**3. Stem cell trophic factors**

In the recent past, stem cell technology has revolutionized the field of regenerative medicine and has been an attractive platform for the purposes of tissue repairs and cancer treatments. Stem cells are ideal for regenerative purposes due to their multipotentiality and self-renew‐ ing capabilities and this concept is fairly well established through many in vitro, in vivo and preclinical studies [22]. These cells play important roles in many biological processes, includ‐

**Figure 1.** Various paracrine factors released by mesenchymal stem cells which play an important role in mitogenesis, angiogenesis, apoptosis and scarring. Endothelial Growth Factor (EGF), Fibroblast Growth Factor (FGF), Hepatocyte Growth Factor (HGF), Insulin Growth Factor (IGF), Kerotinocyte growth factor (KGF ), Macrophage Inflammatory Proteins (MIP), Secreted Frizzled-Related Protein 2, Stanniocalcin-1(STC-1), Stromal cell derived factor (SDF), Trans‐ forming Growth Factor (TGF), Vascular Endothelial Growth Factor (VEGF).

ing anti-inflammation, cell migration, proliferation and differentiation, and signal pathway activation or inhibition. There is strong understanding that stem cells (especially MSCs) are able to repair the tissue by modulating the environment they reside, influencing the im‐ mune response, supporting angiogenesis, and also through the productive cross talk with the resident cells as illustrated in schematic diagram (**Figure 1**). It is believed that the stem cells may be able to achieve these activities through the secretion of a broad panel of biomole‐ cules called as trophic factors including growth factors, cytokines and chemokines and also the factors released in the extracellular vesicles (exosomes and microvesicles) [23–25]. There‐ fore, in recent years, researchers have a notion that the secret to the stem cell-based therapy may lie in the stem cell-secreted biomolecules rather than the cell itself as a therapeutic tool. Hence, there is a curious enthusiasm to explore and understand more about these secretion factors in orderto enable a switch from use of stem cells to the use of stem cell secretion factors in regenerative medicine [22, 26]. MSCs are reported to secrete a variety of trophic factors such as transforming growth factors (TGF-α and β), hepatocyte growth factor (HGF), epithelial growth factor (EGF), basic fibroblast growth factor (FGF-2), insulin-like growth factor-1 (IGF-1), and vascular endothelial growth factor (VEGF) which induces mitogenesis and an‐ giogenesis and are also anti-apoptotic. Other trophic factors like interleukins, stromal cellderived factor-1 and prostaglandin 2 are the key immunomodulatory cytokines [6, 25, 27, 28] as illustrated in **Figure 2**. Some fundamental studies have demonstrated that administration of stem cell condition medium containing bioactive factors released by the cells in culture medium can exert regenerative properties. Stem cell-derived secretory molecules has shown some promising tissue-repairing properties in cardiovascular [29], renal [6, 30], liver [31], lung injury [32], and neurodegenerative disease models [22, 33]. Trophic factors secreted by MSCs have induced proliferation of endogenous cardiac progenitor cells in vitro. Nakanishi et al. highlighted that conditioned media from rat MSCs can promote proliferation and migration of isolated cardiac progenitor cells and prevent their apoptosis when subjected to hypoxia and serum starvation [34]. Furthermore, human MSC secretions harvested in conditioned medi‐ um, reduced infarct size and preserved cardiac function in a large animal model of myocar‐ dial infarction [35]. MSC-conditioned media harvested after 24 h enhanced the paracrine effect and prevented oxygen-induced neonatal lung injury in a rat model [36]. An interesting study by Du et al. showed that MSC-conditioned media could even protect hepatocytes and sinus‐ oidal endothelial cells and stimulate their regeneration in reduced-size rat liver transplanta‐ tion [37]. The outcomes of this work was well complemented by another study undertaken by Van Poll et al., who provided clear evidence that introduction of MSC-conditioned media in a D-galactosamine-induced rat model of acute liver injury could enhance proliferation of hep‐ atocytes and reduce apoptotic hepatocellular death, thereby increasing the survival rates and preventing hepatic failures [38]. The role of trophic factors in the treatment of chronic kid‐ ney disease is well demonstrated by Koppen et al. in a rat model. This study showed that administration of human embryonic MSC-conditioned media decreases the progression of chronic kidney disease with reduced hypertension and glomerular injury indicating the ther‐ apeutic benefits of trophic factors for kidney-related injuries and disease [39]. Most of the investigators have shown the beneficial effects of trophic factors from MSCs; however, it is not just confined to these cells alone. Adipose-derived stem cells which are also gaining popular‐

etal defects without genetic manipulation orthe addition of exogenous growth factors [19, 20]. These animal studies with a combination of scaffolds and stem cells have shown great prom‐ ise with excellent bone regeneration capabilities; however, translation of these into clinical use is limited. A study by Kawate et al. used a tissue engineering approach and transplanted β-TCP with MSCs and a free vascularized fibula into three young patients with steroid-in‐ duced osteonecrosis of the femoral head. Two out of the three patients showed healing of the defect with new bone formation and vascularization within 27 months of implantation. Although these studies with a tissue engineering approach was promising, problems still persist in terms of validating the source of the stem cells, the safety, the cost involved and more importantly understanding the molecular mechanisms involved and these questions has to be

In the recent past, stem cell technology has revolutionized the field of regenerative medicine and has been an attractive platform for the purposes of tissue repairs and cancer treatments. Stem cells are ideal for regenerative purposes due to their multipotentiality and self-renew‐ ing capabilities and this concept is fairly well established through many in vitro, in vivo and preclinical studies [22]. These cells play important roles in many biological processes, includ‐

**Figure 1.** Various paracrine factors released by mesenchymal stem cells which play an important role in mitogenesis, angiogenesis, apoptosis and scarring. Endothelial Growth Factor (EGF), Fibroblast Growth Factor (FGF), Hepatocyte Growth Factor (HGF), Insulin Growth Factor (IGF), Kerotinocyte growth factor (KGF ), Macrophage Inflammatory Proteins (MIP), Secreted Frizzled-Related Protein 2, Stanniocalcin-1(STC-1), Stromal cell derived factor (SDF), Trans‐

forming Growth Factor (TGF), Vascular Endothelial Growth Factor (VEGF).

addressed before any clinical application can be achieved [21].

**3. Stem cell trophic factors**

360 Advanced Techniques in Bone Regeneration

ity as an attractive source of cells forregenerative purposes is showing similar properties. Sowa et al. showed that growth factors from ADSCs can promote peripheral nerve regeneration through paracrine secretion oftrophic factors regardless of donor age or anatomic site of origin. The effects of mouse ADSCs-conditioned medium were tested on Schwann cells and dorsal root ganglion neurons in vitro. The results showed that ADSCs produced factors which were capable of promoting survival and proliferation of Schwann cells and enhancing the neurite outgrowth in dorsal root ganglion neurons in vitro [40]. Yamada et al. showed that ADSCsecreted molecules could induce a trophic effect in pancreatic islet culture conditions in vitro. These results suggested that trophic factors, particularly VEGF, secreted by human ADSCs enhanced the survival and function of porcine islet cells [41]. These studies suggest that the stem cell trophic factors alone have the potential for therapeutic use and can enhance effects in regeneration. The concept of utilizing the stem cell secretome for tissue repair is undoubt‐ edly a step forward towards cell-free regenerative medicine and the effect of trophic factors in many other types of tissues like bone, ligament and for wound healing purposes is being explored.

