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Review

Innovations in extractable compounds from date seeds: Farms to future

  • Since ancient times, date fruit has been used as a staple food because of its high nutritional value and caloric content. With the development of food science and the application of modern instrumentation, we now know that date seeds contain large amounts of dietary fiber, phenols, polyphenols, amino acids, fatty acids, and many vitamins and minerals. Due to the presence of these functional food ingredients, date seeds are used in various applications, including foods such as bread, hot beverages, cosmetics such as hair and skin products, and as feed for culturing aquatic animals. Date seeds have been used in clinical applications, making use of their antioxidant, anti-inflammatory, anti-cancer, anti-diabetic, and antimicrobial properties. There is now growing awareness of the value of date seeds, which were considered a waste product. In this review, we focused on explaining the major biochemical constituents of date seeds and developing these constituents for various applications. We also highlight the expected developments in date seed use for the future.

    Citation: Asma Hussain Alkatheri, Mahra Saleh Alkatheeri, Wan-Hee Cheng, Warren Thomas, Kok-Song Lai, Swee-Hua Erin Lim. Innovations in extractable compounds from date seeds: Farms to future[J]. AIMS Agriculture and Food, 2024, 9(1): 256-281. doi: 10.3934/agrfood.2024016

    Related Papers:

    [1] Mohammad M. Al-Gharabli, Adel M. Al-Mahdi, Mohammad Kafini . Global existence and new decay results of a viscoelastic wave equation with variable exponent and logarithmic nonlinearities. AIMS Mathematics, 2021, 6(9): 10105-10129. doi: 10.3934/math.2021587
    [2] Qian Li . General and optimal decay rates for a viscoelastic wave equation with strong damping. AIMS Mathematics, 2022, 7(10): 18282-18296. doi: 10.3934/math.20221006
    [3] Salim A. Messaoudi, Mohammad M. Al-Gharabli, Adel M. Al-Mahdi, Mohammed A. Al-Osta . A coupled system of Laplacian and bi-Laplacian equations with nonlinear dampings and source terms of variable-exponents nonlinearities: Existence, uniqueness, blow-up and a large-time asymptotic behavior. AIMS Mathematics, 2023, 8(4): 7933-7966. doi: 10.3934/math.2023400
    [4] Adel M. Al-Mahdi . The coupling system of Kirchhoff and Euler-Bernoulli plates with logarithmic source terms: Strong damping versus weak damping of variable-exponent type. AIMS Mathematics, 2023, 8(11): 27439-27459. doi: 10.3934/math.20231404
    [5] Zayd Hajjej, Sun-Hye Park . Asymptotic stability of a quasi-linear viscoelastic Kirchhoff plate equation with logarithmic source and time delay. AIMS Mathematics, 2023, 8(10): 24087-24115. doi: 10.3934/math.20231228
    [6] Mohammad Kafini, Mohammad M. Al-Gharabli, Adel M. Al-Mahdi . Existence and stability results of nonlinear swelling equations with logarithmic source terms. AIMS Mathematics, 2024, 9(5): 12825-12851. doi: 10.3934/math.2024627
    [7] Qian Li, Yanyuan Xing . General and optimal decay rates for a system of wave equations with damping and a coupled source term. AIMS Mathematics, 2024, 9(10): 29404-29424. doi: 10.3934/math.20241425
    [8] Khaled Kefi, Abdeljabbar Ghanmi, Abdelhakim Sahbani, Mohammed M. Al-Shomrani . Infinitely many solutions for a critical p(x)-Kirchhoff equation with Steklov boundary value. AIMS Mathematics, 2024, 9(10): 28361-28378. doi: 10.3934/math.20241376
    [9] Soh E. Mukiawa, Tijani A. Apalara, Salim A. Messaoudi . Stability rate of a thermoelastic laminated beam: Case of equal-wave speed and nonequal-wave speed of propagation. AIMS Mathematics, 2021, 6(1): 333-361. doi: 10.3934/math.2021021
    [10] Keltoum Bouhali, Sulima Ahmed Zubair, Wiem Abedelmonem Salah Ben Khalifa, Najla ELzein AbuKaswi Osman, Khaled Zennir . A new strict decay rate for systems of longitudinal m-nonlinear viscoelastic wave equations. AIMS Mathematics, 2023, 8(1): 962-976. doi: 10.3934/math.2023046
  • Since ancient times, date fruit has been used as a staple food because of its high nutritional value and caloric content. With the development of food science and the application of modern instrumentation, we now know that date seeds contain large amounts of dietary fiber, phenols, polyphenols, amino acids, fatty acids, and many vitamins and minerals. Due to the presence of these functional food ingredients, date seeds are used in various applications, including foods such as bread, hot beverages, cosmetics such as hair and skin products, and as feed for culturing aquatic animals. Date seeds have been used in clinical applications, making use of their antioxidant, anti-inflammatory, anti-cancer, anti-diabetic, and antimicrobial properties. There is now growing awareness of the value of date seeds, which were considered a waste product. In this review, we focused on explaining the major biochemical constituents of date seeds and developing these constituents for various applications. We also highlight the expected developments in date seed use for the future.



    The importance of partial differential equations in comprehending and explaining physical interpretation of problems that arise in numerous fields and engineering motivates many researchers to analyze and investigate the existence and stability of their solutions. Hyperbolic partial differential equations are the most interesting kind of partial differential equations, since they are utilized to simulate a wide and important collection of phenomena, such as aerodynamic flows, fluid and contaminant flows through porous media, atmospheric flows, and so on. Of the higher order hyperbolic equations, the wave equation is the most obvious. Klein-Gordon, Telegraph, sine-Gordon, Van der Pol, dissipative nonlinear wave and others are well-known hyperbolic equations that are important in the fields of wave propagation [1], random walk theory [2], signal analysis [3], relativistic quantum mechanics, dislocations in crystals and field theory [4], quantum field theory, solid-state physics, nonlinear optics [5], mathematical physics [6], solitons and condensed matter physics [7], interaction of solitons in collision-less plasma [8], fluxions propagation in Josephson junctions between two superconductors [9], motion of a rigid pendulum coupled to a stretched wire [10], material sciences [11] and non-uniform transmission lines [12] are some of the topics covered. For more related results, we refer to [13,14,15]. There is a vast range of publications for numerical solutions of hyperbolic partial differential equations, such as the one in [16,17,18,19,20,21]. In recent years, great efforts have been devoted to study problems with nonlinear dampings and source terms, and several existence, decay and blow up results have been established. Georgiev and Todorova [22] considered the following nonlinear problem

    {uttΔu+h(ut)=F(u),onΩ×(0,T)u=0,onΩ×(0,T)u(x,0)=u0(x),ut(x,0)=u1(x),onΩ, (1.1)

    where the damping term h(ut)=|ut|m2ut and the source term F(u)=|u|q2u are localized on the domain and established global existence when qm and a blow up result when q>m. This work was improved by Levine and Serrin [23] to the case of negative energy and m>1. For problems with boundary damping and source terms, we mention the work of Vitillaro [24] who considered the following problem

