**5. Physical and Mechanical Properties of Lightweight Aggregate**

### *5.1. Specific Gravity*

The specific gravity of the aggregate varies depending on the type of raw material used. The cold-bonded fly ash aggregate that used different molarities of alkaline activator had a specific gravity of between 1.8 and 1.85 [22]. In addition, mixing 90% of fly ash with 10% of cement by using cold bonding gives a specific gravity of 1.76 [56]. The artificial aggregate that was made up of fly ash by using the cold bonding method had a specific gravity of 1.63 as compared to normal coarse aggregate at 2.71 [54]. The specific gravity was found to be increased from 1.84 to 1.91 when the styrene–butadiene rubber (SBR) was added from 1% to 3% to the lightweight aggregate [35]. In addition, the aggregate produced by mixing bentonite and metakaolin together with fly ash has a specific gravity of 1.8 to 1.93 and 1.95 to 1.99 [59].

The sintered fly ash aggregate had a specific gravity between 1.41 and 1.44, with a size that varied from 2 mm to 12 mm [5]. The specific gravity of aggregate that was made from water treatment residual increased from 1.21 to 1.78 when the sintering temperature was increased from 1000 ◦C to 1100 ◦C [42]. The sintered dredged sludge lightweight aggregate had a specific gravity of 1.00 to 1.38 for the particle size of 4.75 mm to 12.5 mm [47]. The sintered fly ash aggregate with bentonite added had a specific gravity of 1.57, while the sintered fly ash aggregate with glass powder added had a specific gravity of 1.60 at the temperature at 1200 ◦C [54]. Meanwhile, coarse aggregate manufactured from bentonite and water glass has a specific gravity of 1.63 at a temperature of 800 ◦C [46].

In comparison to natural aggregates, the specific gravity of artificial geopolymer aggregates formed by sintering is quite low [21]. For instance, Kamal and Mishra (2020) [60] reported on the specific gravity of the fly ash aggregates as well as raw materials, including fly ash and binder, and the amount of void space in the aggregate. In addition, whenever cold-bonded aggregate was combined with other pozzolanic binding materials, such as GGBS, the specific gravity was found to be as high as 2.42, in which the hydrated lime acts as a primary binder [61]. Previous research on the determination of specific gravity of aggregates can be summarized as in Table 2.

**Table 2.** Previous studies on specific gravity of lightweight aggregate.

From Table 2, the specific gravity of lightweight aggregate was found to be in the range from 1.41 to 2.2. Based on BS EN 13055-1 [17], the specific gravity of lightweight aggregate should be less than 2.0. The wide range of the specific gravity of lightweight aggregate values can be explained by the influence factors, including type of material used, type of method used, and type of binder used during the manufacturing process. The specific gravity of lightweight aggregate is often increased by adding additives. Furthermore, the specific gravity of lightweight aggregate is affected by the curing temperature, with a greater curing temperature resulting in a lower specific gravity. The addition of a foaming agent will aid in lowering the specific gravity. In addition, the sintering method always was proven to have lower specific gravity compared to other methods due to the formation of voids at higher temperatures. However, the low specific gravity can be achieved by the cold bonding and autoclaving methods through addition of additive, such as protein-based foaming agent.


**2.5 Species and varieties**

The cultivated plums belong to two species:

1.*Prunus domestica* (European plum). It is a hybrid of diploid myrobalan plum (*Prunus cerasifera*) and tetraploid black thorn (*Prunus spinosa*). It is hexaploid in shape. Fruits are larger in size than Japanese plums. Fruit is oval or round having both yellow and green ground colour and also both red and blue skin colour. The cultivated varieties of European plum are classified into three main groups:


1. Introduction

Bamboo belongs to the subfamily Bambusoideae and may be grown in any temperate climate zones in Asia, Africa, and Latin America [1]. The total area of bamboo forests is 22.0 10 ha, which account for about 1% of the total global forest area [2]. Over the last 3 decades, bamboo has evolved from being a raw material for basic goods into a material base of an increasingly diversified array of products; recently, bamboo has been recognized as a potentially important

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

source of cultural and environmental services [3]. Bamboo species, particularly the large clump bamboo, have enormous potential as an energy source. The bamboo industry plays an important role in economy and society development in China and other countries worldwide [4]. With the expansion of bamboo forests, their importance in people's lives has also increased. Hence, scholars have focused on developing bamboo forest production, increasing the bamboo forest yield, and establishing methods for rational use of bamboo resources in global forestry production.

China has the most abundant bamboo resources worldwide and the richest bamboo culture. Bamboo greatly influences not only the Chinese history and culture but also people's daily life. Although the total forest area in many countries has decreased drastically, the area of bamboo forests has consistently increased at a rate of 3% annually [5].

In recent years, significant advances have been achieved in bamboo cultivation and development, carbon fixation and storage, and ecological and environmental functions in China. This chapter reviews the traditional utilization methods of bamboo resources in China.

3. Utilization types of bamboo resources in China

mechanical production of bamboo have continuously improved.

ing industry and daily life of Chinese people.

southern rural areas.

tourism.

Bamboo plays an important role in the development of Chinese historical culture. Through the ages, bamboo has been gaining an increasing attention from Chinese people. As one of the fastest growing plants, bamboo has become one of the most important forest resources and has a high commercial value and ecological function. Bamboo is indispensable in the manufactur-

Table 1. Statistics of increase in bamboo resources in major provinces and autonomous regions in China (unit: 10,000 ha).

Provinces 1980 1995 2005 2013 Provinces 1980 1995 2005 2013 Fujian 56.71 64.08 91.07 106.75 Guangxi 8.60 13.80 16.32 34.09 Jiangxi 58.20 70.93 93.47 99.89 Guizhou 2.40 3.87 4.43 15.69 Hunan 53.30 68.35 88.80 77.83 Jiangsu 1.80 2.23 2.87 3.37 Zhejiang 45.20 62.45 72.60 83.34 Sichuan 1.60 1.90 2.60 54.90 Anhui 15.30 20.34 24.53 33.72 Taiwan 0.50 0.63 0.80 — Guangdong 11.27 31.80 17.80 44.62 Yunnan 0.30 — 0.48 11.04 Hubei 8.60 8.60 13.80 14.40 Henan 0.29 0.47 1.67 2.74

Review of the Resources and Utilization of Bamboo in China

http://dx.doi.org/10.5772/intechopen.76485

135

China is a developing country that has a large number of population dependent on agriculture. Many of their production equipment and supplies are made of bamboo, especially in the

Since ancient times, bamboo has been widely used in the daily life of people in rural China. Therefore, most of the bamboos produced in China are used in rural and agricultural production. Bamboo resources in China were traditionally utilized by local farmers as minor forest products with weak linkage in the market. In recent years, with the fast pace of modernization, bamboo plants have replaced wood because of their advantages, such as fast growth, high yield, short rotation, and easy management. The bamboo processing industry has gathered momentum and entered a new stage. By the end of the twentieth century, dozens of countries established bamboo-based paper milling, with annual output of more than 1 million tons of bamboo paper and bamboo pulp production capacity of 4 million tons. Fine processing of bamboo has also gained increasing attention to produce a new type of artificial bamboo board with features similar to those of wood. Research and production of bamboo products have reached the practical level and production scale. The wood-based panel industry has been in the forefront in terms of variety and scale worldwide. Furthermore, the quality and process of

Table 2 shows the methods for utilizing bamboos. The main application of bamboo in China is divided into two parts: economic use and ecological utilization. Economic utilization can be roughly divided into timber bamboo, shoots bamboo, skin bamboo, and art and crafts bamboo. Ecological value can be divided into water conservation forest and ecological forest


*Article* **One Surface Treatment, Multiple Possibilities: Broadening the Use-Potential of Para-Aramid Fibers with Mechanical Adhesion**

**Sarianna Palola 1,\*, Farzin Javanshour 1, Shadi Kolahgar Azari 2, Vasileios Koutsos 2 and Essi Sarlin 1**

**Abstract:** Aramid fibers are high-strength and high-modulus technical fibers used in protective clothing, such as bulletproof vests and helmets, as well as in industrial applications, such as tires and brake pads. However, their full potential is not currently utilized due to adhesion problems to matrix materials. In this paper, we study how the introduction of mechanical adhesion between aramid fibers and matrix material the affects adhesion properties of the fiber in both thermoplastic and thermoset matrix. A microwave-induced surface modification method is used to create nanostructures to the fiber surface and a high throughput microbond method is used to determine changes in interfacial shear strength with an epoxy (EP) and a polypropylene (PP) matrix. Additionally, Fourier transform infrared spectroscopy, atomic force microscopy, and scanning electron microscopy were used to evaluate the surface morphology of the fibers and differences in failure mechanism at the fiber-matrix interface. We were able to increase interfacial shear strength (IFSS) by 82 and 358%, in EP and PP matrix, respectively, due to increased surface roughness and mechanical adhesion. Also, aging studies were conducted to confirm that no changes in the adhesion properties would occur over time.

