**3. Stability Analysis**

Weidman et al. [42] initiated a study of the stability analysis of multiple solutions. Since then, some researchers, such as Rosca and Pop [43] and Lund et al. [44,45], performed stability analyses in their studies on multiple solutions of fluid flow problems. They found that only the first or upper solution has a physical meaning, while all of the remaining solutions (second or third) are not physically relevant or, in other words, are said to be unstable solutions. The first step in finding the stability of the solutions is to change the momentum, heat, and concentration equations into an unsteady form by considering a new variable τ.  Equating the derivative of functions with respect to *x* being equal to zero leads to the new similarity transfer variables in the presence of τ and η, which can be expressed as:

$$\begin{array}{lcl}\psi = & \sqrt{2\mathcal{S}l\mathcal{U}l\_0e^{\frac{\pi}{2l}}}f(\eta,\tau);\mathcal{N} = \mathcal{U}e^{\frac{3\pi}{2l}}\sqrt{\frac{\mathcal{U}\_0}{2\mathcal{S}l\mathcal{U}}}g(\eta,\tau);\ \mathcal{O}(\eta,\tau) = \frac{(T-T\_{\text{ov}})}{(T\_w-T\_{\text{ov}})};\\\mathcal{O}(\eta,\tau) = & \frac{(\mathcal{C}-\mathcal{C}\_{\text{ov}})}{(\mathcal{C}\_w-\mathcal{C}\_{\text{ov}})};\ \eta = y\sqrt{\frac{\mathcal{U}\_0}{2\mathcal{N}l}}e^{\frac{\pi}{2l}};\ \tau = \frac{\mathcal{U}\_0}{2l}e^{\frac{\pi}{l}}t\end{array} \tag{22}$$

By applying Equation (22) in Equations (18)–(21), we get:

$$f(1+K)\frac{\partial^3 f}{\partial \eta^3} + f \frac{\partial^2 f}{\partial \eta^2} + K \frac{\partial g}{\partial \eta} - 2 \left(\frac{\partial f}{\partial \eta}\right)^2 - F\_S \left(\frac{\partial f}{\partial \eta}\right)^2 - K\_1 \frac{\partial f}{\partial \eta} - M \frac{\partial f}{\partial \eta} - \frac{\partial^2 f}{\partial \tau \partial \eta} = 0 \tag{23}$$

$$f\left(1+\frac{K}{2}\right)\frac{\partial^2 \mathcal{g}}{\partial \eta^2} + f\frac{\partial \mathcal{g}}{\partial \eta} - 3g\frac{\partial f}{\partial \eta} - 2Kg - K\frac{\partial^2 f}{\partial \eta^2} - \frac{\partial g}{\partial \tau} = 0\tag{24}$$

$$\frac{1}{Pr} \frac{\partial^2 \theta}{\partial \eta^2} + f \frac{\partial \theta}{\partial \eta} + N\_b \frac{\partial \mathcal{Q}}{\partial \eta} \frac{\partial \theta}{\partial \eta} + N\_l \left(\frac{\partial \theta}{\partial \eta}\right)^2 - \frac{\partial \theta}{\partial \tau} = 0 \tag{25}$$

$$\frac{\partial^2 \mathcal{Q}}{\partial \eta^2} + \text{Scf} \frac{\partial \mathcal{Q}}{\partial \eta} + \frac{N\_t}{N\_b} \frac{\partial^2 \theta}{\partial \eta^2} - \text{Sc} \frac{\partial \mathcal{Q}}{\partial \tau} = 0 \tag{26}$$

subject to the boundary conditions:

$$f(0, \tau) = \text{S; } \frac{\partial f(0, \tau)}{\partial \eta} = -1 + \lambda \frac{\partial^2 f(0, \tau)}{\partial \eta^2}; \text{g}(0, \tau) = -m \frac{\partial^2 f(0, \tau)}{\partial \eta^2}; \theta(0, \tau) = 1; \mathcal{Q}(0, \tau) = 1 \tag{27}$$

$$\frac{\partial f(\eta, \tau)}{\partial \eta} \to 0; \text{ g}(\eta, \tau) \to 0; \ \theta(\eta, \tau) \to 0; \mathcal{Q}(\eta, \tau) \to 0 \quad \text{as } \eta \to \infty$$

In order to indicate the solution stability of *f*(η) = *f*0(η), *g*(η) = *g*0(η), θ(η) = θ0(η) and ∅(η) = ∅0(η), which satisfy the equation of the boundary value problem (23)–(26) with boundary condition (27), we follow the suggestion of Rehman et al. [46] by introducing the following functions:

$$\begin{cases} f(\eta,\tau) = f\_0(\eta) + e^{-\varepsilon\tau} F(\eta,\tau) \\ g(\eta,\tau) = g\_0(\eta) + e^{-\varepsilon\tau} G(\eta,\tau) \\ \theta(\eta,\tau) = \theta\_0(\eta) + e^{-\varepsilon\tau} H(\eta,\tau) \\ \mathcal{Q}(\eta,\tau) = \mathcal{Q}\_0(\eta) + e^{-\varepsilon\tau} S(\eta,\tau) \end{cases} \tag{28}$$

where *F*(η, τ), *G*(η, τ), *H*(η, τ) and *S* (η, τ) are small relative to *f*0(η), *g*0(η), θ0(η) and ∅0(η) of the steady state solutions. It should be noted that the range of these functions are 0 < *F*(η, τ) < 1, 0 < *G*(η, τ) < 1, 0 < *H*(η, τ) < 1 and 0 < *S*(η, τ) < 1. Furthermore, ε is an unknown eigenvalue parameter, which needs to be found. Substituting the values of the functions and their derivatives from Equation (28) in Equations (23)–(26) with the boundary condition (27), we have:

$$(1+K)F\_{0}^{\prime\prime} + f\_{0}F\_{0}^{\prime\prime} + F\_{0}f\_{0}^{\prime\prime} + KG\_{0}^{\prime} - 4f\_{0}^{\prime}F\_{0}^{\prime} - 2F\_{S}f\_{0}^{\prime}F\_{0}^{\prime} - K\_{1}F\_{0}^{\prime} - MF\_{0}^{\prime} + \varepsilon F\_{0}^{\prime} = 0 \tag{29}$$

$$\left(1+\frac{K}{2}\right)G\_0'' + f\mathfrak{g}G\_0' + F\mathfrak{g}G\_0' - 3\mathfrak{g}\mathfrak{a}F\_0' - 3\mathfrak{g}\mathfrak{a}F\_0' - 2K\delta\mathfrak{G}\_0 - K\delta F\_0''' + \varepsilon\mathfrak{G}\_0 = 0\tag{30}$$

$$\frac{1}{Pr}H\_0'' + f\_0H\_0' + F\_0\theta\_0' + Nb\mathcal{Z}\_0'H\_0' + NbS\_0'\theta\_0' + 2Nt\theta\_0'H\_0' + \varepsilon H\_0 = 0\tag{31}$$

$$\mathcal{S}\_0^{\prime\prime} + \text{Sc}\Big(f\_0 \mathcal{Q}\_0^{\prime} + F\_0 \mathcal{S}\_0^{\prime}\Big) + \frac{\text{Nt}}{\text{Nb}} H\_0^{\prime\prime} + \text{Sc} \cdot \varepsilon \mathcal{S}\_0 = 0\tag{32}$$

subject to the boundary conditions:

$$\begin{aligned} F\_0(0) &= 0, F\_0'(0) = \lambda F\_0''(0), G\_0(0) = -m F\_0''(0), \; H\_0(0) = 0, \; S\_0(0) = 0 \\ F\_0'(\eta) &\to 0, \; G\_0(\eta) \to 0, H\_0(\eta) \to 0, S\_0(\eta) \to 0, \; \text{as } \eta \to \infty \end{aligned} \tag{33}$$

We assumed τ = 0 for Equations (23)–(26) in order to calculate the initial growth and decay of the solution of Equation (28), as recommended by Alarifi et al. [47]. Under these circumstances, *F*(η, τ), *G*(η, τ), *H*(η, τ) and *S* (η, τ) can be written as *F*0(η), *G*0(η), *H*0(η) and *S*0(η), respectively.

It is stated in the studies of Lund et al. [44,45] and Haris et al. [48] that eigenvalues can be determined if and only if the boundary condition of any one function of the following functions *F*0(η), *G*0(η), *H*0(η) and *S*0(η) can be relaxed into the initial condition by differentiating that function one more time. In this study, we relaxed *F*0(η) → 0 as η → ∞ and then solved the system of Equations (29)–(32) subject to Equation (33) along with the new relaxed boundary condition *F*-- 0(0) = 1. It is worth mentioning that the sign of the smallest eigenvalues (ε) determines the stability of the solutions. The smallest eigenvalue is negative (positive), which indicates that the solution of the flow is unstable (stable) and that there is an initial growth (decay) of disturbances.

#### **4. Results and Discussion**

In order to fully understand the considered fluid flow model, the numerical study has been carried out for various important physical parameters, such as the magnetic parameter *M*, permeability parameter *K*1, Forchheimmer parameter *FS*, non-Newtonian parameter *K*, thermophoresis parameter *Nt*, Brownian motion parameter *Nb*, etc. The highly non-linear system of the quasi-ordinary differential Equations (12)–(15), along with the boundary conditions (16), have been solved by using the shooting

method, and triple solutions were found. The value of η∞ is chosen from 4 to 8, and it is worth noting that the value of η∞ increases until the profiles of the velocity, temperature, and concentration converge asymptotically to the momentum, temperature, and concentration boundary layers, respectively.