**Figure 2.** Architecture of the stem cell niche consisting of extracellular matrix, support cells, soluble trophic factors, transmembrane cell adhesion molecules and progenitor cells.

### **4. Stem cell trophic factors for bone regeneration**

So far the use of stem cells in bone regeneration has largely been focussed on either trans‐ planting the stem cells directly to the defect site or through the tissue engineering ap‐ proaches. However, in recent years, the paracrine effects of stem cells in bone regeneration are being extensively explored and this can have positive implications in the field of bone regeneration. The secretion factors of the stem cells (e.g. MSCs) may have potential therapeu‐ tic applications in rheumatoid arthritis, osteoarthritis, genetic bone and cartilage disorders as well as bone metastasis [42]. The secretion factors released from the MSCs during their, osteogenic differentiation process induce recruitment and differentiation of endogenous progenitors. Murine MSCs was cultured in osteogenic medium and the condition media was

collected and assessed for its effects on differentiation and migration of exogenous MSCs. The results showed that MSCs maintained in osteogenic medium, secreted factors at specific time points that induced alkaline phosphatase activity in exogenous MSCs as well as their migra‐ tion thus showing the important contribution of trophic factors in the process of bone repair [43]. A study by Ando et al. showed that MSC-derived trophic factors can accelerate the healing process in distraction osteogenesis. In this study, serum-free conditioned medium derived from human MSCs was locally administered into the distraction gap in a high-speed distrac‐ tion osteogenesis mouse model. The introduction of the MSC condition media supported the recruitment of murine bone marrow stromal cells and endothelial promoting osteoblast proliferation, differentiation and angiogenesis [44]. The role of trophic factors in treating rheumatoid arthritis is well demonstrated by Ishikawa et al. using dental pulp stem cells (DPSCs). This study showed that delivery of serum-free conditioned media from DPSCs into a collagen type II antibody-induced arthritis mouse model of the rheumatoid arthritis can inhibit inflammation-induced M2-type conditions I and suppress osteoclastogenesis and bone destruction in collagen type II antibody-induced arthritis [45]. An excellent study by Doorn et al. showed that trophic factors from human MSCs can contribute immensely to bone forma‐ tion. In this study, human MSCs (hMSCs) were treated with small molecule dibutyryl cyclic adenosine monophosphate (db-cAMP) and the condition media was collected. This was used to culture a variety of cells including human umbilical vein endothelial cells, osteosarcoma, breast cancer and mouse myoblast cell line. The treatment of the condition media from cAMPtreated hMSCs to various cells could improve their proliferation and induce osteogenic differentiation with differential effects on migration. This study indicated that the trophic factors secreted by hMSCs can be tuned for a specific application [26, 46]. An in vitro study to investigate the role of brain-derived neurotrophic factor (BDNF) in spinal cord repair has shown that the condition media with the increased levels of BDNF was able to protect the motoneurons and enhance its survivalrate, thus indicating the therapeutic benefits the trophic factors can have in the treatments of spinal cord injuries [47].

ity as an attractive source of cells forregenerative purposes is showing similar properties. Sowa et al. showed that growth factors from ADSCs can promote peripheral nerve regeneration through paracrine secretion oftrophic factors regardless of donor age or anatomic site of origin. The effects of mouse ADSCs-conditioned medium were tested on Schwann cells and dorsal root ganglion neurons in vitro. The results showed that ADSCs produced factors which were capable of promoting survival and proliferation of Schwann cells and enhancing the neurite outgrowth in dorsal root ganglion neurons in vitro [40]. Yamada et al. showed that ADSCsecreted molecules could induce a trophic effect in pancreatic islet culture conditions in vitro. These results suggested that trophic factors, particularly VEGF, secreted by human ADSCs enhanced the survival and function of porcine islet cells [41]. These studies suggest that the stem cell trophic factors alone have the potential for therapeutic use and can enhance effects in regeneration. The concept of utilizing the stem cell secretome for tissue repair is undoubt‐ edly a step forward towards cell-free regenerative medicine and the effect of trophic factors in many other types of tissues like bone, ligament and for wound healing purposes is being

**Figure 2.** Architecture of the stem cell niche consisting of extracellular matrix, support cells, soluble trophic factors,

So far the use of stem cells in bone regeneration has largely been focussed on either trans‐ planting the stem cells directly to the defect site or through the tissue engineering ap‐ proaches. However, in recent years, the paracrine effects of stem cells in bone regeneration are being extensively explored and this can have positive implications in the field of bone regeneration. The secretion factors of the stem cells (e.g. MSCs) may have potential therapeu‐ tic applications in rheumatoid arthritis, osteoarthritis, genetic bone and cartilage disorders as well as bone metastasis [42]. The secretion factors released from the MSCs during their, osteogenic differentiation process induce recruitment and differentiation of endogenous progenitors. Murine MSCs was cultured in osteogenic medium and the condition media was

transmembrane cell adhesion molecules and progenitor cells.

**4. Stem cell trophic factors for bone regeneration**

explored.

362 Advanced Techniques in Bone Regeneration

Furthermore, Cantinieaux et al. also showed the paracrine-mediated actions of bone marrow stromal cells for treating spinal cord injuries. An in vitro and in vivo study was conducted to evaluate the effects of factors released by the bone marrow stromal cells in a spinal cord injury in a rat model. The in vitro studies showed that bone marrow stromal cell-conditioned medium protected the neurons from apoptosis, activated macrophages and also exhibited some proangiogenic properties. Similar beneficial effects of trophic factors from the bone marrow stromal cells condition was also observed in the in vivo studies with histological analysis showing the proangiogenic action and tissue protection effect [48].

In addition, the effect of secretion factors from human umbilical cord-derived mesenchymal stem cells on the osteogenesis of human MSCs has shown to initiate osteogenic differentia‐ tion with increased amount of calcium deposit, and upregulation of osteogenic gene expres‐ sion [49]. These outcomes suggests that stem cell trophic factors may have key solutions for bone repair and regenerations and further mechanistic understanding can reveal their potential for further clinical applications.