**Keywords:** aramid fibers; surface modification; adhesion; interphase; interfacial shear strength


**2. Preliminaries**

This section briefly touches some fundamental concepts as a basis for a better understanding of this work.

©2012 Callou et al., licensee InTech. This is an open access chapter 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. ©2012 Callou et al., licensee InTech. This is a paper 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.

## **2.1. Petri nets**

Petri nets (PN) were introduced in 1962 by the PhD dissertation of Carl Adams Petri [16], at Technical University of Darmstandt, Germany. The original theory was developed as an approach to model and analyze communication systems. Petri Nets (PNs) [14] are a graphic and mathematical modeling tool that can be applied in several types of systems and allow the modeling of parallel, concurrent, asynchronous and non-deterministic systems. Since its seminal work, many representations and extensions have been proposed for allowing more concise descriptions and for representing systems feature not observed on the early models. Thus, the simple Petri net has subsequently been adapted and extended in several directions, in which timed, stochastic, high-level, object-oriented and coloured nets are a few examples of the proposed extensions.

**Figure 2.** Compact representation of a PN

**Table 1.** Interpretation for places and transitions.

and the set of output transitions (also called post-set) is:

and the set of output places of a transition *tj* ∈ *T* is:

called pre-set) of a place *pi* ∈ *P* is:

*tj* ∈ *T* is:

Input Places Transitions Output Places pre-conditions events post-conditions input data computation step output data input signals signal processor output signals resource needed tasks resource releasing conditions logical clauses conclusions buffers processor buffers

A Petri Net-Based Approach to the Quanti cation of Data Center Dependability 315

It is important to show that there are another way to represent PN's elements. As an example, the set of input and output places of transitions is shown in Definition 2.2. Similarly, the set of

**Definition 2.2. (Input and Output Transitions of a place)** The set of input transitions (also

label = •*pi* = {*tj* ∈ *T*|(*tj*, *pi*) ∈ *F*}.

label = *pi*• = {*tj* ∈ *T*|(*pi*, *tj*) ∈ *F*}.

**Definition 2.3. (Input and output places of a transition)** The set of input places of a transition

label = •*tj* = {*pi* ∈ *P*|(*pi*, *tj*) ∈ *F*}.

label = *tj*• = {*pi* ∈ *P*|(*tj*, *pi*) ∈ *F*}.

input and output transitions of determinate place is shown in Definition 2.3.

## **2.2. Place-Transition nets**

Place/Transition Petri nets are one of the most prominent and best studied class of Petri nets, and it is sometimes called just by Petri net (PN). A marked Place/Transition Petri net is a bipartite directed graph, usually defined as follows:

**Definition 2.1. (Petri net)** A Petri net [14] is a 5-tuple:

$$PN = (P\_{\prime} \, T\_{\prime} \, F\_{\prime} \, W\_{\prime} M\_0)$$

where:

This class of Petri net has two kinds of nodes, called places (*P*) represented by circles and transitions (*T*) represented by bars, such that *P* ∩ *T* = and *P* ∪ *T* �= . Figure 1 depicts the basic elements of a simple PN. The set of arcs *F* is used to denote the places connected to a transition (and vice-versa). *W* is a weight function for the set of arcs. In this case, each arc is said to have multiplicity k, where k represents the respective weight of the arc. Figure 2 shows multiple arcs connecting places and transitions in a compact way by a single arc labeling it with its weight or multiplicity k.

**Figure 1.** Petri net basic elements.

Places and transitions may have several interpretations. Using the concept of conditions and events, places represent conditions, and transitions represent events, such that, an event may have several pre-conditions and post-conditions. For more interpretations, Table 1 shows other meanings for places and transitions [14].

314 Petri Nets – Manufacturing and Computer Science A Petri Net-Based Approach to the Quantification of Data Center Dependability 3 A Petri Net-Based Approach to the Quanti cation of Data Center Dependability 315

**Figure 2.** Compact representation of a PN

2 Petri Nets

Petri nets (PN) were introduced in 1962 by the PhD dissertation of Carl Adams Petri [16], at Technical University of Darmstandt, Germany. The original theory was developed as an approach to model and analyze communication systems. Petri Nets (PNs) [14] are a graphic and mathematical modeling tool that can be applied in several types of systems and allow the modeling of parallel, concurrent, asynchronous and non-deterministic systems. Since its seminal work, many representations and extensions have been proposed for allowing more concise descriptions and for representing systems feature not observed on the early models. Thus, the simple Petri net has subsequently been adapted and extended in several directions, in which timed, stochastic, high-level, object-oriented and coloured nets are a few examples

Place/Transition Petri nets are one of the most prominent and best studied class of Petri nets, and it is sometimes called just by Petri net (PN). A marked Place/Transition Petri net is a

*PN* = (*P*, *T*, *F*,*W*, *M*0)

This class of Petri net has two kinds of nodes, called places (*P*) represented by circles and transitions (*T*) represented by bars, such that *P* ∩ *T* = and *P* ∪ *T* �= . Figure 1 depicts the basic elements of a simple PN. The set of arcs *F* is used to denote the places connected to a transition (and vice-versa). *W* is a weight function for the set of arcs. In this case, each arc is said to have multiplicity k, where k represents the respective weight of the arc. Figure 2 shows multiple arcs connecting places and transitions in a compact way by a single arc labeling it with its

Places and transitions may have several interpretations. Using the concept of conditions and events, places represent conditions, and transitions represent events, such that, an event may have several pre-conditions and post-conditions. For more interpretations, Table 1 shows

**2.1. Petri nets**

of the proposed extensions.

**2.2. Place-Transition nets**

where:

bipartite directed graph, usually defined as follows: **Definition 2.1. (Petri net)** A Petri net [14] is a 5-tuple:

1. *P* = {*p*1, *p*2, ..., *pm*} is a finite set of places; 2. *T* = {*t*1, *t*2, ...,*tn*} is a finite set of transitions;

4. *W* : *F* →{1, 2, 3, ...} is a weight function; 5. *M*0 : *P* → {0, 1, 2, 3, ...} is the initial marking;

weight or multiplicity k.

**Figure 1.** Petri net basic elements.

other meanings for places and transitions [14].

3. *F* ⊆ (*P* × *T*) ∪ (*T* × *P*) is a set of arcs (flow relation);

**Table 1.** Interpretation for places and transitions.

It is important to show that there are another way to represent PN's elements. As an example, the set of input and output places of transitions is shown in Definition 2.2. Similarly, the set of input and output transitions of determinate place is shown in Definition 2.3.

**Definition 2.2. (Input and Output Transitions of a place)** The set of input transitions (also called pre-set) of a place *pi* ∈ *P* is:

$$\text{label} = \bullet p\_i = \{ t\_j \in T | (t\_{j'} p\_i) \in F \}.$$

and the set of output transitions (also called post-set) is:

$$\text{label} = p\_i \\ \bullet = \{ t\_j \in T | (p\_{i\nu} t\_j) \in F \}.$$

**Definition 2.3. (Input and output places of a transition)** The set of input places of a transition *tj* ∈ *T* is:

$$\text{label} = \bullet \\ t\_{\slash} = \{ p\_i \in P | (p\_{i\prime} t\_{\not\choose j}) \in F \}.$$

and the set of output places of a transition *tj* ∈ *T* is:

$$\text{label} = t\_{\hat{j}} \bullet = \{ p\_i \in P | (t\_{j'} p\_i) \in F \}.$$

### *2.2.1. Marked Petri nets*

A marking (also named token) has a primitive concept in PNs such as place and transitions. Markings are information attributed to places; the number and mark distributions consist of the net state in determined moment. The formal definitions are presented as follows.

outlines its respective graphical representation, and Figure 3 (c) provides the same graphical representation after the firing of *t*0. For this example, the set of reachable markings is m = {*m*0 = (3, 1, 0), *m*1 = (1, 0, 2)}. The marking *m*1 was obtained by firing *t*0, such that, *m*1(*p*0) =

A Petri Net-Based Approach to the Quanti cation of Data Center Dependability 317

**Figure 3.** (a) Mathematical formalism; (b) Graphical representation before the firing of *t*0; (c) Graphical

There are two particular cases which the firing rule happens differently. The first one is a transition without any input place that is called as a *source* transition, and the other one is a transition without any output place, named *sink* transition. A *source* transition is unconditionally enabled, and the firing of a *sink* transition consumes tokens, but does not produce any. Figure 4 (a) shows a *source* transition, and Figure (b) 4 depicts a *sink* transition.

**Definition 2.7. (Source transitions)** A transition is said to be source if, and only if, *I*(*p*, *t*) = 0,

**Definition 2.8. (Sink transitions)** A transition is said to be sink if, and only if, *O*(*p*, *t*) = 0,

**Definition 2.9. (Inhibitor arc)** Originally not present in PN, the introduction of the concept of inhibitor arc increases the modeling power of PN, adding the ability of testing if a place does not have tokens. In the presence of an inhibitor arc, a transition is enabled to fire if each input place connected by a normal arc has a number of tokens equal to the arc weight, and if each input place connected by an inhibitor arc has no tokens. Figure 5 illustrates an inhibitor arc connecting the input place *p*0 to the transition *t*0, which is denoted by an arc finished with a

In both, the markings are represented before and after their respective firing.