Figure 2 was drawn to analyze the effect of the material parameter *K* on the velocity profiles. The thickness of the velocity boundary layer increases when the micropolar parameter *K* is increased in the first and the second solutions, due to the fact that the material parameter reduced the drag force and that the hydrodynamic boundary layer therefore rose. We noted that when *K* = 0 (Newtonian fluid), the second solution did not exist. On the other hand, the dual nature of the velocity profile was observed in the third solution. Figure 3 depicts the variation of the velocity profiles for the different values of the Forchheimmer parameter *FS*. We observed that, due to increments in *FS*, the resistant force occurred when the fluid flow was flowing on the porous surface, and hence the velocity of the flow declined in the third solutions. The dual behavior of the velocity profile was noticed in the second solution. However, no change could be seen in the first solution when *FS* was increased. The velocity and thickness of the momentum boundary layers are inversely (directly) proportional to *K*1 and *M* in the first (third) solution. On the other hand, the dual behavior of the velocity profile was seen in the second solution, as illustrated in Figures 4 and 5. The effect of the slip parameters λ and *m* on the velocity profiles are shown in Figures 6 and 7. In the first solution, the velocity boundary thickness was reduced as λ and *m* increased; this was due to the fact that the velocity of the fluid and surface have a big difference when the velocity slip factor is enhanced. For the second (third) solution, the velocity profiles decreased (increased) initially after they inclined (declined) when λ and *m* improved. The dual nature of the flow in some sense indicates that there is an initial growth of disturbance. Initially, the microrotation profile was reduced and then started to rise with increasing values of the micropolar parameter in the first solution, as shown in Figure 8. The thickness of the microrotation boundary layer was enhanced (reduced) as *K* was enhanced in the third (second) solution. The dual behavior of the microrotation profile was been observed in all solutions except the first solution when the value of *m* increased. The thickness of the microrotation boundary layer increased with increasing values of *m* in the first solution, as demonstrated in Figure 9. Figure 10 was drawn to analyze the variation of the temperature profiles for different values of the Prandtl number *Pr*. The thermal boundary layer thickness and temperature were incrementally reduced in the values of the Prandtl number *Pr* for all of the solutions, as expected. This is due to the fact that a high Prandtl number causes the thermal conductivity of nanofluid to diminish, and as a result the temperature is reduced. The variation of the temperature profiles for different values of the Brownian motion parameter *Nb* is shown in Figure 11. It was observed in all solutions of the temperature profiles that the temperature and thermal layer thickness were enhanced with increasing values of *Nb*. This is due to fact that the Brownian motion *Nb* increases the kinetic energy of the nanofluid; thus, the temperature of the nanofluid increases. The temperature profile, with an effect resulting from the thermophoresis parameter *Nt*, is illustrated in Figure 12. In all three solutions of the nanofluid flow problem, we noted that as the thermophoresis parameter *Nt* rose, the temperature and thickness of the thermal layer increased. This is because the thermophoretic force is generated by *Nt* and the temperature gradient, which pushes the flow of the nanofluid far from the boundary layer as a resulting thickness of the thermal boundary layer increases. The thickness of the concentration boundary layer declined with increasing values of the Brownian motion parameter *Nb* in all solutions in Figure 13, which was expected. This was physically justified by the fact that Brownian motion is generated when nanoparticle and base fluid are mixed together in a nanofluid system. Since Brownian diffusion shows the conduction of heat under those circumstances, the thickness of the concentration boundary layer decreases. Figure 14 was sketched to examine the effect of *Nt* on the concentration profile of nanoparticles. In all three solutions, the thickness of the concentration boundary layer was enhanced when thermophoresis increased.

**Figure 2.** Profiles of the velocity for increasing values of *K*.

**Figure 3.** Profiles of the velocity for increasing values of *FS*.

**Figure 4.** Profiles of the velocity for increasing values of *K*1.

**Figure 5.** Profiles of the velocity for increasing values of *M*.

**Figure 6.** Profiles of the velocity for increasing values of λ.

**Figure 7.** Profiles of the velocity for increasing values of *m*.

**Figure 8.** Microrotation profiles for increasing values of *K*.

**Figure 9.** Microrotation profiles for increasing values of *m*.

**Figure 10.** Temperature profiles for increasing values of *Pr*.

**Figure 11.** Temperature profiles for increasing values of *Nb*.

**Figure 12.** Temperature profiles for increasing values of *Nt*.

**Figure 13.** Nanoparticle concentration profiles for increasing values of *Nb*.

**Figure 14.** Nanoparticle concentration profiles for increasing values of *Nt*.

Wang [49] and many researchers also stated in their studies that the similarity solution of the fluid flow problems over the shrinking surface is possible to obtain when sufficient wall mass suction is applied. The flow of Newtonian fluid is different from that of non-Newtonian fluid; it is observed for micropolar nanofluid that when the value of the micropolar parameter *K* increases, a strong mass suction is required to obtain the solution. In this study, we discovered that there exist two regions for similarity solutions, namely multiple solutions and single solution, depending on the mass suction parameter. For *K* = 0.1(*K* = 0.2) there is a range of triple solutions when *S* ≥ 2.0337(*S* ≥ 2.7148), and a single similarity solution exists, *S* < 2.0337(*S* < 2.7148), as shown in Figure 15. When the suction is enhanced, the skin friction increases in the first solution and decreases in the second and the third solutions. Figures 16–18 were drawn to examine the effect of the suction *S* and micropolar parameter *K* on the couple stress coefficient, and the heat and concentration transfer rate, respectively. In all graphs, when the suction is increased, the couple stress coefficient, heat, and concentration transfer rate are enhanced for all of the solutions.

**Figure 15.** Coefficient of the skin friction with various values of *S*.

**Figure 16.** Couple stress coefficient with various values of *S*.

**Figure 17.** Heat transfer rate with various values of *S*.

**Figure 18.** Concentration transfer rate with various values of *S*.

By performing a stability analysis, the stability of the fluid flow solutions is achieved in this research. We need to perform a stability analysis when more than one solution exists in the flow problem. The main focus of this analysis is to determine which solution is stable and physically possible and which one is unstable. It is worth noting that the stability of the solution depends on the sign of the smallest eigenvalue. The value of the smallest eigenvalue is determined through Equation (24), for which we have to solve Equations (25)–(28), along with the boundary conditions (29). The smallest eigenvalues ε are demonstrated in Table 1 for different values of the suction and non-Newtonian parameters. It is clear from Table 1 that the negative (positive) values of the smallest eigenvalue ε

indicate an initial growth (decay) of the disturbance that will interrupt (resume) the boundary layer separation and flow from becoming unstable (stable). It is worth mentioning that the stable solution always provides a good physical meaning which can be realized.

**Table 1.** Smallest eigenvalues for different values of *K* and *S* when *M* = 0.5, *Pr* = *Sc* = 1, *m* = 0.5, *K*1 = 0.1, *FS* = 0.2, λ = 0.1, *Nb* = 0.2 and *Nt* = 0.15.


3. Conclusions

A comprehensive methodology for the design of a wasted heat energy recovery system is given. The general approach is to model separately the single stages starting from physical characteristic and derivate the resulting design constraints. Starting from the characteristic of a thermoelectrical generator cell, the mathematical model and the equivalent electrical model are obtained; after this step it was possible to design the TEG pack. From this point the generator is considered a general input for the power converter. Different topologies are analyzed, and all the fundamental design steps are reported for a non-inverting buck-boost converter: as part of the design, a loss estimation analysis was carried out. The control system is described as nested control loops. Two maximum power point tracking algorithms

placed after the TEG. The operating point is fixed; the value of the resistance seen by the TEG is initialized at a wrong value, after some iteration; and according to the maximum power transfer theorem, the maximum power point is reached. During the steady-state operation, the resistance value continuously changes its value as

seen in Section 2.4.1.

Maximum point tracking.

Figure 22.

Figure 21.

Figure 23.

124

Wasted heat energy recovery system block diagram.

System transfer functions and controller transfer function.

Advanced Thermoelectric Materials for Energy Harvesting Applications

are presented illustrating their characteristics and peculiarity. A state-space averaging method is used to obtain the converter transfer function in order to design a proper controller. Finally, simulation results and converter efficiency are shown in the last section. There are many possible advancements in this field from hardware and software point of view: development of new thermoelectric cells; use of more efficient power devices, for example, Gan FETs, in order to increase frequency and reduce passive components; and, also, development of faster and more efficient control algorithm are only some examples.

References

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[7] Twaha S, Zhu J, Yan Y, Li B, Huang

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[8] Montecucco A, Siviter J, Knox AR. Simple, fast and accurate maximum power point tracking converter for thermoelectric generators. In: 2012 IEEE Energy Conversion Congress and Exposition (ECCE). 2012. DOI: 10.1109/

[9] Lee JH, Bae H, Cho BH. Advanced incremental conductance MPPT algorithm with a variable step size. In:

[10] Liu B, Duan S, Liu F, Xu P. Analysis and improvement of maximum power point tracking algorithm based on incremental conductance method for photovoltaic array. In: 2007 7th International Conference on Power Electronics and Drive Systems. 2007. DOI: 10.1109/PEDS.2007.4487768

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[2] Liu C, Chen P, Li K. A 500 W lowtemperature thermoelectric generator: Design and experimental study. International Journal of Hydrogen Energy. 2014;39:15497-15505. DOI: 10.1016/j.ijhydene.2014.07.163

[3] Ji D, Romagnoli A. Modelling and design of thermoelectric generator for waste heat recovery. In: ASME Proceedings 9th Symposia: Fluid Mechanics (Fundamental Issues and

[4] Esram T, Chapman PL. Comparison of photovoltaic array maximum power point tracking techniques. IEEE Transactions on Energy Conversion. June 2007;22(2):439-449. DOI: 10.1109/

[5] Nagayoshi H, Kajikawa T, Sugiyama T. Comparison of maximum power

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**2. Definitions and sub-types of the cardiorenal syndrome**

Historically, the CRS is thought to have been due to impaired renal perfusion secondary to low cardiac output states or the result of HF therapies negatively impacting renal function. In 2004, the National Heart, Lung and Blood Institute defined CRS as a "state in which therapy to relieve heart failure symptoms is limited by further worsening in renal function" (National Heart, Lung and Blood Institute, 2004). By this paradigm, the heart was considered to be the central driving force behind impaired renal function in patients with HF.

