Review Special Issues

Optimization strategies of human mobility during the COVID-19 pandemic: A review


  • Received: 31 May 2021 Accepted: 30 August 2021 Published: 13 September 2021
  • The impact of the ongoing COVID-19 pandemic is being felt in all spheres of our lives – cutting across the boundaries of nation, wealth, religions or race. From the time of the first detection of infection among the public, the virus spread though almost all the countries in the world in a short period of time. With humans as the carrier of the virus, the spreading process necessarily depends on the their mobility after being infected. Not only in the primary spreading process, but also in the subsequent spreading of the mutant variants, human mobility plays a central role in the dynamics. Therefore, on one hand travel restrictions of varying degree were imposed and are still being imposed, by various countries both nationally and internationally. On the other hand, these restrictions have severe fall outs in businesses and livelihood in general. Therefore, it is an optimization process, exercised on a global scale, with multiple changing variables. Here we review the techniques and their effects on optimization or proposed optimizations of human mobility in different scales, carried out by data driven, machine learning and model approaches.

    Citation: Soumyajyoti Biswas, Amit Kr Mandal. Optimization strategies of human mobility during the COVID-19 pandemic: A review[J]. Mathematical Biosciences and Engineering, 2021, 18(6): 7965-7978. doi: 10.3934/mbe.2021395

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  • The impact of the ongoing COVID-19 pandemic is being felt in all spheres of our lives – cutting across the boundaries of nation, wealth, religions or race. From the time of the first detection of infection among the public, the virus spread though almost all the countries in the world in a short period of time. With humans as the carrier of the virus, the spreading process necessarily depends on the their mobility after being infected. Not only in the primary spreading process, but also in the subsequent spreading of the mutant variants, human mobility plays a central role in the dynamics. Therefore, on one hand travel restrictions of varying degree were imposed and are still being imposed, by various countries both nationally and internationally. On the other hand, these restrictions have severe fall outs in businesses and livelihood in general. Therefore, it is an optimization process, exercised on a global scale, with multiple changing variables. Here we review the techniques and their effects on optimization or proposed optimizations of human mobility in different scales, carried out by data driven, machine learning and model approaches.



    In mathematical analysis and its applications, the hypergeometric function plays a vital role. Various special functions which are used in different branches of science are special cases of hypergeometric functions. Numerous extensions of special functions have introduced by many authors (see [1,2,3,4]). The generalized Gamma k-function and its properties are broadly discussed in [5,6,7,8]. Later on, the researchers [9] motivated by the above idea and presented the k-fractional integral and its applications. The integral representation of generalized confluent hypergeometric and hypergeometric k-functions is presented by Mubeen and Habibullah [10]. The series solution of k-hypergeometric differential equation is proposed by Mubeen et al. [11,12,13]. Li and Dong [14] established the hypergeometric series solutions for the second-order non-homogeneous k-hypergeometric differential equation. The Generalized Wright k-function and its different indispensable properties are briefly discussed in [15,16]. A class of Whittaker integral transforms involving confluent hypergeometric function and Fox H-function as kernels are discussed in [17,18]. An extension of some variant of Meijer type integrals in the class of Bohemians is elaborated in [19].

    Generalization of Gr¨uss-type and Hermite-Hadamard type inequalities concerning with k-fractional integrals are explored in [20,21]. Many researchers have derived the generalized forms of the Riemann-Liouville k-fractional integrals and established several inequalities by considering various generalized fractional integrals. The readers may confer with [22,23,24,25,26] for details.

    The Hadamard k-fractional integrals and Hadamard-type inequalities for k-fractional Riemann-Liouville integrals are presented by Farid et al. [27,28]. In [29,30], the authors have established inequalities by employing Hadamard-type inequalities for k-fractional integrals. Nisar et al. [31] discussed Gronwall type inequalities by considering Riemann-Liouville k and Hadamard k-fractional derivatives. Hadamard k-fractional derivative and its properties are disscussed in [32]. Rahman et al. [33] described generalized k-fractional derivative operator.

    The Mittag-Leffler function naturally occurs in the solutions of fractional integrodifferential equations having an arbitrary order that is similar to that of the exponential function. The Mittag-Leffler functions have acquired significant recognition due to their wide applications in assorted fields. The Mittag-Leffler stability of fractional-order nonlinear dynamic systems is studied in [34]. Dos Santos discussed the Mittag-Leffler function in the diffusion process in [35]. The noteworthy role of the Mittag-Leffler function and its generalizations in fractional modelling is explored by Rogosin [36]. We suggest the readers to study the literature [37,38,39] for more details.