3 - 2 + 0, *m*1(*p*1) = 1 - 1 + 0, and *m*1(*p*2) = 0 - 0 + 2.

representation after the firing of *t*0.

**Figure 4.** (a) *Source* transitions; (b) *Sink* transitions.

small circle. In such Figure, the transition *t*0 is enabled to fire.

∀*p* ∈ *P*.

∀*p* ∈ *P*.

**Definition 2.4. (Marking)** Considering the set of places *P* in a net *N*, the formal definition of marking is represented by a function that maps the set of places P into non negative integers *M* : *P* → **N**.

**Definition 2.5. (Marking vector)** Considering the set of places *P* in a net *N*, the marking can be defined as a vector *M* = (*M*(*p*1), ..., *M*(*pn*)), where *n* = #(*P*), ∀*pi* ∈ *P* / *M*(*pi*) ∈ **N**. Thus, such vector gives the number of tokens in each place for the marking *Mi*.

**Definition 2.6. (Marked net)** A marked Petri net is defined by a tupla *NM* = (*N*; *M*0), where

*N* is the net structure and *M*0 is the initial marking.

A marked Petri net contains tokens, which reside in places, travel along arcs, and their flow through the net is regulated by transitions. A peculiar distribution (M) of the tokens in the places, represents a specific state of the system. These tokens are denoted by black dots inside the places as shown in Figure 1 (d).

### *2.2.2. Transition enabling and firing*

The behavior of many systems can be described in terms of system states and their changes. In order to simulate the dynamic behavior of a system, a state (or marking) in a Petri net is changed according to the following firing rule:

Figure 3 (a) shows the mathematical representation of a Petri net model with three places (*p*0, *p*1, *p*2) and one transition (*t*0). Besides, there is one arc connecting the place *p*0 to the transition *t*0 with weight two, one arc from the place *p*1 to the transition *t*0 with weight one, and one arc connecting the transition *t*0 to the place *p*2 with weight two. The initial marking (*m*0) is represented by three tokens in the place *p*0 and one token in the place *p*1. Figure 3 (b) outlines its respective graphical representation, and Figure 3 (c) provides the same graphical representation after the firing of *t*0. For this example, the set of reachable markings is m = {*m*0 = (3, 1, 0), *m*1 = (1, 0, 2)}. The marking *m*1 was obtained by firing *t*0, such that, *m*1(*p*0) = 3 - 2 + 0, *m*1(*p*1) = 1 - 1 + 0, and *m*1(*p*2) = 0 - 0 + 2.

**Figure 3.** (a) Mathematical formalism; (b) Graphical representation before the firing of *t*0; (c) Graphical representation after the firing of *t*0.

There are two particular cases which the firing rule happens differently. The first one is a transition without any input place that is called as a *source* transition, and the other one is a transition without any output place, named *sink* transition. A *source* transition is unconditionally enabled, and the firing of a *sink* transition consumes tokens, but does not produce any. Figure 4 (a) shows a *source* transition, and Figure (b) 4 depicts a *sink* transition. In both, the markings are represented before and after their respective firing.

**Figure 4.** (a) *Source* transitions; (b) *Sink* transitions.

4 Petri Nets

A marking (also named token) has a primitive concept in PNs such as place and transitions. Markings are information attributed to places; the number and mark distributions consist of

**Definition 2.4. (Marking)** Considering the set of places *P* in a net *N*, the formal definition of marking is represented by a function that maps the set of places P into non negative integers

**Definition 2.5. (Marking vector)** Considering the set of places *P* in a net *N*, the marking can be defined as a vector *M* = (*M*(*p*1), ..., *M*(*pn*)), where *n* = #(*P*), ∀*pi* ∈ *P* / *M*(*pi*) ∈ **N**. Thus,

**Definition 2.6. (Marked net)** A marked Petri net is defined by a tupla *NM* = (*N*; *M*0), where

A marked Petri net contains tokens, which reside in places, travel along arcs, and their flow through the net is regulated by transitions. A peculiar distribution (M) of the tokens in the places, represents a specific state of the system. These tokens are denoted by black dots inside

The behavior of many systems can be described in terms of system states and their changes. In order to simulate the dynamic behavior of a system, a state (or marking) in a Petri net is

1. A transition *t* is said to be enabled, if each input place *p* of *t* is marked with at least the number of tokens equal to the multiplicity of its arc connecting p with *t*. Adopting a mathematical notation, an enabled transition *t* for given marking *mi* is denoted by *mi*[*t* >,

2. An enabled transition may or may not fire (depending on whether or not the respective

3. The firing of an enabled transition *t* removes tokens (equal to the multiplicity of the input arc) from each input place *p*, and adds tokens (equal to the multiplicity of the output

represented by the equation *mj*(*p*) = *mi*(*p*) − *W*(*p*, *t*) + *W*(*t*, *p*), ∀*p* ∈ *P*. If a marking *mj* is

Figure 3 (a) shows the mathematical representation of a Petri net model with three places (*p*0, *p*1, *p*2) and one transition (*t*0). Besides, there is one arc connecting the place *p*0 to the transition *t*0 with weight two, one arc from the place *p*1 to the transition *t*0 with weight one, and one arc connecting the transition *t*0 to the place *p*2 with weight two. The initial marking (*m*0) is represented by three tokens in the place *p*0 and one token in the place *p*1. Figure 3 (b)

reachable from *mi* by firing a transition *t*, it is denoted by *mi*[*t* > *mj* .

. Using a mathematical notation, the firing of a transition is

the net state in determined moment. The formal definitions are presented as follows.

such vector gives the number of tokens in each place for the marking *Mi*.

*N* is the net structure and *M*0 is the initial marking.

changed according to the following firing rule:

the places as shown in Figure 1 (d).

*2.2.2. Transition enabling and firing*

if *mi*(*pj*) ≥ *W*(*pj*, *t*), ∀*pj* ∈ *P*.

arc) to each output place *p*�

event takes place).

*2.2.1. Marked Petri nets*

*M* : *P* → **N**.

**Definition 2.7. (Source transitions)** A transition is said to be source if, and only if, *I*(*p*, *t*) = 0, ∀*p* ∈ *P*.

**Definition 2.8. (Sink transitions)** A transition is said to be sink if, and only if, *O*(*p*, *t*) = 0, ∀*p* ∈ *P*.

**Definition 2.9. (Inhibitor arc)** Originally not present in PN, the introduction of the concept of inhibitor arc increases the modeling power of PN, adding the ability of testing if a place does not have tokens. In the presence of an inhibitor arc, a transition is enabled to fire if each input place connected by a normal arc has a number of tokens equal to the arc weight, and if each input place connected by an inhibitor arc has no tokens. Figure 5 illustrates an inhibitor arc connecting the input place *p*0 to the transition *t*0, which is denoted by an arc finished with a small circle. In such Figure, the transition *t*0 is enabled to fire.

**Fork**

**Join**

**Choice**

**Merging**

the figure). **Confusions**

the end of predecessor processes.

will be in conflict with *t*3 if *t*2 fires first.

**Figure 8.** (a) symmetric confusion; (b) asymmetric confusion.

**2.4. Petri nets modeling examples**

Figure 7(b) shows an example of a fork structure that allows the creation of parallel processes.

A Petri Net-Based Approach to the Quanti cation of Data Center Dependability 319

Generally, concurrent activities need to synchronize with each other. This net (Figure 7(c)) combines two or more nets, allowing that another process continues this execution only after

Figure 7(d) depicts a choice model, in which the firing of the transition *t*0 disables the transition *t*1. This building block is suited for modeling if-then-else statement, for instance.

The merging is an elementary net that allows the enabling of the same transition by two or more processes. Figure 7(e) shows a net with two independent transitions (*t*0 and *t*1) that have an output place in common (*P*2). Therefore, firing of any of these two transitions, a condition is created (*p*2 is marked) which allows the firing of another transition (not shown in

The mixing between conflict and concurrency is called confusion. While conflict is a local phenomenon in the sense that only the pre-sets of the transitions with common input places are involved, confusion involves firing sequences. Figure 8 depicts two types of confusions: (a) symmetric confusion, where two transitions *t*1 and *t*3 are concurrent while each one is in conflict with transition *t*2; and (b) asymmetric confusion, where *t*1 is concurrent with *t*2, but

In this section, several simple examples are given in order to introduce how to model some

basic concepts such as parallel process and mutual exclusion in Petri nets.

**Figure 5.** PN with an inhibitor arc.

**Definition 2.10. (Pure net)** A Petri net is said to be pure if it has no self-loops. A pair of a place *p* and transition *t* is called a self-loop if *p* is both an input and output place of *t*. Figure 6 shows a self-loop net.