    {uttΔu=0,onΩ×(0,T)un+h(ut)=F(u),onΓ1×(0,T)u=0,onΓ0×(0,T)u(x,0)=u0(x),ut(x,0)=u1(x),onΩ. (1.2)

    where the damping term h(ut)=|ut|m2ut and the source term F(u)=|u|q2u are localized on a part of the boundary. The author established local existence and global existence of the solutions under some suitable conditions on the initial data and the exponents. In the presence of the viscoelastic term, Cavalcanti et al. [25] discussed the following problem

    {uttΔu+t0g(ts)Δu(s)ds=0,onΩ×(0,T)unt0g(ts)unds+h(ut)=0,onΓ1×(0,T)u=0,onΓ0×(0,T)u(x,0)=u0(x),ut(x,0)=u1(x),onΩ, (1.3)

    In this work, a global existence result for strong and weak solutions was established and some uniform decay rates were proved under some assumptions on g and h. Al-Gharabli et al. [26] established general and optimal decay result for the same problem (1.3) considered in [25] where the relaxation g satisfies more general conditions than the one in [25]. For more results in this direction, we refer to [27,28,29,30,31]. In particular, Liu and Yu [31] investigated the following problem

    {uttΔu+t0g(ts)Δu(s)ds=0,onΩ×(0,T)unt0g(ts)unds+h(ut)=F(u),onΓ1×(0,T)u=0,onΓ0×(0,T)u(x,0)=u0(x),ut(x,0)=u1(x),onΩ, (1.4)

    where the damping term h(ut)=|ut|m2ut and the source term F(u)=|u|q2u are localized on a part of the boundary, and established several decay and blow up results under some suitable conditions on the initial data, the relaxation function and the exponents. Notice here that both the damping and source terms in [31] are localized on a part of the boundary, although, they are of constant nonlinearity. Moreover, the relaxation function g satisfies the condition

    g(t)ξ(t)g(t),t0, (1.5)

    where ξ is a positive differentiable function. In fact, Liu and Yu [31] used the Multiplier method for stability and the potential well technique to prove the existence of the global solution. Moreover, the authors established a general decay when m2 and an exponential decay m=2.

    Many new real-world problems, such as electro-rheological fluid flows, fluids with temperature-dependent viscosity, filtration processes through porous media, image processing, hemorheological fluids, and others, came as a result of advances in science and technology, such as those problems which required modeling with non-standard mathematical functional spaces. The Lebesgue and Sobolev spaces with variable exponents [32,33,34,35] have shown to be very important and user-friendly tools to tackle such models. PDEs with variable exponents have recently attracted a lot of attention from researchers and academics. However, the majority of the findings for hyperbolic issues with variable exponents dealt with blow-up and non-global existence. On the stability of nonlinear damped wave equations with variable exponent nonlinearities, we only have a few results. It is worth mentioning the work of Messaoudi et al. [36], who explored the stability of the following equation

    uttdiv(|u|r()2u)+|ut|m()2ut=0,

    where m()r()2. The authors in their work showed that the solution energy decays exponentially if m2 and when m2=esssupxΩm(x)>2, they obtained a polynomial decay at the rate of t2/(m22). Also, Ghegal et al. [37] established a stability result similar to that of [36] for the equation

    uttΔu+|ut|m()2ut=|u|q()2u,

    and proved under appropriate conditions on m(),q(), and the initial data, a global existence result. Messaoudi et al. [38] recently looked at the following problem

    uttΔu+t0g(ts)Δu(s)ds+a|ut|m()2ut=|u|q()2u,

    and used the well-depth approach to verify global existence and provide explicit and general decay results under a very general relaxation function assumption.

    In our present work, we are concerned with the following problem

    {uttΔu+t0g(ts)Δu(s)ds=0,onΩ×(0,T)unt0g(ts)unds+|ut|m(x)2ut=|u|q(x)2u,onΓ1×(0,T)u=0,onΓ0×(0,T)u(x,0)=u0(x),ut(x,0)=u1(x),onΩ, (1.6)

    on a bounded domain ΩRn with a smooth boundary Ω=Γ0Γ1 where Γ0 and Γ1 are closed and disjoint and meas.(Γ0)>0. The vector n is the unit outer normal to Ω. The function g is a relaxation function and u0 and u1 are given data. The functions m() and q() are the variable exponents. System 1.6 describes the spread of strain waves in a viscoelastic configuration. We first prove a global existence result for the solutions of problem (1.6) by using the potential well theory. Then we establish explicit and general decay results of problem (1.6) for a larger class of relaxation functions (see Assumption A1 below). To back up our theoretical decay results, we provide two numerical tests. Our decay results extend and improve some earlier results such as the one of Cavalcanti et al. [25], Al-Gharabli et al. [26], Liu and Yu [31] and the one of Messaoudi et al. [39]. In our work, we apply the energy approach (Multiplier Method), combined with various differential and integral inequalities equipped with the Lebesgue and Sobolev spaces with variable exponents. The multiplier method relies mostly on the construction of an appropriate Lyapunov functional L equivalent to the energy of the solution E. By equivalence LE, we mean

    α1E(t)L(t)α2E(t),tR+, (1.7)

    for two positive constants α1 and α2. To prove the exponential stability, we show that L satisfies

    L(t)c1L(t),tR+, (1.8)

    for some c1>0. A simple integration of (1.8) over (0,t) together with (1.7) gives the desired exponential stability result. In the case of a general decay result, we prove that L satisfies a differential inequality that combines the relaxation function and the other terms coming from the nonlinearites. Then we use some properties of the convex functions and other mathematical arguments to obtain general decay estimates depending on the relaxation function and the nature of the variable exponent nonlinearity. In fact, the Multiplier Method proved to be efficient in tackling such problems with dissipative terms either on the domain or in a part of the boundary. In the present paper, some properties of the convex functions are exploited. We also use the well-depth method to establish the global existence of the solutions. We show that the methods and tools used in this paper are sufficient to handle our problem and are less complicated than other methods which guide us to our target.

    Related results to our problem

    ● Cavalcanti et al. [25] and Al-Gharabli et al. [26] investigated the same problem. However, in [25] and [26], the nonlinear damping term is h(ut) which satisfies some specific conditions. In our case h(ut)=|ut|m()2ut where m() is a function of x where x is in a part of the boundary which makes our problem more complicated especially in the numerical computations. Additionally, in [25] the class of the relaxation function is a special case of the one in our paper. The decay results in both [25] and [26] were without numerical tests and without nonlinear source term.

    ● Liu and Yu [31] investigated the same problem where the exponents m and q are of constant nonlinearity and the relaxation function g satisfies the condition g(t)ξ(t)g(t). In our paper, we extend the work of Liu and Yu [31] in which the exponents m() and q() are functions of x where x is in a part of the boundary. Moreover, we use a wider class of relaxation functions; that is g(t)ξ(t)H(g(t)) so that the class of the relaxation function in [31] is a special case. In addition, we provide some numerical experiments to illustrate our decay theories.