### **5. Stem cell microenvironment: biophysical cues and trophic factors**

Stem cells reside in complicated and dynamic three-dimensional (3D) microenvironments in vivo known as stem cell niches where they undergo self-renewal and differentiation. Their function is maintained through an array of complex signals derived from this niche [50–52]. Structurally, the niche is composed of extracellular matrix (ECM), soluble proteins like chemokines, cytokines and growth factors, supporting cells and physical factors. [53, 54]. ECM proteins are the influential components of the niche and they primarily help in maintaining stem cell homoeostasis and direct lineage commitment. ECM forms the vital communication network for transferring the cell signals emanated from soluble and matrix-bound factors and from cell-matrix interactions and the composition of the ECM can govern the fate of the cells considerably [55–57]. This concept is very well demonstrated through the preservation of the decellularized matrix which was able to guide stem cell differentiation into the cell types residing in the tissue from which the ECM was derived. On the basis of these properties, decellularized organs have been used in tissue engineering and for developing cell therapy approaches [58, 59]. ECM parameters are extremely dynamic and are spatially and tempora‐ rily controlled during development suggesting that they play a morphogenetic role in guiding differentiation and arrangement of cells. Support cells play an important role in restricting the stem cells to their niche through the cell surface adhesion proteins. The interactions between the stem cells and the support cells are largely governed by cadherin proteins that form adherens junctions. As such, stem cells are able to maintain their stemness and self-renewal when they are in the vicinity of the support cells [60]. Once the cell divides, one daughter cell remains in contact with the support cell and the other migrates from the niche and commits itself to a particular lineage [61]. Recent study by Polisetti et al. provided excellent insights into molecular mechanisms of progenitor cell niche anchorage mediated by integrins-, cadherins- and dystrophin-associated proteins that regulates both stable and dynamic cellmatrix and cell-cell interactions within the limbal niche [62]. Additionally, support cells such as perivascular stromal cells including nestin+ mesenchymal stromal cell (MSC) [63], leptin receptor (Lepr) expressing mesenchymal cell and Mx1+ stromal cells [64] have shown to play vitalroles in regulating the functions of hematopoietic cells in bone marrow. Support cells such as osteoblasts were believed to play an important role in preserving the HSCs in a quiescent state and help in their maintenance or just form a niche supportive of early lymphoid progenitors [65, 66]. These studies suggest the importance of support cells in the architecture of stem cell niche which eventually affects the functions of stem cells [67]. Soluble molecules are another important component of the niche besides ECM and support cells and are absolutely critical for directing the stem cell fate. Soluble factors can be in the form of growth factors, cytokines, enzymes, transforming growth factors, bone morphogenic factors and vitamin C to name a few [68, 69]. These factors can be either added to the culture conditions or secreted by the stem cells or the supporting cells in the niche. These factors can then bind to the membrane receptors of the cells and trigger the cell signalling pathways altering the gene expression of the stem cells [61, 70, 71]. Soluble molecules that are prevalent in most of the niches include Wnts, hedgehog proteins, FGF and bone morphogenetic proteins (BMP) . Some of these molecules are key factors in regulating the self-renewal of haematopoietic stem

cells. It is well established through many studies that Wnts and hedgehog proteins play a key role in osteogenesis especially in bone formation, maintaining cellular differentiation and regulating the formation of bone and cartilage, whereas FGFs and BMPs have profound impact on the osteoprogenitor differentiation and the regulation of the endochondral and intramem‐ branous ossification [60, 72]. Similarly, soluble growth factors and cell membrane-bound factors such as platelet-derived growth factor (PDGF), TGF-β, VEGF, BMP and Notch signalling have been implicated as having multivariable effects on cardiac development [73, 74]. In recent years, it has been established that the stem cell niche is not just confined to the soluble factors and cell-cell interactions but also to the definable physical and mechanical cues, which influences the decision-making capability of the stem cells. A number of investigators have demonstrated that stem cells have the ability to sense and transduce the physical and mechanical cues. The cues such as mechanical strain, stiffness, shear stress and topography can regulate the fate of the cells. It has been shown that application of mechanical strain can increase proliferation and decrease differentiation in human embryonic cells, which affects the cell alignment in the direction of the strain and also directs the MSCs to myogenic pheno‐ type. It has been shown that MSCs can express high levels of ligament-specific markers under the influence of rotational strain [75–78]. Additionally, the fate of the stem cells can also be influenced by the substrate stiffness. The effect of stiffness on stem cell differentiation has been well demonstrated by numerous investigators and an excellent study by Engler et al. showed that variation in the substrate stiffness can modulate the differentiation of stem cells into various specific lineages such as neuronal, muscle and osteogenic lineages. This lineage commitment was found to depend largely on the elasticity of the substrate [53]. A similarresult was highlighted by Saha et al., and Banerjee et al., who showed that changes in the substrate stiffness can present a defining influence on the differentiation of neural progenitor cells with stiff substrates modulating the cells to astrocytes while the softer ones towards neuronal differentiation [79, 80]. Stem cells are also sensitive to the shear stress and this can result in the morphological changes which in turn affects the cell behaviour at the molecular level. A study by Illi et al. showed that shear stress can stimulate the molecular pathways leading to histone modifications in mouse embryonic stem cells resulting in epigenomic regulations [81]. In addition, the shear stress has been shown to affect the differentiation of stem cells into vascular cells. Exposure of stem cells to shear stress increased the expression of endothelial cell-specific markers such as von Willebrand factor and vascular endothelial-cadherin [75]. Topographi‐ cal cues can also influence various behaviours of the stem cells similar to stress, strain and stiffness. Topographical modifications in the substrate can change the morphological fea‐ tures of the cells which can vary the orientation of the cytoskeletal structure of the cells thus affecting the function of the stem cell fate. Dalby et al. showed the influence of ordered and disordered nanoscale pattern on differentiation of MSCs. This study showed that osteogene‐ sis was more predominant with ordered nanoscale pattern with an increase in the expres‐ sion of genes responsible for osteogenic differentiation as compared to the disordered pattern [82]. A similar outcome was reported by Zouani et al. who showed that substrates with large nanodepths (100 μm) induced higher osteogenic differentiation as compared to the small depths (10 μm) indicating that stem cells can sense and respond to the topographical changes and regulate their function [83–85].

**5. Stem cell microenvironment: biophysical cues and trophic factors**

364 Advanced Techniques in Bone Regeneration

Stem cells reside in complicated and dynamic three-dimensional (3D) microenvironments in vivo known as stem cell niches where they undergo self-renewal and differentiation. Their function is maintained through an array of complex signals derived from this niche [50–52]. Structurally, the niche is composed of extracellular matrix (ECM), soluble proteins like chemokines, cytokines and growth factors, supporting cells and physical factors. [53, 54]. ECM proteins are the influential components of the niche and they primarily help in maintaining stem cell homoeostasis and direct lineage commitment. ECM forms the vital communication network for transferring the cell signals emanated from soluble and matrix-bound factors and from cell-matrix interactions and the composition of the ECM can govern the fate of the cells considerably [55–57]. This concept is very well demonstrated through the preservation of the decellularized matrix which was able to guide stem cell differentiation into the cell types residing in the tissue from which the ECM was derived. On the basis of these properties, decellularized organs have been used in tissue engineering and for developing cell therapy approaches [58, 59]. ECM parameters are extremely dynamic and are spatially and tempora‐ rily controlled during development suggesting that they play a morphogenetic role in guiding differentiation and arrangement of cells. Support cells play an important role in restricting the stem cells to their niche through the cell surface adhesion proteins. The interactions between the stem cells and the support cells are largely governed by cadherin proteins that form adherens junctions. As such, stem cells are able to maintain their stemness and self-renewal when they are in the vicinity of the support cells [60]. Once the cell divides, one daughter cell remains in contact with the support cell and the other migrates from the niche and commits itself to a particular lineage [61]. Recent study by Polisetti et al. provided excellent insights into molecular mechanisms of progenitor cell niche anchorage mediated by integrins-, cadherins- and dystrophin-associated proteins that regulates both stable and dynamic cellmatrix and cell-cell interactions within the limbal niche [62]. Additionally, support cells such as perivascular stromal cells including nestin+ mesenchymal stromal cell (MSC) [63], leptin receptor (Lepr) expressing mesenchymal cell and Mx1+ stromal cells [64] have shown to play vitalroles in regulating the functions of hematopoietic cells in bone marrow. Support cells such as osteoblasts were believed to play an important role in preserving the HSCs in a quiescent state and help in their maintenance or just form a niche supportive of early lymphoid progenitors [65, 66]. These studies suggest the importance of support cells in the architecture of stem cell niche which eventually affects the functions of stem cells [67]. Soluble molecules are another important component of the niche besides ECM and support cells and are absolutely critical for directing the stem cell fate. Soluble factors can be in the form of growth factors, cytokines, enzymes, transforming growth factors, bone morphogenic factors and vitamin C to name a few [68, 69]. These factors can be either added to the culture conditions or secreted by the stem cells or the supporting cells in the niche. These factors can then bind to the membrane receptors of the cells and trigger the cell signalling pathways altering the gene expression of the stem cells [61, 70, 71]. Soluble molecules that are prevalent in most of the niches include Wnts, hedgehog proteins, FGF and bone morphogenetic proteins (BMP) . Some of these molecules are key factors in regulating the self-renewal of haematopoietic stem