**Figure 6.** Self-Loop.

#### **2.3. Elementary structures**

Elementary nets are used as building blocks in the specification of more complex applications. Figure 7 shows five structures, namely, (a) sequence, (b) fork, (c) synchronization, (d) choice, and (e) merging.

**Figure 7.** Elementary PN Structures.

#### **Sequence**

Sequence structure represents sequential execution of actions, provided that a condition is satisfied. After the firing of a transition, another transition is enabled to fire. Figure 7(a) depicts an example of this structure in which a mark in place *p*0 enables the transition *t*0. The firing of transition *t*0 enables the transition *t*1 (*p*1 is marked).

#### **Fork**

6 Petri Nets

**Definition 2.10. (Pure net)** A Petri net is said to be pure if it has no self-loops. A pair of a place *p* and transition *t* is called a self-loop if *p* is both an input and output place of *t*. Figure

Elementary nets are used as building blocks in the specification of more complex applications. Figure 7 shows five structures, namely, (a) sequence, (b) fork, (c) synchronization, (d) choice,

Sequence structure represents sequential execution of actions, provided that a condition is satisfied. After the firing of a transition, another transition is enabled to fire. Figure 7(a) depicts an example of this structure in which a mark in place *p*0 enables the transition *t*0. The

**Figure 5.** PN with an inhibitor arc.

6 shows a self-loop net.

**Figure 6.** Self-Loop.

and (e) merging.

**2.3. Elementary structures**

**Figure 7.** Elementary PN Structures.

firing of transition *t*0 enables the transition *t*1 (*p*1 is marked).

**Sequence**

Figure 7(b) shows an example of a fork structure that allows the creation of parallel processes.

#### **Join**

Generally, concurrent activities need to synchronize with each other. This net (Figure 7(c)) combines two or more nets, allowing that another process continues this execution only after the end of predecessor processes.

#### **Choice**

Figure 7(d) depicts a choice model, in which the firing of the transition *t*0 disables the transition *t*1. This building block is suited for modeling if-then-else statement, for instance.

#### **Merging**

The merging is an elementary net that allows the enabling of the same transition by two or more processes. Figure 7(e) shows a net with two independent transitions (*t*0 and *t*1) that have an output place in common (*P*2). Therefore, firing of any of these two transitions, a condition is created (*p*2 is marked) which allows the firing of another transition (not shown in the figure).

#### **Confusions**

The mixing between conflict and concurrency is called confusion. While conflict is a local phenomenon in the sense that only the pre-sets of the transitions with common input places are involved, confusion involves firing sequences. Figure 8 depicts two types of confusions: (a) symmetric confusion, where two transitions *t*1 and *t*3 are concurrent while each one is in conflict with transition *t*2; and (b) asymmetric confusion, where *t*1 is concurrent with *t*2, but will be in conflict with *t*3 if *t*2 fires first.

**Figure 8.** (a) symmetric confusion; (b) asymmetric confusion.

#### **2.4. Petri nets modeling examples**

In this section, several simple examples are given in order to introduce how to model some basic concepts such as parallel process and mutual exclusion in Petri nets.

#### **Parallel processes**

In order to represent parallel processes, a model may be obtained by composing the model for each individual process with a fork and synchronization models. Two transitions are said to be parallel (or concurrent), if they are causally independent, i.e., one transition may fire either before (or after) or in parallel with the other.

**Dataflow computation**

dataflow computation is completed.

**Figure 11.** Dataflow example.

**2.5. Petri nets properties**

*2.5.1. Behavioral properties*

**Reachability**

on the other hand, are those that are marking-independent.

very important when analyzing a given system.

Petri nets can be used to represent not only the control-flow but also the data-flow. The net shown in Figure 11 is a Petri net representation of a dataflow computation. A dataflow is characterized by the concurrent instruction execution (or transitions firing) as soon as the operands (pre-conditions) are available. In the Petri net representation, tokens may denote values of current data as well as the availability of data. The instructions are represented by transitions such as *Add* and *Subtract* that can be executed in parallel. After that, if the activity *Subtract* has computed a result different from zero, meaning that the pre-conditions to perform *divide* operation were satisfied. Afterwards, when the transition *divide* occur, the

A Petri Net-Based Approach to the Quanti cation of Data Center Dependability 321

The PN properties allow a detailed analysis of the modeled system. For this, two types of properties have been considered in a Petri net model: behavioral and structural properties. Behavioral properties are those which depend on the initial marking. Structural properties,

This section, based on [14], describes some behavioral properties, since such properties are

The firing of an enabled transition changes the token marking in a Petri net, and a sequence of firings results in a sequence of markings. A marking *Mn* is said to be reachable from a

A firing (or occurrence) sequence is denoted by *σ* = *t*1, *t*2, ...,*tn*. In this case, *mi* is reachable from *m*0 by *σ*, and it is denoted by *m*0[*σ* > *mi*. The set of all possible reachable markings from *m*0 in a net (PN, *m*0) is denoted by R(PN,*m*0), or simply R(*m*0). The set of all possible firing sequence from *m*0 in a net (PN,*m*0) is denoted by L(PN, *m*0), or simply L(*m*0).

marking *M*0 if there exists a sequence of firings that transforms *M*0 to *Mn*.

Figure 9 depicts an example of parallel process, where transitions *t*1 and *t*2 represent parallel activities. When transition *t*0 fires, it creates marks in both output places (*p*0 and *p*1), representing a concurrency. When *t*1 and *t*2 are enabled for firing, each one may fire independently. The firing of *t*3 depends on two pre-conditions, *p*2 and *p*3, implying that the system only continues if *t*1 and *t*2 have been fired.

Figure 9 presents a net in which each place has exactly one incoming arc and exactly one outgoing arc. Thus, such model represents a sub-class of Petri nets known as marked graphs. Marked graphs allow representation of concurrency but not decisions or conflicts.

**Figure 9.** A Petri net representing parallel activities.

#### **Mutual exclusion**

The sharing of resources and/or data are common in many system applications, in which most of resources and data should be accessed in a mutual exclusive way. Resources (or data variable) may be modeled by a place with tokens representing the amount of resources. This place is seen as pre-conditions for all transitions that need such resource. After the use of one resource, it must be released. Figure 10 depicts an example of a machine that is accessed in a mutual exclusive way.

**Figure 10.** Mutual Exclusion.

#### **Dataflow computation**

8 Petri Nets

In order to represent parallel processes, a model may be obtained by composing the model for each individual process with a fork and synchronization models. Two transitions are said to be parallel (or concurrent), if they are causally independent, i.e., one transition may fire either

Figure 9 depicts an example of parallel process, where transitions *t*1 and *t*2 represent parallel activities. When transition *t*0 fires, it creates marks in both output places (*p*0 and *p*1), representing a concurrency. When *t*1 and *t*2 are enabled for firing, each one may fire independently. The firing of *t*3 depends on two pre-conditions, *p*2 and *p*3, implying that the

Figure 9 presents a net in which each place has exactly one incoming arc and exactly one outgoing arc. Thus, such model represents a sub-class of Petri nets known as marked graphs.

The sharing of resources and/or data are common in many system applications, in which most of resources and data should be accessed in a mutual exclusive way. Resources (or data variable) may be modeled by a place with tokens representing the amount of resources. This place is seen as pre-conditions for all transitions that need such resource. After the use of one resource, it must be released. Figure 10 depicts an example of a machine that is accessed in a

Marked graphs allow representation of concurrency but not decisions or conflicts.

**Parallel processes**

before (or after) or in parallel with the other.

system only continues if *t*1 and *t*2 have been fired.

**Figure 9.** A Petri net representing parallel activities.

**Mutual exclusion**

mutual exclusive way.

**Figure 10.** Mutual Exclusion.

Petri nets can be used to represent not only the control-flow but also the data-flow. The net shown in Figure 11 is a Petri net representation of a dataflow computation. A dataflow is characterized by the concurrent instruction execution (or transitions firing) as soon as the operands (pre-conditions) are available. In the Petri net representation, tokens may denote values of current data as well as the availability of data. The instructions are represented by transitions such as *Add* and *Subtract* that can be executed in parallel. After that, if the activity *Subtract* has computed a result different from zero, meaning that the pre-conditions to perform *divide* operation were satisfied. Afterwards, when the transition *divide* occur, the dataflow computation is completed.

**Figure 11.** Dataflow example.


4.1.2. Spanish FUA Classification: Many Diversifying Realities

In addition to core–periphery differences, Spanish urban areas can also be grouped according to their recent population changes.

Hence, these results show that FUAs are now quite diverse, making it harder to establish general urban development guidelines. However, all of their growth figures are now much lower than those at the beginning of the 21st century.


