Accordingly, similar to the aflatoxins, the occurrence of OTA seems to be connected to temperature and humidity in the environment during growth and harvesting of crops, and the storage of feed ingredients and feeds. However, for most investigated fish feeds, low OTA levels have been observed [28]. In contrast, recent research has shown that inappropriate storage over a period of 6 weeks of a commercial feed for salmonids can lead to the development of

considerable amounts of OTA (up to 400 μg/kg feed, unpublished results, C. Pietsch). Although dietary contamination is the main route of exposure for fish in aquaculture, mycotoxins may also be introduced to aquatic environments directly. For example, levels of 90 μg/L OTA have been reported in waste water originating from wine production. Furthermore, ZEN can be found in surface waters and in waste-water treatment plants at ng/L levels, which may be environmentally relevant

When data on contamination levels and incidence in common feed ingredients

due to the estrogenic effects of this mycotoxin [36–38]. Thus, the stability of mycotoxins in water may also have an effect on relevant exposure concentrations in

are compiled, there may be significant uncertainties due to the fact that these studies use different methodologies for mycotoxin detection and quantification. Another problem when compiling data from scientific studies is that several studies have not reported accuracy and reliability parameters for their methods, meaning the measured toxin values probably contain uncertainties, since the sample preparation and detection procedures differed. Furthermore, actual mycotoxin concentrations in feed components, animal feeds, and animal tissues are often underestimated, since matrix effects and the problems of detecting masked mycotoxins, which can often not be detected by routine measurement techniques. Since research is continuously improving detection methods for mycotoxins, an increased number of comparative studies addressing the advantages and disadvantages of detection methods for more commonly and emerging mycotoxins, such as can be

Another problem with estimating actual contamination levels in feeds and animal tissues is that metabolites of even commonly occurring mycotoxins are often not analyzed together with their parent compound, although metabolites may occur in significant amounts as has been shown for DON [41]. Furthermore, toxin levels in the control diets used in experimental fish studies have often been reported to contain no mycotoxins, despite the fact that the necessary toxin analyses were rarely performed to provide proof for this assumption. This may lead to an underestimation of the actual toxin levels in both control diets and experimental diets if only a restricted number of mycotoxins are measured. As a result, actual mycotoxin exposure data for fish contain various uncertainties. Therefore, more complete feed contamination databases are required so that risk assessments can be improved.

If the risk to humans by consuming fish products is to be calculated, the first step would be to estimate the uptake and retention of mycotoxins in different fish

found in the study by Pascale [40], should be conducted.

**3. Presence of mycotoxins and their toxicity in fish**

*DOI: http://dx.doi.org/10.5772/intechopen.89002*

aquatic environments [39].

#### *Food Safety: The Risk of Mycotoxin Contamination in Fish DOI: http://dx.doi.org/10.5772/intechopen.89002*

*Mycotoxins and Food Safety*

Europe is wheat flour [1], followed by soybean products. Other feed ingredients are often present in fish feeds at average percentages of less than 10%, and these ingredients may also contain considerable amounts of mycotoxins. One example of such a problematic feed ingredient may be distillers' grain with solubles (DDGS) [1, 2]. The most important mycotoxins in feed ingredients in terms of risk to fish and consumers, since they are either known to be toxic and/or occur at high concentrations, include aflatoxin B1 (AFB1), deoxynivalenol (DON), nivalenol (NIV), zearalenone (ZEN), ochratoxin A (OTA), T-2 toxin (T2), fumonisin B1 (FB1), moniliformin (MON), enniatins (ENNs), and beauvericin (BEA). Nevertheless, there are a number of reasons why mycotoxin contamination levels in feed ingredients can vary widely, for example, different fungal species or strains often grow on specific feed ingredients. Especially, high OTA levels have been found in corn (up to 1850 μg/kg, [3]), followed by wheat (up to 1024 μg/kg, [4]), soybean, and sunflower products (up to 350 and 240 μg/kg, respectively, [3]). Furthermore, *Fusarium* mycotoxins can contaminate peas and soybeans [5], and FB1 can be found in significant amounts in corn [6].

