**1. Introduction**

Even though the propagation of elastic/acoustic waves in inhomogeneous and layered media has been an active research topic for many decades already, new problems and challenges continue to be posed even up to now. In fact, during the last few years, renewed interests have been witnessed by researchers in the various fields of acoustics, such as acoustic mirrors, filters, resonators, waveguides, and other kinds of acoustic devices, in relation to wave propagation in periodic elastic media. In acoustics and applied mechanics, these developments have been triggered by the need for new acoustic devices in order to obtain quality control of elastic/acoustic waves.

What sort of material can allow us to have complete control over the elastic/acoustic wave's propagation? We would like to discuss and answer this question in this chapter. It is well known that the successful applications of photonic band-gap materials have hastened the related researches on phononic band-gap materials. *Analysis of Acoustic Wave in Homogeneous and Inhomogeneous Media Using Finite Element Method* explores the theoretical road leading to the possible applications of phononic band gaps. It should quickly bring the elastic/acoustic professionals and engineers up to speed in this field of study where elastic/acoustic waves and solid-state physics meet. It will also provide an excellent overview to any course in elastic/acoustic media.

Previous research on photonic crystals (Johnson & Joannopoulos, 2001, 2003; Joannopoulos et al., 1995; Leung & Liu, 1990) has sparked rapidly growing interest in the analogous acoustic effects of phononic crystals and periodic elastic structures. The various techniques for band structure calculations were introduced (Hussein, 2009). There are many wellknown methods of calculating the band structures of photonic and phononic crystals in addition to the reduced Bloch mode expansion method: the plane-wave expansion (PWE) method (Huang & Wu, 2005; Kushwaha et al., 1993; Laude et al., 2005; Tanaka & Tamura, 1998; Wu et al., 2004 ; Wu & Huang, 2004), the multiple-scattering theory (MST) (Leung & Qiu, 1993; Kafesaki & Economou, 1999; Psarobas & Stefanou, 2000; Wang et al., 1993), the finite-difference (FD) method (Garica-Pabloset et al., 2000; Sun & Wu, 2005; Yang, 1996), the transfer matrix method (Pendry & MacKinnon, 1992), the meshless method (Jun et al., 2003), the multiple multipole method (Moreno et al., 2002), the wavelet method (Checoury & Lourtioz, 2006; Yan & Wang, 2006), the pseudospectral method (Chiang et al., 2007), the finite element method (FEM) (Axmann & Kuchment, 1999; Dobson, 1999; Huang & Chen,

Analysis of Acoustic Wave

**2.1 Real space and k space**

are determined by (Kittel, 1996)

where *ijk* ε

2 *i j*

πδ*ij* **b a**⋅ = , where *ij*

δ

Fig. 1. Primitive unit cell in real space

in Homogeneous and Inhomogeneous Media Using Finite Element Method 5

It is well-known that the analysis of wave motion in infinite periodic structures is difficult in real space. For dealing with the periodic structures, the Fourier series and Bloch's theorem are used to expand the periodic parameters such as the density, material constants, displacement fields, or potential. Regarding to the transformation of the real space and **k** space, the reciprocal lattice vectors (RLVs) are adopted from the solid-state physics. In general, we consider a three-dimensional phononic crystal with primitive lattice vectors **1 a** , 2 **a** , and 3 **a** . The complete set of lattice vectors is written as {**RR a a a** | =++ *lll* 123 **123**} , where *l*1, *l*2, and *l*3 are integers. The associated primitive reciprocal lattice vectors **b1** , **b2** , and **b3**

> 2 , ( ) *ijk j k*

**aaa**

**123** ⋅ × **a a**

is the three-dimensional Levi-Civita completely antisymmetric symbol. The

**1 a**

**2 a**

III

**b2**

**b1**

is the kronecker symbol. Note that the associated primitive

(1)

ε

complete set of reciprocal lattice vectors is written as {**GG b b b** | =++ *NNN* 123 **123**} , where *N*1, *N*2, and *N*3 are integers. Figure 1 shows the primitive unit cell in two-dimensional real space while the Fig. 2 shows the relationship between the real space and **k** space. A property between the primitive lattice vectors and associated primitive reciprocal lattice vectors is

reciprocal lattice vectors are constructed as **k** space from the concept of crystal diffraction.

**1 a**

Real space **k** space

We will find that, in following sections, the discrete translational symmetry of a phononic crystal allows us to classify the elastic/acoustic waves with a wave vector **k**. The

× =

π

*i*

**b**

**2 a**

**1 a**

II

I

**2 a**

**2 a**

Fig. 2. Relationship between the real space and **k** space

**1 a**

2011; Wu et al., 2008), the mass-in-mass lattice model (Huang & Sun, 2010), and the micropolar continuous modeling (Salehian & Inman, 2010).

Many studies on phononic band structures from the past decade use the PWE, MST, and FD methods to analyze the frequency band gaps of bulk acoustic waves (BAW) in composite materials or phononic band structures. Studies adopting the PWE method investigate the dispersion relations and the frequency band-gap feathers of the BAW and surface acoustic wave (SAW) modes. Other studies use the layered MST to study the frequency band gaps of bulk acoustic waves in three-dimensional periodic acoustic composites and the band structures of phononic crystals consisting of complex and frequency-dependent Lame′ coefficients. Other researchers applied the finite-difference time-domain method to predict the precise transmission properties of slabs of phononic crystals and analyze the mode coupling in joined parallel phononic crystal waveguides.

The techniques for tuning frequency band gaps of elastic/acoustic waves in phononic crystals are very important, and remain exciting research topics in the physics community. The filling fraction, rotation of noncircular rods, different cuts of anisotropic materials, and the temperature effect all produce large frequency band gaps in the BAW and SAW modes of periodic structures. A previous review paper (Burger et al., 2004) discusses the technique used to optimize the unit cell material distribution, achieving the largest possible band gap in photonic crystals for a given cell symmetry. Studies over the past decade focus on the theoretical and numerical analysis of phononic structures based on circular or square cylinders embedded in background materials. In this case, the PWE method can easily calculate the dispersion relations by constructing the structural functions with Bessel or Sinc functions. However, research on the more complicated problem of waves in the reticular and other special periodic band structures has not started until recently.