Antioxidant-Rich Vegetables: Impact on Human Health

*Anne Adebukola Adeyanju, Omolola Rebecca Oyenihi and Oluwafemi Omoniyi Oguntibeju*

## **Abstract**

Antioxidants are valuable ingredients present in vegetables. Vegetables are essential and crucial in human's health and diet because of their minerals, antioxidant vitamins, phytochemical compounds, and dietary fibre content. This is the reason why an adequate consumption of vegetables has been linked with reduced risk and protection against various chronic diseases. Notably, each vegetable belongs to a group that contains a unique quantity of phytochemical compounds, which distinguish them from other groups and even within their group. The exact mechanisms by which the consumption of vegetables protects against human diseases are yet to be fully understood. However, the phytochemicals present in vegetables could be responsible for attenuating some of them. These phytochemicals are strong antioxidants that reduce the risk of chronic diseases by mounting resistance against the generation of free radicals and their damage. They are also involved in the modification of metabolic activation, detoxification of carcinogenic compounds, or attack of tumour formation in cells. This review highlights the inherent antioxidant potentials of vegetables, their roles as an excellent source of antioxidants and their impact on human health and diseases. Information provided in this review will provide more insight into the roles of antioxidants present in vegetables.

**Keywords:** antioxidant, vegetable, phytochemical, disease, free radical

### **1. Introduction**

These days, the new trend of consumption of foods in our society is for the "natural and healthy," which includes vegetables and fruits in the diet. "Western" type diets involve a high intake of food with much calories and animal protein with low consumption of vegetables. The resultant effect of this type of diet with physical inactivity is the development of diseases such as diabetes, obesity and cancer [1]. Therefore, the search for vegetables continues to gain attention as they are known to contain bioactive compounds with medicinal values that can offer healthy diet, build up the body's defences and help to prevent diseases [2].

Vegetables are large class of plants serving numerous purposes in the medicine, food and beverage industry. Their leaves, stems, seeds and flowers are useful for feeding, as flavours and colourants. They are plants of great importance in our diet. They are protective foods that are of great benefit in maintaining good health, building and repairing the body and preventing diseases because of the large number of essential nutrients they contain. They are rich in antioxidants like

carotenoids, ascorbic acid, flavonoids, folic acid and minerals like calcium, iron, phosphorus, phenolic compounds, proanthocyanidins, vitamins and saponins [3]. These phytochemicals exhibit multiple biological effects such as antioxidant, antiinflammatory, antimicrobial and anti-cancer activities. Particularly, the antioxidative activity of phenolic compounds is highly recognised and this is attributed to their chain-breaking and free radical scavenging abilities, which remove free radical intermediates, thereby offering protection against the production of reactive oxygen species [3]. Excessive production of reactive oxygen species (ROS) can cause oxidative damage to biological macromolecules such as nucleic acids and proteins [4].

In rural areas, vegetables form an integral component of the food and nutrition of the local population as they are traditionally reckoned for their medicinal, therapeutic and nutritional values since time immemorial. They are either consumed as raw or cooked as traditional delicacies and the sales from the surplus of these vegetables serve as an additional income to many families. Moreover, to this set of population, vegetable consumption gives variety to their food and add flavours to the diet. It is rich in various nutritive elements and can make up for the dietary shortfalls of vitamins and minerals necessary for the human diet. Generally, malnutrition and food shortages are prevalent among the rural population. Thus, the cultivation of vegetables will contribute to increased food production, balanced nutrition, food and health security and poverty eradication for them.

Study revealed that before the nineteenth century, there has been a particular interest in vegetables and herbs because of the beneficial effects of phytochemicals present in them [5]. They were being used for therapeutic purposes until synthetic drugs were developed. Their consumption has drawn great attention due to the discovery of the fact that, their regular intake has an alliance with declined rates of heart diseases, cancers, diabetes, and other degenerative diseases. Protection that vegetable offer has been ascribed to the presence of antioxidative compounds such as α- tocopherol, ascorbic acid [6] and phytochemicals like carotenoids, flavonoids, lycopene, phenolics and β-carotene [7–9]. These compounds are free radical scavengers, hydrogen-donating compounds, metal ion chelators with ability to inhibit generation of free radicals and reactive oxygen species (ROS) [10].

Thus, this review draws attention to the bioactive compounds present in our vegetables, their biological importance and elucidation of their roles in disease prevention and health.

#### **2. Antioxidant potential of vegetables**

Antioxidants are defined as substances which when present at low concentration compared to those of an oxidizable substrate [11], significantly delay or prevent the oxidation of that substrate. Some of the mechanisms of action of antioxidants involve prevention of lipid peroxidation, oxidative damage to membranes, glycation of proteins and inactivation of enzymes caused by free radicals. Oxidative stress can arise due to the generation of ROS including free radicals and non-free radicals. Evidences have shown that they have roles in the development of several diseased conditions such as lipid peroxidation, protein oxidation, DNA damage and cellular degeneration [12, 13].

Normally, during cellular metabolism, free radicals and other reactive oxygen species are continuously released in the body. They can also be produced from sources such as drugs, food, exhausts and other pollution from the environment. Organisms are endued with endogenous and exogenous antioxidant defence systems against free radical generation. However, when free radical produced in

the body overwhelms the antioxidant system, oxidative stress ensues. This has implications in the aetiology of several pathological conditions [14]. This is the reason for the special attention being given to the use of antioxidants especially of natural origin.

Antioxidant phytochemicals have been recognised for the role they play in the prevention and management of chronic diseases [15]. Phytochemicals are proven to have antioxidant capacities in humans*.* Consumption of vegetables with high contents of these compounds is liable to raise the antioxidant capacity of the body system. For instance, serum total antioxidant capacity was found to be elevated significantly following the consumption of spinach in elderly women [16]. Further, a study has also supported a significant increase in antioxidant capacity caused by the daily consumption of 10 servings of fruit and vegetables for a period of 15 days [17].

Given the growing prospect observed in these phytochemicals, there is a need to identify and quantify them, elucidate their mechanisms of action and assess their potential health benefits. This information could serve as a basis for intervention strategies.

The phytochemical content of some vegetables like Broccoli, Brussels sprout, green cabbage have been revealed [18]. α- and β-carotene are richly present in broccoli (1 and 779 mg/100 FW), carrot (4.6 and 8.8 mg/100 FW), tomato (112 and 393 mg/100 FW), pea (19 and 485 mg/100 FW), and sweet pepper (59 mg/100 FW). However, some factors such as level of growth, handling during post harvesting, and processing could contribute to the significant variation that sometimes occur in structure and function of phytochemicals from vegetable to vegetable [19]. Vegetables such as beans, broccoli, cabbage, cauliflower, cress, pea, spinach, spring onion, and sweet peppers are reported to be rich in ascorbic acid [20]. Asparagus, Brussels sprout, cabbage, carrot, cauliflower, kale, lettuce, spinach, sweet potato, and turnip are abundant in vitamin E [18] while red pepper is high in vitamin C content (144 mg/100 g) [21].

Furthermore, the structure can influence the antioxidant capability of a phytochemical in vegetables. For instance, the antioxidant properties of flavonoids depend on their C-ring structure. Flavonoids like rutin and luteolin with full substituted C-ring and an ether bonded with three oxygen display superior free radical scavenging capacity and higher reaction rate when compared to flavonoids that lack one or more C ring structural elements. Also, individual phenolic units in vegetables have been found to show better antioxidant activity than total phenolics. Generally, the high scavenging property of vegetables with phenolic content may be as a result of hydroxyl groups existing in the phenolic compounds' chemical structure that can provide the needed component for radical scavenging activity (**Figure 1**). The hydrogen atoms of the adjacent hydroxyl groups, situated in various positions of the rings A, B and C, the double bonds of the benzene ring, and the double bond of the oxo functional group (-C**=**O) of some flavonoids, offer them their high antioxidant activity. These structural features are shown in the

**Figure 1.** *Free radical scavenging of flavonoids where R is the radical and Fl-OH is the flavonoid.*

benzene rings of flavonoids as shown in **Figure 2**. The antioxidant ability centre of phenolic acids is in the phenolic hydroxyl group, such that the positioning of phenolic hydroxyls is directly related to their antioxidant activity [22].

The impartation of colours is also an important factor in the antioxidative activity of phytochemicals in vegetables (**Table 1**). It is said to be directly related to the pigment content such as carotene, phytoene, chlorophyll, lycopene and anthocyanin, and their relative quantities at different maturity stages. It is an important trait that largely reflects quality, type of phytochemical as well as antioxidant activity [30]. Jaganath and Crozier [31] inferred that colour difference as observed in vegetables and fruits is an indication of accumulation of phytochemicals such as flavonoids and carotenoids. Red pigment conferred on red bell peppers is linked to a large content of lycopene, a member of the carotenoid family, localised in the prostate gland. Lycopene is a powerful antioxidant that has a connection with lessened risk of some cancers, especially prostate cancer [23], and protection against heart attacks. The yellow or orange colouration noticed in vegetables such as spinach, sweet potatoes and carrots represents produce rich in both α and β-carotene. They are also members of the carotenoid family where β-carotene can be converted to vitamin A in the body, a nutrient that plays a crucial role in vision. The mechanism involves the cleavage of β-carotene into two molecules of vitamin A which is then

#### **Figure 2.**

*Structural characteristics of flavonoids with high antioxidant activity; presence of hydroxyl groups and double bonds (circled) in the benzene rings.*

#### **Table 1.**

*Impartation of colours in vegetables and their health benefits.*

converted to II-cis-retinal and thereafter combines with opsin to form a protein called rhodopsin. When light hits the rods, metarhodopsin is produced [24]. Betacarotenes in vegetables are also involved in improving immune function, skin and bone health as well as prevention of cancer [25].