    ● Messaoudi et al. [38] investigated a similar problem. However, the nonlinear damping terms are in the domain. In our case the nonlinear damping and source terms are localized in the boundary, which makes the computations are more difficult. Also, [38] did not provide numerical computation.

    The remainder of this work is arranged in the following manner: In Section 2, we write some of the assumptions and materials that are needed for our work. In Section 3, we establish and prove the global existence result. In Section 4, we present our main decay result as well as some examples. Section 5 presents and proves some technical lemmas. In Section 6, we prove the main decay results. Finally, in Section 7, we show numerical simulations to support our theoretical findings.

    In this section, we present some background information on the Lebesgue and Sobolev spaces with variable exponents (see [40,41]) as well as some assumptions for the main result proofs. We will use the letter c to denote a generic positive constant.

    Definition 2.1.

    1. The space H1Γ0(Ω)={uH1(Ω):u|Γ0=0} is a Hilbert space endowed with the equivalent norm u22.

    2. Let β:Γ1[1,] be a measurable function, where Ω is a domain of Rn, then:

    a. the Lebesgue space with a variable exponent β() is defined by

    Lβ()(Γ1):={v:Γ1R;measurable inΩ:ϱβ()(αv)<,for someα>0},

    where ϱβ()(v)=Ω1β(x)|v(x)|β(x)dx is a modular.

    b. the variable-exponent Sobolev space W1,β()(Γ1) is:

    W1,β()(Γ1)={vLβ()(Γ1)such thatvexistsand|v|Lβ()(Γ1)}.

    3. W1,β()0(Γ1) is the closure of C0(Γ1) in W1,β()(Γ1).

    Remark 2.2. [42]

    1. Lβ()(Γ1) is a Banach space equipped with the following norm

    vβ():=inf{λ>0:Ω|v(x)α|β(x)dx1},

    2. W1,β()(Γ1) is a Banach space with respect to the norm

    vW1,β()(Ω)=vβ()+vβ().

    We define

    β1:=essinfxΩβ(x),β2:=esssupxΩβ(x).

    Lemma 2.3. [42] If β:Γ1[1,) is a measurable functionwith β2<, then C0(Γ1) is dense in Lβ()(Γ1).

    Lemma 2.4. [42] If 1<β1β(x)β2< holds, then

    min{wβ1β(),wβ2β()}ϱβ()(w)max{wβ1β(),wβ2β()},

    for any wLβ()(Γ1).

    Lemma 2.5 (Hölder's Inequality). [42] Let α,β,γ1 be measurable functions defined on Ω such that

    1γ(y)=1α(y)+1β(y),for a.e.yΩ.

    If fLα()(Ω) and gLβ()(Ω), then fgLγ()(Ω) and

    fgγ()2fα()gβ().

    Lemma 2.6. [42] [Poincaré's Inequality]Let Ω be a bounded domain of Rn and p() satisfies (2.4), then, there exists cρ, such that

    vp()cρvp(),for allvW1,p()0(Ω).

    Lemma 2.7. [42] [Embedding Property] Let Ω be a bounded domain in Rn with a smoothboundary Ω. Assume that p,kC(¯Ω) such that

    1<p1p(x)p2<+,1<k1k(x)k2<+,x¯Ω,

    and k(x)<p(x) in ¯Ω with

    p(x)={np(x)np(x),if p2<n;+,if p2n,

    then we have continuous and compact embedding W1,p(.)(Ω)Lk(.)(Ω). So, thereexists ce>0 such that

    vkcevW1,p(.),vW1,p(.)(Ω). (2.1)

    Assumptions

    The following assumptions are essential in the proofs of the main results in this work.

    (A1) The relaxation function g:R+R+ is a C1 nonincreasing function satisfying

    g(0)>0,10g(s)ds=>0, (2.2)

    and there exists a C1 function Ψ:(0,)(0,) which is linear or it is strictly increasing and strictly convex C2 function on (0,r] for some 0<rg(0), with Ψ(0)=Ψ(0)=0, lims+Ψ(s)=+, ssΨ(s) and ss(Ψ)1(s) are convex on (0,r] and there exists a a C1 nonincreasing function ϑ such that

    g(t)ϑ(t)Ψ(g(t)),t0. (2.3)

    (A2) m:¯Γ1[1,) is a continuous function such that

    m1:=essinfxΓ1m(x),m2:=esssupxΓ1m(x).

    and 1<m1<m(x)m2, where

    {m2<,n=1,2;m22nn2,n3.

    (A3) q:¯Ω[1,) is a continuous function such that 2<q1<q(x)<q2, where

    {q2<,n=1,2;q22nn2,n3.

    (A4) The variable exponents m and q are given continuous functions on ¯Γ1 satisfying the log-Hölder continuity condition:

    |β(x)β(y)|clog|xy|,for allx,yΩ,with|xy|<δ, (2.4)

    where c>0 and 0<δ<1.

    Remark 2.8. [43] Using (A1), one can prove that, for any t[0,t0],

    g(t)ϑ(t)Ψ(g(t))aϑ(t)=ag(0)ϑ(t)g(0)ag(0)ϑ(t)g(t)

    and, hence,

    ϑ(t)g(t)g(0)ag(t),t[0,t0]. (2.5)

    Moreover, we can define ˉΨ, for any t>r, by

    ˉΨ(t):=Ψ(r)2t2+(Ψ(r)Ψ(r)r)t+(Ψ(r)+Ψ(r)2r2Ψ(r)r).

    where ˉΨ:[0,+)[0,+), is a strictly convex and strictly increasing C2 function on (0,), is an extension of Ψ and Ψ is defined in (A1).

    We introduce the "modified energy" associated to our problem

    E(t)=12[ut22+(gu)(t)+(1t0g(s)ds)u22Γ11q(x)|u|q(x)dx], (2.6)

    where for vL2loc(R+;L2(Ω)),

    (gv)(t):=t0g(ts)v(t)v(s)22ds.

    A direct differentiation, using (2.6), leads to

    E(t)=12g(t)u22Γ1|ut|m(x)dx+12(gu)(t)0. (2.7)

    Lemma 2.9. [43] Under the assumptions in (A1), we have, for any tt0,

    ϑ(t)t00g(s)u(t)u(ts)22dscE(t).

    The local existence theorem is stated in this section, and its proof can be demonstrated by combining the arguments of [44,45,46]. We also state and show a global existence result on the initial data under smallness conditions on (u0,u1).

    Theorem 3.1 (Local Existence). Given (u0,u1)H1Γ0(Ω)×L2(Ω) andassume that (A1)(A4) hold. Then, there exists T>0, suchthat problem (1.6) has a weak solution

    uC((0,T),H1Γ0(Ω))C1((0,T),L2(Ω)),utLm(.)(Γ1×(0,T)).