Our understanding of the pathophysiology behind the CRS has evolved in the last number of years and there is increasing recognition of the complexity of interactions which exist between the heart and the kidneys, particularly when either or both organs are diseased. This organ cross talk is bidirectional in nature and the resultant dialogue is dependent on whether the heart or the kidney is the primary affected organ as well as the time course over which the associated pathophysiological changes may occur.

It is within this context, that newer definitions for the CRS have been proposed which recognize that either the heart or kidney may be the primary site of organ injury. A more comprehensive definition and classification schema for the CRS has the advantage of allowing clinicians to make a more accurate diagnosis which in turn informs our understanding of a given patient's natural history, prognosis and optimal treatment strategy.

The definition and classification system for CRS introduced by Ronco and colleagues in 2008 (Ronco et al., 2008) is now widely considered to be the preferred mechanism for describing patients and the pathophysiological processes associated with CRS. Ronco and colleagues broadly define CRS as "a pathophysiological disorder of the heart and kidneys whereby acute or chronic dysfunction of one organ may induce acute or chronic dysfunction of the other." Additionally, they characterize five sub-types of the CRS based on this definition. These are described and discussed below. It should be noted that CRS types 1-5 may frequently co-exist in a given patient, underscoring the complexity of interaction between the heart and kidney and the importance of appointing chronology to these processes.

#### **2.1 Cardiorenal syndrome type 1 (acute cardiorenal syndrome)**

Type 1 CRS is distinguished by an acute deterioration in cardiac function or acute cardiac injury, from any cause, that secondarily results in acute kidney injury (AKI).

of standard HF medications, such as angiotensin converting enzyme inhibitors, angiotensin receptor blockers and beta blockers in patients with HF and CKD, regardless of glomerular

Many novel therapies for HF have been introduced over recent years, several of which were appealing for treatment of the CRS, given the pathophysiological processes towards which they were directed. Unfortunately, natriuretic peptides, vasopressin antagonists, and adenosine antagonists have all failed to show meaningful clinical benefits in patients with HF (Hernandez, 2010; Konstam et al., 2007; Massie et al., 2010). Other approaches, particularly peripheral ultrafiltration, have shown more promise in this patient population

Historically, the CRS is thought to have been due to impaired renal perfusion secondary to low cardiac output states or the result of HF therapies negatively impacting renal function. In 2004, the National Heart, Lung and Blood Institute defined CRS as a "state in which therapy to relieve heart failure symptoms is limited by further worsening in renal function" (National Heart, Lung and Blood Institute, 2004). By this paradigm, the heart was considered to be the central driving force behind impaired renal function in patients with

Our understanding of the pathophysiology behind the CRS has evolved in the last number of years and there is increasing recognition of the complexity of interactions which exist between the heart and the kidneys, particularly when either or both organs are diseased. This organ cross talk is bidirectional in nature and the resultant dialogue is dependent on whether the heart or the kidney is the primary affected organ as well as the time course over

It is within this context, that newer definitions for the CRS have been proposed which recognize that either the heart or kidney may be the primary site of organ injury. A more comprehensive definition and classification schema for the CRS has the advantage of allowing clinicians to make a more accurate diagnosis which in turn informs our understanding of a given patient's natural history, prognosis and optimal treatment

The definition and classification system for CRS introduced by Ronco and colleagues in 2008 (Ronco et al., 2008) is now widely considered to be the preferred mechanism for describing patients and the pathophysiological processes associated with CRS. Ronco and colleagues broadly define CRS as "a pathophysiological disorder of the heart and kidneys whereby acute or chronic dysfunction of one organ may induce acute or chronic dysfunction of the other." Additionally, they characterize five sub-types of the CRS based on this definition. These are described and discussed below. It should be noted that CRS types 1-5 may frequently co-exist in a given patient, underscoring the complexity of interaction between the heart and kidney and the importance of appointing chronology to these processes.

Type 1 CRS is distinguished by an acute deterioration in cardiac function or acute cardiac injury, from any cause, that secondarily results in acute kidney injury (AKI).

filtration rate (GFR) (Berger et al., 2007; Cice et al., 2003).

**2. Definitions and sub-types of the cardiorenal syndrome**

which the associated pathophysiological changes may occur.

**2.1 Cardiorenal syndrome type 1 (acute cardiorenal syndrome)**

(Costanzo et al., 2005).

HF.

strategy.

Pathophysiologically, Type 1 CRS is characterized by decreased cardiac output with impaired renal perfusion as well as elevated central venous pressures and acute renal edema. Renal ischemia may be mediated by decreased oxygen delivery due to impaired myocardial contractile performance, elevated interstitial pressures in the renal medulla and by peripheral/systemic vasoconstriction which occurs as a compensatory mechanism in the face of low cardiac output.

Historically, decreased forward cardiac flow was thought to be the primary determinant for AKI in this context, however recent clinical trials have suggested this mechanism may not be as important in the development of CRS Type I as previously hypothesized. Specifically, data from ADHERE (Acute Decompensated Heart Failure National Registry) which included over 100,000 patients admitted to hospital in the United States with acute decompensated heart failure (ADHF) showed that <2% of patients had systemic hypotension, a surrogate for low cardiac output, while the vast majority of patients had symptoms/signs of volume overload (Adams et al., 2005). This is corroborated by the findings of the ESCAPE (Evaluation Study of Congestive Heart Failure and Pulmonary Artery Catheterization Effectiveness) Trial in which 433 patients admitted to hospital with ADHF were randomized to pulmonary artery catheterization versus standard care to assess the efficacy of tailored haemodynamic therapy (Binanay et al., 2005). In the ESCAPE Trial, cardiac index was not associated with baseline renal function or deterioration in renal function, however right atrial pressure was weakly correlated with baseline creatinine and GFR (Nohria et al., 2008).

The impact of central venous pressures (CVP) on worsening renal function in the setting of ADHF has been receiving greater attention in recent years. Elevated CVP is more predictive of a decline in renal function than other relevant haemodynamic variables such as cardiac index, blood pressure and pulmonary capillary wedge pressure (Mullens et al., 2009). Moreover, elevated CVP predicts risk of re-hospitalization for HF and death suggesting that it is a potent prognosticator for poor outcomes and a potential target for therapy (Uthoff et al., 2011). Elevated intra-abdominal venous pressures have also been shown to have a similar relationship with GFR at baseline and changes in GFR with therapy (Bock & Gottlieb, 2010; S. E. Bradley & G. P. Bradley). This may be the result of a direct mechanical effect on renal blood flow or simply a reflection of elevated CVP.

Among patients with ADHF, activation of the sympathetic nervous system (SNS) and the renin-angiotensin-aldosterone system (RAAS) is a homeostatic mechanism intended to maintain intraglomerular perfusion pressures and preserve GFR. Paradoxically however, systemic vasoconstriction by these mechanisms increases cardiac afterload leading to further decline in cardiac output and renal blood flow. Additionally, these neurohormones have a maladaptive effect on the myocardium resulting in fibrosis and ventricular remodeling. Treatment with β-blockers is relatively contra-indicated in the face of an acute decompensation due to their negative inotropic effects and the relative dependence of cardiac output on heart rate in this patient population; therefore, SNS activation in CRS Type 1 may remain unchecked leading to ischemia of both renal and cardiac tissue beds.

Acute administration of RAAS inhibition may exacerbate renal injury in CRS Type 1 by reducing pressure in Bowman's capsule; this effect may be magnified in the presence of volume shifts associated with diuretics, which remains the mainstay of therapy. Moreover, diuretics may directly result in additional neurohormonal activation and there is now an

Sub-Types and Therapeutic Management of the Cardiorenal Syndrome 127

hospitalization solely to CRS Type 1 thereby underestimating the presence of concomitant CRS Type 2 in this cohort of patients. Novel biomarkers of AKI may help clinicians to decipher the relative contributions of CRS Type 1 versus CRS Type 2 in patients hospitalized for HF who have poor renal function upon presentation (Siew et al., 2011; Coca et al., 2008). Regardless of cause, renal insufficiency in hospitalized HF patients appears to be relatively common; among those enrolled in ADHERE, the prevalence of at least moderate renal impairment, as determined by GFR, was greater than 60% at baseline (Heywood et al., 2007). This is in sharp contrast to initial reports from the same registry which suggested a prevalence rate of only 20% when a serum creatinine of 2.0 mg/dL was employed as a cut off (Adams et al., 2005). Calculation of GFR, therefore, is paramount to accurately

The true burden of pre-existing renal dysfunction among patients with HF was best characterized in a meta-analysis performed by Smith and colleagues. In their systematic review of the literature, approximately 80,000 hospitalized and non-hospitalized patients with HF were identified across 16 clinical trials. While 29% of patients were found to have moderate to severe renal impairment (GFR <53 mL/min or cystatin C of >1.56 mg/dL), 63% were found to have at least some degree of impaired kidney function. Moreover, these findings are likely to underestimate the true prevalence of renal insufficiency in HF populations given that 8 of the clinical trials included in the meta-analysis excluded patients

In the meta-analysis performed by Smith and colleagues, renal impairment at baseline conferred an increased risk of mortality at one year follow-up compared to patients with normal kidney function (Smith et al., 2006). The adjusted hazard ratio for patients with any renal impairment or moderate to severe renal impairment was 1.56 and 2.31 respectively. Excess risk was conferred in an incremental fashion with each 10 mL/min reduction in GFR correlating to a 7% increase in the risk of death. This observation is strengthened by similar findings across a spectrum of clinical trials in both hospitalized and ambulatory HF populations (Adams et al., 2005; Dries et al., 2000; Fonarow et al., 2005; Heywood et al., 2007;

Many of the pathophysiological mechanisms which characterize CRS Type 1 are also implicated in the development of CRS Type 2, although many of these processes may occur slowly and over longer periods of time. For example, elevated central venous pressure is strongly associated with a decline in eGFR among patients with chronic HF (Damman et al., 2009; Firth et al., 1988); as described above, the same is true for patients with ADHF and CRS Type 1. Elevated CVP and secondarily an elevation in renal venous pressure may trigger a number of downstream events, including interstitial ischemia, neurohormonal activation and decreased responsiveness to natriuretic peptides which all combine to reduce GFR directly or indirectly (Damman et al., 2007; Bock & Gottlieb, 2010) in the setting of chronic HF. Chronically low cardiac output, particularly in combination with micro and macrovascular renal disease, may also contribute to fibrosis and structural changes in the

RAAS activation occurs in both HF and CKD with an associated increase in Angiotensin II levels (AII). AII mediates oxidative injury and endothelial dysfunction through both the formation of reactive oxygen species and a decrease in nitric oxide bioavailability. Each of

on the basis of age or an elevated serum creatinine at baseline (Smith et al., 2006).

identifying the burden of renal disease in all forms of CRS.