**Chapter 13**

2017 Applications, Trends and Opportunities. 2–4 November 2017; TUIT, Tashkent, Uzbekistan. IEEE Catalog Part Number: CFP17H74-CDR, ISBN: 978-1-5386-2167-7. Available from: https://www.researchgate.net/

*Design and Manufacturing*

[20] Juraev TX. Conceptual designing of mould board's surface by geometrical modeling. American Journal of

engineering provision of agriculture production. The collection materials of

VIII-th International scientific conference "Modern technologies in agricultural production and education."

Kemerovo, Russia: KSIA. 2017. Available from: http://www.ksai.ru/ upload/files/sborniki/inyaz\_2017/files/ assets/basic-html/page119.html

[26] Matejun M. The process of opportunities exploration and exploitation in the development of SMEs' innovativeness. Management and Production Engineering Review. 2018; **9**(3):3-15. DOI: 10.24425/119529

[27] Juraev TX. Geometric modeling of agriculture and meliorative machines' tools [abstract of PhD dissertation]. Tashkent University of Information Technologies; 2019. Available from:

www.tuit.uz

Mechanics and Applications. 2017;**5**(4):

20170504.11. ISSN: 2376-6115 (Print); ISSN: 2376-6131 (Online). Available from: http://www.ajmechanics.org/arch

[21] Flat plowing plow. SU1732826 (A1)- 1992-05-15 Available from: http://www.

[22] Juraev TX. Decision maintenance management problems in agriculture engineering by constructive geometric modeling methods. Maintenance Management. DOI: 10.5772 /

[24] Juraev TX. Geometric modeling for organizing innovative cluster on designing in agricultural machinery industry. Proceedings of the

international conference on integrated innovative development of Zarafshan region: achievements, challenges and prospects. Vol. II. 26–27 October, 2017. Navoi, Uzbekistan: NSMI. pp. 248-251

[25] Juraev TX. Geometrical modeling of agricultural machines as a mean of

**230**

28-33. DOI: 10.11648/j.ajma.

ive/621/6210504

IntechOpen.81969

[23] Jayakiran Reddy E, Venkatachalapathia N, Pandu Rangadu V. Development of an approach for knowledge-based system for CAD modeling. Selection and/or peer-review under responsibility of international conference on materials manufacturing and modeling (ICMMM-2017). Science direct. Materials Today: Proceedings. 2018;**5**:13375-13382

Espasenet

publication/321821311


**Author details**

/

Improvements in glycemic control were achieved, enabling progressive dosage reduction of the other drugs. At the time of publication, at age 5 months, the infant was on minimal doses of hyperglycemic agents and continued to receive twice-daily sirolimus at a dose of 0.3 mg/m2

Recently, exendin-(9-39), a GLP-1 receptor antagonist that raises blood glucose levels in adults, has been introduced as a possible novel therapy for management of hypoglycemia in patients with CHH. However, further studies on its effectiveness and safety are needed [8].

Growth hormone is used in cases of hypoglycemia associated with deficiency of this hormone

In cases of hypoglycemia due to persistent hyperinsulinemic hypoglycemia that does not respond to treatment with diazoxide, glucose, and sirolimus, partial pancreatectomy may be

Recurrent or sustained hypoglycemia can cause neurological damage, mental retardation, epilepsy, and personality disorders [54]. Transient episodes of hypoglycemia are also associ-

Severe hypoglycemia can lead to impairment of cardiovascular function and is associated

Permanent brain damage is found in 25–50% of patients with recurrent severe symptomatic hypoglycemia under age 6 months. Furthermore, hypoxemia and ischemia may potentiate the permanent damage caused by hypoglycemia. The pathological changes described include gyral atrophy, reduced white-matter myelination, and cerebral cortical atrophy. It bears noting that the cerebral infarctions characteristic of hypoxic-ischemic processes are absent in

Newborns with risk factors for neonatal hypoglycemia or those which, although not considered at risk, exhibit poor suckling or inadequate breast milk intake should receive follow-up monitoring and care after hospital discharge, so as to prevent possible undetected

ated with deficits in math learning around age 10 years [26].

hypoglycemia-associated brain injury [51].

**10. Final considerations**

hypoglycemia.

with high rates of neonatal mortality in very low-birth-weight infants [15].

day, without any complications.

76 Selected Topics in Neonatal Care

*8.3.7. Exendin*

*8.3.8. Other drugs*

indicated.

or with hypopituitarism.

**9. Consequences**

Adauto Dutra Moraes Barbosa\*, Israel Figueiredo Júnior and Gláucia Macedo de Lima

\*Address all correspondence to<EMAIL_ADDRESS>
Fondazione IRCCS Policlinico San Matteo, Pavia, Italy


*Supporting open minds since 2005*

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#### Contributors

Sergey G. Grigori Rusakov, Vladimir V. Rakitin, Xiaohan Wu, Ruijing Ge, Deji Akinwande, Jack C. Lee, Firman Simanjuntak, Sridhar Chandrasekaran, Debashis Panda, Aftab Salem, Themis Prodromakis, Mangal Das, Sandeep Kumar, Ai-Dong Li, Chang Liu, Lin Zhu, Lai-Guo Wang, Amirali Amirsoleimani, Dominique Drouin, Roman Genov, Fabien Alibart, Tony Liu, Serge Eccofey, Yao-Feng Chang, Ronald Tetzlaff, Alon Ascoli, Ahmet Şamil Demirkol, Ioannis Messaris, Majid Ahmadi, Mehri Teimoori, Arash Ahmadi

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**8. Rehabilitation team for pain patients**

The obligatory condition for the staff in Pain management is to have competencies in several thematic fields: Pain theories and the correspondent clinical field.

From the point of view of rehabilitation, the objective must be to assure the quality of life and the dignity of these patients. Our problem is the quality of care of pain patients. For us the most important is to guarantee the quality of life of pain patient.

The multi-disciplinary multi-professional team for pain patients must include:


**Author details**

Reyhaneh Farghadani\* and Rakesh Naidu\* Jeffrey Cheah School of Medicine and Health Sciences, Monash University Malaysia, Bandar Sunway, Selangor Darul Ehsan, Malaysia

\*Address all correspondence to<EMAIL_ADDRESS><EMAIL_ADDRESS>and<EMAIL_ADDRESS>
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*The Role of Apoptosis as a Double-Edge Sword in Cancer DOI: http://dx.doi.org/10.5772/intechopen.97844*


**1. Introduction**

[17] Leite RG. Cañas C, Forsberg B, Barthem R, Goulding M. Larvas dos Grandes Bagres Migradores. Instituto Nacional de Pesquisas da Amazônia (INPA) - Asociación para

[18] Lewis WM. Saunders III JF. Two new integrating samplers for zooplankton, and wa‐

[19] hlstrom EH, Moser HG. Eggs and larvae of fishes and their role in systematic investi‐ gations and in fisheries. Revue des Travaux de l'Institut des Pêches Maritimes 1976;

[20] Snyder DE. Terminologies of intervals for larval fish development. In: J. Boreman (Ed.) Great Lakes Fish Eggs and Larval Identification. U.S. Fisheries and Wildlife

[21] Araujo-Lima CARM. Larval development and reproductive strategies of Amazonian

[22] Torrente-Vilara G. Heterogeneidade ambiental e diversidade ictiofaunística do tre‐ cho de corredeiras do rio Madeira, Rondônia, Brasil. PhD Thesis. Manaus, Instituto Nacional de Pesquisas da Amazônia (INPA)/Fundação Universitária do Amazonas

[23] Bialetzki A, Sanches PV, Cavicchioli, M, Baumgartner, G, Ribeiro, RP, Nakatani K.. Drift of ichthyoplankton in two channels of the Paraná River, between Paraná and Mato Grosso do Sul states, Brazil. Brazilian Archives of Biology and Technology 1999. http://www.scielo.br/pdf/babt/v42n1/v42n1a08.pdf (accessed 18 September

[24] Marcano D, Cardillo E, Rodriguez C., Poleo G, Gago N, Guerrero H.Y. Seasonal re‐ productive biology of two species of freshwater catfish from the Venezuelan flood‐

[25] Carvalho, N. de O., Filizola Jr., N. P., Santos, P. M. C. dos, and Lima, J. E. F. W., 2000

plains. General and Comparative Endocrinology 2007; 153(1-3): 371-377.

fishes. PhD Thesis. Oban, Argyll, Scotland, University of Sterling; 1990.

la Conservación de la Cuenca Amazónica (ACCA). Lima, Peru; 2007.

ter chemistry. Archiv für Hydrobiologie 1979; 85(2):244-249.