Such studies have convinced that the mechanical cues can influence the fate of the stem cells; however, the mechanistic insights as to how these cues direct the differentiation of stem cells is just beginning to be unravelled. Stem cells can sense the stiff microenvironment and transduce the signals through the Rho kinase [86, 87], TGF-β [88, 89], Src family kinases [90] and phosphor-tyrosine signalling pathways [91, 92]. Other studies by Dupont et al. and Swift et al. have shown that yes-associated protein and transcriptional coactivator with PDZ-binding motif also have a significant role in regulating the stem cell differentiation mechanism in response to mechanical parameters. While more and more mechanistic data begins to emerge, it is only clear that mechanical cues are potent physical parameters in the regulation of stem cell differentiation [93–96]. The release and beneficial effects of trophic factors from the stem cells will also depend on the microenvironment it is residing in. Changes in the microenvir‐ onment with respect to the biological and mechanical cues can affect the release of trophic factors which can have profound implications in their functionality. More studies are now beginning to emerge to decipherthese concepts using various artificial platforms. For example, Abdeen et al. studied the combined role of stiffness and matrix protein on the secretory profile of MSCs and their effects on human microvascular endothelial cells. In this work, the condi‐ tioned media from MSCs adherent to polyacrylamide hydrogel with controlled matrix rigidity and protein composition was collected and applied to a model angiogenesis assay using HMVECs within Matrigel. The result from this study showed that secretion of the trophic factors was related to a combined effect of stiffness and adhesion protein for directing proangiogenic signalling [97]. Jose et al. pretreated the MSCs with glycine-histidine-lysine (GHK), a peptide fragment of osteonectin and a matrix cellular protein with reported proangiogenic potential. The study revealed a dose-dependent increase in VEGF concentra‐ tion in media conditioned by GHK-treated MSC, which increased endothelial cell prolifera‐ tion, migration and tubule formation. This study suggested that microenvironment of the stem cells can have significant influence on the trophic factors and their functionality [98]. Furthermore, Silva et al. showed that the secretome of the bone marrow MSCs were affected when the cells were cultured on fibronectin peptide-modified hydrogels as compared to the unmodified gels and this change in the secretome-induced higher metabolic viabilities and neuronal cell densities [99]. Hoch et al. also showed that cell-secreted decellularized extracel‐ lular matrices can preserve the bone-forming phenotype of the differentiated MSC. In this study, osteogenically induced MSCs were cultured on the decellularized matrices and the osteogenic and angiogenic potential was measured after the withdrawal of the induction media. It was found that culturing osteogenically induced MSCs on decellularized matrix can enhance calcium deposition and secretion of proangiogenic factor such as VEGF [100].

It has also been noted that the changes in the microenvironment of the stem cells due to biomolecules can also affect the trophic factors secretion by the stem cells and this can in turn affect the functionality of the cells by our group and others. We have shown that short-term exposure of human osteoblasts to tumour necrosis factor (TNF-α) can promote osteogenic differentiation and also stimulate human osteoblasts to secrete soluble factors that can foster a microenvironment favouring osteogenic differentiation of ADSC [101]. A similar study was performed by Czekanska et al., whereby MSCs were stimulated with interleukin-1β (IL1β), granulocyte-colony stimulating factor (GCSF), stromal cell-derived factor 1 (SDF1) and stem

cell factor (SCF) for about 2 h. The results showed that a mere 2-h stimulation could affect the expression of multiple cytokine genes and proteins in MSC significantly. IL1β strongly promoted the secretion of a wide range of proteins with chemotactic, proinflammatory and angiogenic properties, whereas SCF regulated the expression of proteins involved in prolifer‐ ation, chondrogenesis and ECM regulation. This outcome was clear evidence that the changes in secretome can be directed towards a desired final functional outcome through the selec‐ tion of the most appropriate cytokine [102, 103].

Through numerous studies reported in the literature, it is quite evident that the stem cell function greatly depends on the architecture of the niche; any physical or biochemical disruption can affect the stem cell function profoundly.


*3.15.1 ACCs inhibitors*

Acetyl-Coa carboxylases (ACCs) promote de novo lipogenesis through the conversion of Acetyl-CoA to Malonyl-CoA, which is a signaling molecule that suppresses fatty acid oxidation. Thus, ACC inhibition reduces lipid accumulation in the liver and stimulates fatty acid oxidation, improving hepatic steatosis and insulin sensitivity in studies in animal models and humans. The problem that arises, is that it also causes hypertriglyceridemia which may further worsen NAFLD [43].


**5.2 Example findings library**

An open-source library example from Schmeelk [26] is seen in **Figure 8** applying an example-consistent risk language. The library needs to be expanded from industry working groups, similarly to MITER's CWE and NIST's BF.

Some important elements for language specification and risk clarification are seen in **Figure 8** [26]; they are the following: vulnerability short descriptive name, vulnerability expanded description, techniques to remediate or mitigate the vulnerability, estimated likelihood factors, estimated impact factors, related organizational policies/standards, related NIST Controls, related HIPAA regulatory requirements, other related legal requirements such as non-disclosure agreements, and estimated breach cost factors for insurance and related required patient identity-theft protection costs/notifications.

These categories listed in the prototype can arguably be expanded or removed. Historically, vulnerability standardization libraries [20–22] are maintained by major organizations (e.g. MITER) and/or government entities (e.g. NIST). Based on healthcare operation needs, we developed the following descriptions of the prototype categories.

