Released this past November, the list is based on data collected from the Web of Science and highlights some of the world’s most influential scientific minds by naming the researchers whose publications over the previous decade have included a high number of Highly Cited Papers placing them among the top 1% most-cited.
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We wish to congratulate all of the researchers named and especially our authors on this amazing accomplishment! We are happy and proud to share in their success!
IntechOpen is proud to announce that 191 of our authors have made the Clarivate™ Highly Cited Researchers List for 2020, ranking them among the top 1% most-cited.
\n\n
Throughout the years, the list has named a total of 261 IntechOpen authors as Highly Cited. Of those researchers, 69 have been featured on the list multiple times.
\n\n\n\n
Released this past November, the list is based on data collected from the Web of Science and highlights some of the world’s most influential scientific minds by naming the researchers whose publications over the previous decade have included a high number of Highly Cited Papers placing them among the top 1% most-cited.
\n\n
We wish to congratulate all of the researchers named and especially our authors on this amazing accomplishment! We are happy and proud to share in their success!
Note: Edited in March 2021
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1. Introduction
The development of waves under the action of wind is a process that is difficult to simulate since surface waves are very conservative and their energy changes over hundreds and thousands of periods. This is why the most popular method is spectral modeling based on the averaged over phase equations for spectral energy. In this approach, the waves as physical objects are actually absent since the evolution of spectral distribution of the wave energy is simulated. The description of input and dissipation in this approach is not directly connected with the formulation of the problem, but it is rather adopted from other branches of the wave theory where waves are the objects of investigation. However, the spectral approach was found to be the only method capable to describe the space and time evolution of wave field in the ocean. The phase resolving models (or ‘direct’ models) designed for reproducing waves themselves cannot compete with spectral models since such models typically can reproduce the evolution of just several thousands of large waves. Nevertheless, the direct wave modeling plays an ever-increasing role in the geophysical fluid dynamics because it gives the possibility to investigate the processes that cannot be reproduced by spectral models.
The spectral model assumes that wave field consists of a superposition of linear waves with random phases and arbitrary angle distribution. Being converted to a physical wave field, it looks unreal because real waves usually have prolonged smooth troughs and sharp peaks. Such shape suggests that the waves are similar to Stokes waves. For any given wave spectrum, the wave field can be represented as a superposition of linear Fourier modes with random phases [1]. It can be represented also as a superposition of Stokes modes. The calculations of statistical characteristics for both wave fields show that they are nearly identical. However, such conclusion could be made with no calculations because typical steepness of sea waves at reasonable spectral resolution is of the order of 0.01–0.05, so all the amplitudes of Stokes modes starting from the second one are small. It follows that the specific shape of sea waves is a dynamic property.
The breaking is usually initiated in the vicinity of wave peaks, so the breaking parameterization describes the processes, which are, in principle, impossible in a linear wave field. The breaking is concentrated in the separated narrow intervals; an instantaneous spectrum is discrete and is shifted to high frequencies. The spectral description of the isolated extreme waves is also impossible. The Fourier transform of a large-scale wave field including separated large waves does not provide any indications of their appearance.
The input energy to waves is based on the assumption that each mode induces a pressure mode with a certain amplitude and phase. In reality, the pressure field is quite complicated and not directly connected with the surface elevation because of the systematic separation of air flow behind wave crests (which was shown experimentally in Refs. [2, 3] with the coupled wind-wave model). There are many other complications in the coupled wind-wave dynamics [4] including the processes connected with sprays, bubbles, foam, and structure of the high-frequency wave spectrum.
Most (but not all) of the processes mentioned above can be investigated using the numerical modeling that is a perfect instrument for development of parameterization of physical processes for spectral wave models.
The phase-resolving models can completely replace the spectral models for direct simulation of wave regimes of small water basins, for example, port harbors (see Refs. [5, 6]). Other approaches of direct modeling are discussed in Refs. [7, 8].
Over the past decades, a big volume of papers devoted to the numerical methods developed for investigation of wave processes has been published. The most advanced among them are Finite Difference Method [5, 6], Finite Volume Method [9], Finite Element Method [10, 11], Boundary (Integral) Element Method [12], Spectral HOS Methods [13, 14, 15, 16, 17], the Smoothed Particle Hydrodynamics Method [18], Large Eddy Simulation Method (LES) [19, 20], Moving Particle Semi-Implicit Method [21], Constrained Interpolation Profile Method [22], and Method of Fundamental Solutions [23]. Most of the models were designed for engineering application handling such processes as overturning waves, broken waves, waves generated by landslides, freak waves, solitary waves, tsunamis, violent sloshing waves, interaction of extreme waves with beaches, as well as interaction of steep waves with fixed and different floating structures. The wave models designed for engineering applications seem to be more advanced than the models for pure geophysical research. However, as a rule, the engineering models pay little attention to description of physical processes that are responsible for a long-term evolution of wave spectrum. A more detailed review of direct numerical models is given in Ref. [8].
Until recently, the direct modeling was used for reproduction of a quasi-stationary wave regime when wave spectrum does not change significantly. An example of direct numerical modeling of surface wave evolution is given in Ref. [24] where the development of wave field was calculated by using of a two-dimensional model based on full potential equations written in the conformal coordinates. A model included the algorithms for parameterization of the input and dissipation of energy (a description of similar algorithms is given below). The model successfully reproduced the evolution of wave spectrum under the action of wind. That model was a prototype of 3-D model, because being very fast it was convenient for development of the physical process parameterization. However, the strictly one-dimensional (unidirected) waves are not quite realistic since the unidirected waves in the presence of the small-amplitude perturbations relatively quickly turn into the two-dimensional wave field [25]. Hence, the full problem of wave evolution should be formulated on the basis of three-dimensional equations. Such 3-D calculations were done by Chalikov [26]. The model included parameterization of the main physical processes: input energy, different types of dissipation, and transformation of spectrum due to the nonlinear interaction. The last process does not require any parameterization because the nonlinearity is described with equations. The model used a relatively poor resolution (1024×512 nodes in x and y directions). However, the calculations reproduced the evolution of wave spectrum and the spectra of the main physical processes such as input and dissipation of energy and nonlinear interactions. As long as we know, it was the first attempt to reproduce the development of waves based on full three-dimensional equations with a direct solution of 3-D equation for the velocity potential. The current paper is devoted to development of the method, including the tuning and modifications of the algorithm, the increase of resolution, and the integration for longer periods. The most important but pure technical modifications were introduced in the numerical scheme for Poisson equation for the velocity potential. The algorithms for calculation of the input and dissipation remain nearly the same, but the numerical parameters in those schemes were changed to achieve a better agreement with the rate of spectrum evolution given by JONSWAP approximation.
2. Equations
The nonstationary surface-following nonorthogonal coordinate system is used as follows:
ξ=x,ϑ=y,ζ=z−ηξϑτ,τ=t,E1
where ηxyt=ηξϑτ is a moving periodic wave surface given by the Fourier series
ηξϑτ=∑−Mx<k<Mx∑−My<l<Myhk,lτΘk,l,E2
where k and l are the components of the wave number vector k; hk,lτ are Fourier amplitudes for elevations ηξϑτ; Mx and My are the numbers of modes in the directions ξ and ϑ, respectively, while Θk,l are the Fourier expansion basis functions represented as the matrix:
The 3-D equations of potential waves in the system of coordinates (1) at ζ≤0 take the following form:
ητ=−ηξφξ−ηϑφϑ+1+ηξ2+ηϑ2Φς,E4
φτ=−12φξ2+φϑ2−1+ηξ2+ηϑ2Φζ2−η−p,E5
Φξξ+Φϑϑ+Φζζ=ϒΦ,E6
where ϒ is the operator:
ϒ=2ηξξζ+2ηϑϑζ+ηξξ+ηϑϑζ−ηξ2+ηϑ2ζζ,E7
capital fonts Φ are used for the domain ζ<0, while the lower case φ refers to ζ=0. The term p in Eq. (5) describes the pressure on the surface ζ=0.
It is suggested by Chalikov et al. [7] that it is convenient to represent the velocity potential φ as a sum of the two components: a linear component Φ¯,φ¯=Φ¯ξϑ0 and an arbitrary nonlinear component Φ˜,φ˜=Φ˜ξϑ0:
φ=φ¯+φ˜,Φ=Φ¯+Φ˜.E8
The linear component Φ¯ satisfies Laplace equation:
Φ¯ξξ+Φ¯ϑϑ+Φ¯ζζ=0,E9
with a known solution:
Φ¯ξϑζτ=∑k,lφ¯k,lτexpkζΘk,l,E10
where k=k2+l21/2, φ¯k,l are the Fourier coefficients of the surface linear potential φ¯ at ζ=0). The solution satisfies the following boundary conditions:
The presentation (8) is not used for solution of the evolutionary Eqs. (4) and (5) because it does not provide any improvements of accuracy and speed.
Eqs. (4)–(6) are written in a nondimensional form by using the following scales: length L, where 2πL is a (dimensional) period in the horizontal direction; time L1/2g−1/2; and velocity potential L3/2g1/2 (g is the acceleration of gravity). The pressure is normalized by the water density, so that the pressure scale is Lg. Eqs. (4)–(6) are self-similar to the transformation with respect to L. The dimensional size of the domain is 2πL, so the scaled size is 2π. All of the results presented in this paper are nondimensional. Note that the number of the Fourier modes can be different in the x and y directions. In this case, it is assumed that the two-length scales Lx and Ly are used. The nondimensional length of the domain in the y-direction remains equal to 2π, and a factor r=Lx/Ly is introduced into the definition of a differential operator in the Fourier space.
The derivatives of a linear component Φ¯ in (7) are calculated analytically. The scheme combines a 2-D Fourier transform method in the ‘horizontal surfaces’ and a second-order finite-difference approximation on the stretched staggered grid defined by the relation Δζj+1=χΔζj (Δζ is a vertical step, while j=1 at the surface). The stretched grid provides an increase in accuracy of approximation for the exponentially decaying modes. The values of the stretching coefficient χ lie for different settings within the interval 1.01–1.20; in the current work, the valueγ=1.2 was used at the number of levels Lw=10. Such poor resolution was possible to use because of the separation of the potential into a large linear and a small nonlinear part, so Eq. (12) was used only for calculation of a small correction for the potential. A high value of the stretching coefficient provided high resolution in the vicinity of surface for accurate calculations of the surface vertical derivative for the potential. The finite-difference second-order approximation of vertical operators in Eq. (12) on a nonuniform vertical grid is quite straightforward (see Ref. [8]). Eq. (12) is solved as Poisson equations with the iterations over the right-hand side by TDMA method [27]. At each time step, the iterations start with a right-hand side calculated at the previous time step. A relative accuracy of the solution in terms of the vertical derivative of the potential on the surface was equal to 10−6. The typical number of iterations was 2–5.
The accuracy of the adiabatic version of equations was validated by reproducing a moving Stokes wave with the steepness AK=0.40 (А is a half of trough-to-crest wave height; K=1 is the wave number of the first mode). An algorithm for calculation of Stokes wave with the prescribed accuracy was suggested by Chalikov and Sheinin [28]. The scheme based on the conformal coordinates is very effective: the calculations were carried out in 100 ms at notebook (2.10 GHz). The dependence of Stokes wave spectra on the wave number is shown in Figure 1. In fact, about 2000 curves obtained in the course of calculations, with the interval Δt=1, were plotted. Due to improvement of the numerical scheme, the accuracy of reproduction of Stokes wave is considerably higher than for the scheme used in Refs. [7, 8].
Figure 1.
The 2000 spectra of Stokes wave with steepness AK=0.40 as a function of wave number k superimposed on each other. The gray area in the right left corner is a computational noise.
As seen, up to S∼10−12k=22, the spectra of Stokes waves remain with high accuracy the same as it was assigned in initial conditions. At higher frequencies, the random disturbances appear. Note that this validation is not trivial: even small inaccuracies in the numerical scheme cause a fast distortion of the spectra, like in the bottom part of Figure 1. We consider these results as a serious evidence of high accuracy of the adiabatic version of the model. The previous version of 3-D model [26] allowed carrying out a long simulation of Stokes wave not steeper than AK=0.30. The right-hand sides of Eqs. (4) and (5) were calculated with a use of Fourier transform method: the nonlinear terms were calculated at the extended grid with size 4Mx×4My, and then by the inverse Fourier transform, they were returned to the Fourier grid. The fourth-order Runge-Kutta scheme was used for integration in time. The equation for the potential was solved at each of the four substeps of time step.
The simulations described by Chalikov [26] were a first attempt to reproduce the development of wave field assigned in the initial conditions as a group of small waves at high wave number under the action of strong wind. The initial elevation was generated as a superposition of linear waves corresponding to JONSWAP spectrum [29] with random phases. The initial Fourier amplitudes for the surface potential were calculated by the formulas of the linear wave theory. The details of the initial conditions are of no importance because the initial energy level is quite low. The wave peak was placed to the wave number equal to 100. The wind velocity was assigned equal to4c100, where c100 is a phase velocity of the 100th mode. A detailed description of the scheme and its validation is given in Refs. [7, 8].
The simulation described in the current paper was performed with a doubled resolution in both directions, with the improved numerical scheme for Poisson equations and modified parameters in the scheme for calculations of energy transitions.
3. Energy input
The detailed description of the algorithm for calculation of energy input is given in Ref. [26]. The energy and momentum are transferred from air to water by the surface pressure field and tangent stress. According to the most reasonable theory [30], the Fourier components of surface pressure p are connected with those of the surface elevation through the following expression:
pk,l+ip−k,−l=ρaρwβk,l+iβ−k,−lhk,l+ih−k,−l,E14
where hk,l,h−k,−l,βk,l,β−k,−l are real and imaginary parts of elevation η, and the so-called β-function, ρa/ρw, is the ratio of air and water densities. Both β coefficients are the functions of the nondimensional frequency
Ω=ωU/g,E15
that characterizes the ratio of wind velocity to phase velocity of ck:
Ω=U/ckE16
Since the supplying of wave with the energy and momentum occurs in a layer whose height is proportional to the wave length, it is reasonable to suggest that the reference height for the wind velocity should be different for a different virtual wave length (distance λk/cosθi between the wave peaks in wind direction; the index i denotes a direction of mode). The wind velocity can be found by interpolation or extrapolation to the level:
zi,k=0.5λk/cosθiE17
The definition of Ωк should take into account the angle θi between the vector U and the direction of wave mode. Finally, the virtual nondimensional frequency takes the form:
Ωi,k=ωkcosθiUzk/g=cosθiUzk/ckE18
where ck=g/ωk is the phase velocity of kth mode.
For experimental derivation of the shape of β-function, it is necessary to simultaneously measure the wave surface elevation and nonstatic pressure on the surface [31, 32, 33, 34, 35]. The data obtained in this way allowed constructing an imaginary part of β-function used in some versions of the wave forecasting models [36]. The data on experimental β-function are compared in Ref. [4]. The values of β within the interval 0<Ω<10 differ by decimal orders. Hence, the question arises: in what way, using such a different input, the spectral models provide a reasonable agreement with the observations. The answer is very simple: the researchers have the possibility to modify the parameterization of dissipation. Despite the hundreds of papers, the knowledge on dissipation is even poorer than the knowledge on the energy input. Finally, only the sum of those source terms regulates the growth of total wave energy. Such situation is far from being perfect since the energy input and dissipation have totally different spectral properties.
The second way of the β-function evaluation is based on the results of numerical investigations of the statistical structure of the boundary layer above waves with the use of Reynolds equations and an appropriate closure scheme. In general, this method works so well that many problems in the technical fluid mechanics are often solved not experimentally but by using the numerical models [37, 38]. This method was being developed beginning from Refs. [39, 40] and followed by Refs. [41, 42, 43]. The results were implemented in the WAVEWATCH model, i.e., the third-generation wave forecast model [44], and thoroughly validated against the experimental data in the course of developing WAVEWATCH-III [45]. Most of the schemes for the calculations of β-function consider a relatively narrow interval of the nondimensional frequencies Ω. In the current work, the range of frequencies covers the interval 0<Ω<10, and occasionally, the values of Ω>10 can appear.
The most reliable data on β-function are concentrated in the interval −10<Ω<10 (the negative values of Ω correspond to the wave modes running against wind). In the current calculations, the modes running against wind are absent. The function β can be approximated by the formulas:
βi=β0+a0Ω−Ω0+a1Ω−Ω02Ω>Ω0β0−a0Ω−Ω0+a1Ω−Ω02Ω<Ω0,E19
βr=β1+a3Ω−Ω2Ω<Ω2a2Ω−Ω12Ω2<Ω<Ω3β1−a3Ω−Ω3Ω>Ω3,E20
where Ω0=0.355, Ω1=1.20, Ω2=−18.8, Ω3=21.2, a0=0.0228,a1=0.0948,a2=−0.372,a3=14.8,β0=−0.02,β1=−148.0.
The wind velocity remains constant throughout the integration. The values of Ω for other wave numbers are calculated by assuming that the wind profile is logarithmic.
Note that the formulation of wind and waves interaction can be significantly improved by coupling the wave model with the 1-D Wave Boundary Layer model [4]. The next step can be the coupling of wave model with the 3-D model of WBL based on the closure schemes or LES model (see Ref. [46]).
4. Energy dissipation
The current version of the model includes three types of dissipation (see details in Ref. [26]).
The energy can decrease due to the errors of approximations in space and time that depend on the number of Fourier modes, number of knots in the physical space, the vertical grid used for approximation of Poisson equation (6), and the criterion for accuracy of its solution. All of those errors that produce the ‘numerical dissipation’ can be referred to the adiabatic part of the models (4)–(6) at p=0. The rate of this dissipation can be reduced by the use of a better resolution and a higher accuracy of approximation, but this way leads to deceleration of the calculations with the model already running for a very long time.
Opposite to the numerical dissipation, there exists another type of energy loss that has rather a physical nature. The nonlinear interaction of different modes forms a flux of energy directed outside of the computational domain. We call it the ‘nonlinear dissipation.’ The numerical and nonlinear dissipation can hardly be considered separately. The estimation of rate of the numerical/nonlinear dissipation can be easily done by the comparison of full energy before and after the time step for the adiabatic part of the model (see Section 4 in Ref. [26]). In the current calculations, the loss of energy for one time step was about 10−4%, which is by 2–3 orders less that the rate of energy change due to input energy. Since we prefer to consider the process described by Eqs. (4)–(6) as adiabatic one, at each time step we restore the energy lost by both the numerical and nonlinear dissipation.
A long-term integration of full fluid mechanics equations always shows the spreading of spectrum to both high and low frequencies (wave numbers). The nonlinear flux of energy directed to the small wave numbers produces downshifting of spectrum, while an opposite flux forms a shape of the spectral tail. The second process that we call the ‘tail dissipation’ can produce accumulation of energy near the ‘cut’ wave number. The growth of amplitudes at high wave numbers is followed by growth of the local steepness and development of the numerical instability. To support the stability, additional terms are included into the right-hand sides of Eqs. (4) and (5):
∂ηk,l∂τ=Ek,l−μk,lηk,l,E21
∂φk,l∂τ=Fk,l−μk,lφk,lE22
(where Ek,l and Fk,l are the Fourier amplitudes of the right-hand sides of Eqs. (4) and (5); the value of μk,l is equal to zero inside the ellipse with semi-axes dmMx and dmМy; then, it grows quadratically with k up to the value cm and is equal to cm outside of the outer ellipse (see details in Ref. [26]). This method of filtration that we call the ‘tail dissipation’ was developed and validated with the conformal model [28]. The sensitivity of the results to the parameters in Refs. (21) and (23) is not large. The aim of the algorithm is to support smoothness and monotonicity of the wave spectrum within the high wave number range.
The main process of wave dissipation is the ‘breaking dissipation.’ This process is taken into account in all the spectral wave forecasting models similar to WAVEWATCH (see Refs. [44, 47]). Since there are no waves in the spectral models, no local criteria of wave breaking can be formulated. This is why the breaking dissipation is represented in the spectral models in a distorted form. The real breaking occurs in the relatively narrow areas of the physical space; however, the spectral image of such breaking is stretched over the entire wave spectrum, while in reality, the breaking decreases height and energy of separate waves. This contradiction occurs because the waves in the spectral models are assumed to be linear. In fact, a nonlinear sharp wave breaks in the physical space. Such wave is often composed of several local modes. It is clear that the state-of-art wave models should account for the threshold behavior of a breaking wave, that is, waves will not break unless their steepness exceeds the threshold [48, 49, 50].
The instability of the interface leading to breaking is an important though poorly developed problem of fluid mechanics. In general, this essentially nonlinear process should be investigated for the two-phase flow. Such approach was demonstrated, for example, by Iafrati [51].
The problem of breaking parameterization includes two points: (1) establishment of a criterion of the breaking onset and (2) development of the algorithm of the breaking parameterization. The problem of breaking is discussed in details in Ref. [47]. It was found in Ref. [52] that the clear predictor of breaking formulated in dynamical and geometrical terms, probably, does not exist. The consideration of the exact criterion for the breaking onset for the models using transformation of the coordinate type of (1) is useless since the numerical instability in such models occurs not because of the approach of breaking but because of the appearance of the high local steepness. The description of breaking in the direct wave modeling should satisfy the following conditions: (1) it should prevent the onset of instability at each point of millions of grid points over many thousands of time steps; (2) it should describe in a more or less realistic way the loss of the kinetic and potential energies with preservation of balance between them; and (3) it should preserve the volume. It was suggested by Chalikov [53] that an acceptable scheme can be based on a local highly selective diffusion operator with a special diffusion coefficient. Several schemes of such type were validated, and finally, the following scheme was chosen:
ητ=Eη+J−1∂∂ξBξ∂η∂ξ+∂∂ϑBϑ∂η∂ϑ,E23
φτ=Fφ+J−1∂∂ξBξ∂φ∂ξ+∂∂ϑBϑ∂φ∂ϑ,E24
where Fη and Fφ are the right-hand sides of Eqs. (4) and (5) including the tail dissipation terms; Bξ and Bϑ are the diffusion coefficients. The probability of high negative values of the curvilinearity is by orders larger than the probability calculated over the ensemble of linear modes with the spectra generated by the nonlinear model.
The curvilinearity turned out to be very sensitive to the shape of surface. This is why it was chosen as a criterion of the approaching breaking. The coefficients Bξ and Bϑ depend nonlinearly on the curvilinearity
Bξ=CBηξξ2ηξξ<ηξξcr0ηξξ≥ηξξcrE25
Bϑ=CBηϑϑ2ηϑϑ<ηξξcr0ηϑϑ≥ηξξcrE26
where the coefficients at CB=0.05, ηξξcr=ηϑϑcr=−50. The algorithm (24)–(27) does not change the volume and decreases the local potential and kinetic energies. It is assumed that the lost momentum and energy are transferred to the current and turbulence (see Ref. [42]). Besides, the energy also goes to other wave modes. The choice of parameters in Refs. (24)–(27) is based on simple considerations: the local piece of surface can closely approach the critical curvilinearity but not exceed it. The values of the coefficients were chosen in the course of multiple experiments to provide agreement with the rate of spectrum development given by JONSWAP approximation.
5. Evolution of wave field
The integration was done for 1,200,000 steps with the time step Δt=0.005 up to the nondimensional time T=6000, which corresponded to 9550 initial wave peak periods. The total energy of wave motion Е=Ep+Ek (Ep is the potential energy, while Ek is the kinetic energy) is calculated with the following formulas:
Ep=0.25η2¯,Ek=0.5φx2+φy2+φz2¯¯,E=Ep+Ek,E27
where a single bar denotes the averaging over the ξ and ϑ coordinates, while a double bar denotes the averaging over the entire volume. The derivatives in Ref. (27) are calculated according to the transformation (1). An equation of the integral energy E evolution can be represented in the following form:
dЕdt=I¯+Db¯+Dt¯+N¯,E28
where I¯ is the integral input of energy from wind (Eqs. (14)–(20)); Db¯ is a rate of the energy dissipation due to wave breaking (Eqs. (23)–(26)); Dt¯ is a rate of the energy dissipation due to filtration of high-wave number modes (‘tail dissipation,’ Eqs. (21) and (22)); N¯ is the integral effect of the nonlinear interactions described by the right-hand side of the equations when the surface pressure p is equal to zero. The differential forms for calculation of the energy transformations can be, in principle, derived from Eqs. (4)–(6), but here a more convenient and simple method was applied. Different rates of the integral energy transformations can be calculated with the help of fictitious time steps (i.e., apart from the basic calculations). For example, the value of I¯ is calculated by the following relation:
I¯¯=1ΔtEt+Δt¯¯−Et¯¯,E29
where Et+Δt¯¯ is the integral energy of a wave field obtained after one time step with the right side of Eq. (6) containing only the surface pressure calculated with Eqs. (14)–(18).
The evolution of the characteristics calculated by formula (29) is shown in Figure 2.
Figure 2.
The evolution of integral characteristics. The rate of evolution of the integral energy multiplied by 108 due to: (1) nonlinear interaction I¯¯ (Eq. (29)); (2) tail dissipation D¯¯t(Eqs. (21) and (22)); (3) breaking dissipation Db (Eqs. (23)–(26)); (4) input of energy from wind I¯¯ (Eqs. (14)–(20)); and (5) balance of energy I¯¯+D¯¯t+D¯¯b. Curve 6 shows the evolution of wave energy 105E. Vertical gray bars show instantaneous values; thick curve shows the smoothed behavior.
The sharp variation of all the characteristics at t<500 is explained by adjustment of the linear initial fields to the nonlinearity. The integral effect of the nonlinear interaction I¯¯ (straight line 1) was very close to zero. The tail dissipation Dt¯¯ (curve 2) is smaller than the breaking dissipation Dt¯¯(curve 3). The value of Db¯¯ has significant fluctuations due to introduction of the criteria (25) and (26). The dissipation D¯¯b+D¯¯t absorbs nearly all of the incoming energy, and just a small part of it is going for growth of waves. The balance of energy B¯¯=I¯¯+D¯¯t+D¯¯b (curve 5) fluctuates and approaches zero when energy E¯¯ (curve 6 in Figure 2) approaches saturation.
The time evolution of the integral spectral characteristics is presented in Figure 3.
Figure 3.
Dependence of integral characteristics on fetch (Eq. (32)): (1) weighted mean frequency ωw (Eq. (31)); (2) peak frequency ωp; (3) energy E (Eq. (27)); and (4) approximation of the peak frequency evolution (Eq. (32)).
Curve 1 corresponds to the weighted frequency ωw
ωw=∫ωSdkdl∫Sdkdl1/2,E30
where integrals are taken over the entire Fourier domain. The value ωw is not sensitive to the details of spectrum; hence, it well characterizes the position of spectrum and spectral peak shifting. Curve 2 describes the evolution of the spectral maximum. The step shape of curve corresponds to the fundamental property of downshifting. Opposite to common views, the development of spectrum occurs not monotonically, but by appearance of a new maximum at a lower wave number as well as by attenuation of the previous maximum. It is interesting to note that the same phenomenon is also observed in the spectral model [36].
The value of fetch in the periodic problem can be calculated by integration of the peak phase velocity cp=k−1/2 over time.
F=∫t0tcpdt.E31
The numerical experiment reproduces the case when development of wave field occurs under the action of a permanent and uniform wind. This case corresponds to the JONSWAP experiment [29]. It is suggested that the frequency of spectral peak changes as F−1/3, while the full energy grows linearly with F. Neither of the dependences can be exact since they do not take into account approaching a stationary regime. Besides, the dependence of frequency on fetch is singular at F=0. A more accurate is the approximation:
ωp=75.65.63+F1/3.E32
Obviously, the dependence ωp∼F−1/3 is valid in a narrower interval of F. As seen, contrary to ωw, the peak frequency changes not monotonically, but by appearance of a new maximum at a lower wave number as well as by attenuation of the previous maximum. It is interesting to note that the same phenomenon is also observed in the spectral model (16). The dependence of the total energy E on fetch F does not look like a linear one, but it is worth to note that the JONSWAP dependence is evidently inapplicable to a very small and large fetch.
On the whole, the evolutions of integral characteristics of the solution shown in Figures 2 and 3 are smoother than those calculated by Chalikov [26]. It can be explained by multiple technical improvements of the numerical scheme and higher resolution.
The evolution of wave spectrum is shown in Figure 4.
Figure 4.
The wave spectra Shr integrated over angle ψ in the polar coordinates and averaged over the consequent intervals of length about 500 units of the nondimensional time t (thin curves). The spectra are growing and shifting from right to left. Thick dashed curve is the dependence S∼ω−4; dotted curve corresponds to S∼ω−5 .
The 2-D wave spectrum Skl0≤k≤Mx−My≤l≤My averaged over nine time intervals of length equal to Δt≈500 was transferred to the polar coordinates Spψr−π/2≤ψ≤π/20≤r≤Mx and then averaged over the angle ψ to obtain the 1-D spectrumShr:
Shr=∑SpψrrΔψ.E33
The angle ψ=0 coincides with the direction of wind U, Δψ=π/180. Even the averaged over angle spectrum looks quite irregular and contains multiple holes and peaks. The spectra are smoothed.
The two-dimensional wave spectra are shown in Figure 5, where the log10Sψr averaged over the successive eight periods of length Δt=500 is given.
Figure 5.
Sequence of 2-D images of lоg10Srψ averaged over the consequent eight periods of length Δt=500. The numbers indicate the period of averaging (the first panel marked 0 refers to the initial conditions). The spectra are normalized by the maximum value of spectrum 8. The horizontal axis corresponds to the wave numbers r=k; the angles are shown by rays.
The first panel with a mark 0 refers to the initial conditions. The pictures well characterize the downshifting and angle spreading of spectrum due to the nonlinear interactions.
As seen, each spectrum consists of separated peaks and holes. This phenomenon was observed and discussed by Chalikov et al. [7]. The same results were obtained by Chalikov [26]. The repeated calculations with different resolutions showed that such structure of 2-D spectrum is typical. The locations of peaks cannot be explained by the fixed combination of interacting modes, since in different runs (with the same initial conditions but a different set of phases for the modes), the peaks are located in different locations in the Fourier space.
It is interesting to note that while increasing resolution, the patches with low energy extend. It can be supposed that the current and higher resolutions are excessive, and the process can be simulated with a lower resolution. This statement may be too optimistic, but it can be supported by the following arguments. The multi-mode wave mechanics is different from the multi-scale turbulent motion. The modeling of turbulence at increase of resolution just allows reproducing more details of motion. The increase of resolution in a wave model introduces other wave modes with different phase velocities. Due to dispersion, the solutions (i.e., the evolution of surface) in these two cases will be completely different. It means that the solution does not converge with increase of resolution, which makes no sense.
The situation can be saved if upon reaching the optimal resolution, the new added positions for the modes will not obtain the energy and not participate in solution. The existence of such effect should be carefully validated with the exact wave model. If this effect does not exist, it means that the results of simulations depend completely on the resolution, the reliable simulation of individual evolution of wave field being, in fact, impossible.
The method of calculation of the simulated one-dimensional input and dissipation spectra was described by Chalikov [26]; still, it will be explained here once again, though briefly.
The evolution of the integrated over angle ψ wave spectrum Shr can be described with the equation:
dShrdt=Ir+Dtr+Dbr+Nr,E34
where Ir,Dtr,DbrandNr are the spectra of the input energy, tail dissipation, breaking dissipation, and the rate of nonlinear interactions. All of the spectra shown below were obtained by transformation of the 2-D spectra into a polar coordinate ψr and then integrated over the angles ψ within the interval −π/2π/2. The spectra can be calculated using an algorithm similar to Eq. (29) for integral characteristics. For example, the spectrum of the energy input Ikl is calculated as follows:
Ikl=Sct+Δtkl−Sctkl/Δt,E35
where Sckxky is a spectrum of the columnar energy calculated by the relation:
where the grid values of velocity components u,v,w are calculated by the relations:
u=φξ+φζηξ,v=φϑ+φζηϑ,w=φζ,E37
and uk,l,vk,landwk,l are the real Fourier coefficients, while for the negative indices—the imaginary ones.
For calculation of Ikl, the fictitious time steps Δt are made only with a term responsible for the energy input, that is, the surface pressure p. The spectrum Ikl was averaged over the periods Δt≈500, then transformed into a polar coordinate system and integrated in the Fourier space over the angles ψ within the interval −π/2π/2. Such procedure was used for calculation of all the terms in the right side of Eq. (34). In the current version of the model, the calculations of integral (28) and spectral (34) transformations were combined with the calculations of the right sides of Eqs. (4) and (5).
The rates of transformation of spectrum are shown in Figure 6. The integral term describing the nonlinear interaction N¯ in Eq. (28) is small (as compared with the local values of Nk,l), but the magnitude of spectrum Nr is comparable with the input Ir and dissipation Dtr and Dbr terms (panel 1 in Figure 5). The shape of spectrum Nr confirms prediction of the quasi-linear theory [54, 55]. At the low wave number slope of the spectrum, the nonlinear influx of energy is positive, while at the opposite slope, it is negative. This process produces shifting of spectrum to the lower wave number (downshifting). The input of energy due to the nonlinear interactions is observed in a high frequency part of spectrum, which also agrees with Hasselmann’s theory. Note that the nonlinear interactions also produce widening of spectrum.
Figure 6.
The rates of transformation spectra multiplied by 109: (1) nonlinear interaction Nr(1); (2) input energy Ir; (3) breaking dissipation Dbr; (4) tail dissipations Dtr multiplied by 1011. All spectra are obtained by transformation of the 2-D spectra into the polar coordinate ψr and then integrated over the angles ψ within the interval −π/2π/2.
The spectral distribution of the energy input from wind Ir (panel 2 in Figure 6) is in general similar to wave spectrum since it depends linearly on the spectral density (Figure 3). The dissipation rate Dbr is negative (panel 3), and its minimum is shifted a little to higher frequencies from the wave spectrum peak. The tail dissipation (Panel 4) is smaller by two orders than the other terms, but it plays an important role of supporting numerical stability.
The residual rate of transformation of spectrum dShr/dt averaged over eight consequent periods is shown in Figure 7. The numbers in the top part of panel indicate the averaged wave number of the spectral peak. The second set of numbers refers to the corresponding spectrum of the residual input of energy. As seen, the maximum of the input energy is located to the left of the spectral peak, that is, on a low-wavenumber spectral slope. The obtained energy causes downshifting of spectrum and supports the shape of a high wavenumber slope and spectral tail. In the equilibrium regime, all the incoming energy are consumed for supporting the shape of the entire spectrum.
Figure 7.
The spectral distribution of the residual input of energy dShr/dt in the energy-containing part of spectrum for different stages of wave development. The numbered vertical lines indicate positions of the spectral peak. The second set of numbers shows the peaks of the corresponding residual input.
However, the dynamics of the tale is not adiabatic, that is, it is not completely controlled by the spectral energy cascade since the input of energy due to the nonlinear interaction competes with the energy input from wind (curve 2) and breaking dissipation (curves 3 and 4). The tail dissipation (curve 4) is small and concentrated in the vicinity of the cut wave number. The input and dissipation in the spectral tail are nearly in balance (curve 4) (Figure 8).
Figure 8.
The rates of transformation spectra multiplied by 109 for the last period: (1) nonlinear interaction Nr(1); (2) input energy; (3) breaking dissipation Dbr; (4) tail dissipations 1010Dtr; and (5) balance of all the terms.
6. Statistical properties of wave field
The phase-resolving modeling requires a higher computer capacity for calculations of any statistical characteristics of sea waves. In the course of simulations, 1.200 two-dimensional fields of the elevation and surface potential with the size 2048 × 1024 points were recorded. Following the solution of the 3-D equation for the velocity potential, these data allow us to reproduce any kinematic and dynamic characteristics of the three-dimensional structure of waves.
The most important statistical characteristics of wave field are mean Hs, variance V, skewness Sk, and kurtosis Ku calculated by the averaging over each of 1200 fields:
V=η−η¯2¯,Sk=η−η¯3¯V−3/2,Ku==η−η¯4¯V−2−3.E38
The evolution of these characteristics in time is shown in Figure 9.
Figure 9.
Evolution of the statistical characteristics of elevation: (1) mean value η¯, (2) variance V, (3) skewness Sk, and (4) kurtosis Ku.
The volume of the domain characterized by η¯ is preserved with the accuracy of the order of 10−8. The variance V is the potential energy that is growing up to the saturation. When the wave field is a superposition of a large number of linear waves, both the skewness and kurtosis are equal to zero. The skewness S characterizes asymmetry of the probability distribution indicating that the positive values of η are larger than the negative ones, then S>0. The kurtosis Ku is positive if the crests are sharper and the troughs are smoother than in the case of linear waves.
The probabilities of the geometrical characteristics (elevation, first and second derivatives over x) are shown in Figure 10. The elevation Z (normalized by the significant wave height) is characterized by asymmetry: the heights of waves are significantly larger than the depths of troughs, that is, the wave field is closer to the superposition of Stokes waves than to that of the harmonic modes. The distribution of slopes exhibits horizontal asymmetry: the negative slopes are larger than the positive ones, that is, the waves, on the average, are inclined in the direction of movements. The second derivative (curvilinearity) has the most striking tendency for asymmetry: the negative values corresponding to the sharpness of crests are much larger by absolute value than the positive values corresponding to the curvilinearity of troughs. This property of curvilinearity was used for the parameterizing of breaking. The limit value Zxx=−50 was used as a criterion for the initiating of breaking (see Eq. (26)).
Figure 10.
Geometric characteristics of elevation: (1) probability of elevation PZ; (2) probability of slopes PZx; and (3) probability of curvilinearity PZxx.
The probability for three components of the surface velocity is given in Figure 11. The distributions of the vertical and transverse components of velocity are symmetrical. For a horizontal component, the values of positive fluctuations are considerably larger than the negative fluctuations. This effect cannot be explained by the influence of Stokes drift, which value for those specific conditions does not exceed 10−3. The asymmetry of the probability distribution for the u-components is definitely connected with the asymmetry of the probability distribution for inclinations of surface (Figure 10, panel 2).
Figure 11.
Probability of the longitudinal u, transverse v, and vertical w components of the surface velocity calculated for the last of nine periods corresponding approximately to the quasi-stationary regime.
The number of extreme waves with a high crest Zc/Hs>1.2 is shown in Figure 12. Because such wave is not presented in each of the wave fields, the picture looks as discrete bars of different heights. The total number of values Z/Hs>1.2 is 17.214. The formally calculated probability of the values equals 0.67⋅10−5. Note that the data on the probability of wave height contain uncertainty because it is not always clear which event should be considered as a single freak wave. The straightforward way suggests calculation of a portion of all the records including freak waves, out of the total volume of the data.
Figure 12.
The number of points where the nondimensional height Zc/Hs exceeds 1.2. The total number of values is 2.57⋅109.
However, some of the records can belong to the single moving freak waves. The cause of this uncertainty is the absence of a strict definition of freak wave being either a case or a process. The number of extreme waves grows with development of wave field.
The integral probability of the total wave height Ztc/Hs, the wave height above mean level Zc/Hs, and the depth of trough Zt/Hs are shown in Figure 13.
Figure 13.
The cumulative probability of crest-to-trough wave height Ztc/Hs (curve 3); crest height Zc/Hs (curve 2); and trough depth −Zt/Hs (curve 3). The number of points in each filed is equal to 2048×1024. The number of fields is 1200.
Thin lines show that Ztc/Hs=2 correspond approximately to Zc/Hs=1.2 and −Zt/Hs=−.86. It is worth to remind that here the nondimensional ‘extreme’ waves are considered. The true extreme waves are the product of the real wave field. The probability of real extreme waves can be estimated by multiplying the probability of the nondimensional wave by the probability of significant wave height.
The statistical connection between the total wave heights, crest heights, and trough depths is shown in Figure 14.
Figure 14.
Dependence of crest height Zc/Hs (top section) and depth trough Zt/Hs(bottom section) on the total wave height Ztc/Hs.
The dependences between these characteristics can be approximated by the formulas:
where the tilde denotes the normalizing by significant wave height Hs. Note that the first and third coefficients in (39) turned out to be a match. The correlation coefficient between Z˜tandZ˜c is −0.354, while between Z˜tandZ˜tc, it is −0.721, and between Z˜candZ˜tc, it is 0.903, that is, the correlation between the full wave height Z˜tc and the wave height above mean level Z˜c is so high that Z˜c can be used for identification of extreme waves.
The last characteristics that we consider here is the angle distribution of the spectral density. This characteristic can be described by the function ϒω/ωp (see Ref. [60]).
ϒ=∫Sωψθdωdψ∫SωψdωdψE40
where the integrals are taken over the domain 0<ω<ωc−π/2<ψ<π/2. The value ϒ is weighted by the absolute spectrum value of wave direction. The wave spectra as the functions of frequency ω normalized by peak frequency ωp for the first seven periods are shown in the upper panel of Figure 15.
Figure 15.
The shape of wave spectrum as a function of the nondimensional frequency ω/ωp (top panel) and a function ϒ (Eq. (40); ωp is the frequency in the spectral peak.
The function ϒω/ωp calculated for the same spectra is given in the bottom panel. As seen, the ϒ curves corresponding to different wave ages are close to each other. All of them have a sharp maximum at the frequencies below the spectral peak, a well-pronounced minimum in the spectral peak, and a relatively slow growth above the spectral peak. The decrease of ϒ at high frequencies is probably caused by the high-frequency dumping. The angle distribution was investigated in Refs. [56, 57, 58, 59, 60]. The approximations of ϒω/ωp from the different sources collected in Ref. [61] show considerable scatter, but the general features are quite similar to those calculated in the current work. Note that the spectrum has undergone a long development; hence, the characteristics presented in Figure 14 were produced by the numerical model itself.
7. Conclusions
The paper is devoted to the wind wave simulations based on the initial equations of potential motion of fluid with a free surface. The system of equations includes the evolutionary kinematic and dynamic surface conditions and Laplace equation for the velocity potential. In this paper, a case of the double-periodic domain of infinite depth is considered. The construction of the exact numerical scheme for a long-term integration of these equations in the Cartesian coordinate system is impossible, since the surface moves between the grid knots. Instead, the system of the curvilinear coordinates (1) fitted with the surface is introduced. The main advantage of this coordinate system is that the surface coincides with a coordinate line ζ=0. The penalty follows immediately after turning the simple Cartesian coordinates into the curvilinear, nonstationary, and nonorthogonal coordinate system. Fortunately, the evolutionary Eqs. (4) and (5) become just slightly complicated, while Laplace equation transforms into the full elliptic equation. At each time step, these equations can be represented as Poisson equation with the right-hand side depending on the solution itself as well as on the metric coefficient. Since the norm of the right sight of the equation is usually small, the solution of Poisson equation can be found with the three-diagonal matrix algorithm and with iterations over the right-hand side. This procedure being formulated in the Fourier space is greatly simplified by the assumption of periodicity since in this case the derivatives over the horizontal coordinates are represented by the absolute value of wave number k in the diagonal terms. When constructing a numerical scheme, we noticed that the significant simplification of the problem can be achieved by separation of the velocity potential into the linear and nonlinear components (see Ref. [7]). It is assumed that the linear component satisfies Laplace equations with the known solution. The equation for the nonlinear component can be obtained by extracting Laplace equation from the initial Poisson equation. Such procedure has a lot of advantages since the nonlinear component is on the average less by 1–2 decimal orders than the linear one. It means that for solution of the reduced Poisson equation the lesser number of levels in vertical, the lesser number of iterations and a smaller accuracy criterion can be used. The use of two components in the evolutionary equation does not seem to provide noticeable advantages; however, this way deserves further consideration.
The adiabatic version of the model was validated by simulation of a running Stokes wave with the steepness AK=0.40 in Ref. [7]. It was shown that the amplitudes of Stokes modes remain practically constant up to the accuracy of 10−7. The current version of the model after some technical improvements of the numerical scheme provides accuracy up to 10−12. Then, the adiabatic version of the model was used for reproduction of a quasi-stationary regime for investigation of the statistical properties of sea waves [1, 7, 8].
For calculations of development of wave field under the action of wind, it was necessary to include the algorithms for calculations of input and dissipation of energy. The scheme for calculation of the energy input was developed by Chalikov and Rainchik [3] on the basis of coupling the one-dimensional phase-resolving model and the two-dimensional boundary layer model with the second-order turbulence closure scheme. The parameterization suggested is still quasi-linear (similar to Miles’ scheme [30]), but in our opinion, it is the only scheme confirmed by the extended results of the numerical simulations. The theoretical and observational data on β−function are dramatically scattered (see Ref. [4], Figure 1).
For stabilization of the solution, the algorithm of high-frequency dumping in the Fourier space suggested by Chalikov and Sheinin [28] was used. The numerous attempts were made to improve that scheme (for example by reduction of the spectral interval of dumping) but without much success.
The most complicated problem is the parameterization of dissipation due to wave breaking. Such algorithm should not describe a process of breaking as it is, which within the frame of such model is impossible, but it should prevent the numerical instability that interrupts a run (see discussion in Ref. [26]). Currently, the algorithm used is very simple. It is based on the diffusion operator with a highly selective coefficient of ‘viscosity.’ It works satisfactorily, but we are far from thinking that it cannot be substantially improved or completely replaced by another one.
The results described in this paper show that the wave field development under the action of wind is reproduced quite realistically. The area of application of such models is very wide. Such modeling should be used for improvement of the algorithms of the energy input and dissipation. A model with the periodic boundary conditions can be used for the local interpretation of the spectral forecast in terms of real waves. The finite-difference version of the model can be used for simulation of wave regimes in the basins with real shapes and bathymetry (see, e.g., Ref. [5]).
Acknowledgments
Author would like to thank Mrs. O. Chalikova for her assistance in preparation of the manuscript. This research was performed in the framework of the state assignment of Russian Academy of Science (Theme No. 0149-2019-0015) supported in part 15 (Section 2) by RFBR (project No. 18-05-01122).
\n',keywords:"numerical simulation, wind waves, waves’ development, wave spectrum, Fourier-transform method, wind input, waves’ dissipation, wave statistics",chapterPDFUrl:"https://cdn.intechopen.com/pdfs/72024.pdf",chapterXML:"https://mts.intechopen.com/source/xml/72024.xml",downloadPdfUrl:"/chapter/pdf-download/72024",previewPdfUrl:"/chapter/pdf-preview/72024",totalDownloads:651,totalViews:0,totalCrossrefCites:2,dateSubmitted:"December 13th 2019",dateReviewed:"March 25th 2020",datePrePublished:"June 3rd 2020",datePublished:"March 17th 2021",dateFinished:"May 2nd 2020",readingETA:"0",abstract:"The paper describes the numerical experiments with a three-dimensional phase-resolving model based on the initial potential equation of motion with free surface at deep water in the periodic domain written in the surface-following nonstationary curvilinear nonorthogonal coordinate system. The numerical scheme is based on Fourier-transform method. The vertical velocity on surface is calculated by solving the three-dimensional Poisson equation for the velocity potential. The velocity potential is represented as a sum of linear and nonlinear components. The linear component is described by Laplace equation. The nonlinear component is calculated by solution of the three-dimensional Poisson equation with the iterated right-hand side. The model includes some algorithms for calculation of the energy input from wind as well as for calculation of breaking and high-frequency dissipation. Initially, the conditions are assigned as a set of small waves corresponding to JONSWAP spectrum at high wave number. In response to waves’ growth, the spectrum shifts to lower wave numbers. The evolution of spectrum is generally in an agreement with the observed data. The wave spectrum and the spectra of different rates of energy transformation as well as the statistical characteristics of wave field for different stages of development are described.",reviewType:"peer-reviewed",bibtexUrl:"/chapter/bibtex/72024",risUrl:"/chapter/ris/72024",signatures:"Dmitry Chalikov",book:{id:"9984",type:"book",title:"Geophysics and Ocean Waves Studies",subtitle:null,fullTitle:"Geophysics and Ocean Waves Studies",slug:"geophysics-and-ocean-waves-studies",publishedDate:"March 17th 2021",bookSignature:"Khalid S. Essa, Marcello Di Risio, Daniele Celli and Davide Pasquali",coverURL:"https://cdn.intechopen.com/books/images_new/9984.jpg",licenceType:"CC BY 3.0",editedByType:"Edited by",isbn:"978-1-78985-445-9",printIsbn:"978-1-78985-372-8",pdfIsbn:"978-1-78985-446-6",isAvailableForWebshopOrdering:!0,editors:[{id:"102766",title:"Prof.",name:"Khalid S.",middleName:null,surname:"Essa",slug:"khalid-s.-essa",fullName:"Khalid S. Essa"}],productType:{id:"1",title:"Edited Volume",chapterContentType:"chapter",authoredCaption:"Edited by"}},authors:[{id:"316767",title:"Prof.",name:"Dmitry",middleName:null,surname:"Chalikov",fullName:"Dmitry Chalikov",slug:"dmitry-chalikov",email:"dmitry-chalikov@yandex.ru",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",institution:null}],sections:[{id:"sec_1",title:"1. Introduction",level:"1"},{id:"sec_2",title:"2. Equations",level:"1"},{id:"sec_3",title:"3. Energy input",level:"1"},{id:"sec_4",title:"4. Energy dissipation",level:"1"},{id:"sec_5",title:"5. Evolution of wave field",level:"1"},{id:"sec_6",title:"6. Statistical properties of wave field",level:"1"},{id:"sec_7",title:"7. Conclusions",level:"1"},{id:"sec_8",title:"Acknowledgments",level:"1"}],chapterReferences:[{id:"B1",body:'Chalikov D, Babanin AV. Comparison of linear and nonlinear extreme wave statistics. Acta Oceanologica Cinica. 2016;5(5):99-105. 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Marine and Freshwater Research. 1998;49:89-101. DOI: 10.1071/MF96126'},{id:"B59",body:'Banner ML. Equilibrium spectra of wind waves. Journal of Physical Oceanography. 1990;20:966-984. DOI: 10.1175/1520-0485(1990)020,0966:ESOWW.2.0.CO;2'},{id:"B60",body:'Romero L, Melville WK. Airborne observations of fetch-limited waves in the Gulf of Tehuantepec. Journal of Physical Oceanography. 2010;40:441-465. DOI: 10.1175/2009JPO4127.1'},{id:"B61",body:'Liu Q, Rogers WE, Babanin AV, Young IR, Romero L, Zieger S, et al. Observation-based source terms in the third-generation wave model WAVEWATCH III: Updates and verification. Journal of Physical Oceanography. 2019;49(2):489-517. DOI: 10.1175/JPO-D-18-0137.1'}],footnotes:[],contributors:[{corresp:"yes",contributorFullName:"Dmitry Chalikov",address:"dmitry-chalikov@yandex.ru",affiliation:'
Shirshov Institute of Oceanology RAS, Russia
University of Melbourne, Australia
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The vacuum thermal evaporation technique, electron beam evaporation, pulsed-layer deposition, direct current/radio frequency magnetron sputtering, and chemical route deposition systems will be discussed in detail.",book:{id:"5541",slug:"modern-technologies-for-creating-the-thin-film-systems-and-coatings",title:"Modern Technologies for Creating the Thin-film Systems and Coatings",fullTitle:"Modern Technologies for Creating the Thin-film Systems and Coatings"},signatures:"Asim Jilani, Mohamed Shaaban Abdel-wahab and Ahmed Hosny\nHammad",authors:[{id:"192377",title:"Dr.",name:"Asim",middleName:null,surname:"Jilani",slug:"asim-jilani",fullName:"Asim Jilani"},{id:"192972",title:"Dr.",name:"M.Sh",middleName:null,surname:"Abdel-Wahab",slug:"m.sh-abdel-wahab",fullName:"M.Sh Abdel-Wahab"},{id:"192973",title:"Dr.",name:"Ahmed",middleName:"H",surname:"Hammad",slug:"ahmed-hammad",fullName:"Ahmed Hammad"}]},{id:"53225",doi:"10.5772/66396",title:"Radio Frequency Magnetron Sputter Deposition as a Tool for Surface Modification of Medical Implants",slug:"radio-frequency-magnetron-sputter-deposition-as-a-tool-for-surface-modification-of-medical-implants",totalDownloads:2252,totalCrossrefCites:8,totalDimensionsCites:28,abstract:"The resent advances in radio frequency (RF)‐magnetron sputtering of hydroxyapatite films are reviewed and challenges posed. The principles underlying RF‐magnetron sputtering used to prepare calcium phosphate‐based, mainly hydroxyapatite coatings, are discussed in this chapter. The fundamental characteristic of the RF‐magnetron sputtering is an energy input into the growing film. In order to tailor the film properties, one has to adjust the energy input into the substrate depending on the desired film properties. The effect of different deposition control parameters, such as deposition time, substrate temperature, and substrate biasing on the hydroxyapatite (HA) film properties is discussed.",book:{id:"5541",slug:"modern-technologies-for-creating-the-thin-film-systems-and-coatings",title:"Modern Technologies for Creating the Thin-film Systems and Coatings",fullTitle:"Modern Technologies for Creating the Thin-film Systems and Coatings"},signatures:"Roman Surmenev, Alina Vladescu, Maria Surmeneva, Anna Ivanova,\nMariana Braic, Irina Grubova and Cosmin Mihai Cotrut",authors:[{id:"193921",title:"Dr.",name:"Alina",middleName:null,surname:"Vladescu",slug:"alina-vladescu",fullName:"Alina Vladescu"},{id:"193922",title:"Prof.",name:"Roman",middleName:null,surname:"Surmenev",slug:"roman-surmenev",fullName:"Roman Surmenev"},{id:"193923",title:"Dr.",name:"Maria",middleName:null,surname:"Surmeneva",slug:"maria-surmeneva",fullName:"Maria Surmeneva"},{id:"193948",title:"Dr.",name:"Mariana",middleName:null,surname:"Braic",slug:"mariana-braic",fullName:"Mariana Braic"},{id:"194047",title:"Ms.",name:"Anna",middleName:null,surname:"Ivanova",slug:"anna-ivanova",fullName:"Anna Ivanova"},{id:"194048",title:"BSc.",name:"Irina",middleName:null,surname:"Grubova",slug:"irina-grubova",fullName:"Irina Grubova"},{id:"196398",title:"Prof.",name:"Cosmin Mihai",middleName:null,surname:"Cotrut",slug:"cosmin-mihai-cotrut",fullName:"Cosmin Mihai Cotrut"}]},{id:"53792",doi:"10.5772/67085",title:"Silver-Based Low-Emissivity Coating Technology for Energy- Saving Window Applications",slug:"silver-based-low-emissivity-coating-technology-for-energy-saving-window-applications",totalDownloads:3132,totalCrossrefCites:7,totalDimensionsCites:13,abstract:"Low-emissivity (low-E) technology is a unique and cost-effective solution to save energy in buildings for different climates. Its development combines advances in materials science, vacuum deposition, and optical design. In this chapter, we will review the fundamentals of energy saving window coatings, the history of its application, and the materials used. The current low-E coating technologies are overviewed, especially silver-based low-E technologies, which comprise more than 90% of the overall low-E market today. Further, the advanced understanding of generating high-quality silver thin films is discussed, which is at the heart of silver-based low-E product technology development. How the silver thin film electrical, optical, and emissivity properties are influenced by their microstructure, thickness, and by the materials on neighboring layers will be discussed from a theoretical and an experimental perspective.",book:{id:"5541",slug:"modern-technologies-for-creating-the-thin-film-systems-and-coatings",title:"Modern Technologies for Creating the Thin-film Systems and Coatings",fullTitle:"Modern Technologies for Creating the Thin-film Systems and Coatings"},signatures:"Guowen Ding and César Clavero",authors:[{id:"195240",title:"Dr.",name:"Guowen",middleName:null,surname:"Ding",slug:"guowen-ding",fullName:"Guowen Ding"},{id:"197064",title:"Dr.",name:"Cesar",middleName:null,surname:"Clavero",slug:"cesar-clavero",fullName:"Cesar Clavero"}]},{id:"52951",doi:"10.5772/66125",title:"Chemical Solution Deposition Technique of Thin-Film Ceramic Electrolytes for Solid Oxide Fuel Cells",slug:"chemical-solution-deposition-technique-of-thin-film-ceramic-electrolytes-for-solid-oxide-fuel-cells",totalDownloads:2392,totalCrossrefCites:7,totalDimensionsCites:10,abstract:"Chemical solution deposition (CSD) technique is recently gaining momentum for the fabrication of electrolyte materials for solid oxide fuel cells (SOFCs) due to its cost-effectiveness, high yield, and simplicity of the process requirements. The advanced vacuum deposition techniques such as sputtering, atomic layer deposition (ALD), pulsed laser deposition (PLD), metallo-organic chemical vapor deposition (MOCVD) are lacking in scalability and cost-effectiveness. CSD technique includes a variety of approaches such as sol-gel process, chelate process, and metallo-organic decomposition. The present chapter discusses briefly about the evolution of CSD method and its subsequent entry to the field of SOFCs, various solution methods associated with different chemical compositions, film deposition techniques, chemical reactions, heat treatment strategies, nucleation and growth kinetics, associated defects, etc. Examples are cited to bring out the history dating back to the discovery of amorphous zirconia film through the successful fabrication of the crystalline fluorite-type films such as yttria-stabilized zirconia (YSZ), scandia-doped ceria (SDC), and crystalline perovskite-type films such as yttria-doped barium zirconate (BZY) and yttria-doped barium cerate (BCY), to name a few.",book:{id:"5541",slug:"modern-technologies-for-creating-the-thin-film-systems-and-coatings",title:"Modern Technologies for Creating the Thin-film Systems and Coatings",fullTitle:"Modern Technologies for Creating the Thin-film Systems and Coatings"},signatures:"Mridula Biswas and Pei-Chen Su",authors:[{id:"193015",title:"Dr.",name:"Pei-Chen",middleName:null,surname:"Su",slug:"pei-chen-su",fullName:"Pei-Chen Su"},{id:"193328",title:"Dr.",name:"Mridula",middleName:null,surname:"Biswas",slug:"mridula-biswas",fullName:"Mridula Biswas"}]},{id:"53336",doi:"10.5772/66476",title:"Molecular Precursor Method for Fabricating p-Type Cu2O and Metallic Cu Thin Films",slug:"molecular-precursor-method-for-fabricating-p-type-cu2o-and-metallic-cu-thin-films",totalDownloads:2360,totalCrossrefCites:5,totalDimensionsCites:10,abstract:"Functional thin films are used in various fields of our life. Many different methods are used to fabricate these films including physical vapor deposition (PVD) and chemical processes. The chemical processes can be used to manufacture thin films in a relatively cheap way, as compared to PVD methods. This chapter summarizes the procedures of the molecular precursor method (MPM), a chemical process, for fabrication of both metal oxide semiconductor Cu2O and metallic Cu thin films by utilizing Cu(II) complexes in coating solutions. The MPM, recently developed and reported by the present authors, represents a facile procedure for thin film fabrication of various metal oxides or phosphates. This method pertinent to the coordination chemistry and materials science including nanoscience and nanotechnology has provided various thin films of high quality. The MPM is based on the design of metal complexes in coating solutions with excellent stability, homogeneity, miscibility, coatability, etc., which are practical advantages. The metal oxides and phosphates are useful as the electron and/or ion conductors, semiconductors, dielectric materials, etc. This chapter will describe the principle and recent achievement, mainly on fabricating the p-type Cu2O and metallic Cu thin films of the MPM.",book:{id:"5541",slug:"modern-technologies-for-creating-the-thin-film-systems-and-coatings",title:"Modern Technologies for Creating the Thin-film Systems and Coatings",fullTitle:"Modern Technologies for Creating the Thin-film Systems and Coatings"},signatures:"Hiroki Nagai and Mitsunobu Sato",authors:[{id:"148259",title:"Prof.",name:"Mitsunobu",middleName:null,surname:"Sato",slug:"mitsunobu-sato",fullName:"Mitsunobu Sato"},{id:"148920",title:"Dr.",name:"Hiroki",middleName:null,surname:"Nagai",slug:"hiroki-nagai",fullName:"Hiroki Nagai"}]}],mostDownloadedChaptersLast30Days:[{id:"52684",title:"Advance Deposition Techniques for Thin Film and Coating",slug:"advance-deposition-techniques-for-thin-film-and-coating",totalDownloads:7563,totalCrossrefCites:31,totalDimensionsCites:58,abstract:"Thin films have a great impact on the modern era of technology. Thin films are considered as backbone for advanced applications in the various fields such as optical devices, environmental applications, telecommunications devices, energy storage devices, and so on . The crucial issue for all applications of thin films depends on their morphology and the stability. The morphology of the thin films strongly hinges on deposition techniques. Thin films can be deposited by the physical and chemical routes. In this chapter, we discuss some advance techniques and principles of thin-film depositions. The vacuum thermal evaporation technique, electron beam evaporation, pulsed-layer deposition, direct current/radio frequency magnetron sputtering, and chemical route deposition systems will be discussed in detail.",book:{id:"5541",slug:"modern-technologies-for-creating-the-thin-film-systems-and-coatings",title:"Modern Technologies for Creating the Thin-film Systems and Coatings",fullTitle:"Modern Technologies for Creating the Thin-film Systems and Coatings"},signatures:"Asim Jilani, Mohamed Shaaban Abdel-wahab and Ahmed Hosny\nHammad",authors:[{id:"192377",title:"Dr.",name:"Asim",middleName:null,surname:"Jilani",slug:"asim-jilani",fullName:"Asim Jilani"},{id:"192972",title:"Dr.",name:"M.Sh",middleName:null,surname:"Abdel-Wahab",slug:"m.sh-abdel-wahab",fullName:"M.Sh Abdel-Wahab"},{id:"192973",title:"Dr.",name:"Ahmed",middleName:"H",surname:"Hammad",slug:"ahmed-hammad",fullName:"Ahmed Hammad"}]},{id:"53792",title:"Silver-Based Low-Emissivity Coating Technology for Energy- Saving Window Applications",slug:"silver-based-low-emissivity-coating-technology-for-energy-saving-window-applications",totalDownloads:3132,totalCrossrefCites:7,totalDimensionsCites:13,abstract:"Low-emissivity (low-E) technology is a unique and cost-effective solution to save energy in buildings for different climates. Its development combines advances in materials science, vacuum deposition, and optical design. In this chapter, we will review the fundamentals of energy saving window coatings, the history of its application, and the materials used. The current low-E coating technologies are overviewed, especially silver-based low-E technologies, which comprise more than 90% of the overall low-E market today. Further, the advanced understanding of generating high-quality silver thin films is discussed, which is at the heart of silver-based low-E product technology development. How the silver thin film electrical, optical, and emissivity properties are influenced by their microstructure, thickness, and by the materials on neighboring layers will be discussed from a theoretical and an experimental perspective.",book:{id:"5541",slug:"modern-technologies-for-creating-the-thin-film-systems-and-coatings",title:"Modern Technologies for Creating the Thin-film Systems and Coatings",fullTitle:"Modern Technologies for Creating the Thin-film Systems and Coatings"},signatures:"Guowen Ding and César Clavero",authors:[{id:"195240",title:"Dr.",name:"Guowen",middleName:null,surname:"Ding",slug:"guowen-ding",fullName:"Guowen Ding"},{id:"197064",title:"Dr.",name:"Cesar",middleName:null,surname:"Clavero",slug:"cesar-clavero",fullName:"Cesar Clavero"}]},{id:"52908",title:"Smart Thermoresponsive Surfaces Based on pNIPAm Coatings and Laser Method for Biological Applications",slug:"smart-thermoresponsive-surfaces-based-on-pnipam-coatings-and-laser-method-for-biological-application",totalDownloads:1836,totalCrossrefCites:3,totalDimensionsCites:7,abstract:"Various applications within last decades such as bacterially resistant surfaces, soft robotics, drug delivery systems, sensors and tissue engineering are poised to feature the importance of the ability to control bio-interfacial interactions. An enhanced attention is dedicated to designing smart stimuli-responsive interfaces for DNA, drug delivery, protein and cell based applications. Within this context, the thermoresponsive materials, especially poly(N-isopropylacrylamide) (pNIPAm) have been intensively used in tissue engineering applications for a controlled detachment of proteins and cells with a minimum of invasive effect on protein and cell structural conformation. The properties of smart bio-interfaces can be controlled by its composition and polymer architecture. Therefore, appropriate methods for obtaining controlled coatings are necessary. Laser methods were successfully used in the last decades for obtaining controlled organic and inorganic coatings for various types of applications, from electronics to tissue engineering. Among these, Matrix-Assisted Pulsed Laser Evaporation (MAPLE) technique bring us a step forward to other laser methods by avoiding damage and photochemical decomposition of materials. In this chapter we describe materials and approaches used for design of smart bio-interfaces aimed at controlling protein and cells behavior in vitro, focusing MAPLE method for tuning coatings characteristics in relation with biological response.",book:{id:"5541",slug:"modern-technologies-for-creating-the-thin-film-systems-and-coatings",title:"Modern Technologies for Creating the Thin-film Systems and Coatings",fullTitle:"Modern Technologies for Creating the Thin-film Systems and Coatings"},signatures:"Laurentiu Rusen, Valentina Dinca, Cosmin Mustaciosu, Madalina\nIcriverzi, Livia Elena Sima, Anca Bonciu, Simona Brajnicov, Natalia\nMihailescu, Nicoleta Dumitrescu, Alexandru I. Popovici, Anca\nRoseanu and Maria Dinescu",authors:[{id:"32241",title:"Dr.",name:"Maria",middleName:null,surname:"Dinescu",slug:"maria-dinescu",fullName:"Maria Dinescu"},{id:"176781",title:"Dr.",name:"Valentina",middleName:null,surname:"Dinca",slug:"valentina-dinca",fullName:"Valentina Dinca"},{id:"176783",title:"Dr.",name:"Laurentiu",middleName:null,surname:"Rusen",slug:"laurentiu-rusen",fullName:"Laurentiu Rusen"},{id:"177680",title:"B.Sc.",name:"Anca",middleName:"Florina",surname:"Bonciu",slug:"anca-bonciu",fullName:"Anca Bonciu"},{id:"193439",title:"Ph.D.",name:"Madalina",middleName:null,surname:"Icriverzi",slug:"madalina-icriverzi",fullName:"Madalina Icriverzi"},{id:"193441",title:"Dr.",name:"Livia Elena",middleName:null,surname:"Sima",slug:"livia-elena-sima",fullName:"Livia Elena Sima"},{id:"193442",title:"Ph.D.",name:"Simona",middleName:null,surname:"Brajnicov",slug:"simona-brajnicov",fullName:"Simona Brajnicov"},{id:"193443",title:"Ph.D.",name:"Nicoleta",middleName:"Luminita",surname:"Dumitrescu",slug:"nicoleta-dumitrescu",fullName:"Nicoleta Dumitrescu"},{id:"193444",title:"Dr.",name:"Cosmin",middleName:null,surname:"Mustaciosu",slug:"cosmin-mustaciosu",fullName:"Cosmin Mustaciosu"},{id:"193445",title:"Dr.",name:"Anca",middleName:null,surname:"Roseanu",slug:"anca-roseanu",fullName:"Anca Roseanu"},{id:"196184",title:"Prof.",name:"Natalia",middleName:null,surname:"Serban",slug:"natalia-serban",fullName:"Natalia Serban"},{id:"198275",title:"Ms.",name:"A.I.",middleName:null,surname:"Popovici",slug:"a.i.-popovici",fullName:"A.I. Popovici"}]},{id:"52951",title:"Chemical Solution Deposition Technique of Thin-Film Ceramic Electrolytes for Solid Oxide Fuel Cells",slug:"chemical-solution-deposition-technique-of-thin-film-ceramic-electrolytes-for-solid-oxide-fuel-cells",totalDownloads:2392,totalCrossrefCites:7,totalDimensionsCites:10,abstract:"Chemical solution deposition (CSD) technique is recently gaining momentum for the fabrication of electrolyte materials for solid oxide fuel cells (SOFCs) due to its cost-effectiveness, high yield, and simplicity of the process requirements. The advanced vacuum deposition techniques such as sputtering, atomic layer deposition (ALD), pulsed laser deposition (PLD), metallo-organic chemical vapor deposition (MOCVD) are lacking in scalability and cost-effectiveness. CSD technique includes a variety of approaches such as sol-gel process, chelate process, and metallo-organic decomposition. The present chapter discusses briefly about the evolution of CSD method and its subsequent entry to the field of SOFCs, various solution methods associated with different chemical compositions, film deposition techniques, chemical reactions, heat treatment strategies, nucleation and growth kinetics, associated defects, etc. Examples are cited to bring out the history dating back to the discovery of amorphous zirconia film through the successful fabrication of the crystalline fluorite-type films such as yttria-stabilized zirconia (YSZ), scandia-doped ceria (SDC), and crystalline perovskite-type films such as yttria-doped barium zirconate (BZY) and yttria-doped barium cerate (BCY), to name a few.",book:{id:"5541",slug:"modern-technologies-for-creating-the-thin-film-systems-and-coatings",title:"Modern Technologies for Creating the Thin-film Systems and Coatings",fullTitle:"Modern Technologies for Creating the Thin-film Systems and Coatings"},signatures:"Mridula Biswas and Pei-Chen Su",authors:[{id:"193015",title:"Dr.",name:"Pei-Chen",middleName:null,surname:"Su",slug:"pei-chen-su",fullName:"Pei-Chen Su"},{id:"193328",title:"Dr.",name:"Mridula",middleName:null,surname:"Biswas",slug:"mridula-biswas",fullName:"Mridula Biswas"}]},{id:"53122",title:"Anomalous Rashba Effect of Bi Thin Film Studied by Spin-Resolved ARPES",slug:"anomalous-rashba-effect-of-bi-thin-film-studied-by-spin-resolved-arpes",totalDownloads:2099,totalCrossrefCites:1,totalDimensionsCites:1,abstract:"The Rashba effect is a momentum‐dependent splitting of spin bands in two‐dimensional systems such as surface, interface and heterostructure. The effect is caused by broken space‐inversion symmetry and spin‐orbit coupling and allows to manipulate and generate the spin by the electric fields, that is, without the magnetic field. It means that the devices applied to the Rashba effect have many advantages. Bismuth is known as a promising candidate to investigate the surface Rashba effect, and the spin structure of Bi surface has also been intensively discussed. However, it is unclear to what extent the so far believed simple vortical spin structure is adequate. To understand the surface properties of the Rashba system is particularly important when utilizing the Rashba effect to the spintronic devices, since it is desirable to control the spin polarization when developing new types of devices. In this chapter, we report that the surface spin states of the Bi thin film exhibit unusual characteristics unlike the conventional Rashba splitting by using a spin‐ and angle‐resolved photoemission spectroscopy measurement.",book:{id:"5541",slug:"modern-technologies-for-creating-the-thin-film-systems-and-coatings",title:"Modern Technologies for Creating the Thin-film Systems and Coatings",fullTitle:"Modern Technologies for Creating the Thin-film Systems and Coatings"},signatures:"Akari Takayama",authors:[{id:"192655",title:"Dr.",name:"Akari",middleName:null,surname:"Takayama",slug:"akari-takayama",fullName:"Akari Takayama"}]}],onlineFirstChaptersFilter:{topicId:"955",limit:6,offset:0},onlineFirstChaptersCollection:[],onlineFirstChaptersTotal:0},preDownload:{success:null,errors:{}},subscriptionForm:{success:null,errors:{}},aboutIntechopen:{},privacyPolicy:{},peerReviewing:{},howOpenAccessPublishingWithIntechopenWorks:{},sponsorshipBooks:{sponsorshipBooks:[],offset:0,limit:8,total:null},allSeries:{pteSeriesList:[{id:"14",title:"Artificial Intelligence",numberOfPublishedBooks:9,numberOfPublishedChapters:87,numberOfOpenTopics:6,numberOfUpcomingTopics:0,issn:"2633-1403",doi:"10.5772/intechopen.79920",isOpenForSubmission:!0},{id:"7",title:"Biomedical Engineering",numberOfPublishedBooks:12,numberOfPublishedChapters:99,numberOfOpenTopics:3,numberOfUpcomingTopics:0,issn:"2631-5343",doi:"10.5772/intechopen.71985",isOpenForSubmission:!0}],lsSeriesList:[{id:"11",title:"Biochemistry",numberOfPublishedBooks:27,numberOfPublishedChapters:290,numberOfOpenTopics:4,numberOfUpcomingTopics:0,issn:"2632-0983",doi:"10.5772/intechopen.72877",isOpenForSubmission:!0},{id:"25",title:"Environmental Sciences",numberOfPublishedBooks:1,numberOfPublishedChapters:10,numberOfOpenTopics:4,numberOfUpcomingTopics:0,issn:"2754-6713",doi:"10.5772/intechopen.100362",isOpenForSubmission:!0},{id:"10",title:"Physiology",numberOfPublishedBooks:11,numberOfPublishedChapters:139,numberOfOpenTopics:4,numberOfUpcomingTopics:0,issn:"2631-8261",doi:"10.5772/intechopen.72796",isOpenForSubmission:!0}],hsSeriesList:[{id:"3",title:"Dentistry",numberOfPublishedBooks:8,numberOfPublishedChapters:129,numberOfOpenTopics:0,numberOfUpcomingTopics:2,issn:"2631-6218",doi:"10.5772/intechopen.71199",isOpenForSubmission:!1},{id:"6",title:"Infectious Diseases",numberOfPublishedBooks:13,numberOfPublishedChapters:108,numberOfOpenTopics:3,numberOfUpcomingTopics:1,issn:"2631-6188",doi:"10.5772/intechopen.71852",isOpenForSubmission:!0},{id:"13",title:"Veterinary Medicine and Science",numberOfPublishedBooks:11,numberOfPublishedChapters:104,numberOfOpenTopics:3,numberOfUpcomingTopics:0,issn:"2632-0517",doi:"10.5772/intechopen.73681",isOpenForSubmission:!0}],sshSeriesList:[{id:"22",title:"Business, Management and Economics",numberOfPublishedBooks:1,numberOfPublishedChapters:12,numberOfOpenTopics:2,numberOfUpcomingTopics:1,issn:"2753-894X",doi:"10.5772/intechopen.100359",isOpenForSubmission:!0},{id:"23",title:"Education and Human Development",numberOfPublishedBooks:0,numberOfPublishedChapters:1,numberOfOpenTopics:2,numberOfUpcomingTopics:0,issn:null,doi:"10.5772/intechopen.100360",isOpenForSubmission:!1},{id:"24",title:"Sustainable Development",numberOfPublishedBooks:0,numberOfPublishedChapters:12,numberOfOpenTopics:5,numberOfUpcomingTopics:0,issn:null,doi:"10.5772/intechopen.100361",isOpenForSubmission:!0}],testimonialsList:[{id:"6",text:"It is great to work with the IntechOpen to produce a worthwhile collection of research that also becomes a great educational resource and guide for future research endeavors.",author:{id:"259298",name:"Edward",surname:"Narayan",institutionString:null,profilePictureURL:"https://mts.intechopen.com/storage/users/259298/images/system/259298.jpeg",slug:"edward-narayan",institution:{id:"3",name:"University of Queensland",country:{id:null,name:"Australia"}}}},{id:"13",text:"The collaboration with and support of the technical staff of IntechOpen is fantastic. The whole process of submitting an article and editing of the submitted article goes extremely smooth and fast, the number of reads and downloads of chapters is high, and the contributions are also frequently cited.",author:{id:"55578",name:"Antonio",surname:"Jurado-Navas",institutionString:null,profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bRisIQAS/Profile_Picture_1626166543950",slug:"antonio-jurado-navas",institution:{id:"720",name:"University of Malaga",country:{id:null,name:"Spain"}}}}]},series:{item:{id:"24",title:"Sustainable Development",doi:"10.5772/intechopen.100361",issn:null,scope:"
\r\n\tTransforming our World: the 2030 Agenda for Sustainable Development endorsed by United Nations and 193 Member States, came into effect on Jan 1, 2016, to guide decision making and actions to the year 2030 and beyond. Central to this Agenda are 17 Goals, 169 associated targets and over 230 indicators that are reviewed annually. The vision envisaged in the implementation of the SDGs is centered on the five Ps: People, Planet, Prosperity, Peace and Partnership. This call for renewed focused efforts ensure we have a safe and healthy planet for current and future generations.
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\r\n\tThis Series focuses on covering research and applied research involving the five Ps through the following topics:
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\r\n\t1. Sustainable Economy and Fair Society that relates to SDG 1 on No Poverty, SDG 2 on Zero Hunger, SDG 8 on Decent Work and Economic Growth, SDG 10 on Reduced Inequalities, SDG 12 on Responsible Consumption and Production, and SDG 17 Partnership for the Goals
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\r\n\t2. Health and Wellbeing focusing on SDG 3 on Good Health and Wellbeing and SDG 6 on Clean Water and Sanitation
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\r\n\t3. Inclusivity and Social Equality involving SDG 4 on Quality Education, SDG 5 on Gender Equality, and SDG 16 on Peace, Justice and Strong Institutions
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\r\n\t4. Climate Change and Environmental Sustainability comprising SDG 13 on Climate Action, SDG 14 on Life Below Water, and SDG 15 on Life on Land
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\r\n\t5. Urban Planning and Environmental Management embracing SDG 7 on Affordable Clean Energy, SDG 9 on Industry, Innovation and Infrastructure, and SDG 11 on Sustainable Cities and Communities.
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\r\n\tThe series also seeks to support the use of cross cutting SDGs, as many of the goals listed above, targets and indicators are all interconnected to impact our lives and the decisions we make on a daily basis, making them impossible to tie to a single topic.
",coverUrl:"https://cdn.intechopen.com/series/covers/24.jpg",latestPublicationDate:"May 26th, 2022",hasOnlineFirst:!0,numberOfPublishedBooks:0,editor:{id:"262440",title:"Prof.",name:"Usha",middleName:null,surname:"Iyer-Raniga",slug:"usha-iyer-raniga",fullName:"Usha Iyer-Raniga",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bRYSXQA4/Profile_Picture_2022-02-28T13:55:36.jpeg",biography:"Usha Iyer-Raniga is a professor in the School of Property and Construction Management at RMIT University. Usha co-leads the One Planet Network’s Sustainable Buildings and Construction Programme (SBC), a United Nations 10 Year Framework of Programmes on Sustainable Consumption and Production (UN 10FYP SCP) aligned with Sustainable Development Goal 12. The work also directly impacts SDG 11 on Sustainable Cities and Communities. She completed her undergraduate degree as an architect before obtaining her Masters degree from Canada and her Doctorate in Australia. Usha has been a keynote speaker as well as an invited speaker at national and international conferences, seminars and workshops. Her teaching experience includes teaching in Asian countries. She has advised Austrade, APEC, national, state and local governments. She serves as a reviewer and a member of the scientific committee for national and international refereed journals and refereed conferences. She is on the editorial board for refereed journals and has worked on Special Issues. Usha has served and continues to serve on the Boards of several not-for-profit organisations and she has also served as panel judge for a number of awards including the Premiers Sustainability Award in Victoria and the International Green Gown Awards. Usha has published over 100 publications, including research and consulting reports. Her publications cover a wide range of scientific and technical research publications that include edited books, book chapters, refereed journals, refereed conference papers and reports for local, state and federal government clients. She has also produced podcasts for various organisations and participated in media interviews. She has received state, national and international funding worth over USD $25 million. Usha has been awarded the Quarterly Franklin Membership by London Journals Press (UK). Her biography has been included in the Marquis Who's Who in the World® 2018, 2016 (33rd Edition), along with approximately 55,000 of the most accomplished men and women from around the world, including luminaries as U.N. Secretary-General Ban Ki-moon. 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Radiotherapy and Nuclear Medicine Technology has always been my aspiration and my life. As years passed I accumulated a tremendous amount of skills and knowledge in Radiotherapy and Nuclear Medicine, Conventional Radiology, Radiation Protection, Bioinformatics Technology, PACS, Image processing, clinically and lecturing that will enable me to provide a valuable service to the community as a Researcher and Consultant in this field. My method of translating this into day to day in clinical practice is non-exhaustible and my habit of exchanging knowledge and expertise with others in those fields is the code and secret of success.",institutionString:null,institution:{name:"Majmaah University",country:{name:"Saudi Arabia"}}},{id:"313277",title:"Dr.",name:"Bartłomiej",middleName:null,surname:"Płaczek",slug:"bartlomiej-placzek",fullName:"Bartłomiej Płaczek",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/313277/images/system/313277.jpg",biography:"Bartłomiej Płaczek, MSc (2002), Ph.D. (2005), Habilitation (2016), is a professor at the University of Silesia, Institute of Computer Science, Poland, and an expert from the National Centre for Research and Development. His research interests include sensor networks, smart sensors, intelligent systems, and image processing with applications in healthcare and medicine. He is the author or co-author of more than seventy papers in peer-reviewed journals and conferences as well as the co-author of several books. He serves as a reviewer for many scientific journals, international conferences, and research foundations. Since 2010, Dr. Placzek has been a reviewer of grants and projects (including EU projects) in the field of information technologies.",institutionString:"University of Silesia",institution:{name:"University of Silesia",country:{name:"Poland"}}},{id:"35000",title:"Prof.",name:"Ulrich H.P",middleName:"H.P.",surname:"Fischer",slug:"ulrich-h.p-fischer",fullName:"Ulrich H.P Fischer",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/35000/images/3052_n.jpg",biography:"Academic and Professional Background\nUlrich H. P. has Diploma and PhD degrees in Physics from the Free University Berlin, Germany. He has been working on research positions in the Heinrich-Hertz-Institute in Germany. Several international research projects has been performed with European partners from France, Netherlands, Norway and the UK. He is currently Professor of Communications Systems at the Harz University of Applied Sciences, Germany.\n\nPublications and Publishing\nHe has edited one book, a special interest book about ‘Optoelectronic Packaging’ (VDE, Berlin, Germany), and has published over 100 papers and is owner of several international patents for WDM over POF key elements.\n\nKey Research and Consulting Interests\nUlrich’s research activity has always been related to Spectroscopy and Optical Communications Technology. Specific current interests include the validation of complex instruments, and the application of VR technology to the development and testing of measurement systems. He has been reviewer for several publications of the Optical Society of America\\'s including Photonics Technology Letters and Applied Optics.\n\nPersonal Interests\nThese include motor cycling in a very relaxed manner and performing martial arts.",institutionString:null,institution:{name:"Charité",country:{name:"Germany"}}},{id:"341622",title:"Ph.D.",name:"Eduardo",middleName:null,surname:"Rojas Alvarez",slug:"eduardo-rojas-alvarez",fullName:"Eduardo Rojas Alvarez",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/341622/images/15892_n.jpg",biography:null,institutionString:null,institution:{name:"University of Cuenca",country:{name:"Ecuador"}}},{id:"215610",title:"Prof.",name:"Muhammad",middleName:null,surname:"Sarfraz",slug:"muhammad-sarfraz",fullName:"Muhammad Sarfraz",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/215610/images/system/215610.jpeg",biography:"Muhammad Sarfraz is a professor in the Department of Information Science, Kuwait University, Kuwait. His research interests include optimization, computer graphics, computer vision, image processing, machine learning, pattern recognition, soft computing, data science, and intelligent systems. Prof. Sarfraz has been a keynote/invited speaker at various platforms around the globe. He has advised/supervised more than 110 students for their MSc and Ph.D. theses. He has published more than 400 publications as books, journal articles, and conference papers. He has authored and/or edited around seventy books. Prof. Sarfraz is a member of various professional societies. He is a chair and member of international advisory committees and organizing committees of numerous international conferences. He is also an editor and editor in chief for various international journals.",institutionString:"Kuwait University",institution:{name:"Kuwait University",country:{name:"Kuwait"}}},{id:"32650",title:"Prof.",name:"Lukas",middleName:"Willem",surname:"Snyman",slug:"lukas-snyman",fullName:"Lukas Snyman",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/32650/images/4136_n.jpg",biography:"Lukas Willem Snyman received his basic education at primary and high schools in South Africa, Eastern Cape. He enrolled at today's Nelson Metropolitan University and graduated from this university with a BSc in Physics and Mathematics, B.Sc Honors in Physics, MSc in Semiconductor Physics, and a Ph.D. in Semiconductor Physics in 1987. After his studies, he chose an academic career and devoted his energy to the teaching of physics to first, second, and third-year students. After positions as a lecturer at the University of Port Elizabeth, he accepted a position as Associate Professor at the University of Pretoria, South Africa.\r\n\r\nIn 1992, he motivates the concept of 'television and computer-based education” as means to reach large student numbers with only the best of teaching expertise and publishes an article on the concept in the SA Journal of Higher Education of 1993 (and later in 2003). The University of Pretoria subsequently approved a series of test projects on the concept with outreach to Mamelodi and Eerste Rust in 1993. In 1994, the University established a 'Unit for Telematic Education ' as a support section for multiple faculties at the University of Pretoria. In subsequent years, the concept of 'telematic education” subsequently becomes well established in academic circles in South Africa, grew in popularity, and is adopted by many universities and colleges throughout South Africa as a medium of enhancing education and training, as a method to reaching out to far out communities, and as a means to enhance study from the home environment.\r\n\r\nProfessor Snyman in subsequent years pursued research in semiconductor physics, semiconductor devices, microelectronics, and optoelectronics.\r\n\r\nIn 2000 he joined the TUT as a full professor. Here served for a period as head of the Department of Electronic Engineering. Here he makes contributions to solar energy development, microwave and optoelectronic device development, silicon photonics, as well as contributions to new mobile telecommunication systems and network planning in SA.\r\n\r\nCurrently, he teaches electronics and telecommunications at the TUT to audiences ranging from first-year students to Ph.D. level.\r\n\r\nFor his research in the field of 'Silicon Photonics” since 1990, he has published (as author and co-author) about thirty internationally reviewed articles in scientific journals, contributed to more than forty international conferences, about 25 South African provisional patents (as inventor and co-inventor), 8 PCT international patent applications until now. Of these, two USA patents applications, two European Patents, two Korean patents, and ten SA patents have been granted. A further 4 USA patents, 5 European patents, 3 Korean patents, 3 Chinese patents, and 3 Japanese patents are currently under consideration.\r\n\r\nRecently he has also published an extensive scholarly chapter in an internet open access book on 'Integrating Microphotonic Systems and MOEMS into standard Silicon CMOS Integrated circuitry”.\r\n\r\nFurthermore, Professor Snyman recently steered a new initiative at the TUT by introducing a 'Laboratory for Innovative Electronic Systems ' at the Department of Electrical Engineering. The model of this laboratory or center is to primarily combine outputs as achieved by high-level research with lower-level system development and entrepreneurship in a technical university environment. Students are allocated to projects at different levels with PhDs and Master students allocated to the generation of new knowledge and new technologies, while students at the diploma and Baccalaureus level are allocated to electronic systems development with a direct and a near application for application in industry or the commercial and public sectors in South Africa.\r\n\r\nProfessor Snyman received the WIRSAM Award of 1983 and the WIRSAM Award in 1985 in South Africa for best research papers by a young scientist at two international conferences on electron microscopy in South Africa. He subsequently received the SA Microelectronics Award for the best dissertation emanating from studies executed at a South African university in the field of Physics and Microelectronics in South Africa in 1987. In October of 2011, Professor Snyman received the prestigious Institutional Award for 'Innovator of the Year” for 2010 at the Tshwane University of Technology, South Africa. This award was based on the number of patents recognized and granted by local and international institutions as well as for his contributions concerning innovation at the TUT.",institutionString:null,institution:{name:"University of South Africa",country:{name:"South Africa"}}},{id:"317279",title:"Mr.",name:"Ali",middleName:"Usama",surname:"Syed",slug:"ali-syed",fullName:"Ali Syed",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/317279/images/16024_n.png",biography:"A creative, talented, and innovative young professional who is dedicated, well organized, and capable research fellow with two years of experience in graduate-level research, published in engineering journals and book, with related expertise in Bio-robotics, equally passionate about the aesthetics of the mechanical and electronic system, obtained expertise in the use of MS Office, MATLAB, SolidWorks, LabVIEW, Proteus, Fusion 360, having a grasp on python, C++ and assembly language, possess proven ability in acquiring research grants, previous appointments with social and educational societies with experience in administration, current affiliations with IEEE and Web of Science, a confident presenter at conferences and teacher in classrooms, able to explain complex information to audiences of all levels.",institutionString:null,institution:{name:"Air University",country:{name:"Pakistan"}}},{id:"75526",title:"Ph.D.",name:"Zihni Onur",middleName:null,surname:"Uygun",slug:"zihni-onur-uygun",fullName:"Zihni Onur Uygun",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/75526/images/12_n.jpg",biography:"My undergraduate education and my Master of Science educations at Ege University and at Çanakkale Onsekiz Mart University have given me a firm foundation in Biochemistry, Analytical Chemistry, Biosensors, Bioelectronics, Physical Chemistry and Medicine. After obtaining my degree as a MSc in analytical chemistry, I started working as a research assistant in Ege University Medical Faculty in 2014. In parallel, I enrolled to the MSc program at the Department of Medical Biochemistry at Ege University to gain deeper knowledge on medical and biochemical sciences as well as clinical chemistry in 2014. In my PhD I deeply researched on biosensors and bioelectronics and finished in 2020. Now I have eleven SCI-Expanded Index published papers, 6 international book chapters, referee assignments for different SCIE journals, one international patent pending, several international awards, projects and bursaries. In parallel to my research assistant position at Ege University Medical Faculty, Department of Medical Biochemistry, in April 2016, I also founded a Start-Up Company (Denosens Biotechnology LTD) by the support of The Scientific and Technological Research Council of Turkey. Currently, I am also working as a CEO in Denosens Biotechnology. The main purposes of the company, which carries out R&D as a research center, are to develop new generation biosensors and sensors for both point-of-care diagnostics; such as glucose, lactate, cholesterol and cancer biomarker detections. My specific experimental and instrumental skills are Biochemistry, Biosensor, Analytical Chemistry, Electrochemistry, Mobile phone based point-of-care diagnostic device, POCTs and Patient interface designs, HPLC, Tandem Mass Spectrometry, Spectrophotometry, ELISA.",institutionString:null,institution:{name:"Ege University",country:{name:"Turkey"}}},{id:"246502",title:"Dr.",name:"Jaya T.",middleName:"T",surname:"Varkey",slug:"jaya-t.-varkey",fullName:"Jaya T. Varkey",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/246502/images/11160_n.jpg",biography:"Jaya T. Varkey, PhD, graduated with a degree in Chemistry from Cochin University of Science and Technology, Kerala, India. She obtained a PhD in Chemistry from the School of Chemical Sciences, Mahatma Gandhi University, Kerala, India, and completed a post-doctoral fellowship at the University of Minnesota, USA. She is a research guide at Mahatma Gandhi University and Associate Professor in Chemistry, St. Teresa’s College, Kochi, Kerala, India.\nDr. Varkey received a National Young Scientist award from the Indian Science Congress (1995), a UGC Research award (2016–2018), an Indian National Science Academy (INSA) Visiting Scientist award (2018–2019), and a Best Innovative Faculty award from the All India Association for Christian Higher Education (AIACHE) (2019). She Hashas received the Sr. Mary Cecil prize for best research paper three times. She was also awarded a start-up to develop a tea bag water filter. \nDr. Varkey has published two international books and twenty-seven international journal publications. She is an editorial board member for five international journals.",institutionString:"St. Teresa’s College",institution:null},{id:"250668",title:"Dr.",name:"Ali",middleName:null,surname:"Nabipour Chakoli",slug:"ali-nabipour-chakoli",fullName:"Ali Nabipour Chakoli",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/250668/images/system/250668.jpg",biography:"Academic Qualification:\r\n•\tPhD in Materials Physics and Chemistry, From: Sep. 2006, to: Sep. 2010, School of Materials Science and Engineering, Harbin Institute of Technology, Thesis: Structure and Shape Memory Effect of Functionalized MWCNTs/poly (L-lactide-co-ε-caprolactone) Nanocomposites. Supervisor: Prof. Wei Cai,\r\n•\tM.Sc in Applied Physics, From: 1996, to: 1998, Faculty of Physics & Nuclear Science, Amirkabir Uni. of Technology, Tehran, Iran, Thesis: Determination of Boron in Micro alloy Steels with solid state nuclear track detectors by neutron induced auto radiography, Supervisors: Dr. M. Hosseini Ashrafi and Dr. A. Hosseini.\r\n•\tB.Sc. in Applied Physics, From: 1991, to: 1996, Faculty of Physics & Nuclear Science, Amirkabir Uni. of Technology, Tehran, Iran, Thesis: Design of shielding for Am-Be neutron sources for In Vivo neutron activation analysis, Supervisor: Dr. M. Hosseini Ashrafi.\r\n\r\nResearch Experiences:\r\n1.\tNanomaterials, Carbon Nanotubes, Graphene: Synthesis, Functionalization and Characterization,\r\n2.\tMWCNTs/Polymer Composites: Fabrication and Characterization, \r\n3.\tShape Memory Polymers, Biodegradable Polymers, ORC, Collagen,\r\n4.\tMaterials Analysis and Characterizations: TEM, SEM, XPS, FT-IR, Raman, DSC, DMA, TGA, XRD, GPC, Fluoroscopy, \r\n5.\tInteraction of Radiation with Mater, Nuclear Safety and Security, NDT(RT),\r\n6.\tRadiation Detectors, Calibration (SSDL),\r\n7.\tCompleted IAEA e-learning Courses:\r\nNuclear Security (15 Modules),\r\nNuclear Safety:\r\nTSA 2: Regulatory Protection in Occupational Exposure,\r\nTips & Tricks: Radiation Protection in Radiography,\r\nSafety and Quality in Radiotherapy,\r\nCourse on Sealed Radioactive Sources,\r\nCourse on Fundamentals of Environmental Remediation,\r\nCourse on Planning for Environmental Remediation,\r\nKnowledge Management Orientation Course,\r\nFood Irradiation - Technology, Applications and Good Practices,\r\nEmployment:\r\nFrom 2010 to now: Academic staff, Nuclear Science and Technology Research Institute, Kargar Shomali, Tehran, Iran, P.O. Box: 14395-836.\r\nFrom 1997 to 2006: Expert of Materials Analysis and Characterization. Research Center of Agriculture and Medicine. Rajaeeshahr, Karaj, Iran, P. O. Box: 31585-498.",institutionString:"Atomic Energy Organization of Iran",institution:{name:"Atomic Energy Organization of Iran",country:{name:"Iran"}}},{id:"248279",title:"Dr.",name:"Monika",middleName:"Elzbieta",surname:"Machoy",slug:"monika-machoy",fullName:"Monika Machoy",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/248279/images/system/248279.jpeg",biography:"Monika Elżbieta Machoy, MD, graduated with distinction from the Faculty of Medicine and Dentistry at the Pomeranian Medical University in 2009, defended her PhD thesis with summa cum laude in 2016 and is currently employed as a researcher at the Department of Orthodontics of the Pomeranian Medical University. She expanded her professional knowledge during a one-year scholarship program at the Ernst Moritz Arndt University in Greifswald, Germany and during a three-year internship at the Technical University in Dresden, Germany. She has been a speaker at numerous orthodontic conferences, among others, American Association of Orthodontics, European Orthodontic Symposium and numerous conferences of the Polish Orthodontic Society. She conducts research focusing on the effect of orthodontic treatment on dental and periodontal tissues and the causes of pain in orthodontic patients.",institutionString:"Pomeranian Medical University",institution:{name:"Pomeranian Medical University",country:{name:"Poland"}}},{id:"252743",title:"Prof.",name:"Aswini",middleName:"Kumar",surname:"Kar",slug:"aswini-kar",fullName:"Aswini Kar",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/252743/images/10381_n.jpg",biography:"uploaded in cv",institutionString:null,institution:{name:"KIIT University",country:{name:"India"}}},{id:"204256",title:"Dr.",name:"Anil",middleName:"Kumar",surname:"Kumar Sahu",slug:"anil-kumar-sahu",fullName:"Anil Kumar Sahu",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/204256/images/14201_n.jpg",biography:"I have nearly 11 years of research and teaching experience. I have done my master degree from University Institute of Pharmacy, Pt. Ravi Shankar Shukla University, Raipur, Chhattisgarh India. I have published 16 review and research articles in international and national journals and published 4 chapters in IntechOpen, the world’s leading publisher of Open access books. I have presented many papers at national and international conferences. I have received research award from Indian Drug Manufacturers Association in year 2015. My research interest extends from novel lymphatic drug delivery systems, oral delivery system for herbal bioactive to formulation optimization.",institutionString:null,institution:{name:"Chhattisgarh Swami Vivekanand Technical University",country:{name:"India"}}},{id:"253468",title:"Dr.",name:"Mariusz",middleName:null,surname:"Marzec",slug:"mariusz-marzec",fullName:"Mariusz Marzec",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/253468/images/system/253468.png",biography:"An assistant professor at Department of Biomedical Computer Systems, at Institute of Computer Science, Silesian University in Katowice. Scientific interests: computer analysis and processing of images, biomedical images, databases and programming languages. He is an author and co-author of scientific publications covering analysis and processing of biomedical images and development of database systems.",institutionString:"University of Silesia",institution:null},{id:"212432",title:"Prof.",name:"Hadi",middleName:null,surname:"Mohammadi",slug:"hadi-mohammadi",fullName:"Hadi Mohammadi",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/212432/images/system/212432.jpeg",biography:"Dr. Hadi Mohammadi is a biomedical engineer with hands-on experience in the design and development of many engineering structures and medical devices through various projects that he has been involved in over the past twenty years. Dr. Mohammadi received his BSc. and MSc. degrees in Mechanical Engineering from Sharif University of Technology, Tehran, Iran, and his PhD. degree in Biomedical Engineering (biomaterials) from the University of Western Ontario. He was a postdoctoral trainee for almost four years at University of Calgary and Harvard Medical School. He is an industry innovator having created the technology to produce lifelike synthetic platforms that can be used for the simulation of almost all cardiovascular reconstructive surgeries. He’s been heavily involved in the design and development of cardiovascular devices and technology for the past 10 years. He is currently an Assistant Professor with the University of British Colombia, Canada.",institutionString:"University of British Columbia",institution:{name:"University of British Columbia",country:{name:"Canada"}}},{id:"254463",title:"Prof.",name:"Haisheng",middleName:null,surname:"Yang",slug:"haisheng-yang",fullName:"Haisheng Yang",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/254463/images/system/254463.jpeg",biography:"Haisheng Yang, Ph.D., Professor and Director of the Department of Biomedical Engineering, College of Life Science and Bioengineering, Beijing University of Technology. He received his Ph.D. degree in Mechanics/Biomechanics from Harbin Institute of Technology (jointly with University of California, Berkeley). Afterwards, he worked as a Postdoctoral Research Associate in the Purdue Musculoskeletal Biology and Mechanics Lab at the Department of Basic Medical Sciences, Purdue University, USA. He also conducted research in the Research Centre of Shriners Hospitals for Children-Canada at McGill University, Canada. Dr. Yang has over 10 years research experience in orthopaedic biomechanics and mechanobiology of bone adaptation and regeneration. He earned an award from Beijing Overseas Talents Aggregation program in 2017 and serves as Beijing Distinguished Professor.",institutionString:"Beijing University of Technology",institution:null},{id:"255757",title:"Dr.",name:"Igor",middleName:"Victorovich",surname:"Lakhno",slug:"igor-lakhno",fullName:"Igor Lakhno",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/255757/images/system/255757.jpg",biography:"Lakhno Igor Victorovich was born in 1971 in Kharkiv (Ukraine). \nMD – 1994, Kharkiv National Medical Univesity.\nOb&Gyn; – 1997, master courses in Kharkiv Medical Academy of Postgraduate Education.\nPhD – 1999, Kharkiv National Medical Univesity.\nDSc – 2019, PL Shupik National Academy of Postgraduate Education \nLakhno Igor has been graduated from an international training courses on reproductive medicine and family planning held in Debrecen University (Hungary) in 1997. Since 1998 Lakhno Igor has worked as an associate professor of the department of obstetrics and gynecology of VN Karazin National University and an associate professor of the perinatology, obstetrics and gynecology department of Kharkiv Medical Academy of Postgraduate Education. Since June 2019 he’s a professor of the department of obstetrics and gynecology of VN Karazin National University and a professor of the perinatology, obstetrics and gynecology department of Kharkiv Medical Academy of Postgraduate Education . He’s an author of about 200 printed works and there are 17 of them in Scopus or Web of Science databases. Lakhno Igor is a rewiever of Journal of Obstetrics and Gynaecology (Taylor and Francis), Informatics in Medicine Unlocked (Elsevier), The Journal of Obstetrics and Gynecology Research (Wiley), Endocrine, Metabolic & Immune Disorders-Drug Targets (Bentham Open), The Open Biomedical Engineering Journal (Bentham Open), etc. He’s defended a dissertation for DSc degree \\'Pre-eclampsia: prediction, prevention and treatment”. Lakhno Igor has participated as a speaker in several international conferences and congresses (International Conference on Biological Oscillations April 10th-14th 2016, Lancaster, UK, The 9th conference of the European Study Group on Cardiovascular Oscillations). His main scientific interests: obstetrics, women’s health, fetal medicine, cardiovascular medicine.",institutionString:"V.N. Karazin Kharkiv National University",institution:{name:"Kharkiv Medical Academy of Postgraduate Education",country:{name:"Ukraine"}}},{id:"89721",title:"Dr.",name:"Mehmet",middleName:"Cuneyt",surname:"Ozmen",slug:"mehmet-ozmen",fullName:"Mehmet Ozmen",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/89721/images/7289_n.jpg",biography:null,institutionString:null,institution:{name:"Gazi University",country:{name:"Turkey"}}},{id:"243698",title:"M.D.",name:"Xiaogang",middleName:null,surname:"Wang",slug:"xiaogang-wang",fullName:"Xiaogang Wang",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/243698/images/system/243698.png",biography:"Dr. Xiaogang Wang, a faculty member of Shanxi Eye Hospital specializing in the treatment of cataract and retinal disease and a tutor for postgraduate students of Shanxi Medical University, worked in the COOL Lab as an international visiting scholar under the supervision of Dr. David Huang and Yali Jia from October 2012 through November 2013. Dr. Wang earned an MD from Shanxi Medical University and a Ph.D. from Shanghai Jiao Tong University. Dr. Wang was awarded two research project grants focused on multimodal optical coherence tomography imaging and deep learning in cataract and retinal disease, from the National Natural Science Foundation of China. He has published around 30 peer-reviewed journal papers and four book chapters and co-edited one book.",institutionString:"Shanxi Eye Hospital",institution:{name:"Shanxi Eye Hospital",country:{name:"China"}}},{id:"242893",title:"Ph.D. Student",name:"Joaquim",middleName:null,surname:"De Moura",slug:"joaquim-de-moura",fullName:"Joaquim De Moura",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/242893/images/7133_n.jpg",biography:"Joaquim de Moura received his degree in Computer Engineering in 2014 from the University of A Coruña (Spain). In 2016, he received his M.Sc degree in Computer Engineering from the same university. He is currently pursuing his Ph.D degree in Computer Science in a collaborative project between ophthalmology centers in Galicia and the University of A Coruña. His research interests include computer vision, machine learning algorithms and analysis and medical imaging processing of various kinds.",institutionString:null,institution:{name:"University of A Coruña",country:{name:"Spain"}}},{id:"267434",title:"Dr.",name:"Rohit",middleName:null,surname:"Raja",slug:"rohit-raja",fullName:"Rohit Raja",position:null,profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bRZkkQAG/Profile_Picture_2022-05-09T12:55:18.jpg",biography:null,institutionString:null,institution:null},{id:"294334",title:"B.Sc.",name:"Marc",middleName:null,surname:"Bruggeman",slug:"marc-bruggeman",fullName:"Marc Bruggeman",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/294334/images/8242_n.jpg",biography:"Chemical engineer graduate, with a passion for material science and specific interest in polymers - their near infinite applications intrigue me. \n\nI plan to continue my scientific career in the field of polymeric biomaterials as I am fascinated by intelligent, bioactive and biomimetic materials for use in both consumer and medical applications.",institutionString:null,institution:null},{id:"244950",title:"Dr.",name:"Salvatore",middleName:null,surname:"Di Lauro",slug:"salvatore-di-lauro",fullName:"Salvatore Di Lauro",position:null,profilePictureURL:"https://intech-files.s3.amazonaws.com/0030O00002bSF1HQAW/ProfilePicture%202021-12-20%2014%3A54%3A14.482",biography:"Name:\n\tSALVATORE DI LAURO\nAddress:\n\tHospital Clínico Universitario Valladolid\nAvda Ramón y Cajal 3\n47005, Valladolid\nSpain\nPhone number: \nFax\nE-mail:\n\t+34 983420000 ext 292\n+34 983420084\nsadilauro@live.it\nDate and place of Birth:\nID Number\nMedical Licence \nLanguages\t09-05-1985. Villaricca (Italy)\n\nY1281863H\n474707061\nItalian (native language)\nSpanish (read, written, spoken)\nEnglish (read, written, spoken)\nPortuguese (read, spoken)\nFrench (read)\n\t\t\nCurrent position (title and company)\tDate (Year)\nVitreo-Retinal consultant in ophthalmology. Hospital Clinico Universitario Valladolid. Sacyl. National Health System.\nVitreo-Retinal consultant in ophthalmology. Instituto Oftalmologico Recoletas. Red Hospitalaria Recoletas. Private practise.\t2017-today\n\n2019-today\n\t\n\t\nEducation (High school, university and postgraduate training > 3 months)\tDate (Year)\nDegree in Medicine and Surgery. University of Neaples 'Federico II”\nResident in Opthalmology. Hospital Clinico Universitario Valladolid\nMaster in Vitreo-Retina. IOBA. University of Valladolid\nFellow of the European Board of Ophthalmology. Paris\nMaster in Research in Ophthalmology. University of Valladolid\t2003-2009\n2012-2016\n2016-2017\n2016\n2012-2013\n\t\nEmployments (company and positions)\tDate (Year)\nResident in Ophthalmology. Hospital Clinico Universitario Valladolid. Sacyl.\nFellow in Vitreo-Retina. IOBA. University of Valladolid\nVitreo-Retinal consultant in ophthalmology. Hospital Clinico Universitario Valladolid. Sacyl. National Health System.\nVitreo-Retinal consultant in ophthalmology. Instituto Oftalmologico Recoletas. Red Hospitalaria Recoletas. \n\t2012-2016\n2016-2017\n2017-today\n\n2019-Today\n\n\n\t\nClinical Research Experience (tasks and role)\tDate (Year)\nAssociated investigator\n\n' FIS PI20/00740: DESARROLLO DE UNA CALCULADORA DE RIESGO DE\nAPARICION DE RETINOPATIA DIABETICA BASADA EN TECNICAS DE IMAGEN MULTIMODAL EN PACIENTES DIABETICOS TIPO 1. Grant by: Ministerio de Ciencia e Innovacion \n\n' (BIO/VA23/14) Estudio clínico multicéntrico y prospectivo para validar dos\nbiomarcadores ubicados en los genes p53 y MDM2 en la predicción de los resultados funcionales de la cirugía del desprendimiento de retina regmatógeno. Grant by: Gerencia Regional de Salud de la Junta de Castilla y León.\n' Estudio multicéntrico, aleatorizado, con enmascaramiento doble, en 2 grupos\nparalelos y de 52 semanas de duración para comparar la eficacia, seguridad e inmunogenicidad de SOK583A1 respecto a Eylea® en pacientes con degeneración macular neovascular asociada a la edad' (CSOK583A12301; N.EUDRA: 2019-004838-41; FASE III). Grant by Hexal AG\n\n' Estudio de fase III, aleatorizado, doble ciego, con grupos paralelos, multicéntrico para comparar la eficacia y la seguridad de QL1205 frente a Lucentis® en pacientes con degeneración macular neovascular asociada a la edad. (EUDRACT: 2018-004486-13). Grant by Qilu Pharmaceutical Co\n\n' Estudio NEUTON: Ensayo clinico en fase IV para evaluar la eficacia de aflibercept en pacientes Naive con Edema MacUlar secundario a Oclusion de Vena CenTral de la Retina (OVCR) en regimen de tratamientO iNdividualizado Treat and Extend (TAE)”, (2014-000975-21). Grant by Fundacion Retinaplus\n\n' Evaluación de la seguridad y bioactividad de anillos de tensión capsular en conejo. Proyecto Procusens. Grant by AJL, S.A.\n\n'Estudio epidemiológico, prospectivo, multicéntrico y abierto\\npara valorar la frecuencia de la conjuntivitis adenovírica diagnosticada mediante el test AdenoPlus®\\nTest en pacientes enfermos de conjuntivitis aguda”\\n. National, multicenter study. Grant by: NICOX.\n\nEuropean multicentric trial: 'Evaluation of clinical outcomes following the use of Systane Hydration in patients with dry eye”. Study Phase 4. Grant by: Alcon Labs'\n\nVLPs Injection and Activation in a Rabbit Model of Uveal Melanoma. Grant by Aura Bioscience\n\nUpdating and characterization of a rabbit model of uveal melanoma. Grant by Aura Bioscience\n\nEnsayo clínico en fase IV para evaluar las variantes genéticas de la vía del VEGF como biomarcadores de eficacia del tratamiento con aflibercept en pacientes con degeneración macular asociada a la edad (DMAE) neovascular. Estudio BIOIMAGE. IMO-AFLI-2013-01\n\nEstudio In-Eye:Ensayo clínico en fase IV, abierto, aleatorizado, de 2 brazos,\nmulticçentrico y de 12 meses de duración, para evaluar la eficacia y seguridad de un régimen de PRN flexible individualizado de 'esperar y extender' versus un régimen PRN según criterios de estabilización mediante evaluaciones mensuales de inyecciones intravítreas de ranibizumab 0,5 mg en pacientes naive con neovascularización coriodea secunaria a la degeneración macular relacionada con la edad. CP: CRFB002AES03T\n\nTREND: Estudio Fase IIIb multicéntrico, randomizado, de 12 meses de\nseguimiento con evaluador de la agudeza visual enmascarado, para evaluar la eficacia y la seguridad de ranibizumab 0.5mg en un régimen de tratar y extender comparado con un régimen mensual, en pacientes con degeneración macular neovascular asociada a la edad. CP: CRFB002A2411 Código Eudra CT:\n2013-002626-23\n\n\n\nPublications\t\n\n2021\n\n\n\n\n2015\n\n\n\n\n2021\n\n\n\n\n\n2021\n\n\n\n\n2015\n\n\n\n\n2015\n\n\n2014\n\n\n\n\n2015-16\n\n\n\n2015\n\n\n2014\n\n\n2014\n\n\n\n\n2014\n\n\n\n\n\n\n\n2014\n\nJose Carlos Pastor; Jimena Rojas; Salvador Pastor-Idoate; Salvatore Di Lauro; Lucia Gonzalez-Buendia; Santiago Delgado-Tirado. Proliferative vitreoretinopathy: A new concept of disease pathogenesis and practical\nconsequences. Progress in Retinal and Eye Research. 51, pp. 125 - 155. 03/2016. DOI: 10.1016/j.preteyeres.2015.07.005\n\n\nLabrador-Velandia S; Alonso-Alonso ML; Di Lauro S; García-Gutierrez MT; Srivastava GK; Pastor JC; Fernandez-Bueno I. Mesenchymal stem cells provide paracrine neuroprotective resources that delay degeneration of co-cultured organotypic neuroretinal cultures.Experimental Eye Research. 185, 17/05/2019. DOI: 10.1016/j.exer.2019.05.011\n\nSalvatore Di Lauro; Maria Teresa Garcia Gutierrez; Ivan Fernandez Bueno. Quantification of pigment epithelium-derived factor (PEDF) in an ex vivo coculture of retinal pigment epithelium cells and neuroretina.\nJournal of Allbiosolution. 2019. ISSN 2605-3535\n\nSonia Labrador Velandia; Salvatore Di Lauro; Alonso-Alonso ML; Tabera Bartolomé S; Srivastava GK; Pastor JC; Fernandez-Bueno I. Biocompatibility of intravitreal injection of human mesenchymal stem cells in immunocompetent rabbits. Graefe's archive for clinical and experimental ophthalmology. 256 - 1, pp. 125 - 134. 01/2018. DOI: 10.1007/s00417-017-3842-3\n\n\nSalvatore Di Lauro, David Rodriguez-Crespo, Manuel J Gayoso, Maria T Garcia-Gutierrez, J Carlos Pastor, Girish K Srivastava, Ivan Fernandez-Bueno. A novel coculture model of porcine central neuroretina explants and retinal pigment epithelium cells. Molecular Vision. 2016 - 22, pp. 243 - 253. 01/2016.\n\nSalvatore Di Lauro. Classifications for Proliferative Vitreoretinopathy ({PVR}): An Analysis of Their Use in Publications over the Last 15 Years. Journal of Ophthalmology. 2016, pp. 1 - 6. 01/2016. DOI: 10.1155/2016/7807596\n\nSalvatore Di Lauro; Rosa Maria Coco; Rosa Maria Sanabria; Enrique Rodriguez de la Rua; Jose Carlos Pastor. Loss of Visual Acuity after Successful Surgery for Macula-On Rhegmatogenous Retinal Detachment in a Prospective Multicentre Study. Journal of Ophthalmology. 2015:821864, 2015. DOI: 10.1155/2015/821864\n\nIvan Fernandez-Bueno; Salvatore Di Lauro; Ivan Alvarez; Jose Carlos Lopez; Maria Teresa Garcia-Gutierrez; Itziar Fernandez; Eva Larra; Jose Carlos Pastor. Safety and Biocompatibility of a New High-Density Polyethylene-Based\nSpherical Integrated Porous Orbital Implant: An Experimental Study in Rabbits. Journal of Ophthalmology. 2015:904096, 2015. DOI: 10.1155/2015/904096\n\nPastor JC; Pastor-Idoate S; Rodríguez-Hernandez I; Rojas J; Fernandez I; Gonzalez-Buendia L; Di Lauro S; Gonzalez-Sarmiento R. Genetics of PVR and RD. Ophthalmologica. 232 - Suppl 1, pp. 28 - 29. 2014\n\nRodriguez-Crespo D; Di Lauro S; Singh AK; Garcia-Gutierrez MT; Garrosa M; Pastor JC; Fernandez-Bueno I; Srivastava GK. Triple-layered mixed co-culture model of RPE cells with neuroretina for evaluating the neuroprotective effects of adipose-MSCs. Cell Tissue Res. 358 - 3, pp. 705 - 716. 2014.\nDOI: 10.1007/s00441-014-1987-5\n\nCarlo De Werra; Salvatore Condurro; Salvatore Tramontano; Mario Perone; Ivana Donzelli; Salvatore Di Lauro; Massimo Di Giuseppe; Rosa Di Micco; Annalisa Pascariello; Antonio Pastore; Giorgio Diamantis; Giuseppe Galloro. Hydatid disease of the liver: thirty years of surgical experience.Chirurgia italiana. 59 - 5, pp. 611 - 636.\n(Italia): 2007. ISSN 0009-4773\n\nChapters in books\n\t\n' Salvador Pastor Idoate; Salvatore Di Lauro; Jose Carlos Pastor Jimeno. PVR: Pathogenesis, Histopathology and Classification. Proliferative Vitreoretinopathy with Small Gauge Vitrectomy. Springer, 2018. ISBN 978-3-319-78445-8\nDOI: 10.1007/978-3-319-78446-5_2. \n\n' Salvatore Di Lauro; Maria Isabel Lopez Galvez. Quistes vítreos en una mujer joven. Problemas diagnósticos en patología retinocoroidea. Sociedad Española de Retina-Vitreo. 2018.\n\n' Salvatore Di Lauro; Salvador Pastor Idoate; Jose Carlos Pastor Jimeno. iOCT in PVR management. OCT Applications in Opthalmology. pp. 1 - 8. INTECH, 2018. DOI: 10.5772/intechopen.78774.\n\n' Rosa Coco Martin; Salvatore Di Lauro; Salvador Pastor Idoate; Jose Carlos Pastor. amponadores, manipuladores y tinciones en la cirugía del traumatismo ocular.Trauma Ocular. Ponencia de la SEO 2018..\n\n' LOPEZ GALVEZ; DI LAURO; CRESPO. OCT angiografia y complicaciones retinianas de la diabetes. PONENCIA SEO 2021, CAPITULO 20. (España): 2021.\n\n' Múltiples desprendimientos neurosensoriales bilaterales en paciente joven. Enfermedades Degenerativas De Retina Y Coroides. SERV 04/2016. \n' González-Buendía L; Di Lauro S; Pastor-Idoate S; Pastor Jimeno JC. Vitreorretinopatía proliferante (VRP) e inflamación: LA INFLAMACIÓN in «INMUNOMODULADORES Y ANTIINFLAMATORIOS: MÁS ALLÁ DE LOS CORTICOIDES. 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We welcome chapters presenting research on the many applications of multi-agent studies including, but not limited to, the following key areas: machine learning for multi-agent systems; modeling swarms robots and flocks of UAVs with multi-agent systems; decision science and multi-agent systems; software engineering for and with multi-agent systems; tools and technologies of multi-agent systems.",coverUrl:"https://cdn.intechopen.com/series_topics/covers/27.jpg",keywords:"Collaborative Intelligence, Learning, Distributed Control System, Swarm Robotics, Decision Science, Software Engineering"}],annualVolumeBook:{},thematicCollection:[],selectedSeries:null,selectedSubseries:null},seriesLanding:{item:{id:"25",title:"Environmental Sciences",doi:"10.5772/intechopen.100362",issn:"2754-6713",scope:"
\r\n\tScientists have long researched to understand the environment and man’s place in it. The search for this knowledge grows in importance as rapid increases in population and economic development intensify humans’ stresses on ecosystems. Fortunately, rapid increases in multiple scientific areas are advancing our understanding of environmental sciences. Breakthroughs in computing, molecular biology, ecology, and sustainability science are enhancing our ability to utilize environmental sciences to address real-world problems. \r\n\tThe four topics of this book series - Pollution; Environmental Resilience and Management; Ecosystems and Biodiversity; and Water Science - will address important areas of advancement in the environmental sciences. They will represent an excellent initial grouping of published works on these critical topics.
",coverUrl:"https://cdn.intechopen.com/series/covers/25.jpg",latestPublicationDate:"April 13th, 2022",hasOnlineFirst:!1,numberOfOpenTopics:4,numberOfPublishedChapters:9,numberOfPublishedBooks:1,editor:{id:"197485",title:"Dr.",name:"J. Kevin",middleName:null,surname:"Summers",fullName:"J. Kevin Summers",profilePictureURL:"https://mts.intechopen.com/storage/users/197485/images/system/197485.jpg",biography:"J. Kevin Summers is a Senior Research Ecologist at the Environmental Protection Agency’s (EPA) Gulf Ecosystem Measurement and Modeling Division. He is currently working with colleagues in the Sustainable and Healthy Communities Program to develop an index of community resilience to natural hazards, an index of human well-being that can be linked to changes in the ecosystem, social and economic services, and a community sustainability tool for communities with populations under 40,000. He leads research efforts for indicator and indices development. Dr. Summers is a systems ecologist and began his career at the EPA in 1989 and has worked in various programs and capacities. This includes leading the National Coastal Assessment in collaboration with the Office of Water which culminated in the award-winning National Coastal Condition Report series (four volumes between 2001 and 2012), and which integrates water quality, sediment quality, habitat, and biological data to assess the ecosystem condition of the United States estuaries. He was acting National Program Director for Ecology for the EPA between 2004 and 2006. He has authored approximately 150 peer-reviewed journal articles, book chapters, and reports and has received many awards for technical accomplishments from the EPA and from outside of the agency. Dr. Summers holds a BA in Zoology and Psychology, an MA in Ecology, and Ph.D. in Systems Ecology/Biology.",institutionString:null,institution:{name:"Environmental Protection Agency",institutionURL:null,country:{name:"United States of America"}}},subseries:[{id:"38",title:"Pollution",keywords:"Human activity, Pollutants, Reduced risks, Population growth, Waste disposal, Remediation, Clean environment",scope:"
\r\n\tPollution is caused by a wide variety of human activities and occurs in diverse forms, for example biological, chemical, et cetera. In recent years, significant efforts have been made to ensure that the environment is clean, that rigorous rules are implemented, and old laws are updated to reduce the risks towards humans and ecosystems. However, rapid industrialization and the need for more cultivable sources or habitable lands, for an increasing population, as well as fewer alternatives for waste disposal, make the pollution control tasks more challenging. Therefore, this topic will focus on assessing and managing environmental pollution. It will cover various subjects, including risk assessment due to the pollution of ecosystems, transport and fate of pollutants, restoration or remediation of polluted matrices, and efforts towards sustainable solutions to minimize environmental pollution.
",annualVolume:11966,isOpenForSubmission:!0,coverUrl:"https://cdn.intechopen.com/series_topics/covers/38.jpg",editor:{id:"110740",title:"Dr.",name:"Ismail M.M.",middleName:null,surname:"Rahman",fullName:"Ismail M.M. Rahman",profilePictureURL:"https://mts.intechopen.com/storage/users/110740/images/2319_n.jpg",institutionString:null,institution:{name:"Fukushima University",institutionURL:null,country:{name:"Japan"}}},editorTwo:{id:"201020",title:"Dr.",name:"Zinnat Ara",middleName:null,surname:"Begum",fullName:"Zinnat Ara Begum",profilePictureURL:"https://mts.intechopen.com/storage/users/201020/images/system/201020.jpeg",institutionString:null,institution:{name:"Fukushima University",institutionURL:null,country:{name:"Japan"}}},editorThree:null,editorialBoard:[{id:"252368",title:"Dr.",name:"Meng-Chuan",middleName:null,surname:"Ong",fullName:"Meng-Chuan Ong",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bRVotQAG/Profile_Picture_2022-05-20T12:04:28.jpg",institutionString:null,institution:{name:"Universiti Malaysia Terengganu",institutionURL:null,country:{name:"Malaysia"}}},{id:"63465",title:"Prof.",name:"Mohamed Nageeb",middleName:null,surname:"Rashed",fullName:"Mohamed Nageeb Rashed",profilePictureURL:"https://mts.intechopen.com/storage/users/63465/images/system/63465.gif",institutionString:null,institution:{name:"Aswan University",institutionURL:null,country:{name:"Egypt"}}},{id:"187907",title:"Dr.",name:"Olga",middleName:null,surname:"Anne",fullName:"Olga Anne",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bSBE5QAO/Profile_Picture_2022-04-07T09:42:13.png",institutionString:null,institution:{name:"Klaipeda State University of Applied Sciences",institutionURL:null,country:{name:"Lithuania"}}}]},{id:"39",title:"Environmental Resilience and Management",keywords:"Anthropic effects, Overexploitation, Biodiversity loss, Degradation, Inadequate Management, SDGs adequate practices",scope:"
\r\n\tThe environment is subject to severe anthropic effects. Among them are those associated with pollution, resource extraction and overexploitation, loss of biodiversity, soil degradation, disorderly land occupation and planning, and many others. These anthropic effects could potentially be caused by any inadequate management of the environment. However, ecosystems have a resilience that makes them react to disturbances which mitigate the negative effects. It is critical to understand how ecosystems, natural and anthropized, including urban environments, respond to actions that have a negative influence and how they are managed. It is also important to establish when the limits marked by the resilience and the breaking point are achieved and when no return is possible. The main focus for the chapters is to cover the subjects such as understanding how the environment resilience works, the mechanisms involved, and how to manage them in order to improve our interactions with the environment and promote the use of adequate management practices such as those outlined in the United Nations’ Sustainable Development Goals.
",annualVolume:11967,isOpenForSubmission:!0,coverUrl:"https://cdn.intechopen.com/series_topics/covers/39.jpg",editor:{id:"137040",title:"Prof.",name:"Jose",middleName:null,surname:"Navarro-Pedreño",fullName:"Jose Navarro-Pedreño",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bRAXrQAO/Profile_Picture_2022-03-09T15:50:19.jpg",institutionString:"Miguel Hernández University of Elche, Spain",institution:null},editorTwo:null,editorThree:null,editorialBoard:[{id:"177015",title:"Prof.",name:"Elke Jurandy",middleName:null,surname:"Bran Nogueira Cardoso",fullName:"Elke Jurandy Bran Nogueira Cardoso",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bRGxzQAG/Profile_Picture_2022-03-25T08:32:33.jpg",institutionString:"Universidade de São Paulo, Brazil",institution:null},{id:"211260",title:"Dr.",name:"Sandra",middleName:null,surname:"Ricart",fullName:"Sandra Ricart",profilePictureURL:"https://mts.intechopen.com/storage/users/211260/images/system/211260.jpeg",institutionString:null,institution:{name:"University of Alicante",institutionURL:null,country:{name:"Spain"}}}]},{id:"40",title:"Ecosystems and Biodiversity",keywords:"Ecosystems, Biodiversity, Fauna, Taxonomy, Invasive species, Destruction of habitats, Overexploitation of natural resources, Pollution, Global warming, Conservation of natural spaces, Bioremediation",scope:"
\r\n\tIn general, the harsher the environmental conditions in an ecosystem, the lower the biodiversity. Changes in the environment caused by human activity accelerate the impoverishment of biodiversity.
\r\n
\r\n\tBiodiversity refers to “the variability of living organisms from any source, including terrestrial, marine and other aquatic ecosystems and the ecological complexes of which they are part; it includes diversity within each species, between species, and that of ecosystems”.
\r\n
\r\n\tBiodiversity provides food security and constitutes a gene pool for biotechnology, especially in the field of agriculture and medicine, and promotes the development of ecotourism.
\r\n
\r\n\tCurrently, biologists admit that we are witnessing the first phases of the seventh mass extinction caused by human intervention. It is estimated that the current rate of extinction is between a hundred and a thousand times faster than it was when man first appeared. The disappearance of species is caused not only by an accelerated rate of extinction, but also by a decrease in the rate of emergence of new species as human activities degrade the natural environment. The conservation of biological diversity is "a common concern of humanity" and an integral part of the development process. Its objectives are “the conservation of biological diversity, the sustainable use of its components, and the fair and equitable sharing of the benefits resulting from the use of genetic resources”.
\r\n
\r\n\tThe following are the main causes of biodiversity loss:
\r\n
\r\n\t• The destruction of natural habitats to expand urban and agricultural areas and to obtain timber, minerals and other natural resources.
\r\n
\r\n\t• The introduction of alien species into a habitat, whether intentionally or unintentionally which has an impact on the fauna and flora of the area, and as a result, they are reduced or become extinct.
\r\n
\r\n\t• Pollution from industrial and agricultural products, which devastate the fauna and flora, especially those in fresh water.
\r\n
\r\n\t• Global warming, which is seen as a threat to biological diversity, and will become increasingly important in the future.
",annualVolume:11968,isOpenForSubmission:!0,coverUrl:"https://cdn.intechopen.com/series_topics/covers/40.jpg",editor:{id:"209149",title:"Prof.",name:"Salustiano",middleName:null,surname:"Mato",fullName:"Salustiano Mato",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bRLREQA4/Profile_Picture_2022-03-31T10:23:50.png",institutionString:null,institution:{name:"University of Vigo",institutionURL:null,country:{name:"Spain"}}},editorTwo:{id:"60498",title:"Prof.",name:"Josefina",middleName:null,surname:"Garrido",fullName:"Josefina Garrido",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bRj1VQAS/Profile_Picture_2022-03-31T10:06:51.jpg",institutionString:null,institution:{name:"University of Vigo",institutionURL:null,country:{name:"Spain"}}},editorThree:{id:"464288",title:"Dr.",name:"Francisco",middleName:null,surname:"Ramil",fullName:"Francisco Ramil",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0033Y00003RI7lHQAT/Profile_Picture_2022-03-31T10:15:35.png",institutionString:null,institution:{name:"University of Vigo",institutionURL:null,country:{name:"Spain"}}},editorialBoard:[{id:"220987",title:"Dr.",name:"António",middleName:"Onofre",surname:"Soares",fullName:"António Soares",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bRNtzQAG/Profile_Picture_1644499672340",institutionString:null,institution:{name:"University of the Azores",institutionURL:null,country:{name:"Portugal"}}}]},{id:"41",title:"Water Science",keywords:"Water, Water resources, Freshwater, Hydrological processes, Utilization, Protection",scope:"
\r\n\tWater is not only a crucial substance needed for biological life on Earth, but it is also a basic requirement for the existence and development of the human society. Owing to the importance of water to life on Earth, early researchers conducted numerous studies and analyses on the liquid form of water from the perspectives of chemistry, physics, earth science, and biology, and concluded that Earth is a "water polo". Water covers approximately 71% of Earth's surface. However, 97.2% of this water is seawater, 21.5% is icebergs and glaciers, and only 0.65% is freshwater that can be used directly by humans. As a result, the amount of water reserves available for human consumption is limited. The development, utilization, and protection of freshwater resources has become the focus of water science research for the continued improvement of human livelihoods and society.
\r\n
\r\n\tWater exists as solid, liquid, and gas within Earth’s atmosphere, lithosphere, and biosphere. Liquid water is used for a variety of purposes besides drinking, including power generation, ecology, landscaping, and shipping. Because water is involved in various environmental hydrological processes as well as numerous aspects of the economy and human society, the study of various phenomena in the hydrosphere, the laws governing their occurrence and development, the relationship between the hydrosphere and other spheres of Earth, and the relationship between water and social development, are all part of water science. Knowledge systems for water science are improving continuously. Water science has become a specialized field concerned with the identification of its physical, chemical, and biological properties. In addition, it reveals the laws of water distribution, movement, and circulation, and proposes methods and tools for water development, utilization, planning, management, and protection. Currently, the field of water science covers research related to topics such as hydrology, water resources and water environment. It also includes research on water related issues such as safety, engineering, economy, law, culture, information, and education.
",annualVolume:11969,isOpenForSubmission:!0,coverUrl:"https://cdn.intechopen.com/series_topics/covers/41.jpg",editor:{id:"349630",title:"Dr.",name:"Yizi",middleName:null,surname:"Shang",fullName:"Yizi Shang",profilePictureURL:"https://mts.intechopen.com/storage/users/349630/images/system/349630.jpg",institutionString:"China Institute of Water Resources and Hydropower Research",institution:{name:"China Institute of Water Resources and Hydropower Research",institutionURL:null,country:{name:"China"}}},editorTwo:null,editorThree:null,editorialBoard:[{id:"216491",title:"Dr.",name:"Charalampos",middleName:null,surname:"Skoulikaris",fullName:"Charalampos Skoulikaris",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bRMsbQAG/Profile_Picture_2022-04-21T09:31:55.jpg",institutionString:null,institution:{name:"Aristotle University of Thessaloniki",institutionURL:null,country:{name:"Greece"}}},{id:"300124",title:"Prof.",name:"Thomas",middleName:null,surname:"Shahady",fullName:"Thomas Shahady",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002kuIgmQAE/Profile_Picture_2022-03-18T07:32:10.jpg",institutionString:null,institution:{name:"Lynchburg College",institutionURL:null,country:{name:"United States of America"}}}]}]}},libraryRecommendation:{success:null,errors:{},institutions:[]},route:{name:"chapter.detail",path:"/chapters/35229",hash:"",query:{},params:{id:"35229"},fullPath:"/chapters/35229",meta:{},from:{name:null,path:"/",hash:"",query:{},params:{},fullPath:"/",meta:{}}}},function(){var e;(e=document.currentScript||document.scripts[document.scripts.length-1]).parentNode.removeChild(e)}()