40(3-4) 379-398

158 Biodiversity - The Dynamic Balance of the Planet

1976: 41-58.

(FUA); 2009

2013).

Arbuscular Mycorrhizal Fungi (AMF) are a group of obligate biotrophs, to the extent that they must develop a close symbiotic association with the roots of a living host plant in order to grow and complete their life cycle [1]. The term "mycorrhiza" literally derives from the Greek *mykes* and *rhiza*, meaning fungus and root, respectively. AMF can symbiotically interact with almost all the plants that live on the Earth. They are found in the roots of about 80-90% of plant species (mainly grasses, agricultural crops and herbs) and exchange benefits with their partners, as is typical of all mutual symbiotic relationships [2]. They represent an interface between plants and soil, growing their mycelia both inside and outside the plant roots. AMF provide the plant with water, soil mineral nutrients (mainly phosphorus and nitrogen) and pathogen protection. In exchange, photosynthetic compounds are transferred to the fungus [3].

Taxonomically, all AMF have been affiliated to a monophyletic group of fungi, i.e. the Glomeromycota phylum [4]. They are considered to be living fossils since there is evidence that their presence on our planet dates back to the Ordovician Period, over 460 million years ago [5]. Investigations on AMF taxonomy began in the nineteenth century with the first description of two species belonging to the genus *Glomus* [6]. Since that date, many Glomer‐ omycotan species, genus and families have been discovered and characterized by means of traditional approaches based on the phenotypic characteristics (mainly spore morphology). Molecular DNA sequencing-based analyses have recently contributed to a great extent by shedding light on a previously unseen and profound diversity within this phylum [7].

© 2014 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.

Nevertheless, an open debate on the phylogeny of AMF, and in particular concerning some taxonomical groups, is still puzzling scientists [8–10] (Figure 1). Besides a general disagreement about the number of families and genera (Figure 1), what emerges from reference [8] is that Gigasporales are considered to be a separate order from Diversisporales. This is different from what has been reported in the tree on the right side of Figure 1, which was presented in reference [9], and supported by the recent reference [10].

Functionally, AMF form the so-called arbuscular mycorrhizae with plant roots. The most typical AMF structure, which also gives the name to this group of fungi, is the arbuscule (Figure 2). This structure, whose shape recalls that of a small shrub, forms inside the root cortical cells by branching in several very thin hyphae. In this way, the surface area, where the nutritional exchanges between the plant and fungus take place, is maximized. Fungal hyphae that grow between root cortical cells are able to produce other AMF structures, such as intercellular hyphae and vesicles (Figure 2). All these structures that grow inside the plant roots represent the intraradical phase of the fungus. Hyphae also grow outside the plant roots, and generate a network that extends over long distances and explores the soil beyond the nutrient depletion zone that normally characterizes the area surrounding the roots. At the end of the AMF life cycle, or in response to particular environmental conditions, spores (Figure 2) of variable size (up to 400 µm), depending on the species, are produced in the roots and/or in the soil. These, along with external explorative and running hyphae, represent the extraradical phase of the fungus. The synergic action of the intra-and extraradical phases is responsible for the ecological significance of the AMF, a soil-root-living key group of organisms [3].

#### **1.1. The ecological roles of AMF**

Arbuscular mycorrhizal fungi have a high relevance in many ecosystem processes. Since they can be found in many different plant species, they can provide their favorable services to almost all terrestrial ecosystems, from grasslands to forests, deserts and agroecosystems [11]. AMF can play several roles in such environments. The most agriculturally significant and frequently investigated one, from both the ecological and physiological points of view [12], is their positive effect on plant nutrition and, consequently, on plant fitness. In particular, they play a pivotal role in helping the plant uptake phosphorus from the soil [13]. Without AMF, it is rather difficult for the plant to absorb this macroelement from the soil, since it is mainly available in its insoluble organic or inorganic form. Besides phosphorus, AMF can also translocate water and other mineral nutrients (in particular nitrogen) from the soil to the plant. These nutritional exchanges are bidirectional. As a consequence, particularly efficient symbiotic associations have been demonstrated to stabilize through unknown mechanisms, with the plant selecting the most cooperative fungal partners and vice versa [14]. The AMF-inducible recovery of plant nutritional deficiency can inevitably lead to an improvement in plant growth, with a potential positive impact on productivity. Needless to say, AMF have attracted a great deal of interest from the agricultural world over the years [15].

of antioxidants, the increment of osmolyte production or the improvement of abscisic acid regulation [16,17], and the enhancement of plant tolerance to heavy metals [18]; (b) they help plants become established in harsh/degraded ecosystems, such as desert areas and mine spoils [19]; (c) they increase the power of phytoremediation (the removal of pollutants from the soil by plants) by allowing their host to explore and depollute a larger volume of soil [20,21]. Another crucial ecological role played by AMF is their capacity to directly influence the diversity and composition of the aboveground plant community. Several studies have

sequences (ca 1.8 kb).

**Figure 1.** A schematic representation of two recently published and partly controversial phylogenetic trees of the Glomeromycota phylum (reference [8] for the tree on the left side and [9] for the tree on the right side). The one pub‐ lished in reference [8] was based on molecular (SSU, ITS, partial LSU rDNA, and partial β-tubuline gene) and morpho‐ logical analyses (spore wall structures, structures of the spore bases and subtending hyphae, germination, and germination shield structures). The tree published in reference [9] was based on concatenated SSU rDNA consensus

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AMF are also responsible for other services that favour the plants they colonize: (a) they positively affect plant tolerance towards both biotic (e.g., pathogens) and abiotic stresses (i.e., drought and soil salinity) by acting on several physiological processes, such as the production

Nevertheless, an open debate on the phylogeny of AMF, and in particular concerning some taxonomical groups, is still puzzling scientists [8–10] (Figure 1). Besides a general disagreement about the number of families and genera (Figure 1), what emerges from reference [8] is that Gigasporales are considered to be a separate order from Diversisporales. This is different from what has been reported in the tree on the right side of Figure 1, which was presented in

Functionally, AMF form the so-called arbuscular mycorrhizae with plant roots. The most typical AMF structure, which also gives the name to this group of fungi, is the arbuscule (Figure 2). This structure, whose shape recalls that of a small shrub, forms inside the root cortical cells by branching in several very thin hyphae. In this way, the surface area, where the nutritional exchanges between the plant and fungus take place, is maximized. Fungal hyphae that grow between root cortical cells are able to produce other AMF structures, such as intercellular hyphae and vesicles (Figure 2). All these structures that grow inside the plant roots represent the intraradical phase of the fungus. Hyphae also grow outside the plant roots, and generate a network that extends over long distances and explores the soil beyond the nutrient depletion zone that normally characterizes the area surrounding the roots. At the end of the AMF life cycle, or in response to particular environmental conditions, spores (Figure 2) of variable size (up to 400 µm), depending on the species, are produced in the roots and/or in the soil. These, along with external explorative and running hyphae, represent the extraradical phase of the fungus. The synergic action of the intra-and extraradical phases is responsible for the ecological

Arbuscular mycorrhizal fungi have a high relevance in many ecosystem processes. Since they can be found in many different plant species, they can provide their favorable services to almost all terrestrial ecosystems, from grasslands to forests, deserts and agroecosystems [11]. AMF can play several roles in such environments. The most agriculturally significant and frequently investigated one, from both the ecological and physiological points of view [12], is their positive effect on plant nutrition and, consequently, on plant fitness. In particular, they play a pivotal role in helping the plant uptake phosphorus from the soil [13]. Without AMF, it is rather difficult for the plant to absorb this macroelement from the soil, since it is mainly available in its insoluble organic or inorganic form. Besides phosphorus, AMF can also translocate water and other mineral nutrients (in particular nitrogen) from the soil to the plant. These nutritional exchanges are bidirectional. As a consequence, particularly efficient symbiotic associations have been demonstrated to stabilize through unknown mechanisms, with the plant selecting the most cooperative fungal partners and vice versa [14]. The AMF-inducible recovery of plant nutritional deficiency can inevitably lead to an improvement in plant growth, with a potential positive impact on productivity. Needless to say, AMF have attracted a great deal of interest

AMF are also responsible for other services that favour the plants they colonize: (a) they positively affect plant tolerance towards both biotic (e.g., pathogens) and abiotic stresses (i.e., drought and soil salinity) by acting on several physiological processes, such as the production

reference [9], and supported by the recent reference [10].

significance of the AMF, a soil-root-living key group of organisms [3].

**1.1. The ecological roles of AMF**

160 Biodiversity - The Dynamic Balance of the Planet

from the agricultural world over the years [15].