Hillege et al., 2006).

kidney which result in impaired renal function.

increasing body of literature suggesting that diuretics, in and of themselves, may be associated with worse outcomes in patients with ADHF independent of other relevant clinical variables. In a single centre retrospective analysis of 1354 patients admitted with ADHF, Eshaghian and colleagues (Eshaghian et al., 2006) demonstrated that patients requiring the highest doses of diuretics, stratified by quartiles, had higher rates of sudden death, death due to progressive pump failure and all cause mortality compared to patients in the lowest quartile of diuretic dose. This type of observation has fueled a growing interest in identifying alternate strategies for fluid management in the acute setting, independent of diuretic administration (see section 3.8).

Of particular concern among patients who present with the features of CRS Type 1 is the impact of diagnostic imaging and invasive cardiac procedures which may have an additional and direct toxic effect on the kidneys through a variety of mechanisms. Individuals who present with an acute deterioration in cardiac function will frequently require imaging or investigation to identify a precipitant or cause for their symptoms. Independently, percutaneous interventions and cardiac surgery impart a risk of AKI which is higher in patients who have pre-existing or concomitant acute renal insufficiency (Anderson et al., 1999; Best et al., 2002).

Upwards of 70% of patients admitted to hospital with ADHF will experience a rise in serum creatinine over the course of their admission (Gottleib et al., 2002); this may be the result of therapies administered, either medical or invasive, or a consequence of the various pathophysiological processes which characterize CRS Type 1. Regardless of mechanism, worsening renal function portends a poor prognosis and is associated with higher mortality rates. (Gottleib et al., 2002; Damman et al., 2007).


**2. Basics of economic assessment of a biomass based power generation system**

The practical outcomes of a biomass-based energy system can be evaluated mainly from two aspects. Number one is from energy content of the biomass in a desired form and number two is economic justification of the specific power generation systems. The evaluation process follows some steps like [6]:


*Edited by Farzad Ebrahimi*

Functionally graded materials (FGMs) were initially designed as thermal barrier materials for aerospace structures and fusion reactors and now they are also considered as potential structural materials for future high-speed spacecraft and recently are being increasingly considered in various applications to maximize strengths and integrities of many engineering structures. This book is a result of contributions of experts from international scientific community working in different aspects of FGMs and structures and reports on the state of the art research and development findings on this topic through original and innovative research studies. Through its six chapters the reader will have access to works related to processing, sintering properties and applications of functionally graded ceramics and new processing routes for FGMs while it introduces some specific applications, such as functionally graded annular fins and the high-performance self-lubricating ceramic composites with laminated graded structure. Besides, it presents an experimental crack propagation analysis of aluminum matrix FGMs and a unified accurate solution for three-dimensional vibration analysis of functionally graded plates and cylindrical shells with general boundary conditions.

ISBN 978-953-51-2274-6

Advances in Functionally Graded Materials and Structures

Photo by Cakeio / iStock


Preface

Medically important RNA viruses with families include: Togavirus, Bunyavirus, Flavivirus, Filovirus, Arenavirus, Rhabdovirus, Paramyxovirus, Orthomyxovirus, Coronavirus, Retrovirus, Picornavirus, Reovirus, and Calicivirus. Some RNA viruses contain double-stranded RNA (Family Reoviridae) and some viruses have a life cycle that uses reverse transcriptase. Viruses contain ribonucleic acid (RNA) as their genetic material. Particularly, several human diseases are caused by RNA viruses. The main objective of this book on RNA viruses was to understand the RNA virus i.e a seroprevalence study based on molecular epidemiology such as genotyping tools by IgM/IgG, ELISA, PCR, FRNT50 and phylogenetic analysis to further confirm the RNA viruses causing diseases in tropical and subtropical countries. However, pathogenesis mechanisms causing viral diseases among the flaviviruses family have not been clearly understood and also little is known about the host responses to RNA viral infection. This book will surely help with these information gaps and also provide research information to the policymaker or planner for further diagnosis, control and prevention in future outbreaks of RNA virus diseases in tropical and subtropical countries.

> **Yogendra Shah** National Zonosis and Food Hygience Research Center, Nepal

> > **Eltayb Abuelzein** Central Veterinary Research Laboratories, Sudan

**1**

**Chapter 1**

**Abstract**

*Adamu Ishaku Akyala*

indicating it may be more transmissible.

clinical characteristics, viral shedding

**1. Introduction**

**Keywords:** coronavirus disease 2019 (COVID-19), transmission,

In late December, 2019, an epidemic of respiratory disease caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) began in the city of Wuhan in China which spread to over 30 countries of the world [1]. In the last 25 years, notable highly infectious respiratory viruses with pandemic potentials has emerged and remerged. Notable of which is the influenza virus that issued a

Mode of Transmission and

Emerging New Paradigms

Viral Shedding of SARS-CoV-2:

SAR CoV-2 is an important group of animal and human pathogens that infect respiratory tract, hepatic, gastroenterological, and nervous systems of mouse, bat, bat, humans and other vertebrates. Middle East Respiratory Syndrome (MERS) and severe acute respiratory syndrome (SARS) Outbreaks in 2002–2003 have demonstrated the possibility of human to human transmission, animals to humans transmission of the emerging SARS-CoV-2. The World Health Organization (WHO) On 12 January 2020 renamed novel coronavirus infectious disease (COVID-19) to SARS-CoV-2 In late 2019, the first case of the COVID-19 was reported. A total of 87,137 confirmed cases globally, 79,968 confirmed in China and 7169 outside of China, with 2977 deaths (3.4%) had been reported by WHO in March 1, 2020. Meanwhile, several independent research groups have identified that SARS-CoV-2 belongs to β-coronavirus, with highly identical genome to bat coronavirus, pointing to bat as the natural host and by proxy has a zoonotic propensity. Angiotensin-converting enzyme 2 (ACE2) is the same receptor been used by the novel coronavirus as that of SARS-CoV and largely spreads through the respiratory tract. Currently, there are few specific antiviral strategies, but several potent candidates of antivirals and repurposed drugs are under urgent investigation. In this review, we summarized the latest research progress on the transmission mode dynamics and viral shedding in provide direction for isolation protocol. R0 estimates for SARS have been reported to range between 2 and 5, which is within the range of the mean R0 for COVID-19 found in this review. Due to similarities of both pathogen and region of exposure, this is expected. On the other hand, despite the heightened public awareness and impressively strong interventional response, the COVID-19 is already more widespread than SARS,


*Supporting open minds since 2005*

Geographic Information Systems in Geospatial Intelligence http://dx.doi.org/10.5772/intechopen.84925 Edited by Rustam B. Rustamov

#### Contributors

Dada Nade, Swapnil Potdar, Rani Pawar, Arnaud Le Bris, Nesrine Chehata, Debasish Chakraborty, Ali Dhafer Abed Yaha, Yashon Ombado Ouma, Andon Dimitrov Lazarov, Dimitar Minchev, Chavdar Minchev, Menachem Domb, Rustam B. Rustamov, Nasim Tohidi, Xavier Briottet, Nicolas Paparoditis

#### © The Editor(s) and the Author(s) 2020

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**1. Introduction**

The implementation of the new legislation on health and safety on work place [1] aims to insure employee's health and safety. The reported‐about research investigates the current situation of the leadership culture, especially concerning the health promotion. Therefore, we first focus on the current research state concerning the role of health and safety at workplace and especially on the attitudes about health promotion and leaders' behavior.

 Therefore, workplaces should be designed in a human‐oriented way, following the tradition since 1950s. Having healthy, satisfied and motivated employees, who enjoy health and safety at workplace, enables positive economic outcomes, increased competitiveness and profitability; it also affects other factors in the business positively. Healthy jobs and workplaces benefit workers/employees, customers and shareholders, citizens, society and the state [2, 3].

After EU‐OSHA [4], workplace health promotion (WHP) encompasses employers', employees' and society's actions improving the human health and well‐being at work. It integrated the following activities in the defined area:

These activities must be planned and implemented. The key factors therefore include leaders who can form, stimulate and change the work environment substantially. This special part can present the health‐promoting leadership culture (HPLC), which we measured in Slovenian organizations. One should know this culture as the basis to develop special trainings for improving leaders' leadership style.

The law on health and safety at work was implemented in Slovenia in 2011. On this basis, Slovenian organizations started their workplace health promotion (WPC) programs. The responsibility for WPC is on employers and leaders, i.e., managers on all hierarchical level. For successful implementation of WHP, leaders should lead their employees in a way, supporting their health. The reported‐about research covered the Slovenian leaders' leadership style concerning their employees' health after implementing the said new legislation. We conducted a survey on health‐promoting leadership culture in Slovenian organizations in 2013, which is the first research, conducted after the above‐mentioned new legislation passing.


**Author details**

Deepa Jatti Patil1 \* and Rakesh Nagaraju2

1 Department of Oral Medicine and Radiology, K.M. Shah Dental College and Hospital, Sumandeep Vidyapeeth (Deemed University), Vadodara, Gujarat, India

2 Faculty of Dental Sciences, Department of Oral Medicine and Radiology, M.S. Ramaiah University of Applied Sciences, Bangalore, India

\*Address all correspondence to<EMAIL_ADDRESS>
© 2021 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.