*Risk in Healthcare Information Technology: Creating a Standardized Risk Assessment Framework DOI: http://dx.doi.org/10.5772/intechopen.96456*

#### **Figure 8.**

*Risk assessment library prototype.*


**4. What is Web3 and how it is different?**

Web3 can be broadly defined as the digital infrastructure whereby the protocols and underlying technology elements (mainly blockchain) facilitates direct interaction between users and removes the need of any centralized agencies (or trusted intermediaries) to verify users or transactions [3]. Currently there are not many academic works that has studied Web3 in detail or provided a well-accepted definition. Liu et al. defines Web3

as an *"era of computing where the critical computing of applications is verifiable"* [4]. The three critical infrastructure elements as outlined for Web3 by these experts [4] include:

While using this definition, this chapter attempts to provide an easy-to-understand comparison with Web 2.0 infrastructure so that readers can understand how the concept of decentralization will impact technology elements that will drive the eCommerce business models. **Table 1** provided below identifies some of the most used Web3 related terms and their definitions.


**1. Introduction**

Human identification is one of the oldest behaviors that were done by people to distinguish each other. In the old ages, it was unusual to wrongly identify a person because the number of people was not much in each community. Consequently, memorizing all the persons that you deal within that time was possible. Additionally, it was enough to see the face of any person or to hear his voice to recognize him; therefore, human identification was not considered as a hard issue. The increase of the number of people and the occurrence of commercial and financial transactions forced people to find new reliable methods for human identification in order to prevent the unauthorized person to access authorized information. The new methods of

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. © 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.

© 2016 The Author(s). Licensee InTech. This chapter is distributed under the terms of the Creative Commons

human identification were classified into two main approaches as traditional and biometrics approaches. Matching process of these methods is conducted not only by humans but also by automated systems, which speed up the matching process in addition to the capability of the large size of memory.

**3.1. Face**

face tagging.

**3.2. Iris**

preprocessed variant are also shown in **Figure 2**.

**Figure 1.** Block diagram of a face recognition system.

Face recognition is one of the most important abilities that we use in our daily lives. Face recognition has been an active research area over the last 40 years, and the first automated face recognition system was developed by Takeo Kanade in 1973 [2]. The increasing interest in the face recognition research is caused by the satisfactory performance in many widely used applications such as the public security, commercial, and multimedia data management applications that use face as biometric trait. Face recognition has several advantages over other biometrics such as fingerprint and iris besides being natural and nonintrusive. First, the most important advantage of face is that it can be captured at a distance and in covert manner. Second, in addition to the identity, the face can also show the expression and emotion of the individual such as sadness, wonder, or scaring. Moreover, it provides a biographic data such as gender and age. Third, large databases of face images are already available, where the users should provide their face image in order to acquire driver's license or ID card. Finally, people are generally more willing to share their face images in the public domain as evinced by the increasing interest in social media applications (e.g., Facebook) with functionalities like

Person Identification Using Multimodal Biometrics under Different Challenges

http://dx.doi.org/10.5772/intechopen.71667

83

A face recognition system generally consists of four modules namely face detection, preprocessing, feature extraction, and matching as shown in **Figure 1**. An original face image and its

Iris recognition is one of the most reliable methods for personal identification. The use of iris texture analysis for biometric identification is clearly well established with the advantages of uniqueness and stability. Iris recognition has been successfully applied in access control systems managing large databases. The United Arab Emirates has been using iris biometrics

Iris is one of the most valuable traits for automatic identification of human being. A number of reasons justify this interest. First of all, the iris is a protected internal organ of the eye that is visible from the exterior. The iris is an annular structure and planar shape that turns easily, and it has a rich texture. Furthermore, iris texture is predominantly a phenotypic with limited genetic penetrance. The appearance is stable over lifetime, which holds tremendous promise

for border control and expellees tracking purposes for the past decade [3].


**ELECTRICAL AND ELECTRONIC PROPERTIES OF MATERIALS**

Edited by **Md. Kawsar Alam**

#### **Electrical and Electronic Properties of Materials**

http://dx.doi.org/10.5772/intechopen.73110 Edited by Md. Kawsar Alam

#### **Contributors**

Turgut Ozturk, Muhammet Tahir Guneser, Fatima Ternero, Juan Manuel Montes, Francisco G. Cuevas, Jesús Cintas, Eduardo S. Caballero, Wieslawa Urbaniak-Domagala, Jianying Li, Kangning Wu, Yuwei Huang, Md. Kawsar Alam

#### **© The Editor(s) and the Author(s) 2019**

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**6.3 On line defects detection in Gas Metal Arc Welding**

Another fuzzy application used in industrial field is proposed by Naso & Turchiano (Naso & Turchiano, 2005), who propose the development of an intelligent optical sensor for on line defects detection in Gas Metal Arc Welding (GMAW).

GMAW (Li & Zhang, 2001) is a welding process widely used in industrial field (Bingul et al., 2000) which presents many advantages, such as low costs, high metal deposition rate and suitability to automation. Also the process monitoring and defect-detections methods are very important tasks in order to improve the weld quality reducing manufacturing costs.

The electro-optical sensor includes two main modules (sensor and telescope) which are interconnected with optical fibers. This equipment aims at filtering and splitting the measured radiation into four components: infrared (*IR*), ultraviolet (*UV*) and two radiations at visible wavelengths (*VIS1, VIS2*). Photodiodes convert the resulting beams in electrical signals. The wavelength of the two signals belonging to the visible spectrum is set to tolerate the computation of the electronic temperature (*Te*) of the plasma. If *VIS1, VIS2, Te* are interdependent, then only *Te* and *VIS1* are taken into account to eliminate redundancies.

Before the on line classification operation, a signal pre-processing phase is necessary in order to improve the signal quality. The pre-processing phase includes two stages: signal filtering and extraction of the regularity indices. Signal filtering is a fundamental step in this context because a large amount of noise affects the observed signals. The Kalman filter (Brown & Hwang, 1992) has been adopted to this purpose, which provides efficient algorithms for estimating useful parameters in the stochastic environments. Regularity indices are extracted considering several factors: first of all, given a fixed configuration of the welding equipment, the signals associated to successful welding processes have the same behaviour; in contrast, signals observed during defective welds contain particularly features which are easily associable to the occurred defect. Also, it is possible to discover when the quality of the weld decreases, the cause of such downgrading and the type of defect. For the classification task the information describing the behaviour of the observed signal can be synthesized in three independent features:

The extracted features are fed as inputs into a classifier. In order to develop a classifier that directly exploits the experts knowledge a fuzzy system has been chosen. It must be noticed that signals belonging to different welds are different due to the stochastic nature of the phenomena under consideration; also the deviation of one or more indices from their expected behaviour often is due to the occurrence of a defect during the welding process. Fuzzy system, in this context, is the ideal classifier, as it is simple, it can directly use the knowledge of the experts and it can be easily reconfigured when new knowledge is available.

In order to limit the number of membership functions and rules the classification task is developed through two different fuzzy systems operating parallel. The first fuzzy classification system is used to provide a percentile index of acceptability of the weld, while the second fuzzy system detects the simultaneous signal patters directly connected with a specific defect. The first FIS gives a real time estimate of the quality of each weld, also for each time-window the system analyzes the indices through a rule-based method. Firstly a partition of the range of each observed input three fuzzy set is been made basing on the set of reference welds used as training set. The three introduced fuzzy sets are referred to quality: Optimal (OPT), acceptable (ACC) and unacceptable (UNA) and the membership functions have a trapezoidal shape. Finally the fuzzy system uses the welding time (*Time*) as an input to let the classification ignore the first seconds of process when the welding equipment is warming up. To describe the time interval a single linear piecewise increasing membership function regime (*REG*) is introduced. The output is represented by three membership functions as well. In this case the membership function are represented by three singletons as follows:

256 Fuzzy Inference System – Theory and Applications

Another fuzzy application used in industrial field is proposed by Naso & Turchiano (Naso & Turchiano, 2005), who propose the development of an intelligent optical sensor for on line

GMAW (Li & Zhang, 2001) is a welding process widely used in industrial field (Bingul et al., 2000) which presents many advantages, such as low costs, high metal deposition rate and suitability to automation. Also the process monitoring and defect-detections methods are very important tasks in order to improve the weld quality reducing manufacturing costs.