    Now, we present some basic definitions and results.

    The normalized Wright function is defined as

    Wγ,δ(z)=Γ(δ)n=0znΓ(δ+nγ)n!,γ>1,δC. (1.1)

    Fox [40] and Wright [41] defined the Fox-Wright hypergeometric function uψv as:

    uψv[(γ1,C1),.....,(γu,Cu)(δ1,D1)),.....,(δv,Dv)|z]=n=0ui=1Γ(γi+nCi)znvi=1Γ(δi+nDi)n!, (1.2)

    where Ci0,i=1,...,u;Di0,i=1,...,v. The function uψv is the generalized form of the well-known hypergeometric function uFv with u and v number of parameters in numerator and denominator respectively. It is given in [42] as:

    uFv[γ1,.....,γuδ1,.....,δv|z]=n=0ui=1   (γi)nznvi=1   (δi)nn!, (1.3)

    where (κ)n is called the Pochhammer symbol and is defined by Petojevic [43] as:

    (κ)0=1,and(κ)n=κ(κ+1).....(κ+n1)=Γ(κ+n)Γ(κ),nN.

    From definitions (1.2) and (1.3), we have the following relation

    uψv[(γ1,1),.....,(γu,1)(δ1,1),.....,(δv,1)|z]=Γ(γ1).....Γ(γu)Γ(δ1).....Γ(δv)uFv[γ1,.....,γuδ1,.....,δv|z]. (1.4)

    The Mittag-Leffler function with 2m parameters [44] is defined as follows:

    E(δ,D)m(z)=n=0znmi=1Γ(δi+nDi),zC (1.5)

    and in the form of Fox-Wright function it can be expressed as:

    E(δ,D)m(z)=1ψm[(1,1)(δ1,D1),.....,(δv,Dv)|z],zC. (1.6)

    The function ϕ(δ1,D1)(γ1,δ2):(0,)R is defined in [45] as

    ϕ(δ1,D1)(γ1,δ2)(z)=Γ(δ1)Γ(δ2)Γ(γ1)1ψ2[(γ1,1)(δ1,D1),(δ2,D2)|z],zC, (1.7)

    where γ1,δ1,δ2 and D1>0.

    Diaz and Pariguan [46] proposed the following Pochhammer's k-symbol (z)n,k and the generalized Gamma k-function by

    (u)n,k=u(u+k)(u+2k)....(u+(n1)k);uC,kR,nN+
    Γk(u)=limn=n!kn(nk)uk1u)n,k,k>0,uCkZ,

    respectively. They also introduced the generalized hypergeometric k-function in [46] as follows:

    uFv,k[(γ1,k),.....,(γu,k)(δ1,k),.....,(δv,k)|z]=n=0ui=1    (γi)n,k z nvi=1    (δi)n,k n!. (1.8)

    Now, we define the normalized Wright k-function as follows:

    Wγ,δ,k(z)=Γk(δ)n=0znΓk(δ+knγ)n!,γ>1,δC

    and the Fox -Wright type k-function is as follows:

    uψv[(γ1,kC1),.....,(γu,kCu)(δ1,kD1)),.....,(δv,kDv)|z]=n=0ui=1    Γk    (γi+nkCi)znvi=1    Γk    (δi+nkDi)n!, (1.9)

    So from Eqs (1.9) and (1.8), we have

    uψv,k[(γ1,k),.....,(γu,k)(δ1,k),.....,(δv,k)|z]=Γk(γ1).....Γk(γu)Γk(δ1).....Γk(δv)uFv,k[(γ1,k),.....,(γu,k)(δ1,k),.....,(δv,k)|z] (1.10)

    and (1.5) takes the form

    E(δ,D)m,k(z)=n=0znmi=1Γk(δi+nkDi),zC. (1.11)

    The function E(δ,D)m,k(z) in terms of the function uψv,k is expressed as

    E(δ,D)m,k(z)=1ψm,k[(1,k)(δ1,kD1),.....,(δv,kDv)|z]zC. (1.12)

    So the function (1.7) is given by

    ϕ(δ1,D1)γ1,δ2,k(z)=Γk(δ1)Γk(δ2)Γk(γ1)1ψ2,k[(γ1,k)(δ1,kD1),(δ2,k)|z]zC. (1.13)