**Figure 1.** A schematic representation of two recently published and partly controversial phylogenetic trees of the Glomeromycota phylum (reference [8] for the tree on the left side and [9] for the tree on the right side). The one pub‐ lished in reference [8] was based on molecular (SSU, ITS, partial LSU rDNA, and partial β-tubuline gene) and morpho‐ logical analyses (spore wall structures, structures of the spore bases and subtending hyphae, germination, and germination shield structures). The tree published in reference [9] was based on concatenated SSU rDNA consensus sequences (ca 1.8 kb).

of antioxidants, the increment of osmolyte production or the improvement of abscisic acid regulation [16,17], and the enhancement of plant tolerance to heavy metals [18]; (b) they help plants become established in harsh/degraded ecosystems, such as desert areas and mine spoils [19]; (c) they increase the power of phytoremediation (the removal of pollutants from the soil by plants) by allowing their host to explore and depollute a larger volume of soil [20,21]. Another crucial ecological role played by AMF is their capacity to directly influence the diversity and composition of the aboveground plant community. Several studies have

process. This aspect has led to the recognition of the importance of this group of organisms in

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All the services offered by arbuscular mycorrhizal fungi confirm the need to study and describe all their features, including their biology, ecology, taxonomy, phylogeny and biodiversity. Over the years, several techniques have been developed to reach this goal: a brief history is

This group of organisms has a constraining characteristic that makes their study very complex: as obligate symbionts, they cannot be cultivated in vitro, away from their host plant. The development of an artificial system that is capable of going beyond this barrier dates back to the 1980s, when in vitro transformed carrot roots were successfully colonized by AMF species [30]. Thanks to this method, the study of arbuscular mycorrhizae became easier and many researches on both physiology and genetics became possible [31,32]. Over the last two decades, many molecular and physiological mechanisms involved in the symbiotic process between plants and AMF have been discovered and described, thanks to the increasing innovations and opportunities offered by molecular biology. For example, it is now known how the infectious process of AMF arises, and many of the involved genes have been identified

Molecular biology has also revolutionized the analysis of the biodiversity of AMF, making it easier and more accurate to characterize the AMF community composition of large quantities of samples from many different ecosystems, from prairies to savannas, and from grasslands to forests (Table 1). The first studies on the diversity and distribution of AMF were mainly focused on the identification of the species that colonize the roots of a given plant in a given environment [34]. This was mainly due to the deficiency in the available investigation techniques, as they were primarily based on spore surveys and intraradical fungal structure morphological identification by means of microscopy. Such morphological identification surveys were time consuming and often lacked accuracy, since many species were easily confused with others. The situation changed radically when the use of DNA-based techniques became common, and the extraction of DNA from plant tissue was reduced to a few relatively easy steps that could be reproduced in any laboratory [35,36]. The load bearing principle is simple: by sequencing a specific DNA region, it is possible to univocally identify the corre‐ sponding AMF [37]. So far, the most used DNA target regions for AMF identification are located on the ribosomal genes (Small and Large ribosomal Subunits – SSU and LSU, respec‐ tively – and the Internal Transcribed Spacers – ITS1 and ITS2), as they show a rate of variability that is sufficient to discriminate between AMF species/isolates [9]. All this has led to the current era of molecular identification of AMF species [10]. Next-Generation Sequencing (NGS) tools represent a further step forward for biodiversity surveys of all organisms [38], including AMF. Over the last few years, the number of NGS-based AMF biodiversity studies has increased, while the spectrum of the target environments has broadened [39]. Furthermore, new primer pair sets for the specific amplification of AMF DNA sequences, capable of providing higher accuracy and a comprehensive coverage of the whole Glomeromycota phylum, have been

processes related to climate change mitigation [29].

**1.2. Methods used in the study of AMF**

reported in section 1.2.

successfully [33].

**Figure 2.** Extraradical and intraradical phases of AMF growth. The spore (Figure E, a *Scutellospora sp.* spore stained with Melzer's reagent and squeezed) germinates in the bulk soil and approaches the root of a host plant. The fungus penetrates through a hyphopodium (Figure A, stained with 0.1% cotton blue encountered in *Camellia japonica* L. roots) and develops intracellular coils, extracellular vesicles and intracellular arbuscules (Figures B, C, D) within cortical parenchyma, without entering the central cylinder where the vessels are.

confirmed that plant species richness can be altered not only by climatic and edaphic factors, but also by soil microbial assemblages [22–24]. The underlying mechanism is not completely understood, but could be related to the promotion of seedling establishment of secondary plant species [25]. Nevertheless, on some occasions, AMF can also negatively affect the diversity and growth of plants, which is particularly significant for the management of weeds [26]. Last but not least, AMF play a critical role in soil aggregation, thanks to their thick extraradical hyphal network, which envelops and keeps the soil particles compact. It has been suggested that glycoproteins (glomalin and glomalin related proteins) secreted by AMF into the soil could exert a key role in this process [27,28]. These proteins are exuded in great quantities into the soil, and could have implications on carbon sequestration. This potential capability of AMF is likely to contribute to a great extent to the soil ecosystem carbon dioxide (CO2) sequestration process. This aspect has led to the recognition of the importance of this group of organisms in processes related to climate change mitigation [29].

All the services offered by arbuscular mycorrhizal fungi confirm the need to study and describe all their features, including their biology, ecology, taxonomy, phylogeny and biodiversity. Over the years, several techniques have been developed to reach this goal: a brief history is reported in section 1.2.

#### **1.2. Methods used in the study of AMF**

confirmed that plant species richness can be altered not only by climatic and edaphic factors, but also by soil microbial assemblages [22–24]. The underlying mechanism is not completely understood, but could be related to the promotion of seedling establishment of secondary plant species [25]. Nevertheless, on some occasions, AMF can also negatively affect the diversity and growth of plants, which is particularly significant for the management of weeds [26]. Last but not least, AMF play a critical role in soil aggregation, thanks to their thick extraradical hyphal network, which envelops and keeps the soil particles compact. It has been suggested that glycoproteins (glomalin and glomalin related proteins) secreted by AMF into the soil could exert a key role in this process [27,28]. These proteins are exuded in great quantities into the soil, and could have implications on carbon sequestration. This potential capability of AMF is likely to contribute to a great extent to the soil ecosystem carbon dioxide (CO2) sequestration

parenchyma, without entering the central cylinder where the vessels are.

162 Biodiversity - The Dynamic Balance of the Planet

**Figure 2.** Extraradical and intraradical phases of AMF growth. The spore (Figure E, a *Scutellospora sp.* spore stained with Melzer's reagent and squeezed) germinates in the bulk soil and approaches the root of a host plant. The fungus penetrates through a hyphopodium (Figure A, stained with 0.1% cotton blue encountered in *Camellia japonica* L. roots) and develops intracellular coils, extracellular vesicles and intracellular arbuscules (Figures B, C, D) within cortical This group of organisms has a constraining characteristic that makes their study very complex: as obligate symbionts, they cannot be cultivated in vitro, away from their host plant. The development of an artificial system that is capable of going beyond this barrier dates back to the 1980s, when in vitro transformed carrot roots were successfully colonized by AMF species [30]. Thanks to this method, the study of arbuscular mycorrhizae became easier and many researches on both physiology and genetics became possible [31,32]. Over the last two decades, many molecular and physiological mechanisms involved in the symbiotic process between plants and AMF have been discovered and described, thanks to the increasing innovations and opportunities offered by molecular biology. For example, it is now known how the infectious process of AMF arises, and many of the involved genes have been identified successfully [33].

Molecular biology has also revolutionized the analysis of the biodiversity of AMF, making it easier and more accurate to characterize the AMF community composition of large quantities of samples from many different ecosystems, from prairies to savannas, and from grasslands to forests (Table 1). The first studies on the diversity and distribution of AMF were mainly focused on the identification of the species that colonize the roots of a given plant in a given environment [34]. This was mainly due to the deficiency in the available investigation techniques, as they were primarily based on spore surveys and intraradical fungal structure morphological identification by means of microscopy. Such morphological identification surveys were time consuming and often lacked accuracy, since many species were easily confused with others. The situation changed radically when the use of DNA-based techniques became common, and the extraction of DNA from plant tissue was reduced to a few relatively easy steps that could be reproduced in any laboratory [35,36]. The load bearing principle is simple: by sequencing a specific DNA region, it is possible to univocally identify the corre‐ sponding AMF [37]. So far, the most used DNA target regions for AMF identification are located on the ribosomal genes (Small and Large ribosomal Subunits – SSU and LSU, respec‐ tively – and the Internal Transcribed Spacers – ITS1 and ITS2), as they show a rate of variability that is sufficient to discriminate between AMF species/isolates [9]. All this has led to the current era of molecular identification of AMF species [10]. Next-Generation Sequencing (NGS) tools represent a further step forward for biodiversity surveys of all organisms [38], including AMF. Over the last few years, the number of NGS-based AMF biodiversity studies has increased, while the spectrum of the target environments has broadened [39]. Furthermore, new primer pair sets for the specific amplification of AMF DNA sequences, capable of providing higher accuracy and a comprehensive coverage of the whole Glomeromycota phylum, have been