This chapter uses the 2D and 3D finite element methods to discuss the wave velocities of isotropic and anisotropic materials in homogeneous media. It also considers the tunable band gaps of acoustic waves in two-dimensional phononic crystals with reticular geometric structures (Huang & Chen, 2011). The concept of adopting a reticular geometric structure comes from the variations of similar geometry in bio-structural reticular formation and fibers. The PWE method used to calculate the structural functions of densities and elastic constants cannot numerically analyze the Gibbs phenomenon. Therefore, this chapter adopts the FEM to discuss this special periodic band structure. Changing the filling fraction, scale parameters, and rotating angles of reticular geometric structures can tune the frequency band gaps of mixed polarization modes. This technique is suitable for analyzing the phenomenon of frequency band gaps in special band structures.

### **2. Theory**

In this chapter, based on the theorems of solid-state physics and the finite element method with Bloch calculations, equation of motion of the acoustic modes in two-dimensional inhomogeneous media, phononic band structures, are derived and discussed in detail. In the beginning, the concepts of the real space and **k** space are introduced while the Brillouin zone is also addressed in the text. Generalized techniques of Bloch calculations in finite element method are used to analyze the acoustic modes in two-dimensional homogeneous and inhomogeneous media, phononic band structures, consisting of materials with general anisotropy. The mixed and transverse polarization modes and quasi-polarization modes are investigated in the text.

### **2.1 Real space and k space**

4 Acoustic Waves – From Microdevices to Helioseismology

2011; Wu et al., 2008), the mass-in-mass lattice model (Huang & Sun, 2010), and the

Many studies on phononic band structures from the past decade use the PWE, MST, and FD methods to analyze the frequency band gaps of bulk acoustic waves (BAW) in composite materials or phononic band structures. Studies adopting the PWE method investigate the dispersion relations and the frequency band-gap feathers of the BAW and surface acoustic wave (SAW) modes. Other studies use the layered MST to study the frequency band gaps of bulk acoustic waves in three-dimensional periodic acoustic composites and the band structures of phononic crystals consisting of complex and frequency-dependent Lame′ coefficients. Other researchers applied the finite-difference time-domain method to predict the precise transmission properties of slabs of phononic crystals and analyze the mode

The techniques for tuning frequency band gaps of elastic/acoustic waves in phononic crystals are very important, and remain exciting research topics in the physics community. The filling fraction, rotation of noncircular rods, different cuts of anisotropic materials, and the temperature effect all produce large frequency band gaps in the BAW and SAW modes of periodic structures. A previous review paper (Burger et al., 2004) discusses the technique used to optimize the unit cell material distribution, achieving the largest possible band gap in photonic crystals for a given cell symmetry. Studies over the past decade focus on the theoretical and numerical analysis of phononic structures based on circular or square cylinders embedded in background materials. In this case, the PWE method can easily calculate the dispersion relations by constructing the structural functions with Bessel or Sinc functions. However, research on the more complicated problem of waves in the reticular

This chapter uses the 2D and 3D finite element methods to discuss the wave velocities of isotropic and anisotropic materials in homogeneous media. It also considers the tunable band gaps of acoustic waves in two-dimensional phononic crystals with reticular geometric structures (Huang & Chen, 2011). The concept of adopting a reticular geometric structure comes from the variations of similar geometry in bio-structural reticular formation and fibers. The PWE method used to calculate the structural functions of densities and elastic constants cannot numerically analyze the Gibbs phenomenon. Therefore, this chapter adopts the FEM to discuss this special periodic band structure. Changing the filling fraction, scale parameters, and rotating angles of reticular geometric structures can tune the frequency band gaps of mixed polarization modes. This technique is suitable for analyzing the

In this chapter, based on the theorems of solid-state physics and the finite element method with Bloch calculations, equation of motion of the acoustic modes in two-dimensional inhomogeneous media, phononic band structures, are derived and discussed in detail. In the beginning, the concepts of the real space and **k** space are introduced while the Brillouin zone is also addressed in the text. Generalized techniques of Bloch calculations in finite element method are used to analyze the acoustic modes in two-dimensional homogeneous and inhomogeneous media, phononic band structures, consisting of materials with general anisotropy. The mixed and transverse polarization modes and quasi-polarization modes are

micropolar continuous modeling (Salehian & Inman, 2010).

coupling in joined parallel phononic crystal waveguides.

and other special periodic band structures has not started until recently.

phenomenon of frequency band gaps in special band structures.

**2. Theory**

investigated in the text.

It is well-known that the analysis of wave motion in infinite periodic structures is difficult in real space. For dealing with the periodic structures, the Fourier series and Bloch's theorem are used to expand the periodic parameters such as the density, material constants, displacement fields, or potential. Regarding to the transformation of the real space and **k** space, the reciprocal lattice vectors (RLVs) are adopted from the solid-state physics. In general, we consider a three-dimensional phononic crystal with primitive lattice vectors **1 a** , 2 **a** , and 3 **a** . The complete set of lattice vectors is written as {**RR a a a** | =++ *lll* 123 **123**} , where *l*1, *l*2, and *l*3 are integers. The associated primitive reciprocal lattice vectors **b1** , **b2** , and **b3** are determined by (Kittel, 1996)

$$\mathbf{b}\_{i} = 2\pi \frac{\mathbf{c}\_{ijk}\mathbf{a}\_{j} \times \mathbf{a}\_{k}}{\mathbf{a}\_{1} \cdot (\mathbf{a}\_{2} \times \mathbf{a}\_{3})},\tag{1}$$

where *ijk* ε is the three-dimensional Levi-Civita completely antisymmetric symbol. The complete set of reciprocal lattice vectors is written as {**GG b b b** | =++ *NNN* 123 **123**} , where *N*1, *N*2, and *N*3 are integers. Figure 1 shows the primitive unit cell in two-dimensional real space while the Fig. 2 shows the relationship between the real space and **k** space. A property between the primitive lattice vectors and associated primitive reciprocal lattice vectors is 2 *i j* πδ *ij* **b a**⋅ = , where *ij* δ is the kronecker symbol. Note that the associated primitive reciprocal lattice vectors are constructed as **k** space from the concept of crystal diffraction.