The electro-optical sensor includes two main modules (sensor and telescope) which are interconnected with optical fibers. This equipment aims at filtering and splitting the measured radiation into four components: infrared (*IR*), ultraviolet (*UV*) and two radiations at visible wavelengths (*VIS1, VIS2*). Photodiodes convert the resulting beams in electrical signals. The wavelength of the two signals belonging to the visible spectrum is set to tolerate the computation of the electronic temperature (*Te*) of the plasma. If *VIS1, VIS2, Te* are interdependent, then only *Te* and *VIS1* are taken into account to eliminate redundancies.

Before the on line classification operation, a signal pre-processing phase is necessary in order to improve the signal quality. The pre-processing phase includes two stages: signal filtering and extraction of the regularity indices. Signal filtering is a fundamental step in this context because a large amount of noise affects the observed signals. The Kalman filter (Brown & Hwang, 1992) has been adopted to this purpose, which provides efficient algorithms for estimating useful parameters in the stochastic environments. Regularity indices are extracted considering several factors: first of all, given a fixed configuration of the welding equipment, the signals associated to successful welding processes have the same behaviour; in contrast, signals observed during defective welds contain particularly features which are easily associable to the occurred defect. Also, it is possible to discover when the quality of the weld decreases, the cause of such downgrading and the type of defect. For the classification task the information describing the behaviour of the observed

1. *Normalized Signal Offset* (NSO), which is used to quantify the deviation of the signal

2. *Change of Normalized Signal Offset* (CNSO), which measures the change in signal levels

3. *Residual Signal Noise* (RSN), which represents the remain noise in the signal after the

The extracted features are fed as inputs into a classifier. In order to develop a classifier that directly exploits the experts knowledge a fuzzy system has been chosen. It must be noticed that signals belonging to different welds are different due to the stochastic nature of the phenomena under consideration; also the deviation of one or more indices from their expected behaviour often is due to the occurrence of a defect during the welding process. Fuzzy system, in this context, is the ideal classifier, as it is simple, it can directly use the knowledge of the experts and it can be easily reconfigured when new knowledge

**6.3 On line defects detection in Gas Metal Arc Welding**

defects detection in Gas Metal Arc Welding (GMAW).

signal can be synthesized in three independent features:

between two consecutive time windows.

Kalman filtering.

is available.

from the expected value belonging to an ideal weld.

Once the membership functions have been defined, a few generic rules are introduced. The first rules refer to obvious conditions; then, each time, another rule is included and the overall classification performance is evaluated in order to adjust membership function and rule weights. The output is so defined as an index of weld quality, in particular 0% (UNA) indicates the occurrence of defect while 100% (OPT) represents an optimal weld, values in the range 0-100% represent intermediate acceptability. Subsequently a threshold of acceptability is introduced in order to convert the fuzzy degree of quality in a binary decision: good or defective weld.

The fuzzy rules used by the quality estimation system can be described as follow:

Fuzzy Inference Systems Applied to Image Classification in the Industrial Field 259

Both Fuzzy Inference Systems are Mandani type and a general scheme of the proposed

The proposed approach has been evaluated with 40 different welding processes, where the 70% of processes are non defective while the remaining 30% present particular defects voluntarily induced or *a posteriori* detected with an appropriate tool. Furthermore, 60% of

In order to demonstrate the effectiveness of the proposed method a comparison with a stochastic approach (Sforza & DeBlasiis, 2002) is provided. It is important consider that stochastic approach is not able to indicate the type of defect and, in order to make the comparison, the fuzzy index of quality must be convert in a binary value, also a threshold is necessary. The obtained results show that the fuzzy classification system correctly classifies

Finally a sensitivity analysis in order to evaluate the robustness of the proposed approach, when membership function, rules and operating condition vary, is carried out. The sensitivity investigation on the several variation of parameters leads to the following conclusion: if a proper pre-processing signal phase and a correct identification of the important features are been carried out, then the proposed fuzzy classification system can be

An interesting industrial application which exploits the advantages of the fuzzy theory is due to (Tong et al., 2003). The authors propose a process control chart which integrate both fuzzy theory and engineering experience in order to monitor the defects on a wafer which

The wafer manufacturing process contains many step, such as alignment, etch and deposition. It is a very complex process; the occurrence of defects on the wafer surface is

Typically Integrated Circuits (IC) manufacturers use c-charts to monitor wafer defects. This technique assumes that wafer defects are randomly and independently distributed so that the number of defects has a Poisson distribution. A limit of this approach is that the real defect clustering infringes this constraint creating a non acceptable occurrences of false alarms. A modified c-chart, introduced in order to solve this problem, is presented by Albin & Friedman (Albin & Friedman, 1991) and it is based on a Neyman Type-A distribution. Unfortunately also this approach presents a considerable limit, as it can monitor only the variation in the number of defects but it is not able to detect variation located within the wafer. The authors demonstrate that applying fuzzy theory in combination with engineering experience it is possible to build a process control chart which is able to monitor the clustered defect and defect clustering simultaneously. The proposed algorithm is

The KLA 2110 wafer inspection system (Castucci et al., 1991) is adopted to obtain the wafer map. This system provides in-line wafer inspection information such as number of defects, size of defects, placement of defects and, finally, type of defects. The number of defects are determined and the cluster index is calculated. Some cluster indices are provide to calculate

all considered welds while the stochastic approach misclassifies 14% of the welds.

approach is shown in Fig.6.

effectively built and tuned.

have been clustered.

illustrated in Fig.7.

**6.4 Detection of wafer defects**

unavoidable and decreases the wafer yield.

data are used as training set and 40% as validation set.

The second fuzzy system is used to display messages which explain the occurred defect or the anomaly operation in the considered weld. The considered events for this aim are the common ones such as current increase, current decrease, voltage variation, gases assistance decrease, contamination of with materials having different thermal properties and occurrence of hole in the metal. The second FIS is similar to the first one working with analogous membership functions and rules and provides six outputs, one for each considered defect. It is evident that a single defect could be associated to one or more causes.

Fig. 6. Diagram of the proposed approach

Both Fuzzy Inference Systems are Mandani type and a general scheme of the proposed approach is shown in Fig.6.

The proposed approach has been evaluated with 40 different welding processes, where the 70% of processes are non defective while the remaining 30% present particular defects voluntarily induced or *a posteriori* detected with an appropriate tool. Furthermore, 60% of data are used as training set and 40% as validation set.