*Personalised Precision Medicine - A Novel Approach for Oral Cancer Management DOI: http://dx.doi.org/10.5772/intechopen.99558*


**7.1.1. Sedimentary phosphate rocks**

Most marine sediments and rocks contain less than 0.3% of P2O5. However, periodically through geological time, phosphorites (with the content of P2O5 of 5% or greater) formed on the seafloor in response to specialized oceanic conditions and accumulated in sufficient concentrations to produce major deposits of regional extent4 [26].

Marine phosphate formation and deposition represent the periods of low rates of sedimenta‐ tion in combination with large supplies of nutrients. Phosphorus is then concentrated by various mechanisms, possibly bacterial (refer to discussion of **Fig. 7**), at either the sedimentwater interface or within interstitial pore waters. This process leads to primary formation and growth of phosphate grains, which remain where they were formed or are transported as clastic particles within the environment offormation. During subsequent periods oftime, some primary phosphate grains may be physically reworked into another sediment unit in re‐ sponse to either changing or different environmental processes [26].

**Fig. 2.** The distribution of the world's phosphate resources [20].

4 Most of the world's phosphate production comes from marine phosphorites [27].

ical systems, the phosphate content is the limiting factor for growth. Nearly all igneous rocks contain some phosphate, even if it is only ~0.1% (0.2% P2O5 on average in lithosphere), with nearly all of it in the form of apatite. Sedimentary rocks generally contain rather less (~0.1% P2O5 on average). Sedimentary phosphorite is believed to originate from widely dispersed

Most marine sediments and rocks contain less than 0.3% of P2O5. However, periodically through geological time, phosphorites (with the content of P2O5 of 5% or greater) formed on the seafloor in response to specialized oceanic conditions and accumulated in sufficient

Marine phosphate formation and deposition represent the periods of low rates of sedimenta‐ tion in combination with large supplies of nutrients. Phosphorus is then concentrated by various mechanisms, possibly bacterial (refer to discussion of **Fig. 7**), at either the sedimentwater interface or within interstitial pore waters. This process leads to primary formation and growth of phosphate grains, which remain where they were formed or are transported as clastic particles within the environment offormation. During subsequent periods oftime, some primary phosphate grains may be physically reworked into another sediment unit in re‐

[26].

apatite mainly in igneous rocks [25].

**7.1.1. Sedimentary phosphate rocks**

concentrations to produce major deposits of regional extent4

338 Apatites and their Synthetic Analogues - Synthesis, Structure, Properties and Applications

sponse to either changing or different environmental processes [26].

**Fig. 2.** The distribution of the world's phosphate resources [20].

Most of the world's phosphate production comes from marine phosphorites [27].

4

**Fig. 3.** Stratigraphic distribution of phosphorites based on 1982 production data (a) and distribution of major Protero‐ zoic-Cambrian phosphorites (b) [28].

The stratigraphic distribution5 [29] of phosphorites [28] is shown in **Fig. 3**(**a**). The major discoveries in Proterozoic and Cambrian rocks were not made until late 1930s, initially in the USSR (Kazakhstan), Poland, Korea, China and northern Vietnam. Early discoveries were made in the course of regional geological mapping and exploration for metal deposits, but later deposits were found mainly using more direct exploration techniques. It is possible that the greatest global phosphogenic episode in geological history took place in Late Proterozoic and Cambrian. While pelletal phosphorites are common in most Cambrian deposits, the Protero‐ zoic age phosphorites contain mudstone (**Fig. 3**(**b**), microphosphorite) and stromatolitic phosphorite6 [28],[30].

Some phosphates were formed during all major sea-level transgressions during 67 million years of Cenozoic history; however, some periods were more important than others with respect to producing large volumes of phosphorites and preserving them in the geologic column. During the Paleocene and Eocene, several major episodes of phosphogenesis occurred within the major episodes of phosphogenesis in the major east-west ocean, which included Tethys [31],7 producing extensive amounts of phosphorites throughout the Middle East, Mediterranean and northern South American regions. By the Neogene, this circum-global ocean had been destroyed by the plate tectonic processes, and the north-south Pacific and

5 Since the Earth is stratified, in a broad sense, all rocks and classes of rocks (sedimentary, igneous and metamorphic) fall within the scope of stratigraphy and stratigraphic classification. Rocks can be classified according to lithology, fossil content, magnetic polarity, electrical properties, seismic response, chemical or mineralogical composition, etc. Rocks can be also classified according to time of their origin or environment of genesis. Rock bodies can be classified into many different categories of stratigraphic classification, including lithostratigraphic units (1), biostratigraphic units (2), chronostratigraphic units (3), unconformity-bounded units (4) and magnetostratigraphic units (5). Please see work [29] for further details.

6 Phosphate occurs as concentrated in stromatolite columns, laminar algal (stromatolitic) phosphorite, reworked fragments of stromatolites forming silicified conglomeratic or brecciated phosphorite, massive-bedded phosphorite with sandy and clayey laminate and disseminate pellets and nodules in dolomite [30].

7 The Tethys Ocean divided the continental masses into northern and southern groups. It merged at both ends with the Panthalassa or proto-Pacific Ocean. The remnants of Tethys are now located within Alpine mountain belts from the Caribbean in the west to recent collision zone between Australia and Eurasia in the east and within still-growing Central Atlantic Ocean between Africa and North America [31].

Atlantic oceans dominated global circulation patterns. Upper Cenozoic phosphogenesis (**Table 1**) occurred along the north-south ocean-ways, which now contain modern continen‐ tal margins. On the basis of the extent of known phosphate deposits, the Miocene was by far the most important episode of phosphate formation in Upper Cenozoic [26].

*ma* – million years ago, *ta* – thousand years

**Table 1.** Formation of phosphorites during Upper Cenozoic phosphogenesis [26].

Phosphorites and phosphatic sediments are known on the floor of the Pacific, Indian and Atlantic oceans. They occur in a number of inshore areas (the shelves and upper part of the continental slopes) and in pelagic zones, chiefly on seamounts. Most of the shelf phosphor‐ ites are localized in four very large oceanic phosphorite provinces [32],[26],[33]:

Sedimentary rocks with the content of 18 – 20 wt.% of P2O5 are termed as phosphorites. The main phosphate mineral in phosphorites is carbonate-fluorapatite (CAF, francolite): Ca10−a−b −cNaaMgb(PO4)6−x(CO3)x−y−z(CO3,F)y(SO4)zF2, where *x* = *y* + *a* + 2*c* and *c* denotes the number of Ca vacancies, present as grain or mud. Most phosphorites are of marine origin [34],[35],[36]. Phosphorites on the sea floor occur in two types of environments on [37]:

Atlantic oceans dominated global circulation patterns. Upper Cenozoic phosphogenesis (**Table 1**) occurred along the north-south ocean-ways, which now contain modern continen‐ tal margins. On the basis of the extent of known phosphate deposits, the Miocene was by far

the most important episode of phosphate formation in Upper Cenozoic [26].

**Quaternary** 258 *ma* to present

340 Apatites and their Synthetic Analogues - Synthesis, Structure, Properties and Applications

**Neogene** 23.03 – 2.58 *ma*

**Table 1.** Formation of phosphorites during Upper Cenozoic phosphogenesis [26].

**Phanerozoic** (541 *ma* to present) **Cenozoic** (66 *ma* to present)

*ma* – million years ago, *ta* – thousand years

and East Australian shelf.

**Geological period Age Duration**

**Holocene**

**Pleistocene** 2.58 – 0.0117 *ma*

**Pliocene** 5.333 – 2.58 *ma*

**Miocene** 23.03 – 5.333 *ma*

**Paleogene** 66 – 23.03 *ma*

Phosphorites and phosphatic sediments are known on the floor of the Pacific, Indian and Atlantic oceans. They occur in a number of inshore areas (the shelves and upper part of the continental slopes) and in pelagic zones, chiefly on seamounts. Most of the shelf phosphor‐

**a. East Atlantic**: Portugal, northwest Africa throughout South Africa and Agulhas Bank;

**b. West Atlantic**: North Carolina throughout Florida, Cuba, Venezuela and Argentina;

**c. East Pacific**: California throughout Baja California, Mexico and Peru throughout Chile;

**d. West Pacific**: Sakalin Island, Sea of Japan, Indonesia, Chathman Rise east of New Zealand

Sedimentary rocks with the content of 18 – 20 wt.% of P2O5 are termed as phosphorites. The main phosphate mineral in phosphorites is carbonate-fluorapatite (CAF, francolite): Ca10−a−b −cNaaMgb(PO4)6−x(CO3)x−y−z(CO3,F)y(SO4)zF2, where *x* = *y* + *a* + 2*c* and *c* denotes the number of Ca vacancies, present as grain or mud. Most phosphorites are of marine origin [34],[35],[36].

**ii.** Submerged mountains in association with calcareous and volcanogenic rocks.

ites are localized in four very large oceanic phosphorite provinces [32],[26],[33]:

Phosphorites on the sea floor occur in two types of environments on [37]:

**i.** Continental margins in association with terrigenous;

0.0117 *ma* to present

<3 *ma* 10 *ta*

5 – 4 *ma* 1 *ma*

19 – 13 *ma* 6 *ma*

29 – 25 *ma* 4 *ma*

**Oligocene** 33.9 – 23.03 *ma*

**Fig. 4.** The surface currents in an idealized ocean, showing the areas of ascending nutrient-rich water (a) and the distri‐ bution of upwelling water and related phenomena in modern oceans (b) [27].

Phosphorites consist mainly of phosphate cement enveloping small grains of phosphatic and non-phosphatic materials. Phosphate in the cavities of foraminifera is purer than that enveloping the grains [37].