Fig. 1. Primitive unit cell in real space

Fig. 2. Relationship between the real space and **k** space

We will find that, in following sections, the discrete translational symmetry of a phononic crystal allows us to classify the elastic/acoustic waves with a wave vector **k**. The

Analysis of Acoustic Wave

π *a* to π

**2.2 Equation of motion**

the displacement vector **u r**(,)*t* can be written as

 ( ) ( , ) [ ( ) ( , )], ρ

between −

is recovered.

x

y

to coincide, the homogeneous case is recovered

components in the periodic structure are expressed as follows:

( , ) ( , ), *i u t eU t i i*

A B

in Homogeneous and Inhomogeneous Media Using Finite Element Method 7

By the periodicity of the reciprocal lattice, any reciprocal lattice point which represents a wave vector **k** outside the first Brillouin zone can be found a corresponding point in the first Brillouin zone. Therefore, the wave vectors **k** can always be confined in the first Brillouin zone. In the square lattice, only the wave vectors **k** in the region of the first Brillouin zone

*first*, *second*, and *third Brillouin zones*. For more details, it is best to consult the first few chapters of a solid-state physics text, such as Kittel, 1996, or consult the appendix of popular

This section provides a brief introduction of the theory of analyzing acoustic wave propagation in inhomogeneous media like as phononic band structures. The theory in this chapter can also be used to discuss acoustic wave propagation in homogeneous media

In an inhomogeneous linear elastic medium with no body force, the equation of motion of

are the position-dependent mass density and elastic stiffness tensor, respectively. The following discussion considers a periodic structure consisting of a two-dimensional periodic array (x-y plane) of material A embedded in a background material B shown in Fig. 5. It is noted that when the properties of materials A and B tend to coincide, the homogeneous case

z

0

Half space r0

Fig. 5. Periodic structures with square lattice. When the properties of materials A and B tend

To calculate the dispersion diagrams of periodic structures, this study uses COMSOL Multiphysics software to apply the Bloch boundary condition to the unit cell domain in the FEM method. Based on the periodicity of phononic crystals, the displacement and stress

a

x

y

photonic text like Joannopoulos et al. 1995 and Johnson & Joannopoulos, 2001, 2003.

because a homogeneous medium is symmetric with respect to any periodicity.

where **r x** = = (,) (,,) *z xyz* is the position vector, *t* is the time variable, and

*a* (the lattice constant is *a*) need to be considered. The Fig. 4 shows the

*ut C u t i* =∂ ∂ *j ijmn n m* **rr r r** (3)

B A

⋅ = **k x x x** (4)

ρ

( )**r** and ( ) *Cijmn* **r**

propagating modes can be written in "Bloch form," consisting of a plane wave modulated by a function that shares the periodicity of the lattice (Joannopoulos et al., 1995):

$$\mathbf{P\_{k}(r)} = e^{i\mathbf{k}\cdot\mathbf{r}}\mathbf{u\_{k}(r)} = e^{i\mathbf{k}\cdot\mathbf{r}}\mathbf{u\_{k}(r+R)}.\tag{2}$$

The important feature of the Bloch states is that different values of **k** do not necessarily lead to different modes. It is clear that a mode with wave vector **k** and a mode with wave vector **k+G** are the same mode, where **G** is a reciprocal lattice vector. The wave vector **k** serves to specify the phase relationship between the various cells that are described by **u**. If **k** is increased by **G**, then the phase between cells is increased by **G**⋅**R**, which we know is 2π*n* (*n= l*1*N*1*+l*2*N*2*+ l*3*N*3 is an integer) and not really a phase difference at all. So incrementing **k** by **G** results in the same physical mode. This means that we can restrict our attention to a finite zone in reciprocal space in which we *cannot* get from one part of the volume to another by adding any **G**. All values of **k** that lie outside of this zone, by definition, can be reached from within the zone by adding **G**, and are therefore redundant labels shown in Fig. 3. This zone is the so-called *Brillouin zone*.

Fig. 3. All values of **k** that lie outside of this zone, by definition, can be reached from within the zone by adding **G**

Fig. 4. Brillouin zones in a square lattice

By the periodicity of the reciprocal lattice, any reciprocal lattice point which represents a wave vector **k** outside the first Brillouin zone can be found a corresponding point in the first Brillouin zone. Therefore, the wave vectors **k** can always be confined in the first Brillouin zone. In the square lattice, only the wave vectors **k** in the region of the first Brillouin zone between −π *a* to π *a* (the lattice constant is *a*) need to be considered. The Fig. 4 shows the *first*, *second*, and *third Brillouin zones*. For more details, it is best to consult the first few chapters of a solid-state physics text, such as Kittel, 1996, or consult the appendix of popular photonic text like Joannopoulos et al. 1995 and Johnson & Joannopoulos, 2001, 2003.


**Acknowledgements**

This research work has been supported by Higher Education Department (HED) of Khyber Pakhtankhwa Government under grant No: HEREF-46 and Higher Education Commission of Pakistan under grant No: 10039.


3.2.5. Gas Phase Composition

The composition of the gas phase in the samples is shown in Table 4. In the samples containing sewage sludge and/or rumen fluid pretreated at 38.6 ◦C, significant concentrations of CH4 were observed in the gas phase. The addition of rumen fluid increases cell wall degradation and thus allows microorganisms easier access to nutrients; therefore, more CH4 is formed [56].