    Redheffer [47] presented the following inequality in 1969,

    π2x2π2+x2sinxx. (1.14)

    In the same year, Redheffer and Williams [48] proved the above inequality. Zhu and Sun [49] used the hyperbolic functions sinhx and coshx and proved the following Redheffer-type inequalities

    (r2+x2r2x2)γsinhxx(r2+x2r2x2)δ (1.15)

    and

    (r2+x2r2x2)γcoshx(r2+x2r2x2)δ1, (1.16)

    where 0<x<r,γ0,δr212 and δ1r24. By using the inequalities (1.15) and (1.16), Mehrez proved the following Theorem (see[50]).

    Theorem 1.1. The following inequalities

    (s+zsz)σγ,δWγ,δ(z)(s+zsz)ργ,δ (1.17)

    holds true for all s>0, γ,δ>0, 0<z<s, where σγ,δ=0 and ργ,δ=sΓ(δ)2Γ(δ+γ) are the best possible constants and Wγ,δ is the normalized Wright function defined by (1.1).

    Recently, the same author has proved the following inequality (see[45]).

    Theorem 1.2. Suppose that r,γ1,δ1,δ2,D1>0. Then the subsequent inequalities

    (r+zrz)λ(δ1  ,D1)γ1,δ2ϕ(δ1,D1)γ1,δ2(z)(r+zrz)μ(δ1  ,D1)γ1,δ2 (1.18)

    are true for all z(0,r), where λ(δ1,D1)γ1,δ2=0 and μ(δ1,D1)γ1,δ2=rγ1Γ(δ1)2δ2Γ(δ1+D1) are the best possible constants. Where ϕ(δ1,D1)γ1,δ2(z) is defined in (1.7).

    In this article, we extend the Redheffer-type inequality (1.18) for the normalized Fox-Wright k-functions ϕ(δ1,D1)γ1,δ2,k(z) and establish new Redheffertype inequalities for the hypergeometric k-function 1F2,k and for the four parametric Mittag-Leffler k-function ˜Eδ1,D1;δ2,1,k(z)=Γk(δ1)Γk(δ2)Eδ1,D1;δ2,1,k(z).

    In this section, we first state the two lemmas which are helpful for proving the main results. The first lemma from [51] describes the monotonicity of two power series, and the second lemma is the monotone form of the L'Hospitals' rule [52]. The two lemmas are stated below.

    Lemma 2.1. Suppose that the two sequences {un}n0 and {vn}n0 of real numbers, and let the power series f(x)=n0unxn and g(x)=n0vnxn be convergent for |x|<r. If vn>0 for n0 and if the sequence {unvn}n0 is (strictly) increasing (decreasing), then the function xf(x)g(x) is (strictly) increasing (decreasing) on (0,r).

    Lemma 2.2. Suppose that the two functions f1,g1:[a,b]R be continuous and differentiable on (a,b). Assume that g10 on (a,b). If f1g1 is increasing (decreasing) on (a,b), then the functions

    xf1(x)f1(a)g1(x)g1(a)andxf1(x)f1(b)g1(x)g1(b)

    are also increasing (decreasing) on (a,b).

    Theorem 2.3. Letr>0γ1,δ1,δ2,D1>0. Then the following inequalities holds

    (r+zrz)λ(δ1  ,D1)γ1,δ2ϕ(δ1  ,D1)γ1,δ2,k(z)(r+zrz)μ(δ1  ,D1)γ1,δ2, (2.1)

    where z(0,r), λ(δ1,D1)γ1,δ2=0 and μ(δ1,D1)γ1,δ2=rγ1Γk(δ1)2δ2Γk(δ1+kD1) are the appropriate constants.

    Proof. From definition of the function ϕ(δ1,D1)γ1,δ2,k(z) from Eq (1.13), we have

    ddz(ϕ(δ1  ,D1)γ1,δ2,k(z))=Γk(δ1)Γk(δ2)Γk(γ1)×n=0Γk(γ1+(n+1)k)znΓk(δ1+D1(n+1)k)Γk(δ2+(n+1)k)n!. (2.2)