The occurrence of mycotoxins in feed ingredients is also known to vary as a result of climate effects and differences in the distribution of various fungal species and strains that have differing abilities to form toxins [7–9]. The problem with mycotoxin contamination in feed ingredients is thought to have increased as a result of climate changes and the shipping of commodities on a global scale, which has led to the worldwide distribution of many fungal species, often resulting in higher contamination in cereals [9–11]. However, the presence of mycotoxins in feed ingredients does not mean that these substances will also be present in compounded animal feeds, since a number of mycotoxins have been reported to possess different degrees of stability when thermally processed and extruded [12]. Furthermore, the processing of feed ingredients, which includes cleaning, sorting, milling, and the application of thermal processes, also influences the mycotoxin load in the final products [13–16]. Nevertheless, the extent of the reduction in mycotoxin contamination during these procedures differs widely for each mycotoxin [15, 17–20]. Generally, mycotoxins that are most stable and widely distributed and, in most cases, occur at high concentrations in certain feed ingredients are problematic for fish production. Two mycotoxins that are already problematic at relatively low concentrations in fish feeds and will be reviewed in the

section on fish toxicity are AFB1 and OTA due to their high toxicity.

The most prominent member of the fumonisins in naturally contaminated

ZEN is a mycotoxin that commonly occurs after crops have been infected have been infected with *Fusarium* species in the field, but this toxin can also develop during the storage of the cereals [25, 26]. ZEN contamination appears to be common in commercial fish feeds [27, 28], which raises concerns about the effects of chronic exposure to this mycotoxin, since besides exhibiting toxic characteristics, it is also a

The trichothecenes include some very important mycotoxins, such as T-2 toxin, DON, and NIV. Recent research has focused on DON since it is known for its high prevalence and incidence in feed ingredients and animal feeds in Europe [30]. However, *Fusarium* fungi are also known to produce some less commonly described mycotoxins, known as emerging mycotoxins, which include BEA, ENNs, and MON [31, 32]. Although ENNs and BEA have been reported to be extremely prevalent in cereals [33], there has not been enough detailed research into their presence in feed components, compounded animal feeds, or farmed animals that have been exposed

animal feeds is FB1 [21], which often occurs at high concentrations in feed ingredients (e.g., [22, 23]). However, since fumonisins are relatively unstable and easily affected by feed production processes, they are assumed to be less problematic than other mycotoxins. Nonetheless, feed processing may yield mycotoxin metabolites, in some cases resulting in increased toxicity [24].

**18**

potent natural estrogen [29].

to these mycotoxins. The other important *Fusarium*-related mycotoxin is MON. Up to 1.2 mg/kg MON has been detected in feeds for higher vertebrates [34], whereas the levels present in commercial fish feeds remain unknown.

As mentioned above, mycotoxin contamination often occurs on crop fields, but improper storage of feed ingredients and feeds also contributes to the final toxin levels in fish diets. Toxin production depends on the fungi's ability to produce certain chemical compounds as well as environmental factors, such as physical, chemical, and biological factors [35]. Accordingly, similar to the aflatoxins, the occurrence of OTA seems to be connected to temperature and humidity in the environment during growth and harvesting of crops, and the storage of feed ingredients and feeds. However, for most investigated fish feeds, low OTA levels have been observed [28]. In contrast, recent research has shown that inappropriate storage over a period of 6 weeks of a commercial feed for salmonids can lead to the development of considerable amounts of OTA (up to 400 μg/kg feed, unpublished results, C. Pietsch).

Although dietary contamination is the main route of exposure for fish in aquaculture, mycotoxins may also be introduced to aquatic environments directly. For example, levels of 90 μg/L OTA have been reported in waste water originating from wine production. Furthermore, ZEN can be found in surface waters and in waste-water treatment plants at ng/L levels, which may be environmentally relevant due to the estrogenic effects of this mycotoxin [36–38]. Thus, the stability of mycotoxins in water may also have an effect on relevant exposure concentrations in aquatic environments [39].

When data on contamination levels and incidence in common feed ingredients are compiled, there may be significant uncertainties due to the fact that these studies use different methodologies for mycotoxin detection and quantification. Another problem when compiling data from scientific studies is that several studies have not reported accuracy and reliability parameters for their methods, meaning the measured toxin values probably contain uncertainties, since the sample preparation and detection procedures differed. Furthermore, actual mycotoxin concentrations in feed components, animal feeds, and animal tissues are often underestimated, since matrix effects and the problems of detecting masked mycotoxins, which can often not be detected by routine measurement techniques. Since research is continuously improving detection methods for mycotoxins, an increased number of comparative studies addressing the advantages and disadvantages of detection methods for more commonly and emerging mycotoxins, such as can be found in the study by Pascale [40], should be conducted.