Besides CH4, other gases such as CO2 and H2S were also analyzed and detected in the gas phase of the samples. The mixture of grass and rumen fluid (G + R) contains the highest amount of CO2. Rumen fluid degrades the lignocellulosic fibers in the grass and consumes oxygen, which leads to CO2 increase [63]. Accordingly, CO2 production could be used as an indicator of the degradation efficiency of lignocellulosic biomass during rumen fermentation [30].

The concentrations of H2S were more significant in the samples containing rumen fluid (G + R and G + S + R). Slightly higher concentrations of this gas were found in mixtures containing grass. The production of H2S comes mostly from microbial degradation of organic matter [64].

**Table 4.** Gas phase composition.

On the other hand, when pretreatment was performed at 80 ◦C, production of the gases under analysis was negligible. The reason for such results is that bacteria in materials are highly active only in mesophilic ranges (between 25 and 42 ◦C) [65] and thermophilic ranges (between 50 and 65 ◦C) [66]. At temperatures below 15 ◦C and above 70 ◦C, methanogenic bacteria are limited in activity [67].


Chapter 8 **A Unified Approach to Analysing the Anisoplanatism of Adaptive Optical Systems 191** Jingyuan Chen and Xiang Chang

Preface

and technology.

ence tomography, and laser processing.

porting theory and analysis.

applications of the devices.

images.

For over four decades there has been continuous progress in adaptive optics technology, theory, and systems development. Recently there also has been an explosion of applications of adaptive optics throughout the fields of communications and medicine in addition to its original uses in astronomy and beam propagation. This volume is a compilation of research and tutorials from a variety of international authors with expertise in theory, engineering,

The first section, Integrated Adaptive Optics Systems, contains a chapter by Zoran Popovic, Jörgen Thaung, Per Knutsson and Mette Owner-Peterson from Sweden that describes in great detail the challenges, system development, and success of high resolution retinal imag‐ ing. The second chapter in this section, Deqing Ren and Yongtian Zhu from China present a

The second section, Devices and Techniques, goes into more detail in various areas. Bonora, Zawadzki, Naletto, Bortolozzo, Residori describe a number of algorithms to assist an adap‐ tive optics system that does not directly use wavefront sensors. The Italian team show the principle applied to a number of applications such as conventional imaging, optical coher‐

A broad tutorial chapter by Chinese reseachers Xuan, Cao, Mu, Hu, and Peng presents an overview of liquid crystal technology with the applications to wavefront correction. The chapter describes many of the benefits as well as the limitations of liquid crystals with sup‐

Over the past 20 years, micromachined deformable membrane mirrors have been advancing rapidly, and because of their low cost, they have become commonplace. Europeans Thomas Ruppel et al. present a chapter to bring us up to date on the technology, manufacture, and

The final chapter of this section by Aubailly and Vorontsov discusses the limitations of con‐ ventional adaptive optics in terms of field-of-view and anisoplanatism. Then the American collaborators present a novel approach the does not use a wavefront measurement alone, but rather a measure of the entire received complex electromagnatic field to synthesize the

The third and last section to the volume, Optical and Atmospheric Effects, explores the ap‐ plication of adaptive optics to complex wave phonomena. Russian researchers Garanin, Starikov, and Malakhov present a discussion of optical vortices, showing how they appear

design and detailed performance analysis of a solar adaptive optics system.


*2.1. Fruit Supply*

Commercially mature, harvested pomegranate fruit (cv. Wonderful) of uniform diameter 81.8 ± 2.5 mm and mass 286 ± 15 g were procured from a farm in Bonnievale (33◦58 12.02 S, 20◦09 21.03 E), Western Cape, South Africa. Fruit were transported in refrigerated truck to Postharvest Technology Research Laboratory at Stellenbosch University.


**Abstract**

Although Uganda has abundant energy resources including hydropower, oil and gas, biomass, geothermal, and solar energy, energy poverty is still very high and constrains socio-economic transformation. Biomass energy accounts for approx. 88% of the energy mix and only up to 28% of the country population have access to electricity, and the two energy sources are climate sensitive. The reliance on biomass energy is a driver to deforestation and forest degradation that also reduces the country's resilience to climate hazards such as flooding, drought and landslides. Besides, deforestation is driver to greenhouse gas (GHG) emissions and adversely affects the delivery of ecosystem services. Uganda is also warming very first and rainfall patterns are becoming more variable. Coupled with increasing occurrence and severity of drought, intense rainfall, flooding and landslides, energy supply systems are becoming more vulnerable. While Uganda is currently not a major emitter of GHG, emissions will rise significantly in the future given the country's rapidly growing population and urbanization that are increasing demand for energy and exacerbated by ongoing oil and gas development. Therefore, as Uganda strives to attain a middle-income status country, building climate resilient and transiting to decarbonized energy systems is not only a necessity but transformational to reducing energy poverty, increasing access to clean and affordable energy services, spurring investment and economic growth, job creation, improved health and poverty reduction. In this chapter, we examine the nexus between energy and climate change in Uganda, focusing on energy as both a driver and victim of climate change while at the same time exploring opportunities for achieving enhanced access to affordable, reliable and clean energy as a contribution to sustainable, green and resilient development.