The largest phosphorite-bearing regions are situated along the west coasts of Africa and America, at the east coast of the USA, off New Zealand and in the central part of the north‐ ern Pacific. The phosphatic matter of phosphorites consists of carbonate-fluorapatite and is intermixed with variable amounts of terrigenous, biogenic and diagenetic non-phosphatic components, which are the cause of a wide range of fluctuations in their chemical composi‐ tions. The age of sea-floor phosphorites varies from Cretaceous to Recent. Recent phosphor‐ ites are localized in the south west of Africa and at Peru-Chile shelves, which are the areas influenced by strong upwelling of nutrient-rich waters (**Fig. 4**(**a**)), resulting in high biologi‐ cal productivity, intensive biogenic sedimentation and diagenetic redistribution of geochem‐ ically active, mobile, organic-derived phosphorus in sediments. This phosphorus is accreted in the form of initially soft and friable nodules undergoing gradual lithification [27],[37].

Pronounced climatic, biological and geologic effects accompany upwelling, especially where it is produced by the divergence in coastal areas (**Fig. 4**(**b**)). The presence of cold waters along the coasts produces the coastal fogs and humid-air deserts, such as those of northern Chile and southwest Africa. The nutrient-rich waters that lie alongside these deserts are the lushest gardens of the sea, as the upwelling cold waters there support tremendous quantities of organisms. Most of large accumulations of guano (**Section 7.2.2**) are formed by the seafowl colonies feeding in these waters, and it is the extremely dry climate created by upwelling that makes the preservation of guano possible [27].

Sedimentary deposits usually contain varieties of carbonate-fluorapatite called francolite (described in **Section 2.6**). Francolite is defined as apatite that contains significant amount of CO2 with less than 1% of fluorine. Apatite associated with igneous source rocks may be of primary magmatic, hydrothermal or secondary origin. Primary apatite from igneous sources may be of fluorapatite, hydroxylapatite or chlorapatite varieties. Pure apatites from igneous deposits contain slightly over 42% of P2O5 [23].

Since a wide range of very different particles and processes offormation complicates the simple classification of phosphorites, there is not any unified phosphorite classification8 [18],[36],[38]. The proposed classification schemes for phosphorites describe their constituent particles, such as pelletal phosphorite. Nonetheless, the descriptor pelletal indicates nothing more than rounded phosphate particles of any origin. A widely recognized distinction in phosphorites is based on the grain size and holds specifically among phosphorites where the phosphate particles are of sand- or coarse silt-size and those that are of clay- and fine silt-size [28]. The phosphorites can be classified as follows [37]:

	- **a. Ferruginized** with glazed surface. The cement of ferruginized phosphorites is much richer in finely dispersed goethite than that of non-ferruginized phosphorites. Furthermore, ferruginized phosphorites do not contain the fragments of macrofauna.
	- **b. Non-ferruginized** with rough surface. In non-ferruginized phosphorites, the cement is micrite-collophane and its color varies form yellow (collophane, described in **Section 2.6**) to gray (micrite9 [19]). The chambers of foraminifera are filled with phosphate-carbonate cement, less often with glauconite or goethite (FeO(OH) [33]).

Some nodules of phosphatized limestone are coated with a discontinuous layer of secondary phosphate with the thickness up to 1 cm.

**2. Conglomeratic phosphorites** consist of pebbles of phosphatized limestone (up to 50% of the rock) held together by the cement similar in composition to the phosphatized glauconite-quartz sandstones described above. In many samples of this type, two orthree conglomerate layers are clearly visible, differing in size of pebbles and in content of glauconite. The bedding planes separating the layers with denser or less dense packing of grains are also distinguished in the cement. The surface of these planes is glazed and brown due to higher content of iron hydroxides and organic matter. Upon impact, the rock breaks along the planes. In addition, irregular microerosion surfaces are observed in

8 The nature and origin of phosphorites have been a matter of much speculation since they were first discovered more than 150 years ago [38], and there is not any commonly accepted nomenclature [39].

9 Micrite (the abbreviation for microcrystalline calcite) is characterized by crypto- to microcrystalline crystal texture. As the synonym of micrite, the names as lime mud, lime ooze, lime mudstone, calcimudstone and calcilutite are also used. The original definition sets a grain-size limit to < 4 μm, but current terminology distinguishes between minimicrite (<1 μm), micrite I (1 – 4 μm) and micrite II (4 – 30 μm). Furthermore, primary micrites (orthomicrites and nannoagorites), secondary micrites and pseudomicrites are recognized. Orthomicrites consist of subhedral polygonal calcite grains meeting at the interfaces. Nannoagorites are composed of calcareous pelagic biota. Secondary and pseudo micrites result from the diagenetic processes [19].

the conglomeratic phosphorites, which run across the grains of glauconite, shells and bedding planes [33].

The investigation of the microstructure of phosphorites by electron microscopy enables to recognize the following varieties [33]:

CO2 with less than 1% of fluorine. Apatite associated with igneous source rocks may be of primary magmatic, hydrothermal or secondary origin. Primary apatite from igneous sources may be of fluorapatite, hydroxylapatite or chlorapatite varieties. Pure apatites from igneous

Since a wide range of very different particles and processes offormation complicates the simple

The proposed classification schemes for phosphorites describe their constituent particles, such as pelletal phosphorite. Nonetheless, the descriptor pelletal indicates nothing more than rounded phosphate particles of any origin. A widely recognized distinction in phosphorites is based on the grain size and holds specifically among phosphorites where the phosphate particles are of sand- or coarse silt-size and those that are of clay- and fine silt-size [28]. The

**1. Non-conglomeratic** (also termed as **nodular**) phosphorites: consist of phosphatized limestones and gluconate-quartz sandstones. Two varieties of nodular phosphorites can

**a. Ferruginized** with glazed surface. The cement of ferruginized phosphorites is much richer in finely dispersed goethite than that of non-ferruginized phosphorites. Furthermore, ferruginized phosphorites do not contain the fragments of macrofauna.

**b. Non-ferruginized** with rough surface. In non-ferruginized phosphorites, the cement is micrite-collophane and its color varies form yellow (collophane, described in

Some nodules of phosphatized limestone are coated with a discontinuous layer of

**2. Conglomeratic phosphorites** consist of pebbles of phosphatized limestone (up to 50% of the rock) held together by the cement similar in composition to the phosphatized glauconite-quartz sandstones described above. In many samples of this type, two orthree conglomerate layers are clearly visible, differing in size of pebbles and in content of glauconite. The bedding planes separating the layers with denser or less dense packing of grains are also distinguished in the cement. The surface of these planes is glazed and brown due to higher content of iron hydroxides and organic matter. Upon impact, the rock breaks along the planes. In addition, irregular microerosion surfaces are observed in

8 The nature and origin of phosphorites have been a matter of much speculation since they were first discovered more

9 Micrite (the abbreviation for microcrystalline calcite) is characterized by crypto- to microcrystalline crystal texture. As the synonym of micrite, the names as lime mud, lime ooze, lime mudstone, calcimudstone and calcilutite are also used. The original definition sets a grain-size limit to < 4 μm, but current terminology distinguishes between minimicrite (<1 μm), micrite I (1 – 4 μm) and micrite II (4 – 30 μm). Furthermore, primary micrites (orthomicrites and nannoagorites), secondary micrites and pseudomicrites are recognized. Orthomicrites consist of subhedral polygonal calcite grains meeting at the interfaces. Nannoagorites are composed of calcareous pelagic biota. Secondary and pseudo micrites result

phosphate-carbonate cement, less often with glauconite or goethite (FeO(OH) [33]).

[19]). The chambers of foraminifera are filled with

[18],[36],[38].

classification of phosphorites, there is not any unified phosphorite classification8

342 Apatites and their Synthetic Analogues - Synthesis, Structure, Properties and Applications

deposits contain slightly over 42% of P2O5 [23].

phosphorites can be classified as follows [37]:

**Section 2.6**) to gray (micrite9

secondary phosphate with the thickness up to 1 cm.

than 150 years ago [38], and there is not any commonly accepted nomenclature [39].

be recognized:

from the diagenetic processes [19].

With regard to their texture and petrographic character, phosphorites can be classified according to the predominant size of the phosphorite component into four types [40]:

Although the types are named on the structural basis, the phosphate grains do not always have the dimensions given above. At the same time, the classified types fairly differ in many features, such as the association with various geological formations, the phosphate mineralo‐ gy and the stratigraphic sequence, thus being of lithologic character [40].

Most attempts to classify the phosphorite rocks adopt and modify the classification scheme for carbonates [36]. In 1962, DUNHAM [41] published the classification scheme for limestone. This scheme for carbonate rocks was modified for non-genetic classification of phosphorites (**Fig. 5**) [28].

**Fig. 5.** The classification scheme of carbonate rocks modified for phosphorites [28].

The macroscopic classification scheme for phosphate sediments suggested by RIGGS [42] is shown in **Fig. 6**(**a**). The ancient deposits are better characterized via the scheme in **Fig. 6**(**b**), which was proposed by KASTERN and GARRISON [43]. In this model, three types of phosphates were recognized [39],[43]:

CFAP cements in P- and D-phosphates are often replaced microbial structures, but our data do not reveal whether this microbial involvement was passive or active. F-phosphates are most common in deeper water, outer-shelf/upper-slope sites, whereas D- and P-phosphates tend to predominate at shallower shelf sites more subjected to episodic high-energy conditions, especially during the low stands of sea level. This concept reveals the paleoenvironmental and time relationships of various phosphate sediments [39],[43].