Another problem with estimating actual contamination levels in feeds and animal tissues is that metabolites of even commonly occurring mycotoxins are often not analyzed together with their parent compound, although metabolites may occur in significant amounts as has been shown for DON [41]. Furthermore, toxin levels in the control diets used in experimental fish studies have often been reported to contain no mycotoxins, despite the fact that the necessary toxin analyses were rarely performed to provide proof for this assumption. This may lead to an underestimation of the actual toxin levels in both control diets and experimental diets if only a restricted number of mycotoxins are measured. As a result, actual mycotoxin exposure data for fish contain various uncertainties. Therefore, more complete feed contamination databases are required so that risk assessments can be improved.


**Author details**

Andrea Aprovitola, Fabrizio Medugno, Giuseppe Pezzella\*, Luigi Iuspa and Antonio Viviani Department of Engineering, University of Campania "L. Vanvitelli", Aversa*,* Italy

\*Address all correspondence to<EMAIL_ADDRESS>
© 2022 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.

*Lifting Entry Analysis for Manned Mars Exploration Missions DOI: http://dx.doi.org/10.5772/intechopen.101993*


*Review* **Personalizing Oncolytic Virotherapy for Glioblastoma: In Search of Biomarkers for Response**

**Eftychia Stavrakaki, Clemens M. F. Dirven and Martine L. M. Lamfers \***

Department of Neurosurgery, Brain Tumor Center, Erasmus University Medical Center, 3015 CN Rotterdam, The Netherlands<EMAIL_ADDRESS>(E.S<EMAIL_ADDRESS>(C.M.F.D.) **\*** Correspondence<EMAIL_ADDRESS>
**Simple Summary:** Glioblastoma (GBM) is the most frequent and aggressive primary brain tumor. Despite multimodal treatment, the prognosis of GBM patients remains very poor. Oncolytic virotherapy is being evaluated as novel treatment for this patient group and clinical trials testing oncolytic viruses have shown impressive responses, albeit in a small subset of GBM patients. Obtaining insight into specific tumor- or patient-related characteristics of the responding patients, may in the future improve response rates. In this review we discuss factors related to oncolytic activity of the most widely applied oncolytic virus strains as well as potential biomarkers and future assays that may allow us to predict response to these agents. Such biomarkers and tools may in the future enable personalizing oncolytic virotherapy for GBM patients.

**Abstract:** Oncolytic virus (OV) treatment may offer a new treatment option for the aggressive brain tumor glioblastoma. Clinical trials testing oncolytic viruses in this patient group have shown promising results, with patients achieving impressive long-term clinical responses. However, the number of responders to each OV remains low. This is thought to arise from the large heterogeneity of these tumors, both in terms of molecular make-up and their immune-suppressive microenvironment, leading to variability in responses. An approach that may improve response rates is the personalized utilization of oncolytic viruses against Glioblastoma (GBM), based on specific tumor- or patientrelated characteristics. In this review, we discuss potential biomarkers for response to different OVs as well as emerging ex vivo assays that in the future may enable selection of optimal OV for a specific patient and design of stratified clinical OV trials for GBM.

**Keywords:** oncolytic viruses; glioblastoma; clinical trials; biomarkers; personalized oncolyticvirotherapy


**1.1. Introduction to bio-inspired robotic manta ray**

Aquatic animals (e.g., fishes, cetaceans, etc.) are ultimate examples of superior swimmers as a result of millions of years of evolution, endowed with a variety of morphological and structural features for moving through water with speed, agility, and efficiency (Chen et al, 2010). The manta ray (*Manta birostris*, shown in Fig. 2) demonstrates excellent swimming capabilities; generating highly efficient thrust via flapping of dorsally flattened pectoral fins (Rosenberger, 2001). Many efforts have been directed towards building a bio-inspired pectoral fin structure to mimic the swimming behavior of the ray. Examples include rigid plates or tensegrity structures actuated by servo-motors (Gao et al, 2007; Moored et al, 2008; Moored & Bart-Smith, 2009; Zhou & Low, 2012) and flexible membrane actuated by shape memory alloy (SMA) (Wang et al, 2009). However, these methods are not suitable for smallscale robots (on the order of 5-10 cm) (Shahinpoor, 1992; Mojarrad & Shahinpoor, 1996; Tan et al, 2006; Guo et al, 2003; Punning et al, 2004) because of either the limitations in scaling or high power consumption. To construct a free swimming and small-scale robotic manta ray, there is a need for a bio-inspired actuating material that is lightweight, compliant, resilient, and capable of generating 3 dimensional (3D) deformations with portable power consumption.