**Keywords:** energy, climate change, vulnerability, sustainable development, Uganda


*Article* **Research on Flexible End-Effectors with Humanoid Grasp Function for Small Spherical Fruit Picking**

**Fu Zhang 1,2,3,\*, Zijun Chen 1, Yafei Wang 3, Ruofei Bao 1, Xingguang Chen 1, Sanling Fu 4, Mimi Tian 1 and Yakun Zhang 1**

**Abstract:** The rapid, stable, and undamaged picking of small-sized spherical fruits are one of the key technologies to improve the level of intelligent picking robots and reduce grading operations. Cherry tomatoes were selected as the research object in this work. Picking strategies of two-stage "Holding-Rotating" and finger-end grasping were determined. The end-effector was designed to separate the fruit from the stalk based on the linear motion of the constraint part and the rotating gripper. This work first studied the human hand-grasping of cherry tomatoes and designed the fingers with sinusoidal characteristics. The mathematical model of a single finger of the gripper was established. The structural parameters of the gripper were determined to meet the requirements of the grabbing range from 0 to 61.6 mm. Based on the simulation model, the constraint part was set to 6 speeds, and the fruit sizes were set to 20 mm, 30 mm, and 40 mm, respectively. When the speed was 0.08m/s, the results showed that the grabbing time was 0.5381 s, 0.387 s, and 0.2761 s, respectively, and the maximum grabbing force was 0.9717 N, 3.5077 N, and 4.0003 N now of clamping, respectively. It met the picking requirements of high speed and low loss. The criterions of two-index stability and undamaged were proposed, including the grasping index of the fixed value and the slip detection of variance to mean ratio. Therefore, the control strategy and algorithm based on two-stage and two-index for rapid, stable, and non-destructive harvesting of small fruit were proposed. The results of the picking experiment for seventy-two cherry tomatoes showed that the picking success rate was 95.82%, the average picking time was 4.86 s, the picking damage rate was 2.90%, the browning rate was 2.90% in 72 h, and the wrinkling rate was 1.49% in 72 h, which can meet the actual small spherical fruit picking requirements. The research will provide an idea for the flexible end-effectors with humanoid grasp function and provides a theoretical reference for small spherical fruit picking.

**Keywords:** small spherical fruits; end-effector; design; mathematical model; slip detection


**NOBLE METALS**

Edited by **Yen-Hsun Su**

**INTECHOPEN.COM**

http://dx.doi.org/10.5772/1916 Edited by Yen-Hsun Su

#### **Contributors**

Fatma Arslan, Jesus Leobardo Valenzuela, Vaso Bojanic, Miomir Pavlovic, Jeffrey Elam, Junling Lu, Yu Lei, Yasser A. Abdelfatah Abdelaziz, Yen-Hsun Su, Leandro Andres Voisin Aravena, Oana-Georgiana Dragos-Pinzaru, Horia Chiriac, Dumitru-Daniel Herea, Wei Lin, Mieczysława Najbar, Sherif El-Safty, Nguyen Duc Hoa, Yong Yang, Lixin Zhao, Song Hu, Shaolin Zhou, Guanxiao Cheng, Takashiro Muroi, Victor Sánchez-Mendieta, Alfredo R. Vilchis-Nestor, Sachiko Ono, Hidetaka Asoh, Maddalena Pedio, Cinzia Cepek, Roberto Felici, Shigeki Matsunaga, Shigeru Tamaki, Takahiro Koishi, Masatoshi Saito, Ryo Watanabe, Mauro C. Geraldes

#### **© The Editor(s) and the Author(s) 2012**

The moral rights of the and the author(s) have been asserted.

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

#### **Notice**

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

First published in Croatia, 2012 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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*Review* **Overview of the Analytes Applied in Genotypic HIV Drug Resistance Testing**

**Hezhao Ji 1,2,\* and Paul Sandstrom 1,2**

**Abstract:** The close monitoring of HIV drug resistance using genotypic HIV drug resistance testing (HIVDRT) has become essential for effective HIV/AIDS management at both individual and population levels. Over the years, a broad spectrum of analytes or specimens have been applied or attempted in HIVDRT; however, the suitability and performance of these analytes in HIVDRT and the clinical relevance of the results from them may vary significantly. This article provides a focused overview of the performance, strengths, and weaknesses of various analytes while used in HIVDRT, which may inform the optimal analytes selection in different application contexts.

**Keywords:** HIV; drug resistance; testing; analytes; specimens; performance


*4.2. Materials and Culture Conditions*

The fungal strain *S. lamellicola* HDN13-430 was isolated from marine sediment collected in Antarctic Pritz Bay. The strain was identified by an internal transcribed spacer (ITS) sequence and the sequence data were submitted to GenBank (GenBank accession number KY794926). The strains were deposited at the Ministry of Education of China, School of Medicine and Pharmacy, Ocean University of China, Qingdao, China.

For RNA isolation, *S. lamellicola* HDN13-430 was cultured at 28 ◦C on media potato dextrose agar (PDA, 20% potato, 2% dextrose, and 2% agar) plates for 5 days, and inoculated into Elenmeyer flasks containing 150 mL of 6 different liquid culture medium for 4 days. For genomic DNA extraction, *S. lamellicola* HDN13-430 was cultured at 28 ◦C on PDA plates for 7 days.

*Escherichia coli* strain XL-1 was used for plasmids preservation and amplification. *Saccharomyces cerevisiae* Y31 was used for in vivo DNA recombination for plasmids construction.

*A. nidulans* A1145 was grown at 28 ◦C in CD (0.1% Glucose, 0.5 *v*/*v*% 20×Nitrate salts, 0.01 *v*/*v*% Trace elements, and 2% agar for solid media) media for sporulation, CDS (0.1% Glucose, 1.2 M D-sorbitol, 0.5 *v*/*v*% 20×Nitrate salts, 0.01 *v*/*v*% Trace elements, and 2% agar for solid media) to screen transformants or in CD-ST (2% starch, 2% Casamino acids, 5 *v*/*v*% 20×Nitrate salts, 0.1 *v*/*v*% Trace elements) media for heterologous expression and compound production. All medias were prepared with appropriate supplements, including 10 mM uridine, 5 mM uracil and/or 0.5 μg/mL pyridoxine HCl and/or 2.5 μg/mL riboflavin, depending on the plasmids being transformed.


**7.1 Partial autocorrelation function: for average daily milk production**

In Box–Jenkins models, the partial autocorrelation plot or partial correlogram is also often employed for model identification. In the same way, there is one lag number. As a result, we must test the MA model to ensure that it is adequate. That is, under the partial autocorrelations graph, the average daily milk output shows that there is a point outside the bottom boundaries, which is MA [1]. In other words, the distributions of average daily milk output are neither balanced nor equal, as observed in **Figure 7**.