    Let

    M(z)=logϕ(δ  1,  D  1)γ  1  ,δ  2  ,k  (z)log(r+zrz)=g(z)h(z),

    where g(z)=log(ϕ(δ1,D1)γ1,δ2,k(z)) and h(z)=log(r+zrz). Now we will find g(z)h(z) as given below

    g(z)h(z)=(r2z2)ddz(ϕ(δ  1,  D  1)γ  1  ,δ  2  ,k  (z))2rϕ(δ  1  ,D  1)γ  1  ,δ  2  ,k  (z)=G(z)2rH(z),

    where G(z)=(r2z2)ddz(ϕ(δ1,D1)γ1,δ2,k) and H(z)=ϕ(δ1,D1)γ1,δ2,k(z)

    Using 2.2, we have

    G(z)=Γk(δ1)Γk(δ2)Γk(γ1)(r2z2)×n=0Γk(γ1+(n+1)k)znΓk(δ1+D1(n+1)k)Γk(δ2+(n+1)k)n!=Γk(δ1)Γk(δ2)Γk(γ1)(r2z2)(n=0Γk(γ1+(n+1)k)znΓk(δ1+D1(n+1)k)Γk(δ2+(n+1)k)n!n=2Γk(γ1+(n1)k)znΓk(δ1+D1(n1)k)Γk(δ2+(n1)k)(n2)!)=r2Γk(δ1)Γk(δ2)Γk(γ1+k)Γk(γ1)Γk(δ1+D1k)Γk(δ2+k)+r2Γk(δ1)Γk(δ2)Γk(γ1+2k)Γk(γ1)Γk(δ1+2D1k)Γk(δ2+2k)+Γk(δ1)Γk(δ2)Γk(γ1)n=2(r2Γk(γ1+(n+1)k)znΓk(δ1+D1(n+)k)Γk(δ2+(n+1)k)n!Γk(γ1+(n1)k)znΓk(δ1+D1(n1)k)Γk(δ2+(n1)k)(n2)!)zn=n=0vnzn,

    where b0, b1 and vn are as follows:

    b0=r2Γk(δ1)Γk(δ2)Γk(γ1+k)Γk(γ1)Γk(δ1+D1k)Γk(δ2+k),b1=r2Γk(δ1)Γk(δ2)Γk(γ1+2k)Γk(γ1)Γk(δ1+2D1k)Γk(δ2+2k)

    and for n2, we have

    vn=Γk(δ1)Γk(δ2)Γk(γ1)n=2(r2Γk(γ1+(n+1)k)Γk(δ1+D1(n+)k)Γk(δ2+(n+1)k)n!
    Γk(γ1+(n1)k)znΓk(δ1+D1(n1)k)Γk(δ2+(n1)k)(n2)!).

    Similarly, we can write H(z) as

    H(z)=n=0dnzn,

    where

    dn=Γk(δ1)Γk(δ2)Γk(γ1+nk)Γk(γ1)Γk(δ1+nkD1)Γk(δ2+nk).

    Next, we consider the sequence wn=vndn such that w0=a0 and w1=b1d1 and so on.

    Now, we have

    w1w0=r2Γk(δ2+k)Γk(γ1+2k)Γk(δ1+kD1)Γk(δ2+2k)Γk(δ1+2kD1)Γk(γ1+k)r2Γk(δ1)Γk(δ2)Γk(γ1+k)Γk(γ1)Γk(δ1+D1k)Γk(δ2+k)=r2(γ1+k)Γk(δ1+kD1)(δ2+k)Γk(δ1+2D1k)r2Γk(δ1)δ2)Γk(δ1+D1k)γ1δ2[Γk(δ1+kD1))Γk(δ1+2kD1)Γk(δ1)Γk(δ1+kD1)]0. (2.3)

    Since γ1δ2 and employing the log-convexity property of Γk function, the ratio zΓk(z+c)Γk(z) is increasing on (0,) for c>0. This shows that the inequality stated below

    Γk(z+c)Γk(z)Γk(z+c+d)Γk(z+d) (2.4)

    holds for all z,c,d>0. Using (2.4) in (2.3) by letting z=δ1 and c=d=kD1, we observed that w1w0. Likely, we have