In order to demonstrate the effectiveness of the proposed method a comparison with a stochastic approach (Sforza & DeBlasiis, 2002) is provided. It is important consider that stochastic approach is not able to indicate the type of defect and, in order to make the comparison, the fuzzy index of quality must be convert in a binary value, also a threshold is necessary. The obtained results show that the fuzzy classification system correctly classifies all considered welds while the stochastic approach misclassifies 14% of the welds.

Finally a sensitivity analysis in order to evaluate the robustness of the proposed approach, when membership function, rules and operating condition vary, is carried out. The sensitivity investigation on the several variation of parameters leads to the following conclusion: if a proper pre-processing signal phase and a correct identification of the important features are been carried out, then the proposed fuzzy classification system can be effectively built and tuned.


2.1.2. Pacific Island Countries Reports

All the reports used here came from the two main organizations in the Pacific, which are the Pacific Community (SPC) and the Secretariat of the Pacific Regional Environment Programme(SPREP). These included: SPREP Annual Report [24], Status and Trends of Coral Reefs of the Pacific [25], Pacific Regional Energy Assessment [26], Pacific Marine Climate Change Report Card [27], and Pacific Community Results Reports [28]. Each document provided information on the current or latest status of the environmental, social, and economic sectors. They were the basis of understanding the local vulnerabilities and intricacies that should be considered during a project.

#### *2.2. Methods*

#### 2.2.1. Integrated Conceptual Framework for the Pacific Island Countries

By studying the concepts behind wave energy harnessing and the Pacific environment, it was possible to construct an integrated conceptual framework for the Pacific Island countries (ICFPICs). The ICFPICs is integrative since it integrates knowledge and concepts from different fields and organize variables connected to a central idea; it is also a conceptual framework considering that all the information here gathered stems from literature reviews and methodological assumptions. After reviewing the available documents, guidelines, and reports, every item considered to be a potential challenge was categorized using the PESTEL approach and fit into a cluster diagram. Each PESTEL dimension was structured into separate clusters that revolved around a core concept, and where elements shared similar characteristics.

#### 2.2.2. PESTEL-SWOT Combined Analysis

The ICFPICs provided an overview of the relevant elements for wave energy in the Pacific, which were be combined with the SWOT analysis to point towards the related internal and external factors. Each item from the ICFPICs was analyzed from the perspective of strengths, weaknesses, opportunities, and threats, resulting in a PESTEL-SWOT combined matrix. In this case, strengths and weaknesses were related to wave energy, representing the internal factors; opportunities and threats were external factors, being related to the macro-environmental variables that could justify or hinder a project. The resulting matrix shows the possible factors for each category and should be further adapted to individual case studies.

#### **3. Results**

Each division of the framework is explained below and further divided into important factors. Further information on each PESTEL element can be found in Appendix A, where the reasoning behind their connection to wave energy in the Pacific is explained.

The decision to invest in renewable energy, regardless of the source, is still connected to the political sphere of a country. This is particularly important for wave energy or marine technologies as a whole, considering their long lifecycle and higher investment rate of return. For the political sector, the main factors are political stability, renewable energy targets, and government support.

How affordable the energy is, the risks, and the benefits involved are all essential parts of the feasibility study of a wave energy project. The main concepts to be analyzed here are the cost of energy, the risks of the project, and the feed-in tariff. Therefore, for the economic sector, the main factors are economic stability, cost of energy, feed-in tariff, risk assessment, and access to funds.

Social aspects of an island nation are fairly complex; they are usually associated with the local environment and local economy making it an intricate task to classify which factors only belong to the social sphere. For instance, exploring natural resources, such as sand, can be for home construction or for export. For this study, social factors are all the activities that involve the local society, either to make profits or for subsistence purposes. For the social sector, the main factors are offshore mining, tourism, navigation, fishery, aquaculture, recreation sites, cultural and world heritage sites, and local acceptance.

The processes of building, maintaining, and connecting a WEC to the grid require additional infrastructure and resources. Bringing the device from the supplier to the potential site is a long process that relies on a port for logistic purposes, and also on specialists and qualified workers. In addition to that, if the main objective is to supply electricity to the main grid, suitable grid infrastructure is required to minimize installation costs. Therefore, for the technological sector, the main factors are electricity supply and demand, electricity grid, seaports, expertise, and logistics.

The island environment provides essential services to the local communities and therefore is a crucial element when analyzing the feasibility of any type of development. Wave energy converters are placed in the ocean, where there might be located important marine species or coral reefs. These devices might also be subjected to extreme weather scenarios and this factor will be accentuated if the WEC is situated in a hazard-prone area. For the environmental sector, the main factors are natural hazards, biodiversity, and coral reefs.

Lastly, there are mainly two forms of legal concerns regarding wave energy, which are related to the physical space and energy regulations. There are offshore zones that are either prohibited from being accessed or under protection, including areas being utilized as military bases, conservation areas, or the boundaries of the EEZ. Each country also has its own regulations when it comes to the generation of electricity and these should be accounted for. For the legal sector, the main factors are regulations, maritime zones, marine protected areas, military zones, and dependent territories.

#### *3.1. Integrative Conceptual Framework for the PICs (ICFPICs)*

Figure 2 shows an illustration of all the PESTEL components combined and each of their related factors. There is a total of 29 potential obstacles that were identified through the previous stages, and these are grouped by categories on the resulting visual representation. Each item should be further analyzed for a particular location by gathering relevant information and by mapping barriers when applicable.

To facilitate the process of utilizing the ICFPICs, a decision tree was created (Figure 3). The purpose is to assist the user in identifying potential challenges and determining which actions to take afterward. As an example, the tree starts with the ICFPICs item aquaculture, which is shown here as "Presence of aquaculture activities"; for this item, decision makers need to verify if it will present a challenge to the project and follow the necessary steps. In

brief, for each challenge encountered the solutions will vary between five main options: changing the location of the site, conducting further analysis, consulting stakeholders, including additional costs to the project, and canceling or postponing the project. This is a generic tool that gives an overview of the process; however, it should be adapted to each case study and could potentially include additional steps or solutions.

**Figure 2.** Integrative conceptual framework for harnessing wave energy in the PICs (ICFPICs).

**Figure 3.** Decision tree exemplifying the process of utilizing the ICFPICs for a wave energy project in the Pacific environment; highlighted boxes are the main outcomes from the process.

#### *3.2. The Combined PESTEL-SWOT Analysis*

To demonstrate how PESTEL-SWOT analysis can be utilized, every item from the ICFPICs was studied as an external factor and fitted into a SWOT matrix (Table 1). Wave energy was surveyed in the context of the energy resource to be harnessed, and how it would contribute to the local society. The resulting matrix should be adapted to different case studies and provides a run-through of the feasibility of a wave energy project. Strengths and weaknesses are related to the process of installing, operating, and maintaining a wave energy converter device, which is mostly technological. Opportunities and threats are covered by the political, environmental, social, technological, economic, and legal categories.

**Table 1.** PESTEL-SWOT analysis combined; elements in the ICFPICs were used to create a SWOT matrix.

#### **4. Discussion**

PICs face unique challenges and have distinct traits, such as narrow-based economies, limited natural resources, fragile ecosystems, reliance on subsistence activities, and remoteness from major markets. Thus, having a framework that encompasses regional characteristics is important when identifying challenges. The ICFPICs created here focused on wave energy on a regional level and is unique in the sense that such a concept has not been attempted yet.