*Predicting Trends, Seasonal Effects, and Future Yields in Cow's Milk through Time… DOI: http://dx.doi.org/10.5772/intechopen.105704*

**Figure 6.**

*Autocorrelation plot.*

**Figure 7.** *Partial autocorrelation plot.*

#### **7.2 ARMA process**

By combining the autoregressive and moving average processes, we obtain a very general time series model, ARMA (1,1).

#### **7.3 ARIMA process**

ARIMA (p, d, q) stands for autoregressive integrated moving average process, where d denotes the number of times the data is differenced before it is an ARMA (p, q). As a result, the ARIMA model is ARIMA (p, d, q) = ARIMA (1,2,1).

### **7.4 ARIMA model: for average daily milk production**

Final estimates of parameters.

As we have seen from the MINITAB output, the ARIMA model (1, 2, 1) equation is described as follows.

$$\mathbf{Y}\_t = -0.2066 \mathbf{Y}\_{t-1} + 0.997 \mathbf{\tilde{e}}\_{t-1} + \mathbf{e}\_t$$

#### *7.4.1 Testing of parameters*

The final estimates are those that reduce the sum of squared errors to the point where no other estimates yield lower sums of squared errors. As shown in the MINITAB output, a model should include significant parameters. The p-value of ARIMA (1, 2, 1) is less than the significance level (=0.05). This means the parameters are significantly different from zero and have the smallest sum-squared error possible. Then it has parameters that are statistically significant. As a result, the model is adequate.

#### *7.4.2 Forecasting*

The process of obtaining the forecast point and the final model in its original form is as follows.

$$Y\_t = -0.2066Y\_{t-1} + 0.9977e\_{t-1} + e\_t$$

*We can use the 95% confidence interval (CI) defined above to assess the accuracy of the anticipated number. We can state that the forecasted value is accurate since the entire forecast values are found between the lower and upper intervals.*

### **8. Conclusions**

The average amount of milk produced at Andassa dairy farm is dropping. The data for 179 days reveal a high degree of variability in daily milk production

*Predicting Trends, Seasonal Effects, and Future Yields in Cow's Milk through Time… DOI: http://dx.doi.org/10.5772/intechopen.105704*

compared to other days, implying that the amount of milk produced varies greatly from day to day. Because the slope of the trends over the 179 days is 16.066, the amount of milk is falling. The daily milk production graph in the autocorrelations and partial autocorrelations graphs reveals that the top and lower boundaries do not encompass the entire observation. For ARIMA (1, 2, 1), a parameter with a p-value less than the level of significance (0.05) is a parameter. This indicates that the parameter is significantly distinct from zero and has the smallest value.


**4. Discussion**

In the present study, the e ffects of PM and PF extracts on digestive enzymes were assessed. In in vitro studies, PM extract and PF extract have increased dose-dependent inhibitory activity on α*-*amylase (IC50 value: 6.13 mg/mL) and pancreatic lipase (IC50 value: 1.68 mg/mL), respectively. Notably, α-amylase, one of the digestive enzymes secreted from the pancreas and salivary glands, is involved in important biological processes such as the digestion of carbohydrates. α-Amylase inhibitors are well known to be e ffective in reducing postprandial hyperglycemia by slowing the digestion of carbohydrates and absorbing postprandial glucose. Reducing postprandial hyperglycemia prevents glucose uptake into adipose tissue, inhibiting the synthesis and accumulation of triacylglycerol [24,25].

On the other hand, pancreatic lipase is one of the most important enzymes for the digestion of dietary triacylglycerols. It is well known that dietary lipid is not directly absorbed from the intestines unless it has been subjected to the action of pancreatic lipase [24]. It has been clinically reported that a pancreatic lipase inhibitor, orlistat, prevented obesity and hyperlipidemia through the increment of fat excretion in the feces and the inhibition of pancreatic lipase. Based on this fact, the inhibition of these digestive enzymes is an important factor in the treatment of obesity [26,27].

We confirmed the anti-obesity e ffect of DKB-117 by way of digesting enzyme inhibition through in vivo testing. As a result of the test, DKB-117 extracts revealed e ffects of reducing weight and total fat in HFD-induced obese C57BL/6J mice.  This method can readily discriminate between subcutaneous and abdominal fat [28]. Our results revealed that DKB-117 was able to reduce these fats. The in vivo test results demonstrate that DKB-117 administration regulates serum biochemical parameters (TCHO, TG, HDL, and LDL) in HFD-induced obese mice. These results are associated with an anti-hypercholesterolemic e ffect of PF [13,14]. In addition, the DKB-117 extracts increased TG and carbohydrate emissions in feces compared to those in the HFD group. It is expected that DKB-117 extracts promote the release of fat and carbohydrates due to the α-amylase inhibitory e ffect and the lipase inhibitory e ffect.

On the other hand, the DKB-117 extracts are expected to have an anti-obesity e ffect through a complex mechanism that promotes carbohydrate release through the inhibition of carbohydrate-degrading enzymes and which inhibits lipid absorption through lipase inhibition. It was observed that DKB-117 can e ffectively inhibit weight gain in animal experiments through a complex mechanism of inhibition of pancreatic lipase activity and inhibition of amylase activity, which is considered to be a suitable anti-obesity measure for Koreans who use carbohydrate as a staple food.

While the existing research on herbal extract (*Garcinia cambogia, Plantago psyllium, Morus alba*) single-action mechanisms is underway, it has been confirmed through this study that they are e ffective in anti-obesity in the battle against DKB-117 multifunction machines. Based on the results of in vitro and in vivo tests, the anti-obesity e ffects of DKB-117 in human application tests will be confirmed. Furthermore, it is determined that active ingredients should be investigated through the study on the separation of components of DKB-117.