Ionic Polymer-Metal Composite Artificial Muscles in Bio-Inspired Engineering Research: Underwater Propulsion 225

**Figure 2.** Bio-inspiration: The Manta Ray (courtesy of www.elasmodivec.com).

224 Smart Actuation and Sensing Systems – Recent Advances and Future Challenges

**Figure 1.** Actuation mechanism of IPMC (Chen & Tan, 2008).

**1.1. Introduction to bio-inspired robotic manta ray**

generator are presented.

consumption.

on the surface acts as a stable electrolysis catalyst (Millet et al, 1989).

established on the boundary (Nemat-Nasser & Li, 2000; Nemat-Nasser, 2002) breaks down of the water molecules; and (iii) the porous platinum electrodes (Shahinpoor & Kim, 2001)

In this chapter, the advantages and challenges of IPMCs as applied to bio-inspired engineering are discussed. A bio-inspired robotic manta ray integrated with IPMCs as artificial muscles and a novel buoyancy control device using IPMCs as an electrolysis

Aquatic animals (e.g., fishes, cetaceans, etc.) are ultimate examples of superior swimmers as a result of millions of years of evolution, endowed with a variety of morphological and structural features for moving through water with speed, agility, and efficiency (Chen et al, 2010). The manta ray (*Manta birostris*, shown in Fig. 2) demonstrates excellent swimming capabilities; generating highly efficient thrust via flapping of dorsally flattened pectoral fins (Rosenberger, 2001). Many efforts have been directed towards building a bio-inspired pectoral fin structure to mimic the swimming behavior of the ray. Examples include rigid plates or tensegrity structures actuated by servo-motors (Gao et al, 2007; Moored et al, 2008; Moored & Bart-Smith, 2009; Zhou & Low, 2012) and flexible membrane actuated by shape memory alloy (SMA) (Wang et al, 2009). However, these methods are not suitable for smallscale robots (on the order of 5-10 cm) (Shahinpoor, 1992; Mojarrad & Shahinpoor, 1996; Tan et al, 2006; Guo et al, 2003; Punning et al, 2004) because of either the limitations in scaling or high power consumption. To construct a free swimming and small-scale robotic manta ray, there is a need for a bio-inspired actuating material that is lightweight, compliant, resilient, and capable of generating 3 dimensional (3D) deformations with portable power In the past, IPMC actuators have been used as a caudal fin in bio-inspired robotic fishes (Shahinpoor, 1992; Mojarrad & Shahinpoor, 1996; Tan et al, 2006; Guo et al, 2003), where the propulsive fin mimics the bending motion observed in many biological fishes. In the propulsion mechanism of rays, undulatory and oscillatory flapping motions of the pectoral fin play an important role in generating highly efficient propulsion and maneuvering (Rosenberger, 2001). To fabricate an actuating membrane capable of generating complex deformations, lithography-based (Chen & Tan, 2010) and surface machining-based approaches (Kim et al, 2011) have been explored to pattern the electrodes of the IPMC. To create active and passive areas in a Nafion membrane, the electrodes on the membrane were separated. By independently controlling the bending of each active area, 3-dimensional deformations of the membrane have been achieved. However, the stiffness of the Nafion in the passive area limited its capability of generating large twisting motions. Punning et al, developed pectoral fins for ray-like underwater robot by assembling separated IPMC beams with a latex foil (Punning et al, 2004). However, this robot did not achieve free-swimming due to high power consumption and low propulsion efficiency. The challenge in this study is to fabricate a compliant actuating membrane cable of complex 3D kinematic motions capable of generating energy efficient locomotion. This will then be integrated in a smallscale robotic ray capable of free swimming.