There are different prospective applications for the ICFPICs; it can serve as a tool to identify potential challenges to a project, it can be used to identify key stakeholders, and lastly, it can be combined with the SWOT approach, giving an overview of both the barriers and opportunities for wave energy in the Pacific Island countries. The information gathered during the process of utilizing the framework is useful to create a SWOT matrix, which in turn will give an overview of the feasibility of a wave energy project by further categorizing the data into strengths, weaknesses, opportunities, and threats.


**2. Definitions**

From crisis to catastrophe, emergency to disaster, there is a spectrum of events that may threaten people and organizations. Not just the event, but the characteristics of the affected population define disaster. Risk and resilience are opposing forces that must be considered with disaster management.

#### **2.1 Emergencies**

Disasters and emergencies differ in quality and magnitude but are often and inaccurately used synonymously. "Disasters are not just 'big emergencies'" ([4], p. 293). Emergencies are time-sensitive, potentially harmful events that put life and well-being at risk. Resources are available at the local level to prevent, mitigate, or minimize the harm, and a single responding organization is responsible [5, 6]. Local resources, as a variable in the equation, can affect what constitutes an emergency,

**5**

**Figure 1.** *Spectrum of crises.*

*Disaster Management: A State-of-the-Art Review DOI: http://dx.doi.org/10.5772/intechopen.94489*

such an event.

**2.2 Disasters**

prepare for disaster.

**2.4 Catastrophe**

(**Figure 1**).

**2.3 Crisis**

and what goes beyond. An event of the same magnitude, in locations or situations with different capabilities and resources, may be managed within the organization (emergency) or need outside help (disaster). An example in a health care context might be a car crash involving one or two seriously injured people requiring prompt medical investigations and treatment, assuming the facility is equipped to deal with

Disasters are sometimes considered "hypercomplex emergencies" or "major emergencies" involving multiple people at risk of harm, multiple jurisdictions responding, and resources that are not immediately available locally ([5], p. 8; [7]). Coordination between agencies, many of whom have no prior relationships, becomes a challenge [5]. Plans for resource utilization must change when those resources are overwhelmed [8]. Preparations, planning, and training at the local level, within the abilities and available resources of a single agency, do little to

Crisis is a more generic description. A crisis is a "critical event or point of decision which, if not handled in an appropriate and timely manner (or if not handled at all), may turn into a disaster or catastrophe" [9]. We use the word *crisis*, then, nonspecifically, as an emergency event that has potential to evolve; *emergency* as time-sensitive event with potential harm; and *disaster* as an event larger and more harmful than an emergency, with many people at risk, and where management requires resources outside of the responding organization or department.

The word *catastrophe*, more severe than a disaster, completes the spectrum [5]. Many variations of the definition exist, but all suggest a magnitude of harm and inadequacy of response capabilities beyond what would be considered disaster [1] *Disaster Management: A State-of-the-Art Review DOI: http://dx.doi.org/10.5772/intechopen.94489*

and what goes beyond. An event of the same magnitude, in locations or situations with different capabilities and resources, may be managed within the organization (emergency) or need outside help (disaster). An example in a health care context might be a car crash involving one or two seriously injured people requiring prompt medical investigations and treatment, assuming the facility is equipped to deal with such an event.

### **2.2 Disasters**

*Natural Hazards - Impacts, Adjustments and Resilience*

*from washing away."*

*green foothills.*

nature and civilization [2].

**2. Definitions**

**2.1 Emergencies**

*Then the old man added, "unless it stops raining, the bridge stays above water, the power line's fixed, and we have enough sandbags for everyone to keep their houses*

*It wasn't totally exaggerated. The rain had been the worst in decades. Many homes in the low-lying village were already flooded. Those that were a little higher than the rest were already overcrowded with friends and relatives who's houses were in a foot or two of water. And the bridge, the only land access to the village, was visible only as rail posts marking a dotted line through the sea between the village and the*

Disasters require both a potentially harmful event and a component of vulnerability [1]. If an event overwhelms local response capacity, whether by insufficient material resources or by inadequate social systems or structure, outside help is needed. This is a disaster. Thus the magnitude of an event that causes a disaster will vary by organizational capacity. Many of the natural events described elsewhere in this textbook (earthquakes, tsunamis, etc.) create disasters. An earthquake in a remote, uninhabited area might be called a natural disaster, but it is not truly a disaster if people are not severely impacted. Disasters occur at the interface of

Emergency management is usually described in terms of planning, mitigation, response, and recovery. As we move along the spectrum of severity, from emergency to disaster, the same principles apply, with an emphasis on adaptability and collaboration. Specific to hospital disaster management, contextual issues such as triage, decontamination, and patient care are built upon a general and pervasive approach to disaster readiness. In resource-poor environments, the challenge is magnified as the impacts of natural disasters are greater, and the ability to respond and recover less. Education and training will be most effective if methods match the objectives. With all the uncertainty therein, training for disaster must include establishing relationships between organizations and allowing for flexibility in the

*Not every windstorm, earth-tremor, or rush of water is a catastrophe…So long as the ship rides out the storm, so long as the city resists the earth-shocks, so long as the levees hold, there is no disaster. It is the collapse of the cultural protections that*

From crisis to catastrophe, emergency to disaster, there is a spectrum of events that may threaten people and organizations. Not just the event, but the characteristics of the affected population define disaster. Risk and resilience are opposing

Disasters and emergencies differ in quality and magnitude but are often and inaccurately used synonymously. "Disasters are not just 'big emergencies'" ([4], p. 293). Emergencies are time-sensitive, potentially harmful events that put life and well-being at risk. Resources are available at the local level to prevent, mitigate, or minimize the harm, and a single responding organization is responsible [5, 6]. Local resources, as a variable in the equation, can affect what constitutes an emergency,

face of events that can be predicted but never fully anticipated.

*constitutes the disaster proper. ([3], p. 211)*

forces that must be considered with disaster management.

**4**

Disasters are sometimes considered "hypercomplex emergencies" or "major emergencies" involving multiple people at risk of harm, multiple jurisdictions responding, and resources that are not immediately available locally ([5], p. 8; [7]). Coordination between agencies, many of whom have no prior relationships, becomes a challenge [5]. Plans for resource utilization must change when those resources are overwhelmed [8]. Preparations, planning, and training at the local level, within the abilities and available resources of a single agency, do little to prepare for disaster.

## **2.3 Crisis**

Crisis is a more generic description. A crisis is a "critical event or point of decision which, if not handled in an appropriate and timely manner (or if not handled at all), may turn into a disaster or catastrophe" [9]. We use the word *crisis*, then, nonspecifically, as an emergency event that has potential to evolve; *emergency* as time-sensitive event with potential harm; and *disaster* as an event larger and more harmful than an emergency, with many people at risk, and where management requires resources outside of the responding organization or department.

#### **2.4 Catastrophe**

The word *catastrophe*, more severe than a disaster, completes the spectrum [5]. Many variations of the definition exist, but all suggest a magnitude of harm and inadequacy of response capabilities beyond what would be considered disaster [1] (**Figure 1**).