In the future, the safety and e fficacy of the DKB-117 extracts should be demonstrated through ongoing clinical trials; we plan to search for the activity compound in the DKB-117 extracts as well as perform additional testing of enzyme activity for lipid metabolism so that it can be widely used as a functional food material.


**4. Human effects and conservation efforts**

Nowadays, one-third of the human population is already feeling the negative effects of degradation, which include soil erosion, salinization, draining of marshes and bogs, and deforestation [71]. There are already more than 500 million hectares of degraded forests in the tropics and this area is steadily increasing [72]. Deforestation is caused by economic, demographic, technological, and political factors [73]. In total, 52% of the felled timber becomes lumber, 31% firewood and charcoal, 9% is the victim of an uncontrolled fire, and 7% is lost due to grazing [74]. Every biome is losing NPP due to human activities, with a degraded area reaching 2.7 billion hectares worldwide [75]. In abandoned areas, vegetation is able to regenerate. This is often done deliberately as part of a rotation system in order to regenerate soil nutrients [76] or in response to socioeconomic impacts, which alter profitability, access to labor, capital, and markets [77]. Secondary forests appear in the place of previously deforested forests, and their area increased in Brazil from 10 to 17 million hectares between 2004 and 2014, which is very important from the viewpoint of the situation of rainforests in the twenty-first century [78, 79]. Today, there are several programs to restore the original natural vegetation. Theoretical knowledge of the succession process in a given location and consideration of climatic conditions allow decision-making in order to achieve the goal of restoring a given area to a near-natural state or a condition desired by the human community [80]. During the restoration program, vegetation should be monitored continuously. The data obtained as a result of monitoring provide feedback, which can be used to adjust predictions and modify plans if necessary. In addition, monitoring can be the basis for other scientific work, increasing our knowledge of succession and vegetation dynamics. In order to control succession, it is important to know, for example, when it is time for the emergence of desirable species or for their artificial dispersal. What will their mortality be due to the competition? How to reduce harmful abiotic effects? The spread of emerging undesirable adventitious species also needs to be controlled or they have to be eradicated [81]. An adequate response to ongoing degradation is often lacking due to missing adequate knowledge of the causes that trigger it. Even measures that have been initiated are not always successful if the process of degradation itself and the underlying causes are not linked. In the absence of appropriate countermeasures, vegetation cover and soil nutrients may disappear [82].


**3. Criminal career of sex offenders**

#### **3.1 Participation and frequency**

The dimension of participation refers to the proportion of a population who are active offenders at any given time, while frequency refers to the average annual rate at which this subgroup of active offenders commits crimes. In other words, participation refers to the prevalence of offending, while frequency refers to the incidence of crime [26]. Both dimensions are particularly difficult to research and estimate because of the underreporting of sexual offences and the so called "dark figures" of crime. Nevertheless, frequency has been of particular interest to the policymakers as it implicated that it is possible to identify high-frequency offenders and incapacitate them to maximise the incapacitation effect. However, it appears that the frequency of offending is very complex and that its value might fluctuate throughout a criminal career [27]. Another difficulty with the dimension of frequency is that it is challenging to estimate. For instance, one sex offender can offend against one victim over a, for example, 5-year period, multiple times, but official reports will note his offences as one offence.

The Cambridge study [28] found that the prevalence and frequency of sex offending in community samples is low and that that there is little evidence of recidivism or continuity. With respect to the prevalence and frequency of sex offending, conviction data indicated that whereas 41% of the males in the sample had been convicted by age 50, only 2.5% of the males had a conviction for a sex offence.

However, self-report and victimisation studies show a much higher number of individuals participating in sexual offending. For instance, The Bureau of Justice Statistics' (BJS) in the US conducts a National Crime Victimisation Survey (NCVS) [29] every year using a nationally representative sample of 240,000 interviews on criminal victimisation. Results for 2018 showed that the rate of rape or sexual assault victimisation increased 1.6 to 2.7 victimizations per 1000 individuals aged 12 or older in comparison to previous years.  The analyses used self-report data and found that the prevalence of child sexual abuse ranges from 12.7–19.7% for girls and 7.6–7.9% for boys. Both analyses showed that the highest prevalence of sexual abuse of children is in Africa and the lowest prevalence rate in Europe.

It is important to point out that sexual offences are often generalised as heterosexual offence [32] and therefore, there is very little known about male victims [33].

#### *Identifying Criminal Career Patterns of Sex Offenders DOI: http://dx.doi.org/10.5772/intechopen.93972*

Recent figures indicate that around 12,000 males are victims of sexual assault or rape in the UK every year [34] and that nearly 1 in 4 men in the U.S. experienced some form of contact sexual violence in their lifetime. Among male victims of complete or attempted rape, about 71% experienced such victimisation before the age of 25 [35].

The frequency of offending varies significantly depending on the used method and between types of sex offenders. Sex offenders against women have, on average, 1.8 victims, whereas extra-familial child abusers have 3.4 victims on average [36]. Another study [37] suggests that sexual offenders with adult women victims had, on average, 2 official victims, but self-reported close to 12 victims. Similarly, sex offenders who offended against children had, on average, officially offended against 2 victims, but self-reported 7 victims.

 Firstly, about 11% of the sample committed over 300 sex crime events as opposed to about 40% who committed only one sex crime event. Secondly, some offenders take advantage of low-risk short-term opportunities with different victims, while others exploit a single offending opportunity by repeatedly offending against the same victim over a certain period of time. Thirdly, the findings revealed that the most prolific sex offenders were older, had a more conventional background characterised by a stable relationship with an adult partner, a job at the time of the offence (s), no drug issues, and no prior record for a sex crime.