**Fig. 6.** The classification scheme of phosphorites proposed by RIGGS (a) and GARRISON and KASTNER [ 43 ].

Phosphorites can be formed in nature **authigenically** or **diagenically**. In authigenesis, phosphorite forms as a result of the reaction of soluble phosphate with calcium ions forming corresponding insoluble phosphate compound. The role of microbes in these processes may be one or more of the following [44]:

**Fig. 5.** The classification scheme of carbonate rocks modified for phosphorites [28].

344 Apatites and their Synthetic Analogues - Synthesis, Structure, Properties and Applications

were recognized [39],[43]:

The macroscopic classification scheme for phosphate sediments suggested by RIGGS [42] is shown in **Fig. 6**(**a**). The ancient deposits are better characterized via the scheme in **Fig. 6**(**b**), which was proposed by KASTERN and GARRISON [43]. In this model, three types of phosphates

**i.** F-phosphates are friable, light-colored micronodules and peloids of carbonate-

**ii.** Phosphatic sands, termed as P-phosphates, consist of phosphatic peloids, coated

**iii.** Dark and dense phosphates, herein called D-phosphates, are the most abundant.

CFAP cements in P- and D-phosphates are often replaced microbial structures, but our data do not reveal whether this microbial involvement was passive or active. F-phosphates are most common in deeper water, outer-shelf/upper-slope sites, whereas D- and P-phosphates tend to predominate at shallower shelf sites more subjected to episodic high-energy conditions, especially during the low stands of sea level. This concept reveals the paleoenvironmental and

diatom muds deposited within the oxygen-minimum zone.

sands occur in thin layers and burrowed beds up to 2 m thick.

time relationships of various phosphate sediments [39],[43].

fluorapatite (CFAP); they were formed by the precipitation of CFAP in laminated

grains and fish debris, often having an admixture of fine siliciclastic grains. These

They occur as nodules, gravels and hard grounds. These phosphates were formed through complicated cycles of CFAP precipitation during early diagenesis, erosion and exhumation and reburial and rephosphatization processes associated with changing energy conditions, which may reflect the effects of changes in the sea level.

> **c.** Generating or maintaining the pH and redox conditions, which favor the precipitation of phosphate.

The models of authigenic phosphorite genesis (**Fig. 7**) assume the occurrence of mineraliza‐ tion of organic phosphorus in biologically productive waters, such as at ocean margins, that is, at shallow depths on continental slopes, shelf areas or plateaus [44].

Here, detrital accumulations may be mineralized at the sediment-water interface and in interstitial pore waters, liberating phosphate, some of which may then interact chemically with calcium in seawater to form phosphorite grains. These grains may be subsequently redistrib‐ uted within the sediments units. The dissolution of fish debris (bones) is also considered an important source of phosphate in authigenic phosphorite genesis. The upwelling probably also plays an important role in many cases of authigenic formation of phosphorite. During non-upwelling period in winter, the phosphate-sequestering bacteria of oxidative genera *Pseudomonas* and *Acinetobacter* become dominant in the water column. Fermentative Vibrios and Enterobacteriaceae are dominant during upwelling in summer. It was suggested that *Pseudomonas* and *Acinetobacter*, which sequester phosphate as polyphosphate under aerobic conditions and hydrolyze polyphosphate under anaerobic conditions to obtain the energy of maintenance and to sequester volatile fatty acid from polyhydroxybutyrate formation,

**Fig. 7.** The schematic presentation of formation of phosphorite in marine environment [44].

contribute to the phosphorite formation. Locally elevated, excreted orthophosphate becomes available for the precipitation as phosphorite by reacting with seawater calcium [44].

Authigenic phosphorite formation at some eastern continental margins, where upwelling, if occurred at all, was a weak and intermittent process that may have been formed more directly as a result of intracellular bacterial phosphate accumulation, which became transformed into carbonate-fluorapatite upon the death of cells accumulated in sediments in areas where the sedimentation rate was very low [44].

The model of diagenetic formation of phosphorite generally assumes the exchange of phosphate for carbonate in accretions that have the form of calcite and aragonite. The role of bacteria in this process is to mobilize phosphate by mineralizing detrital organic matter. The demonstration of this process in marine and freshwater environment under laboratory conditions leads to the hypothesis that the diagenesis of calcite to form apatite explains the origin of some deposits in the North Atlantic. The phosphorite deposits of Baja California and in the core of eastern Pacific Ocean seem to have formed as a result of partial diagenesis [44].


**3. Results**

The DLP and MSSP models were solved while using Gurobi (version 9.1). The DLP models are quite small, with the largest one being the DLP-SH solved at *t* = 1 in the simulations (1231 constraints and 1291 variables). The DLP-RH with a 10-period window size has 411 constraints and 431 variables. The shrinking and rolling horizon DLP models both have CPU solve times that are below 0.3 s on average. The largest MSSP model solved is the MSSP-SH solved at *t* = 1 (263,958 constraints and 299,941 variables), which has an average CPU solve time of 119 s. The MSSP-RH with a 10-period window size has 64,698 constraints and 71,521 variables. The average CPU time to solve the MSSP-RH model is 12 s.

Table 2 summarizes the performance results from each solution method. Figure 6 shows the total inventory profiles at each node for the lost sales case. The total inventory includes both on-hand inventory and pipeline inventory incoming from a node's suppliers. Similar results (not shown) were observed for the backlogging case. Figures 7 and 8 show sample network flow plots for the RL and MSSP-RH models, respectively. The cumulative network flow plots for both DLP instances and MSSP-SH are not shown as they are similar to that of MSSP-RH. The edge thickness is proportional to the average total amount of material requested through that link. These network flows indicate the suppliers that are prioritized by the different model policies. Figure 9 shows the average unfulfilled market demand at the retailer node (lost sales), which gives an indication of the service levels of the supply network. A similar result is obtained for the backlogging case.

**Table 2.** Total reward comparison for the various models used to solve the IMP. *Performance Ratio* is defined as the ratio of the final cumulative profit of the perfect information model to that of the model used. *DLP* = Deterministic linear program; *MSSP* = Multi-stage stochastic program; *RL* = Reinforcement Learning; *RH* = rolling horizon; *SH* = shrinking horizon; *Oracle* = perfect information LP.

**Figure 6.** Average total inventory at each main network node (lost sales mode). Shaded areas denote ±1 standard deviation of the mean value.

**Figure 7.** Average network flow with the RL policy (lost sales mode). Total flow is proportional to the edge thickness.

**Figure 8.** Average network flow with the MSSP-RH policy (lost sales mode). Total flow is proportional to the edge thickness.

**Figure 9.** Average unfulfilled demands at the retailer node (lost sales mode).


**2. Stiffness**

Normal knee range of motion (ROM) ranges from 0 to 140 degrees, while achievement of postoperative ROM from 0 to 110 degrees can be defined as success TKA [4]. In general, a minimum of 90 degrees of knee flexion is required for functional recovery in daily activities, as 83 degrees of knee flexion is required for going up and down stairs and 93 degrees for sitting, which were demonstrated by a biomechanical study [5, 6]. Stiffness after TKA has variable incidence, ranging from 1.3 to 5.3 percent, but some literature proposed up to 60 percent of patients who suffered from stiff TKA [7]. These variables may cause by a variety of definitions as there was absolutely no consensus on degrees of knee flexion limitation defined as stiff TKA. The standardized definition by the TKA Complications Workgroup of The Knee Society described that limitation of ROM as reported by the patient with physical examination showed extension restriction to 15 degrees short of full extension or flexion less than 90 degrees were defined as stiffness. However, this definition could not be applicable if the preoperative arc of motion is less than 75 degrees [3].


3.11.1 Leaf extracts

To evaluate the antipyretic activity, different doses (100, 200, and 300 mg/kg body wt. p.o.) of ethanolic leaf extracts showed significant dose-dependent reduction in normal body temperature and yeast-induced elevated temperature (pyrexia) in albino rats. The antipyretic effect of this extract was comparable to that of the standard antipyretic agent paracetamol at 150 mg/kg body wt., p.o. The effect extended up to 5 hours after drug administration compared to that of paracetamol (150 mg/kg.b.wt., p.o.) [2, 6].


**Author details**

Tanja Soldatović Department of Chemical-Technological Sciences, State University of Novi Pazar, Novi Pazar, Serbia

\*Address all correspondence to<EMAIL_ADDRESS>
© 2020 The Author(s). Licensee IntechOpen. This chapter is distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/ by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


*2.2. Spectral Data Collection and Nutrient Processing*

Data collection and processing methods included in situ spectral data collection and ex situ laboratory nutrient analyses. The methodology proceeded in four general phases (Figure 2), which are briefly described here and detailed below. First, canopy spectral measurements and plant samples were collected at the four sites immediately prior to peak crop maturity (seed head stage). Next, plant samples were dried and separated in the laboratory where the grain was imaged and both the plant material and grain were subjected to nutrient analyses. Third, the relationship between the nutrients and spectral components were modeled using PLS regression with both the full spectrum and a waveband selection method. Lastly, the replicability of the PLS regression methods were tested through statistical comparisons of model fits and similarity of results.

**Figure 2.** Methods flowchart detailing data collection and processing methods.

In Phase 1, canopy-level hyperspectral measurements and plant material were collected at each site immediately prior to harvest during peak maturity, which was late June/early July 2016 in the US and October 2017 in Ethiopia. For each of the four sites, 40 random points were generated in ArcGIS, providing 80 possible sampling location in each country. These points were then located in the field using a hand-held GPS unit (Trimble Juno 3B, Corvallis, OR, USA). In some cases, locations could not be accessed due to sampling on the days of harvest and attempting to not interfere with the harvesting practices of the respective farmers, so the actual number of samples is below 40 for each field and below 80 for the region. At all sampling sites, canopy spectral data were captured using the same spectroradiometer (FieldSpec Pro FR: Analytical Spectral Devices [ASD], Boulder, CO, USA), measuring reflectance from 350–2500 nm with a spectral sampling width of 1.4 nm from 350–1000 nm and 2.0 nm from 1000–2500 nm. The spectroradiometer was calibrated using a Spectralon diffuse reference panel (Analytical Spectral Devices [ASD], Boulder, CO, USA) approximately every 15 min. The spectralon was held at a distance from the spectroradiometer fiber to ensure no shadows were measured. The spectroradiometer fiber was held 1.2 m above the ground; since the top of canopy was about 0.3 m above ground, the cone of acceptance was 25◦, resulting in a footprint with a diameter of 0.40 m for each sample. This diameter ensured a sufficient mass of plant/grain matter was collected for nutrient testing (10 g of grain; SSSA, 1990; [37]). Reflectance data were captured between 11:00 a.m. and 2:00 p.m. local time under a cloud-free sky. It is important to mention that the same spectroradiometer was operated by the same individual in all locations to ensure the exact same data collection process was reproduced. Each location was imaged five times in succession, and spectra were averaged. Plant material in the footprint of the imaging fiber was then clipped at the base, stored in plastic bags, and placed on ice in a cooler for transport back to the laboratory.