    We will now go over the following functionals:

    J(t)=12((gu)(t)+(1t0g(s)ds)u22)1q1Γ1|u|q(x)dx (3.1)

    and

    I(t)=I(u(t))=(gu)(t)+(1t0g(s)ds)u22Γ1|u|q(x)dx. (3.2)

    Clearly, we have

    E(t)J(t)+12ut22. (3.3)

    Lemma 3.2. Suppose that (A1)(A4) hold and (u0,u1)H1Γ0(Ω)×L2(Ω), such that

    cq2eEq222(0)+cq2eEq122(0)<,I(u0)>0, (3.4)

    then

    I(u(t))>0,t>0.

    Proof. Sine I is continuous and I(u0)>0, then there exists Tm<T such that

    I(u(t))0, t[0,Tm];

    which gives

    J(t)=1q1I(t)+q122q1[(gu)(t)+(1t0g(s)ds)u22]q122q1[(gu)(t)+(1t0g(s)ds)u22] (3.5)

    Now,

    u22(1t0g(s)ds)u222q1q12J(t)2q1q12E(t)2q1q12E(0). (3.6)

    Using Youngs and Poincaré inequalities and the trace theorem, we get t[0,Tm],

    Γ1|u|q(x)dx=Γ+1|u|q(x)dx+Γ1|u|q(x)dxΓ+1|u|q2dx+Γ1|u|q1dxΓ1|u|q2dx+Γ1|u|q1dxcq2euq22+cq1euq12(cq2euq222+cq1euq122)u22<u22(1t0g(s)ds)u22, (3.7)

    where

    Γ1={xΓ1:|u(x,t)|<1}andΓ+1={xΓ1:|u(x,t)|1}.

    Therefore,

    I(t)=(gu)(t)+(1t0g(s)ds)u221q1Γ1|u|q(x)>0.

    Notice that (3.7) shows that uLq()(Γ1×(0,T)).

    Proposition 3.3. Suppose that (A1)(A4) hold. Let (u0,u1)H1Γ0(Ω)×L2(Ω) be given, satisfying (3.4). Then the solution of (1.6) is global andbounded.

    Proof. It suffices to show that u22+ut22 is bounded independently of t. To achieve this, we use (2.7), (3.2) and (3.5) to get

    E(0)E(t)=J(t)+12ut22q122q1(u22+(gu)(t))+12ut22+1q1I(t)q122q1u22+12ut22. (3.8)

    Since I(t) and (gu)(t) are positive, Therefore

    u22+ut22CE(0),

    where C is a positive constant, which depends only on q1 and and the proof is completed.

    Remark 3.4. Using (3.6), we have

    u222q1(q12)E(0). (3.9)

    In this section, we state our decay result and provide some examples to illustrate our theorems.

    Theorem 4.1 (The case: m12). Assume that (A1)(A4) and (3.4) hold. Let(u0,u1)H1Γ0(Ω)×L2(Ω). Then, there exist positive constants λ1, λ2, λ3,λ4 such that

    E(t)λ1eλ2tt0ϑ(s)ds,t>t0, ifΨ is linear; (4.1)

    and

    E(t)λ3Ψ10(λ4tt0ϑ(s)ds),t>t0, ifΨ is nonlinear; (4.2)

    where Ψ0(s)=rt1sΨ(s)ds and r=g(t0).

    Theorem 4.2 (The case: 1<m1<2). Assume that (A1)(A4) and (3.4) hold. Let (u0,u1)H1Γ0(Ω)×L2(Ω). Then, there exist positive constants β1, β2,β3 and t1>t0 such that

    E(t)β1(tt0ϑ(s)ds)m11,t>t0, ifΨ is linear, (4.3)

    and, if Ψ is nonlinear, we have

    E(t)β2(tt0)2m1Ψ11[1β3((tt0)m12m11tt1ϑ(s)ds)],t>t1, (4.4)

    where Ψ1(τ)=τ1m11Ψ(τ).

    Example 1 (The case: m12). ● We consider g(t)=aeσt, t0, where a,σ>0 and a is chosen in such a way that (A1) is hold, then

    g(t)=σΨ(g(t))withϑ(t)=σandΨ(s)=s.

    So, (4.1) gives, for d1,d2>0

    E(t)d1ed2t,t>t0.

    Let g(t)=ae(1+t)ν, for t0, 0<ν<1 and a is chosen so that condition (A1) is satisfied. Then

    g(t)=ϑ(t)Ψ(g(t))withϑ(t)=ν(1+t)ν1andΨ(s)=s.

    Hence, (4.1) implies, for some C>0,

    E(t)Cec(1+t)ν.

    For ν>1, let

    g(t)=a(1+t)ν,t0

    and a is chosen so that hypothesis (A1) remains valid. Then

    g(t)=ρΨ(g(t))withϑ(t)=ρandΨ(s)=sp,

    where ρ is a fixed constant, p=1+νν which satisfies 1<p<2. Therefore, by estimate (4.2), we have

    E(t)C(1+t)ν,t>t0.

    Example 2 (The case: 1<m1<2). ● Consider g(t)=αeσ(1+t)ν,t0,0<ν<1,α,σ>0, and α is chosen so that (A1) holds, then g(t)=σΨ(g(t)) with ϑ(t)=ν(1+t)ν1 and Ψ(s)=s. We next infer that the solution of (1.6) satisfies the following energy estimate under the conditions of Theorem 4.2

    E(t)C(tt0)m11,t>t1.

    Let

    g(t)=α(1+t)ν,ν>1,

    and α is chosen such that hypothesis (A1) remains valid. Then

    g(t)=σΨ(g(t))withϑ(t)=σandΨ(s)=sp,p=1+νν

    where σ is a fixed constant. Then, we conclude for t large enough and some constant C>0 that the solution of (1.6) satisfies the following energy estimate under the conditions of Theorem 4.2

    E(t)C(tt0)λ,

    where λ=(m11)(m1+ν2)m1+ν1>0.

    The proofs of Theorem 4.1 and Theorem 4.2 will be done through several Lemmas.

    We establish various lemmas for our proofs in this section.

    Lemma 5.1 ([47]). Assume that (A1) holds. Then for any 0<ε<1, we have

    Cε(hεv)(t)L0(t0g(ts)(v(t)v(s))ds)2dx,t0. (5.1)

    where

    Cε:=0g2(s)hε(t)dsandhε(t):=εg(t)g(t).

    Lemma 5.2. Assume that (A1)(A4) and (3.4) hold, the functional

    F1(t):=Ωuutdx

    satisfies the estimates:

    F1(t)4||u(t)||22+||ut||22+cCε(hεu)(t)+Γ1|u|q(x)dx+cΓ1|ut|m(x)dx,for m12, (5.2)
    F1(t)4||u(t)||22+||ut||22+cCε(hεu)(t)+Γ1|u|q(x)dx+cΓ1|ut|m(x)dx+(Γ1|ut|m(x))m11,for 1<m1<2. (5.3)

    Proof. By differentiating F1 and using (1.6), we get

    F1(t)=Ωu(t)t0g(ts)(u(s)u(t))dsdx(1t0g(s)ds)||u||22+||ut||22+Γ1|u|q(x)dxΓ1u|ut|m(x)2utdx. (5.4)

    (5.1) and Young's inequality, give, for any δ0>0,

    Ωu.t0g(ts)(u(s)u(t))dsdxδ0Ω|u|2dx+Cϵ4δ0(hϵu)(t). (5.5)

    The use of Young's inequality with λ(x)=m(x)m(x)1 and λ(x)=m(x), leads to

    Γ1u|ut|m(x)utdxΓ1cδ(x)|ut|m(x)dx+δΓ1|u|m(x)dx, (5.6)

    where

    cδ(x)=(m(x)1)m(x)1δm(x)1(m(x))m(x)(m(x))m(x).

    Combining (2.1), (2.6), (2.7) and (3.9), we get

    Γ1|u|m(x)dxΓ+1|u|m(x)dx+Γ1|u|m(x)dxΓ+1|u|m2dx+Γ1|u|m1dxΓ1|u|m2dx+Γ1|u|m1dx(cm1e||u||m12+cm2e||u||m22)(cm1e||u||m122+cm2e||u||m222)||u||22(cm1e(2q1(q12)E(0))m12+cm2e(2q1(q12)E(0))m22)||u||22c0||u||22, (5.7)

    where

    c0=(cm1e(2q1(q12)E(0))m12+cm2e(2q1(q12)E(0))m22).

    From (5.6) and (5.7), we have

    Γ1u|ut|m(x)utdxδc0||u||22+Γ1cδ(x)|ut|m(x)dx. (5.8)

    Combining all the above results, choosing δ0=2 and δ=4c0 and using Poincaré's inequality and the trace theorem completes the proof of (5.2).

    To prove (5.3), we apply Young's and Poincaré's inequalities and the trace theorem to obtain

    Γ11u|ut|m(x)2utdxηΓ11|u|2dx+14ηΓ11|ut|2m(x)2dxηc2ρ||u||22+c[Γ+11|ut|2m(x)2dx+Γ11|ut|2m(x)2dx]ηc2ρ||u||22+c[Γ+11|ut|m(x)dx+Γ11|ut|2m12dx]ηc2ρ||u||22+c[Γ1|ut|m(x)dx+(Γ11|ut|2dx)m11]ηc2ρ||u||22+c[Γ1|ut|m(x)dx+(Γ11|ut|m(x)dx)m11]ηc2ρ||u||22+c[Γ1|ut|m(x)dx+(Γ1|ut|m(x)dx)m11], (5.9)

    where

    Γ11={xΩ:m(x)<2},Γ12={xΩ:m(x)2},
    Γ11={xΓ11:|ut(x,t)|<1}andΓ+11={xΓ11:|ut(x,t)|1}. (5.10)

    By selecting η=8c2ρ, (5.9) becomes

    Γ11u|ut|m(x)2utdxc[+(Γ1|ut|m(x)dx)m11+Γ1|ut|m(x)dx]+8||u||22. (5.11)

    Next, for any δ we have, by the case m(x)2,

    Γ12u|ut|m(x)utdxδc0||u||22+Γ1cδ(x)|ut|m(x)dx. (5.12)

    As a result of combining the estimates above, we arrive at

    F1(t)(38c0δ)||u(t)||22+||ut||22+cCε(hεu)(t)+Γ1|u|q(x)dx+c[(Γ1|ut|m(x))m11+Γ1(1+cδ(x))|ut|m(x)dx].

    By choosing δ=8c0, then cδ(x) is bounded and hence (5.3) is obtained.

    Lemma 5.3. Assume that (A1)(A4) and (3.4) hold. Then for any δ>0, the functional

    F2(t):=Ωutt0g(ts)(u(t)u(s))dsdx

    satisfies the estimates:

    F2(t)δ(1+cq)u22(t0g(s)dsδ)ut22+Γ1cδ(x)|ut|m(x)dx+[cδ(Cε+1)+cCε](hεu)(t)+c1δ(1)m11(gu)(t),for m12, (5.13)

    and for 1<m1<2, we have

    F2(t)δ(1+cq)u22(t0g(s)dsδ)ut22+cδ(gu)(t)+[cδ(Cε+1)+cCε](hεu)(t)+cδ[Γ1|ut|m(x)dx+(Γ1|ut|m(x)dx)m11] (5.14)

    where the constant cm>0 depends on m1,m2 and , andhε is defined earlier in Lemma (5.1).

    Proof. Direct differentiation of F2 and using (1.6) leads to

    F2(t)=Ωut0g(ts)(u(t)u(s))dsdxΩ(t0g(ts)u(s)ds)(t0g(ts)(u(t)u(s))ds)dxΩutt0g(ts)(u(t)u(s))dsdx(t0g(s)ds)ut22Γ1|ut|m(x)2utt0g(ts)(u(t)u(s))dsdx+Γ1|u|q(x)2ut0g(ts)(u(t)u(s))dsdx=(1t0g(s)ds)Ωut0g(ts)(u(t)u(s))dsdx+Ω(t0g(ts)(u(t)u(s))ds)2dxΩutt0g(ts)(u(t)u(s))dsdx(t0g(s)ds)ut22Γ1|ut|m(x)2utt0g(ts)(u(t)u(s))dsdx+Γ1|u|q(x)2ut0g(ts)(u(t)u(s))dsdx. (5.15)

    Using Young's inequality and Lemma 5.1, we get

    (1t0g(s)ds)Ωu.t0g(ts)(u(t)u(s))dsdxδu22+cδCε(hεu)(t)+cCε(hεu)(t). (5.16)

    From Lemma (5.1) and Young's inequality, we get

    Ωutt0g(ts)(u(t)u(s))dsdx=εΩutt0g(ts)(u(t)u(s))dsdx+Ωutt0hε(ts)(u(t)u(s))dsdxδ2ut22+ε22δΩ(t0g(ts)(u(t)u(s))ds)2dx+δ2ut22+12δΩ(t0hε(ts)(u(t)u(s))ds)2dxδut22+cδCε(hεu)(t)+12δt0hε(s)dst0hε(ts)u(t)u(s)22dsδut22+cδ(Cε+1)(hεu)(t). (5.17)

    Now, for almost every xΩ, we get

    t0g(ts)|u(t)u(s)|ds(t0g(s)ds)m(x)1m(x)(t0g(ts)|u(t)u(s)|m(x)ds)1m(x)(1)m(x)1m(x)(t0g(ts)|u(t)u(s)|m(x)ds)1m(x). (5.18)

    Next, for almost every xΩ, we obtain

    |t0g(ts)|u(t)u(s)|ds|m(x)(1)m11t0g(ts)|u(t)u(s)|m(x)ds. (5.19)

    Using Young's, Hölder's, Poincaré's inequalities and Lemma 5.1, we have

    Γ1|ut|m(x)2utt0g(ts)(u(t)u(s))dsdxδΓ1|t0g(ts)(u(t)u(s))ds|m(x)dx+Γ1cδ(x)|ut|m(x)dxδ(1)m11Γ1t0g(ts)|(u(t)u(s)|m(x)dsdx+Γ1cδ(x)|ut|m(x)dx, (5.20)

    where

    cδ(x)=δ1m(x)(m(x))m(x)(m(x)1)m(x)1.

    Further, we have

    Γ1t0g(ts)|(u(t)u(s)|m(x)dsdxΓ+1t0g(ts)|(u(t)u(s)|m2dsdx+Γ1t0g(ts)|(u(t)u(s)|m1dsdxt0g(ts)||(u(t)u(s)||m2m2ds+t0g(ts)||(u(t)u(s)||m1m1ds[cm2e(2q1(q12)E(0))m222+cm1e(2q1(q12)E(0))m122]t0g(ts)||(u(t)u(s)||22ds. (5.21)

    Therefore,

    Γ1|ut|m(x)2utt0g(ts)(u(t)u(s))dsdxc1δ(1)m11(gu)(t)+Γ1cδ(x)|ut|m(x)dx, (5.22)

    where c1=[cm2e(2q1(q12)E(0))m222+cm1e(2q1(q12)E(0))m122].

    To estimate the last term in (5.15), we use Young's inequality and Lemma 5.1, to obtain

    Γ1|u|q(x)1t0g(ts)(u(t)u(s))dsdxδΓ1|u|2q(x)2dx+14δΓ1(t0g(ts)(u(t)u(s))ds)2dxδΓ1|u|2q(x)2dx+Cε4δ(hεu)(t). (5.23)

    The first term in (5.23) can be estimated as follows:

    \begin{equation} \begin{split} \int_{\Gamma_1} |u| ^{2q(x)-2} dx & = \int_{\Gamma_1^{+}}|u| ^{2q(x)-2} dx+\int_{\Gamma_1^{-}}|u| ^{2q(x)-2} dx\\ &\le \int_{\Gamma_1^{+}}|u| ^{2q_2-2} dx+\int_{\Gamma_1^{-}}|u| ^{2q_1-2} dx\\ &\le \int_{\Gamma_1}|u| ^{2q_2-2} dx+\int_{\Gamma_1}|u| ^{2q_1-2} dx\\ & \le c_\rho^{2q_2-2}\vert \vert \nabla u \vert \vert_2^{2q_2-2}+c_\rho^{2q_1-2}\vert \vert \nabla u \vert \vert_2^{2q_1-2}\\ &\le \bigg(c_\rho^{2q_2-2}\bigg( \frac{2q_1}{\ell (q_1-2)}E(0)\bigg)^{2q_2-4}+c_\rho^{2q_1-2} \bigg( \frac{2q_1}{\ell (q_1-2)}E(0)\bigg)^{2q_1-4} \bigg)\vert \vert \nabla u \vert \vert_2^{2}\\ & \le c_{q}\vert \vert \nabla u \vert \vert_2^{2}, \end{split} \end{equation} (5.24)

    where

    c_q = \bigg(c_\rho^{2q_2-2}\bigg( \frac{2q_1}{\ell (q_1-2)}E(0)\bigg)^{2q_2-4}+c_\rho^{2q_1-2} \bigg( \frac{2q_1}{\ell (q_1-2)}E(0)\bigg)^{2q_1-4} \bigg).

    Collecting all the above estimates with (5.15), we see that (5.13) is archived.

    To prove (5.14), we start by re-estimating the fifth term in (5.15) as follows:

    \begin{equation} \begin{aligned} &-\int_{\Gamma_1}|u_t|^{m(x)-2}u_t\int_{0}^{t}g(t-s)\big(u(t)-u(s)\big)dsdx\\ &\le \delta \int_{\Gamma_1}\bigg|\int_{0}^{t}g(t-s)\big(u(t)-u(s)\big)ds\bigg|^{2}dx+\frac{c}{\delta}\int_{\Gamma_1} |u_t|^{2m(x)-2}dx\\ &\le \delta (1-\ell) (g \circ u)(t)+ \frac{c}{\delta} \int_{\Gamma_1}|u_t|^{2m(x)-2}dx\\ &\le c\delta (g \circ \nabla u)(t)+ \frac{c}{\delta} \int_{\Gamma_{11}}|u_t|^{2m(x)-2}dx +\frac{c}{\delta} \int_{\Gamma_{12}}|u_t|^{2m(x)-2}dx \\ &\le c\delta (g \circ \nabla u)(t)+\frac{c}{\delta}\bigg(\int_{\Gamma_1}|u_t|^{m(x)}dx + \bigg(\int_{\Gamma_1}|u_t|^{m(x)}dx\bigg)^{m_1-1}\bigg). \end{aligned} \end{equation} (5.25)

    Hence, (5.14) is established.

    Lemma 5.4. [43] Assume that (A1) and (A3) hold, then the functional

    F_3(t): = \int_{0}^{t}f(t-s)\|\nabla u(s)\|^2_2ds

    satisfies the estimate:

    \begin{equation} \begin{array}{l} F_3'(t)\le 3(1-\ell)\|\nabla u\|^2_2-\frac{1}{2}(g\circ \nabla u)(t), \end{array} \end{equation} (5.26)

    where f(t) = \int_{t}^{\infty}g(s)ds .

    Lemma 5.5. Given t_0 > 0. Assume that (A1)-(A4) and (3.4) holdand m_1 \geq 2 . Then, the functional \mathcal{L} defined by

    \mathcal{L}(t): = N E(t) + {\varepsilon}_1 F_1(t) + {\varepsilon}_2 F_2(t)

    satisfies, for fixed N, \, {\varepsilon}_1, \, {\varepsilon}_2 > 0 ,

    \begin{equation} \mathcal{L} \sim E \end{equation} (5.27)

    and for any \, t \geq t_0 ,

    \begin{equation} \begin{aligned} \mathcal{L}'(t) \leq - c \|u_t\|^2_2 - 4(1 - \ell)\|\nabla u\|^2_2 + \frac{1}{4}( g \circ \nabla u)(t)+c \int_{\Gamma_1}|u| ^{q(x)}dx. \end{aligned} \end{equation} (5.28)

    Proof. The equivalence \mathcal{L} \sim E can be proved straightforward. For the proof of (5.28), we start combining (2.6), (2.7), (5.2) and (5.13) and recalling g'(t): = {\varepsilon} g(t)-h_{\varepsilon}(t) , to get:

    \begin{equation} \begin{aligned} \mathcal{L}'(t)&\le -\Big[\Big(\int_{0}^{t}g(s)ds-\delta\Big){\varepsilon}_2-{\varepsilon}_1\Big]\|u_t\|^2_2-\bigg(\frac{\ell}{4}{\varepsilon}_1-\delta {\varepsilon}_2(1+c_q)\bigg)\|\nabla u\|^2_2 \\ &-\Big[\frac{N}{2}-\frac{{\varepsilon}_2 c}{\delta}-c C_{{\varepsilon}}\bigg( \varepsilon_1+\frac{ \varepsilon_2}{\delta}+ \varepsilon_2\bigg) \Big](h_{{\varepsilon}}\circ \nabla u)(t)\\ &- \int_{\Gamma_1}\big(N-c {\varepsilon}_1 - {\varepsilon}_2 c_{\delta}(x) \big) |u_t|^{m(x)}dx+\varepsilon_1 \int_{\Gamma_1}|u| ^{q(x)}dx\\ &+ \bigg(\frac{N{\varepsilon}}{2}+\varepsilon_2 c_1 \delta (1-\ell)^{m_1-1}\bigg)(g\circ \nabla u)(t). \end{aligned} \end{equation} (5.29)

    Now, set g_0 = \int_{0}^{t_0}g(s)ds and select \delta small enough so that

    \delta < \min\Big\{\frac{1}{2}g_0, \frac{\ell g_0}{16(1+c_q)}, \frac{\ell g_0}{1024 c_1 (1-\ell)^{m_1}}\Big\}.

    Once \delta is fixed, then {c_\delta}(x) is bounded and the choice of {\varepsilon}_1 = \frac{3}{8}g_0 {\varepsilon}_2 yields

    \frac{1}{4}g_0{\varepsilon}_2 < {\varepsilon}_1 < \frac{1}{2}g_0{\varepsilon}_2.
    \begin{equation} \begin{array}{l} c_1: = (g_0-{\delta}){\varepsilon}_2 - {\varepsilon}_1 > \frac{1}{2}g_0{\varepsilon}_2-{\varepsilon}_1 = \frac{1}{8}g_0{\varepsilon}_2 > 0, \\ c_2: = \frac{\ell}{4}{\varepsilon}_1 - {\delta}{\varepsilon}_2 (1+c_q) > \frac{\ell}{32}g_0{\varepsilon}_2 > 0. \end{array} \end{equation} (5.30)

    By taking {\varepsilon}_2 = \frac{1}{8 c_1 \delta (1-\ell)^{m_1-1}}, we get

    c_1 \delta (1-\ell)^{m_1-1}{\varepsilon}_2 = \frac{1}{8} { and }c_2 > \frac{\ell}{32}g_0{\varepsilon}_2 = \frac{\ell g_0}{256c_1 \delta (1-\ell)^{m_1-1}} > 4(1-\ell).

    Then (5.29) becomes

    \begin{equation} \begin{aligned} \mathcal{L}'(t)\le -c_1\|u_t\|^2_2-4(1-\ell)\|\nabla u\|^2_2+\bigg(\frac{N{\varepsilon}}{2}+\frac{1}{8}\bigg)(g\circ \nabla u)(t)+\varepsilon_1 \int_{\Gamma_1}|u| ^{q(x)}dx \\ -\Big[\frac{N}{2}-\frac{{\varepsilon}_2 c}{\delta}-c C_{{\varepsilon}}\bigg( \varepsilon_1+\frac{ \varepsilon_2}{\delta}+ \varepsilon_2\bigg) \Big](h_{{\varepsilon}}\circ \nabla u)(t)- \bigg[N-c({\varepsilon}_1+{\varepsilon}_2) \bigg]\int_{\Gamma_1} |u_t|^{m(x)}dx\\ \end{aligned} \end{equation} (5.31)

    From \frac{{\varepsilon} g^2(s)}{{\varepsilon} g(s)-g'(s)} < g(s) and using the Lebesgue Dominated Convergence Theorem, we conclude that

    \lim\limits_{{\varepsilon}\rightarrow0^+}{\varepsilon} C_{\varepsilon} = \lim\limits_{{\varepsilon}\rightarrow0^+}\int_0^\infty\frac{{\varepsilon} g^2(s)}{{\varepsilon} g(s)-g'(s)}ds = 0.

    So, there exists 0 < {\varepsilon}_0 < 1 such that if {\varepsilon} < {\varepsilon}_0 , then

    {\varepsilon} C_{\varepsilon} < \frac{1}{16\bigg(c \varepsilon_1+\frac{c \varepsilon_2}{\delta}+c \varepsilon_2\bigg) } .

    Now, choosing N large enough so that \mathcal{L} \sim E and

    N > \max \left\lbrace \frac{4c}{{\delta}} {\varepsilon}_2, \, \, \frac{1}{4{\varepsilon}}, \, \, \frac{c({\varepsilon}_1 + {\varepsilon}_2)}{a} \right\rbrace.

    For {\varepsilon} = \frac{1}{4N} , we have

    \frac{N}{4} - \frac{c}{{\delta}} {\varepsilon}_2 > 0 \qquad\mathrm{and}\qquad {\varepsilon} < {\varepsilon}_0.

    This gives

    \begin{equation} \frac{N}{2} - \frac{{\varepsilon}_2 c}{\delta}-C_{{\varepsilon}}\bigg(c \varepsilon_1+\frac{c \varepsilon_2}{\delta}+c \varepsilon_2\bigg) > 0. \end{equation} (5.32)

    A Combination of (5.31)-(5.32), leads to (5.28).

    Lemma 5.6. Given t_0 > 0 . Assume that (A1)-(A4) and (3.4) holdand 1 < m_1 < 2 . Then, the functional \mathcal{L} defined by

    \mathcal{L}(t): = N E(t) + {\varepsilon}_1 F_1(t) + {\varepsilon}_2 F_2(t)

    satisfies, for fixed N, \, {\varepsilon}_1, \, {\varepsilon}_2 > 0 ,

    \begin{equation} \mathcal{L} \sim E \end{equation} (5.33)

    and for any \, t \geq t_0 ,

    \begin{equation} \begin{aligned} \mathcal{L}'(t) \leq - c \|u_t\|^2_2 - 4(1 - \ell)\|\nabla u\|^2_2 + \frac{1}{4} ( g \circ \nabla u)(t) +\varepsilon_1 \int_{\Gamma_1}|u| ^{q(x)}dx+c \bigg(-E'(t)\bigg)^{m_1-1}. \end{aligned} \end{equation} (5.34)

    Proof. Estimate (5.34) can be established by using the same above arguments with some changes only on

    \delta < \min\Big\{\frac{1}{2}g_0, \frac{\ell}{16c(1+c_q)}g_0, \frac{\ell g_0}{1024 (1-\ell)}\Big\}, \ { {\rm{and}} }\ {\varepsilon}_2 = \frac{1}{8\delta}.