    w2w1=r2Γk(γ1+3k)Γk(δ2+2k)Γk(δ1+2kD1)Γk(δ2+3k)Γk(δ1+3kD1)Γk(γ1+2k)r2Γk(δ2+k)Γk(δ1+kD1)Γk(γ1+2k)Γk(δ2+2k)Γk(δ1+2kD1)Γk(γ1+k)2Γk(δ2+2k)Γk(δ1+2kD1)Γk(γ1+k)Γk(δ2+k)Γk(δ1+kD1)Γk(γ1+2k)=r2(γ1+2k)Γk(γ1+2k)(δ2+k)Γk(δ2+k)Γk(δ1+2kD1)(δ2+2k)Γk(δ2+2k)Γk(δ1+3kD1)(γ1+k)Γk(γ1+k)r2Γk(δ2+k)Γk(δ1+kD1)Γk(γ1+2k)Γk(δ2+2k)Γk(δ1+2kD1)Γk(γ1+k)2Γk(δ2+2k)Γk(δ1+2kD1)Γk(γ1+k)Γk(δ2+k)Γk(δ1+kD1)Γk(γ1+2k)
    =r2Γk(γ1+2k)Γk(δ2+k)Γk(δ2+2k)Γk(γ1+k)[(γ1+2k)(δ2+k)Γk(δ1+2kD1)(γ1+k)(δ2+2k)Γk(δ1+3kD1)Γk(δ1+kD1)Γk(δ1+2kD1)]2Γk(δ2+2k)Γk(δ1+2kD1)Γk(γ1+k)Γk(δ2+k)Γk(δ1+kD1)Γk(γ1+2k)0. (2.5)

    Since by using Eq (2.4), when z=δ1+kD1 and c=d=kD1, we have w2w1.

    Now, for n2, we have

    wn+1wn=r2Γk(γ1+(n+2)k)Γk(δ2+(n+1)k)Γk(δ1+(n+1)kD1)Γk(γ1+(n+1)k)Γk(δ2+(n+1)k)Γk(δ1+(n+2)kD1)(n+1)!Γk(γ1+nk)Γk(δ2+(n+1)k)Γk(δ1+(n+1)kD1)(n1)!Γk(γ1+(n+1)k)Γk(δ2+nk)Γk(δ1+nkD1)r2Γk(γ1+(n+1)k)Γk(δ2+nk)Γk(δ1+nkD1)Γk(γ1+nk)Γk(δ2+(n+1)k)Γk(δ1+(n+1)kD1)+n!Γk(γ1+(n1)k)Γk(δ2+nk)Γk(δ1+nkD1)(n2)!Γk(γ1+nk)Γk(δ2+(n11)k)Γk(δ1+(n1)kD1)=r2[(γ1+(n+1)k)Γk(δ1+(n+1)kD1)(δ2+(n+1)k)Γk(δ1+(n+2)kD1)(γ1+n)k)Γk(δ1+nkD1)(δ2+nk)Γk(δ1+(n+1)kD1)]+n!(n2)![(δ2+(n1)k)Γk(δ1+nkD1)(γ1+(n1)k)Γk(δ1+(n2)kD1)(n+1)(δ2+n)k)Γk(δ1+(n+1)kD1)(n1)(γ1+nk)Γk(δ1+nkD1)]r2(γ1+nk)(δ2+nk)[Γk(δ1+(n+1)kD1)Γk(δ1+(n+2)kD1)Γk(δ1+nkD1)Γk(δ1+(n+1)kD1)]+n!(δ2+(n1)k)(n2)!(γ+(n1)k)[Γk(δ1+nkD1)Γk(δ1+(n1)kD1)Γk(δ1+(n+1)kD1)Γk(δ1+nkD1)] (2.6)

    Using z=δ1+nkD1 and c=d=kD1, we have the inequality (2.4) in the following form

    Γk(δ1+(n+2)kD1)Γk(δ1+nkD1)Γ2k(δ1+(n+1)kD1)0 (2.7)

    and similarly for using z=δ1+(n1)kD1 and c=d=kD1, we have from (2.4)

    Γk(δ1+(n+2)kD1)Γk(δ1+nkD1)Γ2k(δ1+(n+1)kD1)0 (2.8)

    so by using (2.7) and (2.8) in (2.6), we have

    wn+1wn. (2.9)

    Now from Eqs (2.3), (2.10) and (2.9), we conclude that the sequence {wn}n0 is a decreasing sequence.

    From Lemma (2.1), we deduce that gh is decreasing on (0,r) and accordingly the function M(z) is also decreasing on (0,r). Alternatively, using the Bernoulli-L'Hospital's rule we get

    limz0M(z)=rγ1Γk(δ1)2δ2Γk(δ1+kD1)andlimz0M(z)=0.

    It is essential to reveal that there is another proof of this theorem which is described as following.