#### **3.2 Seriousness**

The third dimension of the criminal career, seriousness, is in some ways, fundamental for criminal career research. Seriousness refers to the level of seriousness of the offences being committed by a given individual [3] and takes the modern approach to crime by focusing on determining a level of risk. Risk relates to the probability of criminal behaviour and is usually measured as low, moderate, or high [39, 40]. Offender risk is usually determined based on the possibility of reoffending or recidivism. It is important to define two categories here: chronic and recidivists [41]. The chronic type offenders are more at risk of persistent life-span criminal careers, which are costlier to society; over time they may have more victims (and financial loss for the victims) in addition to the costs associated with their arrest and incarceration. Recidivists are less persistent, as they have a lower incidence of reoffending. However, the categories do not differentiate on the severity of offences, only on offending timespan.

  However, meta-analyses reports show that public fear of sexual offenders is often misplaced, and that offender's recidivism rates for sexual offences vary between 11,5% and 13,7% while general recidivism rate varies between 33,2% and 36,2% [46, 47].

Some authors argue that these four key dimensions of criminal career, and especially seriousness, made it possible for a variety of important theoretical opportunities to emerge along with research on criminal careers [48]. This segment of criminal careers has several parameters that are observed through the dimension of seriousness: the severity of the criminal offence, escalation, specialisation, and crime-type switching [49].

#### *3.2.1 The severity and escalation*

The severity of the offence refers to the tendency towards committing severe criminal offences during a criminal career while escalation refers to the tendency towards making initial minor offences towards the increasingly more severe offences [27]. Escalation reflects the concern that as the career develops, the offender engages in more serious offences. There are different causes for escalation, for example, experience, increasing boldness or a stressful experience [6, 27].

Another interesting finding [51] suggested that victim resistance plays a significant role in whether or not offenders will de-escalate in the amount of physical force used between victims. If the first victim resisted the offender, he was more likely to de-escalate in the level of physical force used. However, if the second victim resisted, the offender was less likely to de-escalate, indicating that he is adopting more force to secure subsequent victims if there is resistance. Furthermore, sex offenders who consume drugs in the hours before the first crime are more likely to de-escalate in the level of physical force used than be stable.

Crucial to determining behaviour consistency is the way an offender sources his victims. The "hunting" process is an essential stage of the sexual assault and offenders who find their victims through their relationships, or their occupation will often repeat their behaviour in their future crime. In contrast, offenders who find their victims more spontaneously are less likely to repeat this "hunting" method [52].

#### *3.2.2 Specialisation and crime-type switching*

Specialisation is an aspect of criminal careers and is defined as likely repetitions of the same type of criminal offence [23] while versatility reflects a tendency to commit a broad array of offences without concentrating on a specific behaviour. Researchers use a "crime-switch" matrix, a matrix of crime types reflecting the probability that an offender who has previously committed one crime type will next commit a different type [27]. Research showed that there is a relationship between higher frequency of offending and versatility, but also that offenders who start offending at an early age tend to be involved in a diverse array of offences [6]. Most criminal careers are diverse, but there is some evidence of specialisation [21].

Sex offenders in specific show little empirical evidence of specialisation, but they are characterised by persistent criminal activity and tend to show criminal diversity in non-sexual crime types [53]. It was also found [54–56] that there are substantial differences between sex offenders regarding victim type. Sexual offenders against adults have more versatile criminal records [54–56], are more violent and have a higher frequency in offending [56] than abusers of children. The other group tends to be more specialised, have a higher frequency of sexual crimes, but also tend to be criminally versatile [45–56]. Extrafamilial child molesters are consistently found to specialise more in sexual offences [54, 55].  Research on the dimension of length attracted the attention of the scholarly community from the very beginning of criminal career research. It incorporates three head characteristics of criminal careers: beginning ("onset" or "initiation"), duration and end ("desistance" or "termination") [2, 10].

The relationship between age and crime is of an asymmetrical bell shape (most commonly known as the "age-crime curve"), showing that the prevalence of offending tends to increase from late childhood, peaks in the teenage years (around ages 15–19), and then declines from the early 20s, often with a long tail [22]. Most offenders desist during late adolescence and early adulthood, irrespective of the age of onset [22], but an early age of onset appears to be connected to a relatively long criminal career [6, 50]. Research on recidivism shows that sexual offending decreases with age, as well as general offending, and the recidivism of sexual offenders that offend against adult decreases from early adulthood [57, 58]. However, unlike the general offender, sexual offenders usually start committing offences either in adolescence or in mid to late 30 [2, 59].

Some of the possible explanations of why sex offenders appear to be older when they start offending include that there is a high rate of unreported sex offences because the victims are less likely to report sexual offences than non-sexual offences and because there is a disbalance between official statistics and self-report. A gap between the age of onset in the official statistics and self-report is seven years [2]. Moreover, nearly 20% of sexual offenders are at the end of their criminal career, or their career has already desisted when they are convicted of their first sexual offence [2].

Alternatively, some authors [60] suggest that the discrepancy that goes against the logic of the life-course explanation of desistance could be explained by increased average ages of marriage and parenthood. In specific, the peak in sexual offending seems to occur at a time when adolescents already transitioned into adulthood which could mean that sex offenders do not transition into adulthood at the same pace as non-sexual offenders, or that these transitions do not affect recidivism in the same way as they do non-sexual offenders. Besides the transition into adulthood, several other reasons could influence individuals to start with sexual offending. For example, loneliness is commonly reported among sex offenders, that the transitions that influence common crime do not affect sexual offending (or affect it to a lesser extent), a cost-benefit analysis that makes sex offenders less likely to accept the cost of being labelled as a sex offender, conflicting interpersonal relationships, and maturation factors [60].

The above-described factors could affect the length of a criminal career, but the most significant variable affecting the length of a criminal career is the age of the first conviction. The likelihood of termination of offending is noticeably different as the age of the first conviction rises, and more severe offenders cease to offend after the first conviction only in fewer cases [61].


Use of Fractal Analysis in the Evaluation of Deforested Areas in Romania

*Daniel Constantin Diaconu, R*ă*zvan Mihail Papuc, Daniel Peptenatu, Ion Andronache, Marian Marin, Răzvan Cătălin Dobrea, Cristian Constantin Drăghici, Radu-Daniel Pintilii and Alexandra Grecu*