In the laboratory, samples were dried to remove excess moisture, and the grains were separated from the plant using a traditional method of hand threshing with the assistance of a basket weaved surface. The grains from each sample, which measure approximately 1 mm in length, were aggregated in a petri dish to generate a sufficient amount to fully cover the lens of the imaging equipment. The grains were spectrally imaged in a dark room using a contact probe (Contact Probe: Analytical Spectral Devices [ASD], Boulder, CO, USA) with a halogen light source, while not equivalent to the sun, still emitted spectral wavelengths (350–2500 nm) capable of being identified using the same spectroradiometer used in the field (Figure 3). As with the in situ samples, five spectral readings were collected for each sample, and the values averaged.

**Figure 3.** Use of spectroadiometer in the field (**left**) and a close-up of *Eragrostis tef* (tef; **right**).


**6. Improving collaborations**

If opportunities for identifying and building resilience exist within taking a people-centred approach and embracing the complexity of cities through a systems lens, then a third, vital area concerns improving collaborations between the vast range of actors involved in disaster recovery—and, in particular, engaging those who are often excluded from traditional decision-making processes.

Local actors include local governments, local NGOs and community groups, private sector businesses, community neighbourhood groups and faith-based organisations. Groups often less engaged with include gangs. According to Hagedorn (2014), 'while most gangs are unsupervised teenage peer groups, many are institutionalised in ghettos, barrios and *favelas* across the world' [30].

Disaster recovery operations involving international humanitarian organisations have a poor track record when it comes to collaborating with local actors. Local actors such as local authorities and local NGOs can feel excluded from coordination meetings—usually held in English—that are dominated by cash-rich international NGOs, UN agencies and others. One study of the response of 13 INGOs following Typhoon Haiyan found that, across the track of the typhoon that struck the central region of the Philippines, local government was largely bypassed by aid agencies, which worked directly at the community level [31].

#### *Identifying Opportunities to Build Resilience in Urban Disaster Recovery DOI: http://dx.doi.org/10.5772/intechopen.109475*

The system for agency coordination that has been in place since 2005 is known as 'the cluster system', which essentially convenes meetings between agencies delivering assistance along sectoral lines (such as health, protection and education). The system though has come in for criticism in relation to urban response: as the Inter-Agency Standing Committee (IASC) states, 'the current cluster system is structured around sectors of expertise and sectorial coordination, while in a context of urban crises there might be a need to identify and respond holistically to multi-sectorial needs in a given territory, requiring stronger inter-cluster linkages and coordination at citylevel' [32]. Also, the International Rescue Committee (IRC) notes, 'The traditional cluster system does not lend itself to the complexity of needs, services and systems across an urban landscape with humanitarian agencies struggling to deal with the complexity, density and built environment of towns and cities or [un]able to take full advantage of the potential a city has to offer' [33].

A large opportunity therefore for building resilience in recovery concerns improving collaboration between actors. This in particular means international agencies supporting local actors. Collaboration, ranging from information exchange, negotiation, discussion and possible coordination, with a number of actors, despite the Cluster approach, is vital. Gangs, who are often gatekeepers to lower-income settlements, need to be engaged with. The International Committee of the Red Cross and Red Crescent Societies (ICRC) notes that it is important to gain acceptance from gang leaders, that there needs to be a benefit accrued to gang leaders, and to avoid undermining the status and position of gangs in recovery efforts relief [34].

Better collaboration of course also means sharing—or sometimes reversing—power, something which is very difficult indeed for those who hold the power. This essentially was at the core of the outcomes of the first-ever World Humanitarian Summit (WHS), held in 2016. Some 8000 delegates from across the world attended, including UN agencies, donors, Northern and Southern NGOs and others. The resulting 'Grand Bargain', negotiated at the conference, identified nine thematic work streams, which among other things called for greater transparency (such as in in decision-making and prioritisation of support) and more support and funding tools to local and national responders.


**4.4 RAGE, endothelial dysfunction and insulin resistance**

Impaired insulin action, when assessed by fasting serum insulin levels or the homeostasis model assessment of insulin resistance (HOMA-IR) 92, is associated with atherosclerosis and an increased risk of myocardial infarction. Insulin resistance is associated with endothelial dysfunction 93 and may serve as a link between insulin resistance and atherosclerosis. Recent findings by Harja et al highlighted the involvement of RAGE in endothelial dysfunction 81. Endothelium-dependent vasorelaxation was tested in isolated mouse aortic rings from *apoE– /–* and *apoE–/–RAGE–/–* mice, and relaxation response to acetylcholine was significantly improved in the RAGE deficient mouse. Similarly, impaired endothelial function in diabetic obese mice was also shown to be mediated by AGEs/RAGE system, since blockade of AGE-RAGE interaction by soluble RAGE significantly improved endothelial function 94. Recent clinical observations by Linden et al 44 also implies AGEs/RAGE system is involved in impaired endothelial function in patients with chronic kidney diseases. Thus, not only by the interaction at the cellular signaling level, but RAGE appears to impair endothelial function and potentially blood flow in insulin target tissues, leading to insulin resistance in vivo.


*Article* **Bioinformatic Analysis of** *Ixodes ricinus* **Long Non-Coding RNAs Predicts Their Binding Ability of Host miRNAs**

**José María Medina 1,2 , Muhammad Nadeem Abbas 3 , Chaima Bensaoud 4 , Michael Hackenberg 1,2,\* ,† and Michail Kotsyfakis 4,\* ,†**

**Abstract:** *Ixodes ricinus* ticks are distributed across Europe and are a vector of tick-borne diseases. Although *I. ricinus* transcriptome studies have focused exclusively on protein coding genes, the last decade witnessed a strong increase in long non-coding RNA (lncRNA) research and characterization. Here, we report for the first time an exhaustive analysis of these non-coding molecules in *I. ricinus* based on 131 RNA-seq datasets from three different BioProjects. Using this data, we obtained a consensus set of lncRNAs and showed that lncRNA expression is stable among different studies. While the length distribution of lncRNAs from the individual data sets is biased toward short length values, implying the existence of technical artefacts, the consensus lncRNAs show a more homogeneous distribution emphasizing the importance to incorporate data from different sources to generate a solid reference set of lncRNAs. KEGG enrichment analysis of host miRNAs putatively targeting lncRNAs upregulated upon feeding showed that these miRNAs are involved in several relevant functions for the tick-host interaction. The possibility that at least some tick lncRNAs act as host miRNA sponges was further explored by identifying lncRNAs with many target regions for a given host miRNA or sets of host miRNAs that consistently target lncRNAs together. Overall, our findings suggest that lncRNAs that may act as sponges have diverse biological roles related to the tick–host interaction in different tissues.

**Keywords:** *Ixodes ricinus*; ectoparasite-host interactions; host immunity; RNA-sequencing; lncRNA


**4. Water and aquatic habitats**

**3. Climate change**

6 Pure and Applied Biogeography

manity depend on it.

synergistic way.

also has a significant impact on climate.

edented degree of consensus in the scientific world.

well known in the diversity of nature or near-nature grasslands [32].

today, but there are some important points that are beyond dispute:

society, which are also reflected in large-scale biogeographical patterns.

consequences can be very serious if we are not prepared for them.

Climate change—in close connection with overpopulation, global species extinction and biodiversity crisis, and social crises—is the biggest challenge for mankind in our history. An adequate and stable global climate system is the most basic living condition of the biosphere, and as a part of it, human society and even all other living conditions are dependent on climate. This climatic system also determines the basic biogeographic patterns of our Earth. The fact and the anthropogenic origin of climate change are supported by evidence of a multitude of research findings and observations. With regard to these two things, there is an unprec-

In the background of this phenomenon, there are a lot of causes in strict connection with each other like overpopulation of mankind, the fossil fuel production and burning since the industrial revolution, the rapid eradication of forests and natural wetlands, industrial and transport pollution, unsustainable agricultural practices, and the rapid urbanization. Human activity is causing the greatest damage and dangers by breaking down the healthy functioning and regulatory capacity of the Earth's biosphere, eradicating primeval forests and rainforests, draining bogs and swamps, and reducing forest cover. The importance of grazing is also

There are a number of well-founded and less well-founded opinions about climate change

**1.** The climate determines the living conditions of ecosystems and, at the same time, human

**2.** Past climate changes have always had significant ecological impacts, mass extinction of species, new species becoming dominant, and a fundamental change in landscape.

**3.** The history of the Earth shows a great deal of climate changes, so it must be our basic attitude that, because climate is variable, it changes and the biogeographical and social

**4.** A better understanding of the relationship between climate and biosphere should be seen as one of our most important research tasks because the existence and prosperity of hu-

**5.**  In our time, global crisis phenomena (biodiversity crisis, raw material and energy problems, consequences of overpopulation and climate change) interact with one another in a

Natural ecosystems provide carbon dioxide binding and storing functions, feedback processes, and in a number of direct and indirect ways regulate the climate in a biogeographical scale, and provide retention and dispensing of leaking residues, as well as the development of favorable Aquatic ecosystems were, for a long time, a neglected area of biogeography, though more than 70% of our planet is covered with water. Water is the foundation of all earthly life, plays a key role in climate change and spatial-temporal patterns of biodiversity, and decisively defines human activity and the possibilities of agriculture.

Climate change and biodiversity crisis issues have a particularly large impact on water, aquatic ecosystems and wet habitats such as oceanic biotopes [36], surface freshwater [37, 38], or groundwater [39]. The state of river water vegetation also has a fundamental effect on animal communities [40].

In the biogeographical research on hydrobiology, the following key issues can be identified: