**Complex Bianisotropy E**ff**ect on the Propagation Constant of a Shielded Multilayered Coplanar Waveguide Using Improved Full Generalized Exponential Matrix Technique**

**Djamel Sayad 1, Chemseddine Zebiri 2,3, Issa Elfergani 4,\*, Jonathan Rodriguez 5, Hasan Abobaker 6, Atta Ullah 3, Raed Abd-Alhameed 3, Ifiok Otung 5 and Fatiha Benabdelaziz 7**

Received: 23 December 2019; Accepted: 28 January 2020; Published: 2 February 2020

**Abstract:** A theoretical study of the electromagnetic propagation in a complex medium suspended multilayer coplanar waveguide (CPW) is presented. The study is based on the generalized exponential matrix technique (GEMT) combined with Galerkin's spectral method of moments applied to a CPW printed on a bianisotropic medium. The analytical formulation is based on a Full-GEMT, a method that avoids usual procedures of heavy and tedious mathematical expressions in the development of calculations and uses matrix-based mathematical expressions instead. These particularities are exploited to develop a mathematical model for the characterization of wave propagation in a three-layer shielded suspended CPW structure. This study is based on the development of mathematical formulations in full compact matrix-based expressions resulting in Green's functions in a matrix form. The implemented method incorporates a new accelerating procedure developed in the GEMT which provides an initial value used to speed up searching for the exact solution in the principal computation code. This helped us to obtain accurate solutions with tolerable computing time. Good agreements have been achieved with the literature in terms of accuracy and rapid convergence. The results for different cases of bianisotropy have been investigated, and particularly, the effect on the dispersion characteristics is presented and compared with the isotropic case.

**Keywords:** chiral; Tellegen; multilayer CPW structure; dispersion characteristics; full-GEMT; Muller's method; complex propagation constant; acceleration procedure

#### **1. Introduction**

To establish strong foundations for the development of modern and mass-market applications in the field of telecommunications, microwave designers have to develop further efficient devices, which aim to meet the specific needs of modern telecommunication systems, particularly the 5G

technology. In addition to providing far better levels of reliability and performances by offering new services, the new technology should be fully consistent with traditional services including 2G, 3G, 4G, Wi-Fi, and other relevant wireless systems, which requires suitable and high performance microwave devices in terms of miniaturization and ultra-wideband characteristics that are proven to be the most challenging issues of all time.

An important class of existing microwave devices is that exploiting the particular properties of bianisotropic media [1] for the development of special and innovative devices that may respond to the needs of modern technologies [2]. In this class of promising materials, we may mention, for example, non-reciprocal, gyrotropic, ferrites, chirals, metamaterials, metasurfaces, etc. [1,3]. Over the last three decades, the electromagnetism of bianisotropic media have gained a great deal of interest from scientists and researchers within the frame of artificial media with new and exciting properties [4]. However, practical exploitation of these phenomena did not develop on a large scale; many physics and engineering problems needed to be solved. Recently, as the science of materials has tremendously advanced, the concept of bianisotropic media has substantially reemerged as a field of importance in microwaves and optics technology [5–7].

The particular properties of bianisotropic media arise from a coupling between the electric and magnetic fields that can be explicitly described by general constitutive relations. Due to their diversity, they have found many potential applications from microwaves to optical frequencies such as polarization transformers, directional couplers, antenna and transmission line substrates, antenna radomes, radar systems, chiral waveguides and others [8–13].

The electromagnetic properties of bianisotropic media should be analyzed to perceive their exotic characteristics. Several studies have been conducted to characterize the electromagnetic behavior of bianisotropic media [14–18], ferrites [19], metamaterials [20], chiral [21,22], nonreciprocal [23] for simple and complex dielectric based microwave planar structures using numerical and analytical methods [8,14,17,20,24–35]. In [8] and [35], the method of lines is used to analyze planar transmission lines with conductor losses and to analyze integrated optical waveguide structures, respectively. In [17] and [20], the transmission line matrix (TLM) method is used for modeling dispersive chiral media and the analysis of dispersion in metamaterials. In [25], a fast computation of planar microstrip lines using the generalized equivalent circuit method of moments is presented. The finite difference technique and the iterated moment method are utilized for the analysis of dielectric [33] and optical waveguides [34]. In [27], a complex image method based on genetic algorithm (GA) is proposed to calculate the Green's functions of a coplanar waveguide structure. Anisotropic based multilayers, microstrip and waveguide structures are treated in [28,29,31,32]. Recently, in [14] and [24], Karma et al. studied microstrip transmission lines with anisotropic and uniaxial anisotropic substrates using the discrete mode matching method.

To extract the effective constitutive parameters of bianisotropic materials, various techniques such as stepwise method, S-parameters method, resonator method, coaxial probe method, free-space characterization method, rectangular waveguide measurements and recursive algorithms have been employed [36–39].

By knowing the intrinsic physical properties of complex media, designers can predict the response of microwave components for the development of inventive devices. However, the complexity of mathematical modeling of bianisotropic media is a real challenge in the characterization of microwave components. This has recently become a central area of research in microwaves and optics.

This paper introduces a mathematical modeling of complex media characterized by full 3 × 3 bianisotropic tensors of permittivity, permeability and magneto-electric parameters. The objective of this work is to sufficiently develop predictive mathematical models to judiciously characterize the propagation of electromagnetic waves in a suspended shielded bianisotropic three-layer CPW structure using a Full-GEM technique [28,40,41]. Three primary considerations have been exploited to accomplish new and promising results. These include: the consideration of the most general reciprocal and non-reciprocal chiral and achiral (Tellegen) complex media using the Full-GEMT, estimation of the

effective permittivity constant to be used as an initial value to search for the exact solution, and the use of Muller's method for the extraction of the complex solution of the associated propagation constant in both chiral and achiral media.

The efficient spectral Galerkin-based method of moments (SGMoM) is extensively used to analyze microwave planar structures [18,22,25,27,29,30,41–48]. In our recent work [42], we presented an analytical modeling of a shielded microstrip line based on an anisotropic medium with full 3 × 3 permittivity and permeability tensors. To reduce calculations, some conditions on the permittivity and permeability constants were considered ensuring the decoupling of the TE and TM modes. On the other hand, the computational time drastically increases with the required accuracy because of the slow convergence of integrals and series summations making this approach time intensive [43]. For accelerated convergence and efficient computation, several techniques have been used [44–47]. The time intensive part in the SGMoM is the evaluation of the matrix elements and the determinant calculation, as the matrix size is large in most cases. In [48], the SGMoM calculation of the propagation constant (β) for a shielded microstrip line is accelerated using asymptotic expansions for the Bessel's and the Green's functions with the aid of super convergent series in the approximation of the summation of the leading terms. In [49], for the multilayered shielded microstrip analysis, series summation calculation are accelerated using the Levin's transformation in the spectral method. In [28], the Green's function-based volume integral equation computation is accelerated using the fast Fourier transform technique. In [44,45], the impedance matrix elements based on Sommerfeld-type infinite double integral Green functions evaluation is accelerated by converting the infinite double integral of the impedance-matrix elements into a finite one-dimensional integral by using the asymptotic Green's functions and triangular basis functions with edge condition. In [47], integral-equation formulation in the SGMoM is accelerated by extracting suitable half-space parts of the kernels which leads to an exponentially decaying integrand functions. The integrals of the extracted parts are expressed as combinations of proper integrals and fast converging improper integrals. In [50], an efficient quasi-static analysis is presented, which can be used for speeding up full-wave SGMoM computations as well. Accelerated versions of full-wave spectral domain approach are also reported in [51–54].

In this paper, we propose a novel approach for the numerical acceleration of the SGMoM for the analysis of bianisotropic medium-based microstrip structures by accelerating and fixing problems of the convergence of the series summation in the elements of the Galerkin's matrix based on Green's functions.

The herein considered complex medium is bianisotropic with non-zero magneto-electric tensors (ξ - 0 and η - 0 at the same time). Our previous study, presented in [41], did not treat the case of bianisotropic media with both magneto-electric tensors; only one tensor was considered non zero. The relative simplicity of this case of medium does not require a more complex resolution technique or longer calculation time. Note that this technique failed to provide accurate solutions for general complex bianisotropic media due to the round-off errors and the highly oscillatory fields behavior. A new procedure is implemented to improve the technique and expand it to support the general case of bianisotropy for a CPW structure. Due to the complexity of the considered bianisotropic medium, the resolution method has required a more efficient technique to overcome the drawbacks in terms of non-convergence or considerable calculation time for a tolerable accuracy. An improvement is achieved by introducing an intermediate calculation procedure based on the GEMT to retrieve an approximated initial value of the relative effective permittivity of the three layer-structure as a function of ε*r*, μ*r*, ξ and η: the bianisotropic layer constitutive parameters. This value is used for searching for the exact solutions of the normalized complex constant of propagation ((β/κ0) 2 and (α/κ0) 2).

#### **2. Exponential Matrix Technique Formulation**

The general CPW geometry and the appropriate coordinate system with the z-axis as the direction of propagation are shown in Figure 1. The considered structure is based on a complex bianisotropic medium (region 1) characterized by full 3 × 3-magneto-electric tensors expressing the cross coupling between electric and magnetic fields.

**Figure 1.** Geometry of the shielded suspended 3-layer CPW structure.

Bianisotropic materials, in their general form, are characterized by the following constitutive relations [30,41,45].

$$\begin{array}{lcl}\overrightarrow{D} &=& \varepsilon \omicron [\varepsilon] \overrightarrow{E} + \sqrt{\varepsilon \omicron \mu\_0} [\xi] \overrightarrow{H} \\ \xrightarrow{\longrightarrow} & \mu\_0 [\mu] \overrightarrow{H} + \sqrt{\varepsilon \underline{\mu\_0}} [\eta] \overrightarrow{E} \end{array} \tag{1}$$

The tensors of the relative permittivity [ε], relative permeability [μ] and magneto-electric elements [ξ] and [η] are represented in the Cartesian coordinate system as follows:

$$
\begin{array}{rcl}
\psi &=& \begin{bmatrix}
\psi\_{xx} & \psi\_{xy} & \psi\_{xz} \\
\psi\_{yx} & \psi\_{yy} & \psi\_{yz} \\
\psi\_{zx} & \psi\_{zy} & \psi\_{zz}
\end{bmatrix}
\end{array}
\tag{2}
$$

where ψ stands for [ε], [μ], [ξ], or [η].

Starting from Maxwell's equations and using the GEMT in the spectral domain, we come to four coupled first-order differential equations for the transverse electromagnetic field components as functions of their derivatives [40,41] given in the Fourier domain:

$$\frac{\partial \left[ \widetilde{f}^{(i)}(a,\beta,z) \right]}{\partial z} = \left[ P^{(i)} \right]\_{4 \times 4} \left[ \widetilde{f}^{(i)}(a,\beta,z) \right]\_{\prime} \tag{3}$$

α and β are the Fourier variables corresponding to the space domain wavenumbers κ*x* and κ*y*, with

$$\begin{bmatrix} \overleftarrow{f}^{(i)}(\alpha,\beta,z) \end{bmatrix} = \begin{bmatrix} \overleftarrow{E}\_{\text{x}}^{(i)}(\alpha,\beta,z) \\ \overleftarrow{E}\_{\text{y}}^{(i)}(\alpha,\beta,z) \\ \overleftarrow{H}\_{\text{x}}^{(i)}(\alpha,\beta,z) \\ \overleftarrow{H}\_{\text{y}}^{(i)}(\alpha,\beta,z) \end{bmatrix}' \tag{4}$$

and

$$\left[ \left[ P \right]\_{4 \times 4} = \; \not\text{\&} \left\{ \left[ \mathbf{M} \right] + \left[ \mathbf{N} \right] \left[ \mathbf{Q} \right] \left[ \mathbf{R} \right] \right\} \right] \tag{5}$$

where

$$\begin{aligned} \text{[M]} \quad = \begin{bmatrix} -\eta\_{yx} & -\eta\_{yy} & -\eta\_{\ell}\mu\_{yx} & -\eta\_{\ell}\mu\_{yy} \\ \eta\_{xx} & \eta\_{xy} & \eta\_{\ell}\mu\_{xx} & \eta\_{\ell}\mu\_{xy} \\ \chi\_{0}\varepsilon\_{yx} & \chi\_{0}\varepsilon\_{yy} & \xi\_{yx} & \xi\_{yy} \\ -\chi\_{0}\varepsilon\_{xx} & -\chi\_{0}\varepsilon\_{xy} & -\xi\_{xx} & -\xi\_{xy} \end{bmatrix} = \begin{bmatrix} [\eta\_{T}] & \imath\_{0}[\mu\_{T}] \\ -\varchi\_{0}[\varepsilon\_{T}] & -[\xi\_{T}] \end{bmatrix} \end{aligned} \tag{6a}$$

$$\begin{array}{rcl} \text{[N]} &=& \begin{bmatrix} -\left(\eta\_{yz} + \mathbf{x}\_{x}^{n}\right) & -\eta\_{0}\mu\_{yz} \\ \left(\eta\_{xz} - \mathbf{x}\_{y}^{n}\right) & \mathbf{0}\mu\_{xz} \\ \mathbf{Y}\_{0}\varepsilon\_{yz} & \left(\underline{\boldsymbol{\zeta}}\_{yz} - \mathbf{x}\_{x}^{n}\right) \\ -\mathbf{Y}\_{0}\varepsilon\_{xz} & -\left(\underline{\boldsymbol{\zeta}}\_{xz} + \mathbf{x}\_{y}^{n}\right) \end{bmatrix} \end{array} \tag{6b}$$

$$[\mathbf{Q}] = \frac{-1}{\left(\varepsilon\_{zz}\mu\_{zz} - \underline{\zeta}\_{zz}\eta\_{zz}\right)} \begin{bmatrix} \, \_0\mu\_{zz} & \, \_{\overline{\zeta}\_{zz}} \\ \, \_0\eta\_{zz} & \, \_1\chi\_{\overline{\zeta}\_{zz}} \end{bmatrix} \tag{6c}$$

$$\begin{array}{rcl} \text{[R]} &=& \begin{bmatrix} \chi\_{0\varepsilon\_{xx}} & \chi\_{0\varepsilon\_{yz}} & \left(\xi\_{xx} - \kappa\_y^n\right) & \left(\xi\_{yz} + \kappa\_x^n\right) \\ -\left(\eta\_{xx} + \kappa\_y^n\right) & -\left(\eta\_{yz} - \kappa\_x^n\right) & -\eta\_{0\varepsilon\_{xz}} & -\eta\_{0}\mu\_{yz} \end{bmatrix} \end{array} \tag{6d}$$

$$
\kappa\_x^n = \frac{\kappa\_x}{\kappa\_0},\tag{6e}
$$

$$
\kappa\_y^n = \frac{\kappa\_y}{\kappa\_0},
\tag{6f}
$$

$$
\rho\_0 = \frac{1}{Y\_0} = \sqrt{\frac{\mu\_0}{\varepsilon\_0}},\tag{6g}
$$

with

$$
\begin{bmatrix} \eta \mathbf{r} \end{bmatrix} = \begin{bmatrix} -\eta\_{\text{yx}} & -\eta\_{\text{yy}} \\ \eta\_{\text{xx}} & \eta\_{\text{xy}} \end{bmatrix} \text{ [ $\varepsilon\text{r}$ ] } = \begin{bmatrix} -\varepsilon\_{\text{yx}} & -\varepsilon\_{\text{yy}} \\ \varepsilon\_{\text{xx}} & \varepsilon\_{\text{xy}} \end{bmatrix} \text{ [ $\xi\text{r}$ ] } = \begin{bmatrix} -\xi\_{\text{yx}} & -\xi\_{\text{yy}} \\ \xi\_{\text{xx}} & \xi\_{\text{xy}} \end{bmatrix} \text{ [ $\mu\text{r}$ ] } = \begin{bmatrix} -\mu\_{\text{yx}} & -\mu\_{\text{yy}} \\ \mu\_{\text{xx}} & \mu\_{\text{xy}} \end{bmatrix} \text{ (\"\epsilon\text{h}\") } = \begin{bmatrix} \varepsilon\_{\text{x}} & -\mu\_{\text{xy}} \\ \mu\_{\text{xx}} & \mu\_{\text{xy}} \end{bmatrix} \text{ (\"\epsilon\text{h}\") } = \begin{bmatrix} \varepsilon\_{\text{x}} & -\mu\_{\text{xy}} \\ \varepsilon\_{\text{xx}} & \mu\_{\text{xy}} \end{bmatrix} \text{ (\"\epsilon\text{h}\") } = \begin{bmatrix} \varepsilon\_{\text{x}} & -\mu\_{\text{xy}} \\ \mu\_{\text{xx}} & \mu\_{\text{xy}} \end{bmatrix} \text{ (\"\epsilon\text{h}\") } = \begin{bmatrix} \varepsilon\_{\text{x}} & -\mu\_{\text{xy}} \\ \mu\_{\text{xx}} & \mu\_{\text{xy}} \end{bmatrix} \text{ (\"\epsilon\text{h}\") } = \begin{bmatrix} \varepsilon\_{\text{x}} & -\mu\_{\text{xy}} \\ \mu\_{\text{xx}} & \mu\_{\text{xy}} \end$$

where κ0 is the free space wavenumber and ω is the angular frequency.

This study is essentially based on the development of mathematical formulations in compact matrix-based forms; this is deemed as a promising approach, since it avoids excessive and complex calculation developments. This can dramatically reduce the complexity of wave propagation modeling in complex media.

The matrix [*P*] (Equation (5)) is the first foundation for this technique associated with the studied bianisotropic-medium based CPW structure. Its elements are given as functions of the constitutive tensors elements. In previous works [30,45], for particular cases of media calculations were explicitly developed, which is not obvious with heavy mathematical calculations case that characterize the herein studied complex bianisotropic structure.

Equation (3) admits a general solution of the form:

$$
\begin{bmatrix} E\_x(z) \\ E\_y(z) \\ H\_x(z) \\ H\_y(z) \end{bmatrix} = \begin{bmatrix} T(\kappa\_x, \kappa\_y, z) \\ E\_y(0) \\ H\_x(0) \\ H\_y(0) \end{bmatrix} \tag{7}
$$

with

$$T(\kappa\_{x\_{\prime}}\kappa\_{y\_{\prime}}z) = \exp([P]\cdot z),\tag{8}$$

and

$$
\widetilde{f}^{(i)}(\alpha,\beta,z(i)) = \, \_T (\kappa\_{x\_\prime} \kappa\_{y\_\prime} z) \widetilde{f}^{(i)}(\alpha,\beta,z(i-1)) . \tag{9}
$$

The 4 × 4 transfer matrix *T* κ*x*, κ*y*; *z* is calculated in the formulation of the GEMT by means of the Cayley Hamilton theorem for the determination of the complex function roots [40]. It is expressed in the following polynomial form:

$$T(z) \ = \ a\_0[I] + a\_1[P] + a\_2[P]^2 + a\_3[P]^3,\tag{10}$$

where *aj* are scalar expansion coefficients, determined by solving the Vandermode linear algebraic system [40], and [*I*] is a 4 × 4 identity matrix. The transfer matrix is easily obtained by multiplying the different transfer matrices related to the different layers of the structure, this constitutes the main advantage of this new technique. By imposing the appropriate boundary conditions between the heterogeneous medium layers, the appropriate Green's tensor which models the CPW structure is derived. Details can be found in [41]. This technique exhibits a compact matrix form with the advantage of being easily inserted in the calculation code.

#### *2.1. Implementation of the Acceleration Procedure*

To overcome the drawbacks of the resolution method used in [41], when applied for a general complex bianisotropic medium, the resolution method has to be improved in terms of convergence and accuracy for a tolerable computing time. A new procedure is introduced in the calculation technique. This latter is based on the GEMT technique (detailed calculations can be found in [40]) used to retrieve an approximated value for the effective relative permittivity of the whole inhomogeneous structure to be used as an initial value to search for the exact solution of the propagation constant. This value is evaluated for each frequency point by extracting the eigenvalues of matrix [*P*] by resolving Equation (12) for κ*x* = 0 and κ*y* = 0. By applying this procedure, analytical expressions of the effective relative permittivity maybe obtained as functions of the constitutive parameters of the bianisotropic layer ε*r*, μ*r*, ξ and η. The application of this procedure allows the acceleration of the Matlab® [55] calculation code and provides a better solution accuracy.

The expansion coefficients *ai* (*i* = 0, 1, 2, 3) in Equation (10) are determined by solving the Vandermode linear algebraic system:

$$
\begin{bmatrix} 1 & \lambda\_0 & \lambda\_0^2 & \lambda\_0^3 \\ 1 & \lambda\_1 & \lambda\_1^2 & \lambda\_1^3 \\ 1 & \lambda\_2 & \lambda\_2^2 & \lambda\_2^3 \\ 1 & \lambda\_3 & \lambda\_3^2 & \lambda\_3^3 \end{bmatrix} \begin{bmatrix} a\_0(z) \\ a\_1(z) \\ a\_2(z) \\ a\_3(z) \end{bmatrix} = \begin{bmatrix} \exp(\lambda\_0 z) \\ \exp(\lambda\_1 z) \\ \exp(\lambda\_2 z) \\ \exp(\lambda\_3 z) \end{bmatrix} \tag{11}
$$

λ*i* (*i* = 0, 1, 2, 3): are eigenvalues of [*P*] which correspond to propagating waves [56] defined by:

$$\det(\lambda[I] - [P]) = \lambda^4 + a\mathbf{1}\lambda^3 + a\mathbf{2}\lambda^2 + a\mathbf{3}\lambda + a\mathbf{4} = \mathbf{0}.\tag{12}$$

The coefficients α*i* (*i* = 0, 1, 2, 3) are given in terms of the matrix [*P*], explicit expressions may be found in [40].

#### *2.2. Derivation of the Initial Value Expression of the E*ff*ective Relative Permittivity*

#### *a. Isotropic case*

The initial effective permittivity value expression is calculated in terms of the medium constitutive parameters ε*r*, μ*r*, ξ and η using the total transfer matrix (Equation (10)) for κ*x* = 0 and κ*y* = 0, which permits the extraction of an approximated value. As an example of calculations, we present the derived analytical expressions of the initial effective permittivity of the isotropic and some bianisotropic cases. For the isotropic case, the derived matrix [*P*] is given by:

$$\begin{aligned} \mathbf{[}P\] &= \begin{bmatrix} 0 & 0 & 0 & -\mu\_r Z\_0 \kappa\_0 \\ 0 & 0 & \mu\_r Z\_0 \kappa\_0 & 0 \\ 0 & \varepsilon\_r \kappa\_0 / Z\_0 & 0 & 0 \\ -\varepsilon\_r \kappa\_0 / Z\_0 & 0 & 0 & 0 \end{bmatrix} . \end{aligned} \tag{13a}$$

In this case, the normalized eigenvalues of matrix [*P*], with respect to κ0, are:

$$
\lambda\_{n0} = \sqrt{\varepsilon\_l \mu\_r}, \; \lambda\_{n1} = -\sqrt{\varepsilon\_l \mu\_r}, \; \lambda\_{n2} = \; \sqrt{\varepsilon\_l \mu\_r} \text{ and } \lambda\_{n3} = -\sqrt{\varepsilon\_l \mu\_r}; \tag{13b}
$$

functions of the relative permittivity and permeability of the isotropic medium. For the fundamental propagating mode, the numerical maximal value is taken as the initial value.

$$
\varepsilon\_{ref0} = \lambda\_{n0}^2 = \varepsilon\_r \mu\_r \tag{13c}
$$

#### *b. Uniaxial anisotropic case*

*Electronics* **2020**, *9*, 243

In this example, we consider the following special case of biaxial anisotropy

$$\begin{aligned} \begin{bmatrix} \varepsilon \end{bmatrix} &= \begin{bmatrix} \varepsilon\_x & 0 & 0\\ 0 & \varepsilon\_y & 0\\ 0 & 0 & \varepsilon\_z \end{bmatrix} \begin{bmatrix} \mu \end{bmatrix} = \begin{bmatrix} \mu\_x & 0 & 0\\ 0 & \mu\_y & 0\\ 0 & 0 & \mu\_z \end{bmatrix} \begin{bmatrix} \xi \end{bmatrix} = \begin{array}{c} 0, \ [\eta] \end{array} = \begin{array}{c} \tag{14a} \end{array} \tag{14a} \end{aligned} \tag{14b}$$

the derived matrix [*P*] is:

$$
\begin{bmatrix}
[P\] \ &= \begin{bmatrix}
0 & 0 & 0 & -\mu\_y Z\_0 \kappa\_0 \\
0 & 0 & \mu\_x Z\_0 \kappa\_0 & 0 \\
0 & \varepsilon\_y \kappa\_0 / Z\_0 & 0 & 0 \\
\end{bmatrix}
\tag{14b}
$$

where the four normalized eigenvalues are found to be

$$\begin{array}{rcl}\lambda\_{n0} &=& \sqrt{\frac{\mu\_{\pi}}{\mu\_{\pi}} \{\varepsilon\_{y}\mu\_{z} - 1\}} \; \lambda\_{n1} =& -\sqrt{\frac{\mu\_{\pi}}{\mu\_{\pi}} \{\varepsilon\_{y}\mu\_{z} - 1\}}\\\lambda\_{n2} &=& \sqrt{\frac{\varepsilon\_{z}}{\varepsilon\_{z}} \{\varepsilon\_{z}\mu\_{y} - 1\}} \; \lambda\_{n3} =& -\sqrt{\frac{\varepsilon\_{z}}{\varepsilon\_{z}} \{\varepsilon\_{z}\mu\_{y} - 1\}} \end{array} \tag{14c}$$

and

$$\varepsilon\_{\rm rff}|\_{0} = \max \{ \lambda\_{\rm ni}^{2} \} = \max \left( \sqrt{\frac{\mu\_{\rm x}}{\mu\_{z}} (\varepsilon\_{\rm y} \mu\_{z} - 1)}, \sqrt{\frac{\varepsilon\_{\rm x}}{\varepsilon\_{z}} (\varepsilon\_{z} \mu\_{\rm y} - 1)} \right) \tag{14d}$$

*c. Diagonal bianisotropy case*

As an example, we take the following case:

$$\begin{aligned} \left[\boldsymbol{\varepsilon}\right] &= \left. \varepsilon\_{\mathrm{I}} \left[\boldsymbol{l}\right], \left[\boldsymbol{\mu}\right] = \left. \mu\_{\mathrm{I}} \left[\boldsymbol{l}\right], \left[\boldsymbol{\xi}\right] \right] = \left[\begin{array}{ccc} \boldsymbol{\xi}\_{\mathrm{xx}} & 0 & 0\\ 0 & 0 & 0\\ 0 & 0 & 0 \end{array}\right], \left[\boldsymbol{\eta}\right] &= \left[\begin{array}{ccc} \eta\_{\mathrm{xx}} & 0 & 0\\ 0 & 0 & 0\\ 0 & 0 & 0 \end{array}\right]. \end{aligned} \tag{15a}$$

where [*I*] is a 3 × 3 identity matrix. The derived [*P*] is:

$$\begin{bmatrix} \left[P\right] \end{bmatrix} = \begin{bmatrix} 0 & 0 & 0 & -\mu\_r \mathbf{Z}\_0 \mathbf{x}\_0 \\ \eta\_{\text{xx}} \kappa\_0 & 0 & \mu\_r \mathbf{Z}\_0 \kappa\_0 & 0 \\ 0 & \varepsilon\_r \kappa\_0 / Z\_0 & 0 & 0 \\ -\varepsilon\_r \kappa\_0 / Z\_0 & 0 & -\xi\_{\text{xx}} \kappa\_0 & 0 \end{bmatrix},\tag{15b}$$

and the four normalized eigenvalues of [*P*] are:

$$\begin{array}{rcl}\lambda\_{n0} &=& \sqrt{\varepsilon\_r \mu\_r + \sqrt{\varepsilon\_r \mu\_r \xi\_{\text{xx}} \eta\_{\text{xx}}}} \\ \lambda\_{n2} &=& \sqrt{\varepsilon\_r \mu\_r - \sqrt{\varepsilon\_r \mu\_r \xi\_{\text{xx}} \eta\_{\text{xx}}}} \\ \end{array} \\ \lambda\_{n1} &=& -\sqrt{\varepsilon\_r \mu\_r + \sqrt{\varepsilon\_r \mu\_r \xi\_{\text{xx}} \eta\_{\text{xx}}}} \\ \lambda\_{n3} &=& -\sqrt{\varepsilon\_r \mu\_r - \sqrt{\varepsilon\_r \mu\_r \xi\_{\text{xx}} \eta\_{\text{xx}}}} \\ \end{pmatrix} \tag{15c}$$

The initial value depends on the constitutive parameters ε*r*, μ*r*, ξ*xx* and η*xx*.

$$
\varepsilon\_{\pi f f 0} = \max \{ \lambda\_{\text{ri}}^2 \} = \varepsilon\_r \mu\_r + \sqrt{\varepsilon\_r \mu\_r \xi\_{\text{xx}} \eta\_{\text{xx}}} \tag{15d}
$$

#### *d. Gyrotropic bianisotropy case*

Considering the following medium case:

$$\begin{aligned} \left[ \begin{smallmatrix} \varepsilon \end{smallmatrix} \right] &= \left. \varepsilon\_{\mathbb{I}} [\mathrm{I}] , \ [\mu] = \mu\_{\mathbb{I}} [\mathrm{I}] , \ [\xi] &= \left[ \begin{array}{ccc} 0 & 0 & \xi\_{\mathrm{xz}} \\ 0 & 0 & 0 \\ \xi\_{\mathrm{xz}} & 0 & 0 \end{array} \right] , \ [\eta] &= \left[ \begin{array}{ccc} 0 & 0 & \eta\_{\mathrm{xz}} \\ 0 & 0 & 0 \\ \eta\_{\mathrm{xz}} & 0 & 0 \end{array} \right] . \end{aligned} \tag{16a}$$

The derived corresponding [*P*] is:

$$\begin{array}{c} \begin{bmatrix} \begin{array}{cc} 0 & 0 & 0 & -\mu\_{r}Z\_{0}\kappa\_{0} \\ 0 & 0 & -\frac{\kappa\_{l}\overline{\upsilon}\_{\mathsf{x}}}{\varepsilon\_{r}}(\varepsilon\_{r}\mu\_{r}-\xi\_{zz}\eta\_{zz}) & 0 \\ 0 & \varepsilon\_{r}\kappa\_{0}/Z\_{0} & 0 & 0 \\ -\frac{\kappa\_{0}}{\mu\_{r}Z\_{0}}(\varepsilon\_{r}\mu\_{r}-\xi\_{zz}\eta\_{zz}) & 0 & 0 \end{array} \end{array} \end{array} \tag{16b}$$

which gives as solutions:

$$\begin{array}{rcl}\lambda\_{n0} &=& \sqrt{\varepsilon\_r \mu\_r - \underline{\xi}\_{zx} \eta\_{zx}} & \lambda\_{n1} &=& -\sqrt{\varepsilon\_r \mu\_r - \underline{\xi}\_{zx} \eta\_{zx}} \\ \lambda\_{n2} &=& \sqrt{\varepsilon\_r \mu\_r - \underline{\xi}\_{zx} \eta\_{zx}} & \lambda\_{n3} &=& -\sqrt{\varepsilon\_r \mu\_r - \underline{\xi}\_{zx} \eta\_{zx}} \end{array} \tag{16c}$$

and

$$\varepsilon\_{nff0} = \max \{ \lambda\_{ni}^2 \} = \max \{ \varepsilon\_I \mu\_{\varGamma} - \underline{\zeta}\_{\mathfrak{X}\mathfrak{X}} \eta\_{\varXi \urcorner \mathfrak{x} \urcorner} \varepsilon\_I \mu\_{\varGamma} - \underline{\zeta}\_{\mathfrak{X}\mathfrak{X}} \eta\_{\varXi \urcorner} \}. \tag{16d}$$

It is medium-case dependent.

Notice that if ξ*xz*, ξ*zx*, η*xz* and η*zx* are taken so that ξ*xz*η*zx* ξ*zx*η*xz*, two different solutions are obtained corresponding to bifurcating modes [21]. This may constitute an independent issue, which is outside the scope of this work. This shows the efficiency of the procedure, without which, the calculation code would diverge to adjacent solutions or give spurious ones [57], since the electromagnetic fields of bianisotropic media are highly oscillatory [56]. The result presented by Equation (15d) shows that the use of this approach has not only made it feasible to get the optimal initial value, in some cases, but also to more accurately infer the appropriate approximation, mainly in the presence of the bifurcating modes phenomenon, in which two neighboring modes are excited.

In order to show the benefits of using the new procedure, two examples of the studied cases of bianisotropy are considered. Case1: ξ*zx*,1 = ξ*xz*,1 = −0.75 √ε*r*, η*zx*,1 = −ξ*xz*,1 and η*zx*,1 = η*xz*,1, and Case2: η*xz*,8 = −ξ*xz*,8 = −*j* √ε*r*, ξ*zx*,8 = −ξ*xz*,8 and η*zx*,8 = η*xz*,8. By the introduction of the new procedure, the computing time for Case1, for a frequency point, is reduced by about 33% from 1.937 s to 1.302 s. In Case2, with the aid of the procedure, we get a solution in 1.442 s while without the procedure, the technique failed to find a solution and gave a spurious value instead, after a long execution time. This is due to the oscillating behavior of the series summations of the manipulated complex Galerkin's matrix.

#### **3. Method of Solution**

By applying the boundary conditions, the expressions of the electric and magnetic tangential components are evaluated at the interface air-dielectric in terms of the tangential current densities on the strips *jx* and *jy*. A matrix of the Green's tensor elements *Gij*(α*n*, β) for the CPW structure is achieved. It is arranged in the following system of equations

$$
\begin{bmatrix}
\overline{\dot{j}\_x} \\
\overline{\dot{j}\_y}
\end{bmatrix} = \frac{1}{\Delta\_\mathcal{G}} \begin{bmatrix}
\text{G}\_{22}(\boldsymbol{a}\_{\boldsymbol{n}}\boldsymbol{\beta}) & -\text{G}\_{12}(\boldsymbol{a}\_{\boldsymbol{n}}\boldsymbol{\beta}) \\
\end{bmatrix} \begin{bmatrix}
\overline{\mathcal{E}}\_x \\
\overline{\mathcal{E}}\_y
\end{bmatrix} \tag{17a}
$$

with

$$
\Delta\_{\mathbb{G}} = \mathcal{G}\_{11}\mathcal{G}\_{22} - \mathcal{G}\_{12}\mathcal{G}\_{21}.\tag{17b}
$$

and α*n*: the discrete Fourier transform variable with *n* the Fourier number of terms *n* = 1, 2, 3, ... , *N*.

For the resolution of the problem, the SGMoM is applied, the spectral electric field components are expanded in terms of trigonometric basis function sets [58,59]. A homogeneous system of linear equations arranged in a compact matrix form is derived [58]:

$$\begin{bmatrix} \begin{bmatrix} M(\beta) \end{bmatrix} \begin{bmatrix} a\_1 \ a\_2 \ \dots \ a\_M \ b\_1 \ b\_2 \ \dots \ b\_N \end{bmatrix}^T = \begin{bmatrix} 0 \end{bmatrix},\tag{18}$$

*Electronics* **2020**, *9*, 243

where

$$[\mathcal{M}(\beta)]\;=\begin{bmatrix}\mathcal{M}^{1,1}\_{q',p}\;\mathcal{M}^{1,2}\_{q',q}\\\mathcal{M}^{2,1}\_{p',p}\;\mathcal{M}^{1,1}\_{p',q}\end{bmatrix}\;\tag{19}$$

and

$$M\_{q'p}^{1,1}(\beta) = \sum\_{n} \frac{1}{\Delta\_{\mathcal{G}}} G\_{22}(\alpha\_{n'}\beta) \,\, \widetilde{l\_{x,p}} \,\widetilde{l\_{y,q'}^{\*}} \,\, \tag{20a}$$

$$M\_{q',q}^{1,2}(\beta) = -\sum\_{n} \frac{1}{\Delta\_G} G\_{12}(a\_{n'}\beta) \,\, \widetilde{f}\_{y,q}\widetilde{J}\_{y,q'}^\*;\tag{20b}$$

$$M\_{p',p}^{2,1}(\beta) = -\sum\_{\mathbf{n}} \frac{1}{\Delta\_{\mathbf{G}}} G\_{12}(a\_{\mathbf{n}}, \beta) \, \overleftarrow{J}\_{\mathbf{x},p} \overleftarrow{J}\_{\mathbf{x},p'}^\*;\tag{20c}$$

$$\mathcal{M}\_{p',q}^{2,2}(\beta) = \sum\_{\mathfrak{n}} \frac{1}{\Delta\_{\mathbb{G}}} G\_{11}(a\_{\mathfrak{n},\mathfrak{l}}\beta) \,\,\widetilde{f}\_{\mathfrak{l},\mathfrak{l}}\widetilde{f}\_{\mathfrak{x},p'}^{\*}.\tag{20d}$$

The system admits nontrivial solutions when *det* [*M*(β)] = 0 [41,45,58,60], from which the frequency dependent propagation constant can be determined. For lossy media, a complex constant solution is expected.

Using the new technique, original results for the dispersion characteristics of complex bianisotropic chiral and achiral media are obtained through the ratio (β/κ0) 2, discussed and compared with the isotropic case (ξ = η = 0) using the technique in [41].

Due to the great number of possible medium cases, we have restricted our analysis to highlighting the main results of achiral media that have been less addressed in the literature. Accurate solutions of the determinant roots in Equation (18) are obtained within a tolerance of 10−12.

#### **4. Results and Discussions**

In order to validate our calculations and test the efficiency of the proposed method, three magnetic anisotropic cases have initially been considered. Numerical results have been computed and compared with available literature [61,62] (Figure 2) and good agreements are observed. On the other hand, a rapid convergence has been achieved with a reduced Fourier number (N = 500) and basis functions (K = 8) against (N = 3000) used by Khodja et al. [61] for the same number of basis functions.

**Figure 2.** (β/κ0) 2 for the dominant mode of a shielded CPW with magnetic anisotropy, (2*a* = 3.556 mm, 2*w* = 2*s* = 0.7112 mm, *d*1 = 2.8448 mm, *d*2 = 0.7112 mm, *d*3 = 3.556 mm and ε*r* = 3).

In this study, we consider a suspended three-layer CPW structure implanted on a complex bianisotropic dielectric material (Figure 1) with the following geometrical dimensions *a* = 10 mm, *d*1 = 4.5 mm, *d*2 = 1 mm, *d*3 = 4.5 mm, *w* = 1 mm, *s* = 1 mm, ε*r* = 2.53, μ*r* = 1. Different sub-figures

are differentiated by the included legends where only the sign of the constitutive element changes respectively to the previous case in the same figure.

In order to examine the effect of the magneto-electric parameters on the dispersion characteristics, we first start with the examination of the axial bianisotropy effect. The magneto-electric elements, whether they are real, imaginary, positive or negative directly affect the phase constant as well as the attenuation factor.

The obtained results, treat two principal cases of diagonal bianisotropic medium: achiral and chiral. In each case, the magneto-electric pair (ξ*ij*, η*ij*) is considered non-zero, so that the new original results of the achiral medium case can be validated and compared with the chiral case. In addition, in this parametric study, we examined the effects of the gyrotropic elements of the magneto-electric tensors on the complex propagation coefficient. Results are grouped in figures according to the constitutive parameters effects.

#### *4.1. E*ff*ect of Diagonal Bianisotropy*

For diagonal bianisotropy three cases of magneto-electric elements are considered:

LVRWURSLF>@ [\\ H U [\\ H

 U [\\ H

 U [\\ H

where (*i* = *x*, *y*, *z*) and *a* = (−1, −0.75, −0.5, −0.25, 0.25, 0.5, 0.75, 1). Two main cases are distinguished: achiral (ξ*ii* = *a* √ε*r*) and chiral (ξ*ii* = *ja* √ε*r*).

In Figure 3, the effect of element ξ*yy*, for achiral and chiral media cases is presented. An identical effect is observed on the ratio (β/κ0) 2 (Figure 3a), with reciprocal effect (curves superposition for ξ = ±*a* √ε*r*), for both chiral and achiral cases. These media cases show low losses for achirality (case (i)) with η*yy* = ξ*yy* and almost zero losses for chirality with η*yy* = −ξ*yy* (case (ii)) (Figure 3b). It can be concluded that the effect of a reciprocal chirality is almost the same as for an achiral medium with equal magneto-electric elements. In these cases (*ii* = *yy*) propagating modes are excited in the guiding structure, however, for achiral with η*ii* = ξ*ii* and chiral with η*ii* = −ξ*ii*, no solutions are obtained for *ii* = *xx* and *ii* = *zz*, hence, the medium does not support any propagating modes.

> U

[\\ *M* H U [\\ *M* H U [\\ *M* H U [\\ *M* H U

**Figure 3.** Effect of diagonal bianisotropy ((i) ξ*yy* real with η*yy* = ξ*yy* and (ii) ξ*yy* imaginary with η*yy* = −ξ*yy*) on (**a**): (β/κ0) 2 and (**b**): (α/κ0) 2.

Figure 4 illustrates the effect of diagonal bianisotropic media for the case achiral with η*ii* = −ξ*ii*. Unlike the previous case, the fundamental propagating mode is excited for all diagonal magneto-electric

LVRWURSLF>@*LL [[\\]]*

elements (*ii* = *xx*, *yy*, *zz*). However, each of the elements has its own effect. According to Figure 4, for (*ii* = *xx*), a non-reciprocity for the achiral case (Figure 4a) is observed on (β/κ0) 2. Higher losses are observed for *a* ≥ 0.5 (Figure 4b). The effect of element ξ*yy*,2 is presented in Figure 4c and d. These cases are non-reciprocal and exhibit relatively lower losses. The effect on (β/κ0) 2 is almost identical for both cases ξ*yy*,2 and ξ*zz*,2 (Figure 4c,e).

**Figure 4.** Effect of diagonal bianisotropy elements, ξ*xx* on: (**a**) (β/κ0) 2 and (**b**) (α/κ0) 2; ξ*yy* on: (**c**) (β/κ0) 2 and (**d**) (α/κ0) 2; ξ*zz* on: (**e**) (β/κ0) 2 and (**f**) (α/κ0) 2 with η*xx* = −ξ*xx*.

#### *4.2. E*ff*ect of Gyrotropic Bianisotropy*

For the gyrotropic elements, five achiral cases are considered:

*Electronics* **2020**, *9*, 243

In Figure 5a–d, five cases were grouped, each differs from the other by a single change in sign of the magneto-electric element. It can be seen that the combination of the constitutive parameters shows non-reciprocity and a distinct effect on (β/κ0) 2 and (α/κ0) 2 parameters.  The sign change between η*xy*,1 = η*yx*,1 (case (i)) and η*xy*,2 = −η*yx*,2 (case (ii)) keeps the same effect on (β/κ0) 2 (Figure 5a). Only the ratio (α/κ0) 2 is affected with the appearance of non-reciprocity (Figure 5b). As shown in Figure 5c,d, for the combinations ξ*xy*,3, ξ*xy*,4 and ξ*xy*,5, a sign change has only a weak effect on (β/κ0) 2 and (α/κ0) 2.

**Figure 5.** Effect of gyrotropic achiral bianisotropy for different ξ*xy*, ξ*yx*, η*xy* and η*yx* combinations on: (**a**) (β/κ0) 2, (**b**) (α/κ0) 2, (**c**) (β/κ0) 2 and (**d**) (α/κ0) 2.

In Figure 6 are presented results of the element ξ*xz* combinations.  The elements, ξ*xz*,2 and ξ*xz*,3 have the same effect on both (β/κ0) 2 and (α/κ0) 2 (Figure 6c,d). In this case, only 3 combinations: ξ*xz*,1, ξ*xz*,2 and ξ*xz*,3 support propagating modes, with the appearance of the non-reciprocal effect. For the two other cases ξ*xz*,4 and ξ*xz*,5, no solutions are obtained. The (β/κ0) 2 and (α/κ0) 2 variations of both cases (ii) and (iii) are completely different from case (i). The exchange of sign between ξ*xz*,3 = −ξ*zx*,3 and η*xz*,2 = −η*zx*,2 preserved the same effect ((ii) and (iii) curves are superposed), as shown in Figure 6c,d.

**Figure 6.** Effect of gyrotropic achiral bianisotropy for different ξ*xz*, ξ*zx*, η*xz* and η*zx* combinations on: (**a**) (β/κ0) 2, (**b**) (α/κ0) 2, (**c**) (β/κ0) 2 and (**d**) (α/κ0) 2.

Figure 7a,b presents the effect of sign exchange between the magneto-electric element of achiral medium cases. The positive sign ξ*yz*,2 = η*yz*,2 and ξ*yz*,3 = η*yz*,3 reveals a non-reciprocity on (β/κ0) 2, while it shows a significant effect on (α/κ0) 2 and reduced losses compared to isotropic case.

**Figure 7.** Effect of gyrotropic achiral bianisotropy for different ξ*yz*, ξ*zy*, η*yz* and η*zy* combinations on: (**a**) (β/κ0) 2 and (**b**) (α/κ0) 2.

#### **5. Conclusions**

In this work, an analytical modeling of a three-layer CPW structure implanted on a complex medium is presented. This study is based on the Full-GEMT developed in a matrix form for the characterization of the bianisotropic-substrate CPW structure. This resulted in compact matrix form expressions of the Green's tensor. The implemented resolution method includes a new accelerating procedure developed in the GEMT that contributed to accomplishing accurate solutions with improved computing time. The computing time, for one frequency point, has been reduced by 33% for some calculation cases and more for others. A satisfactory calculation convergence is achieved with a significantly reduced Fourier number compared to literature. The presented technique can dramatically reduce the complexity of wave propagation characterization, in highly complex media, in terms of mathematical modelling and computational solution method.

According to our calculations, cases of complex media have been achieved, where the ratio (β/κ0) 2 is close to unity such as for cases ξ*xz*,1, ξ*xz*,2. and ξ*xz*,3. This characteristic is vital for the realization of media with permittivity close to unity for better use in the design of radiating antenna structures.

For cases ξ*xy*,1 and ξ*xy*,2, where there is only one element that changes sign between one case and another, the results of (β/κ0) 2 are similar (reversed cases with similar effects), however, (α/κ0) 2 presents a different variation either in form or in magnitude.

It is noted that for the case of achiral medium when ξ = η, ξ*ij* = ξ*ji* and η*ij* = −η*ji* (ξ*xy*,2), the medium is reciprocal and the effect is well reversed (non-reciprocal) when ξ*ij* = −ξ*ji* (ξ*xy*,3). For the cases ξ*xy*,3 and ξ*xy*,5, one had to have inverted cases, whereas, it is not the case. This can be explained by the properties imposed by the geometry of the studied structure.

An original result that should be taken into consideration is the losses, which show changes with each sign change between the magneto-electric elements. On the other hand, it is found that losses in achiral media are of the same magnitude as those in non-reciprocal chiral media, which must be taken into account. Furthermore, it is worth noting that the transverse elements ξ*xz* are the most influential on the phase constant in bianisotropic a CPW structure, and this may be attributed to the geometry of the studied structure.

Investigation of some achiral media cases has shown new results such as the notion of achiral media with a relative permittivity approaching unity with reduced losses. This new finding could serve as a valuable concept from which designers of unusual synthetic materials may benefit to enhance the media intrinsic properties for future innovative applications use.

Finally, the technique discussed in this paper may be extended to deal with propagation of bifurcated modes and enclosed multilayer microstrip structures.

**Author Contributions:** Design and concept, D.S. and C.Z.; methodology, C.Z. and I.E.; investigation, I.O., A.U.; resources, I.E. and J.R.; writing—original draft preparation, C.Z. and D.S.; writing—review and editing, I.E., A.U., H.A. and R.A.-A.; supervision, R.A.-A.; project administration, J.R., formal analysis H.A. and F.B. All authors have read and agreed to the published version of the manuscript.

**Funding:** This project has received funding from the European Union's Horizon 2020 research and innovation program under grant agreement H2020-MSCA-ITN-2016 SECRET-722424. This work is also funded by the FCT/MEC through national funds and when applicable co-financed by the ERDF, under the PT2020 Partnership Agreement under the UID/EEA/50008/2019 project.

**Acknowledgments:** This work is supported by the European Union's Horizon 2020 Research and Innovation program under grant agreement H2020-MSCA-ITN-2016-SECRET-722424. This work is also funded by the FCT/MEC through national funds and when applicable co-financed by the ERDF, under the PT2020 Partnership Agreement under the UID/EEA/50008/2019 project.

**Conflicts of Interest:** The authors declare no conflict of interest.

#### **References**

© 2020 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).


**Molecular Mechanisms Underlying Bone Marrow Homing of Hematopoietic Stem Cells**

Aysegul Ocal Sahin and Miranda Buitenhuis

*Department of Hematology and Erasmus MC Stem Cell Institute for Regenerative Medicine, Erasmus MC, Rotterdam, The Netherlands*

#### **1. Introduction**

184 Advances in Hematopoietic Stem Cell Research

Yagi, K., K. Tsuji, A. Nifuji, K. Shinomiya, K. Nakashima, B. DeCrombrugghe & M. Noda

Yokota, T., K. Oritani, I. Takahashi, J. Ishikawa, A. Matsuyama, N. Ouchi, S. Kihara, T.

Yoshimoto, M., T. Shinohara, T. Heike, M. Shiota, M. Kanatsu-Shinohara & T. Nakahata

of spleen and thymus." *Am J Physiol Endocrinol Metab* 295(6): E1349-1357 Zhang, C. C. & H. F. Lodish (2008). "Cytokines regulating hematopoietic stem cell function."

Zhang, J., C. Niu, L. Ye, H. Huang, X. He, W. G. Tong, J. Ross, J. Haug, T. Johnson, J. Q.

Zhang, Y., A. Harada, H. Bluethmann, J. B. Wang, S. Nakao, N. Mukaida & K. Matsushima

Zhu, J., R. Garrett, Y. Jung, Y. Zhang, N. Kim, J. Wang, G. J. Joe, E. Hexner, Y. Choi, R. S.

and differentiation from hematopoietic stem cells." *Blood* 109(9): 3706-3712 Zuckerman, K. S., R. K. Rhodes, D. D. Goodrum, V. R. Patel, B. Sparks, J. Wells, M. S. Wicha

Zuckerman, K. S. & M. S. Wicha (1983). "Extracellular matrix production by the adherent cells of long-term murine bone marrow cultures." *Blood* 61(3): 540-547 Zweegman, S., J. Van Den Born, A. M. Mus, F. L. Kessler, J. J. Janssen, T. Netelenbos, P. C.

murine bone marrow cultures." *J Clin Invest* 75(3): 970-975

stem cell niche using real-time imaging." *Nature* 457(7225): 97-101

Yin, T. & L. Li (2006). "The stem cell niches in bone." *J Clin Invest* 116(5): 1195-1201

chondrocytes." *J Cell Biochem* 88(6): 1077-1083

*Curr Opin Hematol* 15(4): 307-311

TNF alpha in vitro." *Blood* 86(8): 2930-2937

1723-1732

841

392

Johnson, R. A. Feldman & L. Li (2009). "Detection of functional haematopoietic

(2003). "Bone morphogenetic protein-2 enhances osterix gene expression in

Funahashi, A. J. Tenner, Y. Tomiyama & Y. Matsuzawa (2000). "Adiponectin, a new member of the family of soluble defense collagens, negatively regulates the growth of myelomonocytic progenitors and the functions of macrophages." *Blood* 96(5):

(2003). "Direct visualization of transplanted hematopoietic cell reconstitution in intact mouse organs indicates the presence of a niche." *Exp Hematol* 31(8): 733-740 Youn, D. Y., D. H. Lee, M. H. Lim, J. S. Yoon, J. H. Lim, S. E. Jung, C. E. Yeum, C. W. Park,

H. J. Youn, J. S. Lee, S. B. Lee, M. Ikawa, M. Okabe, Y. Tsujimoto & J. H. Lee (2008). "Bis deficiency results in early lethality with metabolic deterioration and involution

Feng, S. Harris, L. M. Wiedemann, Y. Mishina & L. Li (2003). "Identification of the haematopoietic stem cell niche and control of the niche size." *Nature* 425(6960): 836-

(1995). "Tumor necrosis factor (TNF) is a physiologic regulator of hematopoietic progenitor cells: increase of early hematopoietic progenitor cells in TNF receptor p55-deficient mice in vivo and potent inhibition of progenitor cell proliferation by

Taichman & S. G. Emerson (2007). "Osteoblasts support B-lymphocyte commitment

& L. A. Mayo (1985). "Inhibition of collagen deposition in the extracellular matrix prevents the establishment of a stroma supportive of hematopoiesis in long-term

Huijgens & A. M. Drager (2004). "Bone marrow stromal proteoglycans regulate megakaryocytic differentiation of human progenitor cells." *Exp Cell Res* 299(2): 383The formation of blood cells, also called hematopoiesis, is a complex process that occurs in the bone marrow and depends on correct regulation of hematopoietic cell fate decisions. Aberrant regulation of hematopoiesis can result in the development of severe malignant and non-malignant hematological disorders, including leukemia. Hematopoietic stem cell transplantation is the most powerful treatment modality for a large number of those malignancies. Successful hematopoietic recovery after transplantation depends on homing of hematopoietic stem cells to the bone marrow and subsequent lodging of those cells in the bone marrow microenvironment.

Homing is a rapid, coordinated process in which circulating hematopoietic stem and progenitor cells actively enter the bone marrow within a few hours after transplantation (Figure 1). Rolling and firm adhesion of those cells to endothelial cells in small marrow sinusoids is followed by trans-endothelial migration across the endothelium/extracellular matrix barrier. Finally, in irradiated recipients, hematopoietic stem cells anchor to their specialized niches within the bone marrow compartment near osteoblasts and initiate longterm repopulation (Lo Celso et al., 2009). In absence of available niches in, for example, nonirradiated recipients, HSCs tend to be more randomly distributed throughout the bone marrow (Lo Celso et al., 2009). Since the first bone marrow transplantation decades ago, research has focused on understanding the mechanisms underlying homing of hematopoietic stem cells to the bone marrow. This chapter will focus on recent studies that have extended our understanding of the molecular mechanisms underlying adhesion, migration and bone marrow homing of hematopoietic stem cells.

### **2. Selectins and bone marrow homing**

A first step in the process of bone marrow homing is initial tethering and rolling of hematopoietic stem and progenitor cells along the endothelial wall of blood vessels. It has been demonstrated that selectins play an important role in bone marrow homing of hematopoietic stem and progenitor cells by regulating these processes. Intravital microscopy in bone marrow sinoids and venules of mice deficient for individual selectins revealed that rolling of hematopoietic progenitor cells involves both P and E-selectin, but not L-selectin (Mazo et al.,

Molecular Mechanisms Underlying Bone Marrow Homing of Hematopoietic Stem Cells 187

Fig. 1. Homing of hematopoietic Stem Cells to the bone marrow. 1) Initial tethering and 2) rolling are the first steps in bone marrow homing. These processes are mediated by both E-

hematopoietic stem cells to the endothelial wall. 4) Firmly attached hematopoietic stem cells can subsequently transmigrate through the endothelial layer and 5) basal lamina, consisting of fibronectin, collagen and laminin. Integrins involved in these steps are CD49d/CD29, CD49e/CD29 and CD49f/CD29. 6) Finally, hematopoietic stem cells migrate towards the

Integrins are, in addition to selectins, also implicated in playing an important role in regulation of bone marrow homing. Several in vitro studies with blocking antibodies have, for example, shown that both CD49d/CD29 (41 or VLA-4) and CD11a/CD18 (L2 or LFA-1) play an important role in adhesion of hematopoietic stem and progenitor cells to endothelial cells and subsequent transendothelial migration (Imai et al., 1999; Peled et al., 2000; Voermans et al., 2000). In addition, spontaneous migration of CD34+ hematopoietic progenitors underneath a bone marrow derived stromal cell layer, was found to be significantly inhibited by a peptide that blocks CD49d/CD29 integrin binding (Burger et al., 2003). However, adhesion of CD34+ cells to fibronectin was found to be primarily dependent on CD49e/CD29 (51 or VLA-5) and not CD49d/CD29 (Peled et al., 2000). In addition, chemotaxis of peripheral blood CD34+ progenitor cells on recombinant fibronectin appears to be mediated, at least in part, by CD49e/CD29 (Carstanjen et al., 2005). The importance of

and P-selectin. 3) SDF-1 mediated integrin activation induces firm adhesion of the

SDF-1 gradient to the osteoblasts.

**3. Integrins and bone marrow homing**

1998). Similarly, coating of a surface with immobilized P- or E-Selectin was sufficient to induce rolling of human CD34+ hematopoietic progenitor cells under flow conditions (Xia et al., 2004). A next step in bone marrow homing is transendothelial migration. This process requires firm adhesion of hematopoietic stem and progenitor cells to endothelial cells. Although CD34+ hematopoietic progenitor cells are capable of binding to fluid-phase P- and E-selectin (Xia et al., 2004), in vitro adhesion to bone marrow derived endothelial cells under static conditions has been shown not to depend on E-selectin (Naiyer et al., 1999). Transwell experiments performed to study the importance of E-selectin in migration of human hematopoietic progenitor cells through a confluent layer of bone marrow derived endothelial cells, precultured with IL-1B to induce E-selectin expression, yielded contradictory results. While Naiyer et al. have demonstrated with blocking antibodies that E-selectin is important for transendothelial migration (Naiyer et al., 1999), no significant inhibition in transendothelial migration could be observed by Voermans et al. who performed similar experiments (Voermans et al., 2000). Transplantation of lethally irradiated recipient mice deficient for both P-and E-selectin with wild type bone marrow cells resulted in reduced recruitment of hematopoietic progenitors to the bone marrow and enhanced levels of circulating hematopoietic progenitors, indicating that selectins indeed play an important role in bone marrow homing (Frenette et al., 1998).

Ligands for E-selectin include the PSGL-1 glycoform CLA, CD43 and the CD44 glycoform HCELL (Dimitroff et al., 2001; Merzaban et al., 2011).  Immune precipitation experiments revealed that although E-selectin can bind to CLA and CD43 in both mouse and human cells, the interaction between E-selectin and CD44 only occurs in human cells (Merzaban et al., 2011). These studies indicate that the molecular mechanism underlying bone marrow homing may be different for mouse and human hematopoietic stem cells. This hypothesis was confirmed by the observation that human CD34+ hematopoietic progenitor cells exhibit a stronger E-selectin binding capacity compared to mouse Lin-Sca-1+c-kit+ cells (Merzaban et al., 2011). In contrast to PSGL-1 which is also expressed in mature hematopoietic cells, CD44 appears to be predominantly expressed on primitive human CD34+ hematopoietic progenitor cells (Dimitroff et al., 2001). Rolling experiments performed under physiological flow conditions revealed that CD44 mediates E-selectin-dependent rolling interactions over a wider shear range in comparison to PSGL-1 and promotes rolling interactions on human bone marrow endothelial cells (Dimitroff et al., 2001). Silencing of CD44 expression in human cells with shRNAs was sufficient to decrease E-selectin binding under physiologic shear conditions, while enforced CD44 expression in Lin-Sca-1+c-kit+ cells conversely increased E-selectin adherence, resulting in improved bone marrow homing in vivo (Merzaban et al., 2011). In addition, treatment of mice with blocking antibodies against CD44 resulted in an increase in committed progenitors in the peripheral blood, suggesting that CD44 is important for lodging of hematopoietic progenitors in the bone marrow (Vermeulen et al., 1998). It has also been demonstrated that the selectin ligands must be alpha1-3 fucosylated to form glycan determinants such as sialyl Lewis x (sLe(x)). Inadequate alpha1-3 fucosylation of umbilical cord blood derived CD34+CD38-/low cells resulted in reduced interaction with both E-selectin and P-selectin, while increasing the level of cellsurface sLe(x) determinants augmented binding to fluid-phase P- and E-selectin, improved cell rolling on P- and E-selectin under flow and enhanced engraftment of human hematopoietic cells in bone marrows of irradiated NOD/SCID mice (Xia et al., 2004).

1998). Similarly, coating of a surface with immobilized P- or E-Selectin was sufficient to induce rolling of human CD34+ hematopoietic progenitor cells under flow conditions (Xia et al., 2004). A next step in bone marrow homing is transendothelial migration. This process requires firm adhesion of hematopoietic stem and progenitor cells to endothelial cells. Although CD34+ hematopoietic progenitor cells are capable of binding to fluid-phase P- and E-selectin (Xia et al., 2004), in vitro adhesion to bone marrow derived endothelial cells under static conditions has been shown not to depend on E-selectin (Naiyer et al., 1999). Transwell experiments performed to study the importance of E-selectin in migration of human hematopoietic progenitor cells through a confluent layer of bone marrow derived endothelial cells, precultured with IL-1B to induce E-selectin expression, yielded contradictory results. While Naiyer et al. have demonstrated with blocking antibodies that E-selectin is important for transendothelial migration (Naiyer et al., 1999), no significant inhibition in transendothelial migration could be observed by Voermans et al. who performed similar experiments (Voermans et al., 2000). Transplantation of lethally irradiated recipient mice deficient for both P-and E-selectin with wild type bone marrow cells resulted in reduced recruitment of hematopoietic progenitors to the bone marrow and enhanced levels of circulating hematopoietic progenitors, indicating that

selectins indeed play an important role in bone marrow homing (Frenette et al., 1998).

hematopoietic cells in bone marrows of irradiated NOD/SCID mice (Xia et al., 2004).

Ligands for E-selectin include the PSGL-1 glycoform CLA, CD43 and the CD44 glycoform HCELL (Dimitroff et al., 2001; Merzaban et al., 2011).  Immune precipitation experiments revealed that although E-selectin can bind to CLA and CD43 in both mouse and human cells, the interaction between E-selectin and CD44 only occurs in human cells (Merzaban et al., 2011). These studies indicate that the molecular mechanism underlying bone marrow homing may be different for mouse and human hematopoietic stem cells. This hypothesis was confirmed by the observation that human CD34+ hematopoietic progenitor cells exhibit a stronger E-selectin binding capacity compared to mouse Lin-Sca-1+c-kit+ cells (Merzaban et al., 2011). In contrast to PSGL-1 which is also expressed in mature hematopoietic cells, CD44 appears to be predominantly expressed on primitive human CD34+ hematopoietic progenitor cells (Dimitroff et al., 2001). Rolling experiments performed under physiological flow conditions revealed that CD44 mediates E-selectin-dependent rolling interactions over a wider shear range in comparison to PSGL-1 and promotes rolling interactions on human bone marrow endothelial cells (Dimitroff et al., 2001). Silencing of CD44 expression in human cells with shRNAs was sufficient to decrease E-selectin binding under physiologic shear conditions, while enforced CD44 expression in Lin-Sca-1+c-kit+ cells conversely increased E-selectin adherence, resulting in improved bone marrow homing in vivo (Merzaban et al., 2011). In addition, treatment of mice with blocking antibodies against CD44 resulted in an increase in committed progenitors in the peripheral blood, suggesting that CD44 is important for lodging of hematopoietic progenitors in the bone marrow (Vermeulen et al., 1998). It has also been demonstrated that the selectin ligands must be alpha1-3 fucosylated to form glycan determinants such as sialyl Lewis x (sLe(x)). Inadequate alpha1-3 fucosylation of umbilical cord blood derived CD34+CD38-/low cells resulted in reduced interaction with both E-selectin and P-selectin, while increasing the level of cellsurface sLe(x) determinants augmented binding to fluid-phase P- and E-selectin, improved cell rolling on P- and E-selectin under flow and enhanced engraftment of human

Fig. 1. Homing of hematopoietic Stem Cells to the bone marrow. 1) Initial tethering and 2) rolling are the first steps in bone marrow homing. These processes are mediated by both Eand P-selectin. 3) SDF-1 mediated integrin activation induces firm adhesion of the hematopoietic stem cells to the endothelial wall. 4) Firmly attached hematopoietic stem cells can subsequently transmigrate through the endothelial layer and 5) basal lamina, consisting of fibronectin, collagen and laminin. Integrins involved in these steps are CD49d/CD29, CD49e/CD29 and CD49f/CD29. 6) Finally, hematopoietic stem cells migrate towards the SDF-1 gradient to the osteoblasts.

### **3. Integrins and bone marrow homing**

Integrins are, in addition to selectins, also implicated in playing an important role in regulation of bone marrow homing. Several in vitro studies with blocking antibodies have, for example, shown that both CD49d/CD29 (41 or VLA-4) and CD11a/CD18 (L2 or LFA-1) play an important role in adhesion of hematopoietic stem and progenitor cells to endothelial cells and subsequent transendothelial migration (Imai et al., 1999; Peled et al., 2000; Voermans et al., 2000). In addition, spontaneous migration of CD34+ hematopoietic progenitors underneath a bone marrow derived stromal cell layer, was found to be significantly inhibited by a peptide that blocks CD49d/CD29 integrin binding (Burger et al., 2003). However, adhesion of CD34+ cells to fibronectin was found to be primarily dependent on CD49e/CD29 (51 or VLA-5) and not CD49d/CD29 (Peled et al., 2000). In addition, chemotaxis of peripheral blood CD34+ progenitor cells on recombinant fibronectin appears to be mediated, at least in part, by CD49e/CD29 (Carstanjen et al., 2005). The importance of

Molecular Mechanisms Underlying Bone Marrow Homing of Hematopoietic Stem Cells 189

 homing is CD49f (6). In contrast to CD49d that appears to primarily be involved in bone marrow homing of short-term repopulating hematopoietic stem cells, CD49f is thought to be important for homing of both short-term and long-term stem cells (Qian et al., 2006). In contrast, similar experiments with fetal liver cells revealed that, in contrast to CD49d which appeared to be important for homing of both hematopoietic stem and progenitor cells, CD49f is only important for homing of hematopoietic progenitors but not stem cells (Qian et al., 2007). These studies indicate that CD49d and Cd49f play differential roles during homing of cord blood and fetal liver derived hematopoietic stem and progenitor cells (Qian et al., 2007). In contrast, bone marrow homing was not affected in a more recent study in which also mouse bone marrow derived hematopoietic stem and progenitor cells pretreated with blocking antibodies directed against CD49f were transplanted in recipient mice (Bonig et al., 2009). In addition, blocking CD49f in human and primate bone marrow derived hematopoietic stem and progenitor cells, but not mobilized peripheral blood or cord blood derived cells that express little or no CD49f, resulted in enhanced bone marrow homing in a xenogeneic transplant model and significantly improved engraftment levels (Bonig et al., 2009). Finally, intravenous injection of anti-CD49f antibodies, in contrast to antibodies against CD49d integrin, did not mobilize progenitors or enhance cytokine-induced mobilization by G-CSF, suggesting that CD49f is not essential for lodging of hematopoietic stem and progenitor cells in the bone marrow (Qian et al., 2006). Additional research is

required to investigate whether or not CD49f regulates bone marrow homing.

chemoattractants for hematopoietic stem and progenitor cells (Kim et al., 2011).

**4. Chemoattractants involved in migration of hematopoietic stem cells**

Chemoattractants play an important role in directing migration of hematopoietic stem and progenitor cells to the bone marrow. Several studies have demonstrated that Stromal cell Derived Factor 1 (SDF-1), also known as CXC chemokine ligand 12 (CXCL12) (Tashiro et al., 1993) acts as a chemoattractant for hematopoietic stem and progenitor cells and is important for their transendothelial migration (Aiuti et al., 1997; Naiyer et al., 1999; Mohle et al., 1998; Kim & Broxmeyer, 1998; Glass et al., 2011). Further investigation, utilizing a large panel of CC and CXC chemokines, suggested that the only chemokine capable of inducing migration of murine hematopoietic stem and progenitor cells appears to be SDF-1 (Liesveld et al., 2001; Wright et al., 2002). Although the chemokine receptors CCR3 and CCR9 were also expressed at mRNA level, their ligands could not induce migration (Wright et al., 2002). Similarly, examination of a panel of chemokines and cytokines in transendothelial migration assays revealed that SDF-1 is also important for migration of human hematopoietic progenitors through a confluent layer of endothelial cells (Liesveld et al., 2001). However, to a lesser extent, also other chemokines and cytokines, including CCL2 (MCP-1), CCL5 (RANTES), CXCL10 (IP-10), IL-8 and SCF could also induce transendothelial migration (Liesveld et al., 2001). In addition, LTD4, a ligand for CysLT(1), a G protein-coupled receptor recognizing inflammatory mediator of the cysteinyl leukotriene family, which is highly expressed in hematopoietic progenitors, has been demonstrated to up-regulate CD49d/CD29 and CD49e/CD29 dependent adhesion of hematopoietic progenitors (Boehmler et al., 2009) and to induce chemotaxis and in vitro transendothelial migration (Bautz et al., 2001). Recently, a role for the proteolysis-resistant bioactive lipids sphingosine-1-phosphate and ceramide-1-phosphate in regulation of bone marrow homing has been suggested. Conditioning of mice for transplantation resulted in enhanced levels of these lipids in the bone marrow. In addition, both lipids appear to be

both CD49d/CD29 and CD49e/CD29 in directional migration through the basal lamina, which is composed of the extracellular matrix proteins laminin, collagen, and fibronectin, has been examined utilizing a three dimensional extra cellular matrix-like gel. In contrast to the dominant role of CD49e/CD29 in facilitating static adhesion to fibronectin, SDF-1– induced directional migration of CD34+ cells was found to be dependent on both CD49d/CD29 and CD49e/CD29 integrins (Peled et al., 2000). These studies suggest that both CD49d/CD29 and CD49e/CD29 play an important role in migration of hematopoietic stem and progenitor cells in general. However, transwell migration experiments with endothelial cells from different origin showed that CD49d/CD29 is only involved in migration of hematopoietic progenitors through a confluent layer of bone marrow derived, but not human umbilical vein derived, endothelial cells (Peled et al., 2000). In addition, inhibition of CD49e/CD29 alone was not sufficient to inhibit migration through both types of endothelial cells. However, an additive effect was observed when antibodies for CD11a/CD18, CD49d/CD29 and CD49e/CD29 were mixed together (Peled et al., 2000). These results suggest that the mechanisms underlying hematopoietic stem cell migration through endothelial walls of blood vessels depends on the origin of the endothelial cells and the VCAM-1 expression level.

As described above, deletion of both P- and E-selectin in recipient mice significantly reduced bone marrow homing after transplantation of wild type HPCs. Treatment of these mice with a blocking antibody against VCAM-1, thereby prohibiting interaction with CD49d/CD29, was sufficient to further reduce bone marrow homing after transplantation (Frenette et al., 1998), suggesting that both selectins and integrins are important for optimal bone marrow homing. In addition, the capacity of cells either deficient for CD49d (Scott et al., 2003) or pretreated with CD49d antibodies (Vermeulen et al., 1998; Papayannopoulou et al., 2001; Qian et al., 2006; Carstanjen et al., 2005) to migrate to bone marrow has been shown to be impaired resulting in delayed short-term engraftment (Scott et al., 2003). Furthermore, treatment of mice with blocking antibodies against CD49d resulted in an increase in the number of committed progenitors in the peripheral blood, suggesting that CD49d is also important for lodging of hemaopoietic progenitors in the bone marrow (Vermeulen et al., 1998). Since antibodies directed against mouse CD49d can bind to both CD49d/CD29 and CD49d/ITGB7 (47), and CD49d/ITGB7 is also expressed on mouse Lin-Sca-1+c-Kit+ cells, it was hypothesized that in addition to CD49d/CD29, CD49d/ITGB7 could also be involved in bone marrow homing. Indeed, inhibition of CD49d/ITGB7or its substrate MadCam-1 significantly reduced, but not completely abrogated, bone marrow homing after transplantation (Katayama et al., 2004). In contrast, other integrins, including CD11a, appear not be involved in bone marrow homing (Vermeulen et al., 1998). Transplantation studies with hematopoietic stem cells deficient for CD18 indicated that also CD18 is not essential for bone marrow homing. However, since inhibition of CD49d/CD29 in CD18 deficient hematopoietic stem cells resulted in more dramatic reduction in bone marrow homing in comparison to inhibition of CD49d/CD29 in wild type mice, it was suggested that CD18 can contribute to bone marrow homing when the function of CD49d/CD29 is compromised (Papayannopoulou et al., 2001). In addition to CD49d, CD49e/CD29 has also been implicated in playing a role in regulation of bone marrow homing. Treatment of hematopoietic progenitors with an antibody directed against CD49e/CD29 was sufficient to partially reduce homing of those cells to the bone marrow but not to the spleen (Wierenga et al., 2006; Carstanjen et al., 2005). Another integrin implicated in regulation of bone marrow

both CD49d/CD29 and CD49e/CD29 in directional migration through the basal lamina, which is composed of the extracellular matrix proteins laminin, collagen, and fibronectin, has been examined utilizing a three dimensional extra cellular matrix-like gel. In contrast to the dominant role of CD49e/CD29 in facilitating static adhesion to fibronectin, SDF-1– induced directional migration of CD34+ cells was found to be dependent on both CD49d/CD29 and CD49e/CD29 integrins (Peled et al., 2000). These studies suggest that both CD49d/CD29 and CD49e/CD29 play an important role in migration of hematopoietic stem and progenitor cells in general. However, transwell migration experiments with endothelial cells from different origin showed that CD49d/CD29 is only involved in migration of hematopoietic progenitors through a confluent layer of bone marrow derived, but not human umbilical vein derived, endothelial cells (Peled et al., 2000). In addition, inhibition of CD49e/CD29 alone was not sufficient to inhibit migration through both types of endothelial cells. However, an additive effect was observed when antibodies for CD11a/CD18, CD49d/CD29 and CD49e/CD29 were mixed together (Peled et al., 2000). These results suggest that the mechanisms underlying hematopoietic stem cell migration through endothelial walls of blood vessels depends on the origin of the endothelial cells and

As described above, deletion of both P- and E-selectin in recipient mice significantly reduced bone marrow homing after transplantation of wild type HPCs. Treatment of these mice with a blocking antibody against VCAM-1, thereby prohibiting interaction with CD49d/CD29, was sufficient to further reduce bone marrow homing after transplantation (Frenette et al., 1998), suggesting that both selectins and integrins are important for optimal bone marrow homing. In addition, the capacity of cells either deficient for CD49d (Scott et al., 2003) or pretreated with CD49d antibodies (Vermeulen et al., 1998; Papayannopoulou et al., 2001; Qian et al., 2006; Carstanjen et al., 2005) to migrate to bone marrow has been shown to be impaired resulting in delayed short-term engraftment (Scott et al., 2003). Furthermore, treatment of mice with blocking antibodies against CD49d resulted in an increase in the number of committed progenitors in the peripheral blood, suggesting that CD49d is also important for lodging of hemaopoietic progenitors in the bone marrow (Vermeulen et al., 1998). Since antibodies directed against mouse CD49d can bind to both CD49d/CD29 and CD49d/ITGB7 (47), and CD49d/ITGB7 is also expressed on mouse Lin-Sca-1+c-Kit+ cells, it was hypothesized that in addition to CD49d/CD29, CD49d/ITGB7 could also be involved in bone marrow homing. Indeed, inhibition of CD49d/ITGB7or its substrate MadCam-1 significantly reduced, but not completely abrogated, bone marrow homing after transplantation (Katayama et al., 2004). In contrast, other integrins, including CD11a, appear not be involved in bone marrow homing (Vermeulen et al., 1998). Transplantation studies with hematopoietic stem cells deficient for CD18 indicated that also CD18 is not essential for bone marrow homing. However, since inhibition of CD49d/CD29 in CD18 deficient hematopoietic stem cells resulted in more dramatic reduction in bone marrow homing in comparison to inhibition of CD49d/CD29 in wild type mice, it was suggested that CD18 can contribute to bone marrow homing when the function of CD49d/CD29 is compromised (Papayannopoulou et al., 2001). In addition to CD49d, CD49e/CD29 has also been implicated in playing a role in regulation of bone marrow homing. Treatment of hematopoietic progenitors with an antibody directed against CD49e/CD29 was sufficient to partially reduce homing of those cells to the bone marrow but not to the spleen (Wierenga et al., 2006; Carstanjen et al., 2005). Another integrin implicated in regulation of bone marrow

the VCAM-1 expression level.

 homing is CD49f (6). In contrast to CD49d that appears to primarily be involved in bone marrow homing of short-term repopulating hematopoietic stem cells, CD49f is thought to be important for homing of both short-term and long-term stem cells (Qian et al., 2006). In contrast, similar experiments with fetal liver cells revealed that, in contrast to CD49d which

appeared to be important for homing of both hematopoietic stem and progenitor cells, CD49f is only important for homing of hematopoietic progenitors but not stem cells (Qian et al., 2007). These studies indicate that CD49d and Cd49f play differential roles during homing of cord blood and fetal liver derived hematopoietic stem and progenitor cells (Qian et al., 2007). In contrast, bone marrow homing was not affected in a more recent study in which also mouse bone marrow derived hematopoietic stem and progenitor cells pretreated with blocking antibodies directed against CD49f were transplanted in recipient mice (Bonig et al., 2009). In addition, blocking CD49f in human and primate bone marrow derived hematopoietic stem and progenitor cells, but not mobilized peripheral blood or cord blood derived cells that express little or no CD49f, resulted in enhanced bone marrow homing in a xenogeneic transplant model and significantly improved engraftment levels (Bonig et al., 2009). Finally, intravenous injection of anti-CD49f antibodies, in contrast to antibodies against CD49d integrin, did not mobilize progenitors or enhance cytokine-induced mobilization by G-CSF, suggesting that CD49f is not essential for lodging of hematopoietic stem and progenitor cells in the bone marrow (Qian et al., 2006). Additional research is required to investigate whether or not CD49f regulates bone marrow homing.


*Article* **MuseStudio: Brain Activity Data Management Library for Low-Cost EEG Devices**

**Miguel Ángel Sánchez-Cifo \*, Francisco Montero and María Teresa López**

Laboratory of User Interaction & Software Engineering (LoUISE), Department of Computing Systems, University of Castilla-La Mancha, 02071 Albacete, Spain<EMAIL_ADDRESS>(F.M<EMAIL_ADDRESS>(M.T.L.)

**\*** Correspondence<EMAIL_ADDRESS>
**Abstract:** Collecting data allows researchers to store and analyze important information about activities, events, and situations. Gathering this information can also help us make decisions, control processes, and analyze what happens and when it happens. In fact, a scientific investigation is the way scientists use the scientific method to collect the data and evidence that they plan to analyze. Neuroscience and other related activities are set to collect their own big datasets, but to exploit their full potential, we need ways to standardize, integrate, and synthesize diverse types of data. Although the use of low-cost ElectroEncephaloGraphy (EEG) devices has increased, such as those whose price is below 300 USD, their role in neuroscience research activities has not been well supported; there are weaknesses in collecting the data and information. The primary objective of this paper was to describe a tool for data management and visualization, called MuseStudio, for low-cost devices; specifically, our tool is related to the Muse brain-sensing headband, a personal meditation assistant with additional possibilities. MuseStudio was developed in Python following the best practices in data analysis and is fully compatible with the Brain Imaging Data Structure (BIDS), which specifies how brain data must be managed. Our open-source tool can import and export data from Muse devices and allows viewing real-time brain data, and the BIDS exporting capabilities can be successfully validated following the available guidelines. Moreover, these and other functional and nonfunctional features were validated by involving five experts as validators through the DESMET method, and a latency analysis was also performed and discussed. The results of these validation activities were successful at collecting and managing electroencephalogram data.

**Keywords:** brain data; low-cost devices; EEG; BIDS; neuroscience; library


**4. Seed and sowing methods**

### **4.1 Land preparation**

One deep plowing is advised with a mold-board plow in the months of April or May. Before sowing, smooth seedbed preparation with secondary tillage using a cultivator and multiple tooth hoe is required. Therefore, appropriate seed and land preparation aid in better germination, reduce weed issues and effectively save soil moisture. Small seeds take about 5–7 days to germinate. In Uttaranchal, where it is difficult to carry out frequent plowing operations, efficient soil turning and digging, weed removal from perennial plants, land smoothening, and the provision of an inward slope with a shallow drain all help in draining surplus rainwater [20].

### **4.2 Seed rate and sowing**

The recommended seed rate for sowing a one-hectare field is 8–10 kg of seed and 4–5 kg of seed sufficient for transplanting. To avoid infections, seeds should be treated with Thiram @ 2.5 g/kg of seeds. The best time for sowing is between June and July for the *Kharif* and September and October for the rabi. Usually, crops are grown during the *Kharif* season. In some areas, the crop is cultivated in irrigated conditions during the rabi season.

The line sowing is advantageous because it promotes inter-cultivation and provides efficient weed control and sowing with a seed drill and keeping space 22.5–30.0 cm between rows and 7.5–10.0 cm between plants, it is help in to maintain an ideal plant population of 4–5 lakh/ha (**Tables 1** and **2**) [20, 21].

#### **Table 1.**

*Finger millet is grown in all the cropping seasons in different parts of the country.*


**2.4. Preparation of bismuth chalcogenide films by PLD**

PLD is one of the most convenient thin film growth techniques that uses a high-intensity pulsed laser beam as an external energy source to ablate a target, form a plume, and then deposit thin films onto a substrate. **Figure 3** shows a typical PLD system for preparing TE and TI thin films. A substrate is heated and maintained at a desired substrate temperature (*T*S) using a thermocouple and a proportional-integral-derivative temperature controller. The thermocouple was buried inside a stainless steel substrate holder, which is heated by a tungsten lamp just behind the holder. The pressure of ambient gas (He/Ar) can be fine-tuned by the needle valve. A KrF excimer laser beam (*λ* = 248 nm, pulsed duration of 15–20 ns, repetition rate in the range of 1– 15 Hz, and fluence of 1–10 J/cm2 ) is guided by several UV mirrors and focused on a stoichiometric polycrystalline or a single crystal target (e.g., Bi2Te3, Bi2Se3, Bi2Se2Te) within the vacuum chamber by a UV lens. The target-to-substrate distance was 40 mm. During the deposition of Bi2Se3 films, pure (6N) He/Ar gas was introduced into the vacuum chamber, which was evacuated to a base pressure of 4 × 10−4 Pa (or 3 × 10−6 Torr) and maintained at a certain constant pressure (*P*), using a differential evacuation system.

After an initially random nucleation of islands on the surface of the substrates, the deposition on the top of the islands is faster than that in the valleys due to the oblique incident flux (the so-called **shadowing effect**) [12, 13]. Isolated columns are therefore formed on these islands

58 Applications of Laser Ablation - Thin Film Deposition, Nanomaterial Synthesis and Surface Modification

Epitaxy refers to the growth of a single crystal film on top of a single crystal substrate. The deposited film is denoted as an epitaxial film or epitaxial layer. The growth is called homoepitaxy if the film and the substrate are the same material, and it is called heteroepitaxy if they are different materials. Epitaxial relationship is determined as: (*HKL*) || (*hkl*); [*UVW*] || [*uvw*], where (*hkl*) and (*HKL*) are the Miller indices of the overgrowth plane and substrate at the common interface. The corresponding parallel directions in the overgrowth and substrate

The key factors governing epitaxy growths are structural compatibility, chemical compatibility,

**- Structural compatibility:** The structures of a film and a substrate should have good lattice matching in terms of crystal structures (*a*0, sub) and lattice constants (*a*0, film), that is, small lattice

*aa aa f a a* (1)

0, 0, 0, 0, 0, 0, 2. - - = » *sub film sub film film sub*

**- Chemical compatibility:** This includes chemical bonding and chemical diffusion.

**2.4. Preparation of bismuth chalcogenide films by PLD**

**- Growth temperatures:** Good epitaxy growth is obtained at above or around the well-defined elevated substrate temperature (*Te*). *Te* depends on the deposition rate, particle energy, and surface contamination. Generally, a higher temperature is recommended to reduce surface contamination by desorption (or enhance surface mobility) of atoms to reach the favorable sites and also enhance the diffusivity in deposition for favoring re-crystallization and defect

PLD is one of the most convenient thin film growth techniques that uses a high-intensity pulsed laser beam as an external energy source to ablate a target, form a plume, and then deposit thin films onto a substrate. **Figure 3** shows a typical PLD system for preparing TE and TI thin films. A substrate is heated and maintained at a desired substrate temperature (*T*S) using a thermocouple and a proportional-integral-derivative temperature controller. The thermocouple was

planes, denoted by [*wuw*] and [*UVW*], respectively, must also be specified.

during subsequent growths (**Figure 2d**) [13].

**2.3. Factors governing the epitaxy growth**

and growth temperatures.

misfit.

Lattice misfit *f*:

annihilation.

**2.2. Epitaxy growth**

**Figure 3.** Schematic illustration of a pulsed laser deposition (PLD) system. G: gauge.

The surface of substrates should be atomically clean and free from impurities because the contaminants can interact with the thin films being deposited and substantially degrade its quality and adhesion to the substrates. The presence of unwanted surface contaminants can also influence the growth and orientation of the films in an undesired manner. In the depositions for TE thin films, an approximately 300-nm-thick SiO2 layer was thermally grown on the Si wafers (thickness 525 μm) for electrical isolation purpose. The wafers were cut into 1.5 cm × 1.5 cm substrates. The substrates were cleaned with acetone to dissolve any contaminants adhering to the surface of substrates such as grease and oils. This was followed by rinsing with methanol to remove any residues left behind after cleaning with acetone. Afterward, the substrates were rinsed in distilled water and dried with nitrogen flow. The substrates were then used for the deposition of TE thin films.

Here are some examples of PLD growth of TE films. For Bi2Se3 thin films, the depositions were at *T*S of 200–350°C and helium ambient pressure (*P*) of 0.7–173 Pa. The number of laser pulses was 9000 and the deposition took 30 min. The average growth rate was approximately 0.46 Å/ pulse [14]. For the growth of Bi2Te3 thin films, *T*S was varied from room temperature (30°C) to 380°C and the Ar ambient pressure (*PAr*) was at 80 Pa. The number of laser pulses was 12,000 and the deposition took 40 min. The average growth rate was approximately 0.52 Å/pulse [15]. For the growth of Bi-Se-Te thin films, the depositions were at *T*S of 200–350°C and a helium ambient pressure (*P*He) of 0.027–86.7 Pa. The number of laser pulses was 9000 and the deposition took 15 min. The average growth rate was approximately 0.6 Å/pulse [16].


**3. Artificial intelligence (AI) in the diagnosis of GI autoimmune diseases**

Artificial intelligence is a study of methods capable of imitating intelligent human behavior (e.g., making decisions under uncertain conditions) [73]. Machine learning (ML) is a subset of AI. The introduction of machine learning (ML) has revolutionized the image processing and analysis field in medicine. ML in computer science can be defined as the process by which computers can learn without being explicitly programmed. Machine learning is intended to assist in learning from data. There are many datasets available today, leading to an increase in ML demand [74]. The information extracted from the data can sometimes be difficult to interpret after viewing it. The use of ML can make machines more efficient at handling data. There are two famous models in ML which are unsupervised and supervised machines [75]. Supervised learning is an optimum choice for smaller volumes of data and clearly labeled data [76]. For large datasets, unsupervised learning generally results in better performance and results. If a large dataset is readily available and labeled, deep learning techniques are optimum for use [77]. The application of AI and ML in healthcare has a promising potential in providing medical solutions for the healthcare sector. One of the aspects that could be a valuable addition to the healthcare sector is the incorporation of AI into the diagnosis. In this section, we aim to shed the light on some of the recent applications of AI in GI autoimmune diseases.


**5. Discussions**

The localization of the primary tumor in the transverse colon and the type of the emergency: occlusion, peritonitis with diastatic perforation or hemorrhage, as well as hemodynamic and respiratory stability of the patient, severity of hydroelectrolytic imbalance, require as emergency surgical treatment the following surgical therapeutic options (on cases that may benefit from surgical treatment):

standard transverse colon or splenic flexure, the presence of another synchronous tumor formation, vascular abnormalities or anatomical features of the transverse colon, high localization of the splenic flexure, the technical variants that can be achieved are represented by: segmental colectomy of the transverse colon or transversectomy, extended right colectomy, subtotal colectomy with CME and CVL Hohenberger and per-primal anastomosis TT, LL or LT, depending on local factors, technical possibilities – manual or mechanical and experience or preference of the surgeon.


**3. Material and methods**

#### **3.1 Physical surface properties of sorbent/char**

BET specifıc surface areas of sorbent as tested by N2 gas permeability. The sorbent was critical on the base of surface properties such as total surface activity, oxygen functional groups, total surface impurities, metal concentrations, dielectric value, free radical concentration and reactivity. The main chemical texture was related to the stimulation of oxidation reactivity. However, in some investigations, the pore size distribution of activated carbon is also likely to affect desorption kinetics.

The salt slurries were mixed with activated clay bentonite at weight rates of 1/8. The head tests are caried out by CaCl2 adde 10000ppm slurries to 80 gr bentonite solid. The suspension of 80 gr slurry of clay and apatite was mixed in 1lt water as slurry and give through shower in 5 cm diameter glass columns. Finally microwave radiated glass showered to flue gas compressed at 2 bar retained by exposure to at 160 °C for 4 hours. In addition, these samples were further dried at the same temperature for 1 hour to remove vapor species. The experimentation unit as shown in **Figure 1**. The microwave salt slurry washing tests are followed by flowsheet as seen in **Figure 2**. The surface areas of the apatite, coal char, activated compost and shale clay samples were measured with a Quanta Chromosorb surface analyzer. The surface area was determined by measuring the thermal conductivity using a gas mixture prepared in N2 and Ar composition and taking into account the BET equation. The sorbent solids compositions and physical quality are given in **Tables 1** and **2**.

**315**

**Table 1.**

*\**

Şırnak Asphaltite Char Shale

**Figure 2.**

Apatite Phosphate

*LOI: Loss on Ignition at 1000°.*

*Sorbent types for washing treatment.*

*Studied washing by microwave sorption technique.*

**Figure 1.**

*Apatite/Salt Slurry Emission Control of Post Combustion Flue Gas of Lignite and Coal…*

*The schematic view of an washing with microwave recycled by microwave sorption technique.*

**SiO2 Al2O2 Fe2O2 MgO K2O CaO P2O5 TiO2 LOI\***

27,4 7.70 10.83 2.17 1.97 10.5 1.4 1.74 5.47

0,2 0,1 2,3 2,3 4,3 11,3 23,5 0,1 6,5

Kaolin (%) 47.85 37.60 0.83 0.17 0.97 0.57 0.2 0.2 11.27

Bentonite 50.45 17.80 6.83 12.17 4.97 3.57 0.1 0.4 7.37 Marly Shale 17.85 11.60 0.83 5.17 3.97 20.57 0.2 0.4 5.27 Fly ash 27.8 13.60 17.83 4.17 2.97 10.7 1.6 1.4 17.27

*DOI: http://dx.doi.org/10.5772/intechopen.95296*

*Apatite/Salt Slurry Emission Control of Post Combustion Flue Gas of Lignite and Coal… DOI: http://dx.doi.org/10.5772/intechopen.95296*

**Figure 1.**

*Environmental Issues and Sustainable Development*

**2.4 Ca phosphate/Asphaltite shale char composite**

apatite waste/zeolite and char and cleaned [31–37].

**3.1 Physical surface properties of sorbent/char**

and 6 mm is required.

**3. Material and methods**

quality are given in **Tables 1** and **2**.

**2.5 Microwave treated biomass char/apatite phosphate compost**

xP2O5 and NaCO3. The calcinations product is subjected to acid treatment for artificial fertilizer fabrication. The acid dissolution characteristics after calcinations, Mazıdağı apatite phosphate was mostly acid-soluble in their natural state compared to other phosphate minerals. The study utilized the fine waste, compost 32.81% P2O5–30.98% P2O5, soluble% P2O5 27.16%% P2O5 parts - calcination at 625°C at last 1/2 hour [38–40].

In this study, bentonite type clay is used as salt slurry with char fine for emission control. The substrate fine of the bentonite/P2O5 granules use as absorbent in 2020s show improved treatment [24–30]. The industrial waste sludges in some tanning and wood board plants, airplane hangars, ship building bench, other production facilities required neutralization and further treatment. In the workshops, grease, oil, water, chemicals and other undesirable substances absorbed by compost of

Washing of hazardous waste waters by microwave action efficiencies exceeding the total Fe Pb and Hg contents of sludge increased fast on coal char and wood char were also reported by Tosun [6–10]. Material to be used as powder at porous granule at ultrafine grain size, basic as absorption capacity by the gas emission and other fluids reactive and solvents. High absorption capacity having clay, only to absorb the urea not ventilated, but bad reduce smell and bacteria should avoid. The packed grain size distribution of clay granules it is important that it is usually between 1

BET specifıc surface areas of sorbent as tested by N2 gas permeability. The sorbent was critical on the base of surface properties such as total surface activity, oxygen functional groups, total surface impurities, metal concentrations, dielectric value, free radical concentration and reactivity. The main chemical texture was related to the stimulation of oxidation reactivity. However, in some investigations, the pore size distribution of activated carbon is also likely to affect desorption

The salt slurries were mixed with activated clay bentonite at weight rates of 1/8. The head tests are caried out by CaCl2 adde 10000ppm slurries to 80 gr bentonite solid. The suspension of 80 gr slurry of clay and apatite was mixed in 1lt water as slurry and give through shower in 5 cm diameter glass columns. Finally microwave radiated glass showered to flue gas compressed at 2 bar retained by exposure to at 160 °C for 4 hours. In addition, these samples were further dried at the same temperature for 1 hour to remove vapor species. The experimentation unit as shown in **Figure 1**. The microwave salt slurry washing tests are followed by flowsheet as seen in **Figure 2**. The surface areas of the apatite, coal char, activated compost and shale clay samples were measured with a Quanta Chromosorb surface analyzer. The surface area was determined by measuring the thermal conductivity using a gas mixture prepared in N2 and Ar composition and taking into account the BET equation. The sorbent solids compositions and physical

**314**

kinetics.

*The schematic view of an washing with microwave recycled by microwave sorption technique.*

#### **Figure 2.**

*Studied washing by microwave sorption technique.*

#### **Table 1.**

*Sorbent types for washing treatment.*

**Table 2.**

*Phosphate, shale and Marly shale granules, physical packed properties.*

### **3.2 Ca phosphate/carbon compost sorbent applications**

During the experimental studies bentonite and phosphate samples, Ünye region, was investigated with intermediate type bentonite; pure, purified, tap water and CaCl2.2H2O, NaCl, MgCl2, KCl, FeCl3 at concentrations ranging from 125 mg to 1000 ppm. Bentonite suspensions prepared by adding waters such as suspensions decanted by sedimentation method for 30 minutes in a 2 lt scale and bentonite slurries were obtained and then necessary test and characterization procedures were applied afterwards.

Decantation was carried out in 2000 ml mills by adding 75 gr bentonite to 1900 ml of water. For a homogeneous suspension mortar, the bentonite water mixture was first subjected to salt slurry mixing cell for 5 minutes.

After the scurvy, the suspension was allowed to stand for 30 minutes after being agitated so that the impurities were precipitated. At the end of the period, suspended bentonite concentrate was removed by titration method and etch was dried.

The same procedure was repeated with synthetic waters prepared by adding salts at concentrations ranging from 125 ppm to 1000 ppm, until the bentonite slurry were obtained in sufficient quantities with salt slurry mixing water.

The layout of the washing cycle is somewhat simpler than that of the lime slurry: there was no water–compost washing column towers connected to the waste sludge, and the washing unit contained one single microwave radiation column can be used to perform the three decantation washing phases: roughing, scraping and cleaning. The variation of the third cycle washing was also more limited recycled by decantation.

The simple production presented as adapted and optimized depending on the target application. The main applications are briefly described in the following sections. Although this review only focuses on state-of-the art commercially available pellet plants, it should be noted that some prospective advanced applications for heat melting of binder are currently being studied, mainly in the form of prototypes proposed as seen in **Figure 3**. These innovative applications include:

**317**

*Apatite/Salt Slurry Emission Control of Post Combustion Flue Gas of Lignite and Coal…*

For an overview of these more innovative and prospective applications, the general common method can be given in first order linear concentration change. However sequential sorption cycles changed that trend in sorption of heavy metal

*Apatite and salt slurry gas washing plant for emission control of flue gas, proposed for silopi power plant.*

The first order sorption concentration at three stage cycling counted as t time

( ) ( ) Ca,,PO3,S2O3 = Qe Q − *dQ k*

k t Q Qe(1 ) − = − *e*

( ) 2 3 Ca,PO3,S2O3 1 2PO3 3S2O3 ln ( 1! 2! 3! =+ + + *Ca*

*k t ktk t c ab* (2)

*dt* (3)

(4)

*DOI: http://dx.doi.org/10.5772/intechopen.95296*

**4. Langmuir absorption model**

contents of gases.

**Figure 3.**

depended by the Eq. 3 below:

*Pb*

Qe: Equilibrium adsorption capacity (mg/g)

Q: Time adsorption capacity (mg/g)

*Apatite/Salt Slurry Emission Control of Post Combustion Flue Gas of Lignite and Coal… DOI: http://dx.doi.org/10.5772/intechopen.95296*

**Figure 3.** *Apatite and salt slurry gas washing plant for emission control of flue gas, proposed for silopi power plant.*