    For this, we define a function Υ:(0,r)R by

    Υ(z)=rγ1Γk(δ1)2δ2Γk(δ1+D1)log(r+zrz)log(ϕ(δ1,kD1)γ1,δ2,k(z)).

    Consequently,

    ϕ(δ1,kD1)γ1,δ2,k(z)Υ(z)=r2γ1Γk(δ1)δ2Γk(δ1+D1)(r2z2)ϕ(δ1,D1)γ1,δ2,k(z)ddz(ϕ(δ1,D1)γ1,δ2,k(z))=Γk(δ1)Γk(δ2)Γk(γ1)[r2γ1Γk(δ1)δ2Γk(δ1+kD1)(r2z2)n=0Γk(γ1+nk)znΓk(δ1+D1nk)Γk(δ2+nk)n!n=0Γk(γ1+(n+1)k)znΓk(δ1+D1(n+1)k)Γk(δ2+(n+1)k)n!]Γk(δ1)Γk(δ2)Γk(γ1)[γ1Γk(δ1)δ2Γk(δ1+kD1)n=0Γk(γ1+nk)znΓk(δ1+D1nk)Γk(δ2+nk)n!n=0Γk(γ1+(n+1)k)znΓk(δ1+D1(n+1)k)Γk(δ2+(n+1)k)n!]=Γk(δ1)Γk(δ2)Γk(γ1)n=0Γk(γ1+nk)znΓk(δ2+nk)n![γ1Γk(δ1)δ2Γk(δ1+kD1)(γ1+nk)(δ2+nk)Γk(δ1+D1(n+1)k)]. (2.10)

    Since γ1δ2, therefore γ1δ2γ1+nkδ2+nk for every n0 and resultantly

    ϕ(δ1,D1)γ1,δ2,k(z)Υ(z)Γk(δ1)Γk(δ2)Γk(γ1)n=0Γk(γ1+nk)znΓk(δ2+nk)n![Γk(δ1)Γk(δ1+kD1)1Γk(δ1+kD1(n+1))].

    Now, using the values z=δ1,c=kD1 and d=nkD1 in (2.4), function Υ(z) is increasing on (0,r) and consequently Υ(z)Υ(0)=0. This completes the proof of right hand side of the inequality 2.1. For proving the left hand side of (2.1), we conclude from Eq (2.2) that the function ϕ(δ1,D1)γ1,δ2,k(z) is increasing on (0,) and finally

    ϕ(δ1,D1)γ1,δ2,k(z)ϕ(δ1,D1)γ1,δ2,k(0)=1.

    This ends the proof process of theorem 2.3.

    Corollary 2.4. Let r,γ1,δ1,δ2>0. Then inequalities

    (r+zrz)λ(δ1,1)γ1,δ21F2,k(γ1;δ1,δ2;z)(r+zrz)μ(δ1,1)γ1,δ2,

    are true for all z(0,r), where λ(δ1,1)γ1,δ2=0 and μ(δ1,1)γ1,δ2=rγ12δ2δ1 are the suitable values of constants.

    Proof. This inequality can be proved by using D1=1 in (2.1).

    Corollary 2.5. Let r,δ1,D1>0. If 0<δ21, then the following inequalities

    (r+zrz)λ(δ1,D1)1,δ2˜Eδ1,D1;δ2,1,k(z)(r+zrz)μ(δ1,D1)1,δ2,

    hold for all z(0,r), where λ(δ1,D1)1,δ2=0 and μ(δ1,D1)1,δ2=rΓk(δ1)2δ2Γk(δ1+kD1) are the suitable values of constants.

    Proof. This inequality can be proved by using γ1=1 in (2.1).

    Remark 2.6. The particular cases of the inequalities in Corollaries 2.4 and 2.5 for k=1 are reduce to the results in [45,Corollaries 1.2 and 1.3] respectively.

    This article deals with the Redheffer-type inequalities by using the more general Fox-Wright function. Moreover, from the newly established inequalities, the results for generalized hypergeometric functions and the four-parametric generalized Mittag-Leffler functions are also obtained by using the appropriate values of exponents in generalized inequalities. The obtained results are more general, as shown by relating the special cases with the existing literature. The idea we used in this article attracts scientists' attention, and they may stimulate further research in this direction.

    Taif University Researchers Supporting Project number (TURSP-2020/275), Taif University, Taif, Saudi Arabia.

    The authors declares that there is no conflict of interests regarding the publication of this paper.



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