    Lemma 5.7. Assume that (A1)-(A4) and (3.4) hold, then for m_1\geq 2 , then

    \begin{equation} \int_0^{\infty} E(s) ds < \infty. \end{equation} (5.35)

    Proof. Combining Lemmas 5.4 and 5.5 and choosing \varepsilon_1 small enough, we see that the functional L_1 defined by

    L_1(t) : = \mathcal{L}(t) + F_3(t)

    is nonnegative and satisfies, for some c_0 > 0 and for any t \geq t_0 ,

    \begin{equation*} \begin{split} L_1'(t) \leq& -c \|u_t\|^2_2 - (1-\ell)\left\| \nabla u\right\|^2_2 - \frac{1}{4}\left( g \circ \nabla u \right)(t)+\varepsilon_1 \int_{\Gamma_1}|u| ^{q(x)}dx\\ \leq& -c_0 E(t)-\left(\frac{c}{2 q_2}-\varepsilon_1 \right)\int_{\Gamma_1}|u| ^{q(x)}dx\\ \leq& - c_0 E(t). \end{split} \end{equation*}

    An integration over (t_0, t) , leads

    \int_{t_0}^{t}E(s)ds\le -\frac{L_1(t)+L_1(t_0)}{c_0}, \quad \forall t \ge t_0.

    Using the continuity of E , we obtain

    \begin{equation*} \int_0^\infty E(s)ds < +\infty. \end{equation*}

    Lemma 5.8. Assume that (A1)-(A4) and (3.4) hold, then for 1 < m_1 < 2 , we have

    \begin{equation} \int_0^{\infty}E^{\frac{1}{m_1-1}}(s) ds < \infty. \end{equation} (5.36)

    Furthermore,

    \begin{equation} \int_{t_0}^{\infty}E(s) ds \le c(t-t_0)^{2-m_1}, \quad \forall t \ge t_0. \end{equation} (5.37)

    Proof. Combing Lemmas 5.4 and 5.6 and selecting \varepsilon_1 small enough, we conclude that the functional L_2 defined by

    L_2(t) : = \mathcal{L}(t) + F_3(t)

    satisfies, for some c_0, \; c > 0 and for any t \geq t_0 ,

    \begin{equation} \begin{split} L_2'(t) \leq& -c\|u_t\|^2_2 - (1-\ell)\left\| \nabla u\right\|^2_2 - \frac{1}{4}\left( g \circ \nabla u \right)(t)+\varepsilon_1 \int_{\Gamma_1}|u| ^{q(x)}dx+C\Big[\int_{\Gamma_1}|u_t|^mdx\Big]^{m_1-1}\\ \leq& -c_0 E(t)-\left(\frac{c}{2 q_2}-\varepsilon_1 \right)\int_{\Gamma_1}|u| ^{q(x)}dx+c\big(-E'(t)\big)^{m_1-1}\\ \leq& - c_0 E(t)+c\big(-E'(t)\big)^{m_1-1} , \quad \forall t \ge t_0. \end{split} \end{equation} (5.38)

    Now, multiplying (5.38) by E^\alpha(t), \; \alpha = \frac{2-m_1}{m_1-1} , and using Young's inequality, we arrive at

    \begin{equation} \begin{array}{l} E^\alpha(t)L_2'(t)\le - c_0 E^{\alpha+1}(t)+c_1E^\alpha(t)\big(-E'(t)\big)^{m_1-1}\\ \quad \le -c_0(1-{\varepsilon}) E^{\alpha+1}(t)+\frac{c}{{\varepsilon}}\big(-E'(t)\big).\\ \end{array} \end{equation} (5.39)

    Choosing {\varepsilon} small enough and using the fact E'\leq 0 , then (5.39) becomes:

    \begin{equation} E^{\alpha+1}(t)\le -cL_3'(t), \quad \forall t \ge t_0, \end{equation} (5.40)

    where L_3(t) = E^\alpha(t)L_2(t)+cE(t) .

    Integrating over (t_0, t) , we get

    \int_{t_0}^{t}E^{\alpha +1}(s)ds\le L_3(t_0), \quad \forall t \ge t_0.

    Therefore, we get

    \begin{equation*} \int_0^\infty E^{\frac{1}{m_1-1}}(s)ds < +\infty. \end{equation*}

    Using Hölder's inequality, we get

    \begin{equation} \int_{t_0}^{t}E(s)ds\le (t-t_0)^{\frac{\alpha}{\alpha+1}}\Big[\int_{t_0}^{t}E^{\alpha+1}(s)ds\Big]^{\frac{1}{\alpha+1}}\le c(t-t_0)^{\frac{\alpha}{\alpha+1}} = c(t-t_0)^{2-m_1}, \; \forall t\geq t_0. \end{equation} (5.41)

    This completes the proof.

    In this section, we prove Theorem 4.1 and Theorem 4.2.

    Case 1: \Psi is linear. Using (2.3), (2.6), and (5.28), then for any t\geq t_0 , we have

    \begin{equation*} \begin{aligned} &\vartheta(t) \mathcal{L}'(t) \leq -c\vartheta(t)E(t) +c \vartheta (g\circ \nabla u)(t)\le -c\vartheta(t)E(t) +c(g^{\prime}\circ \nabla u)(t)\\ & \quad \le -c\vartheta(t)E(t) - c E'(t). \end{aligned} \end{equation*}

    Letting \vartheta \mathcal{L}+cE\sim E and integrating over (t_0, t) , we get for some C, \lambda > 0,

    \begin{equation*} E(t)\le C\exp{\left(-\lambda \int_{t_0}^{t}\vartheta(s)ds\right)}, \ t\geq t_0. \end{equation*}

    Case 2: \Psi is nonlinear. We start defining the following functional

    \begin{equation} \eta(t) : = \gamma\int_{t_0}^t \left\| \nabla u(t)-\nabla u(t-s)\right\|^2_2, \quad\forall\, t \geq t_0, \end{equation} (6.1)

    where \gamma > 0 should be carefully selected. Using (3.9) and (5.35), we get

    \begin{align*} &\eta(t) = \gamma \int_{t_0}^t\left\| \nabla u(t)-\nabla u(t-s)\right\|^2_2 \\ & \leq 2 \gamma \int_{t_0}^t\left(\left\| \nabla u(t)\right\|^2_2 + \left\|\nabla u(t-s)\right\|^2_2\right)ds \\ & \leq \frac{8\gamma q_1}{\ell (q_1-2)} \int_{t_0}^t \big( E(t) + E(t-s) \big)ds \\ & \leq \frac{8\gamma q_1}{\ell (q_1-2)} \int_{t_0}^\infty E(s) ds < \infty, \qquad\forall\, t \geq t_0. \end{align*}

    Therefore, we can select \gamma small enough so that

    \begin{equation} \eta(t) < 1, \qquad\forall\, t \geq t_0. \end{equation} (6.2)

    We also define the following

    \begin{equation} \theta(t): = -\int_{t_0}^t g'(s) \| \nabla u(t)-\nabla u(t-s)\|^2_2\leq -c E'(t). \end{equation} (6.3)

    Since \bar \Psi is strictly convex and \bar \Psi(0) = 0 , we have

    \bar \Psi(s\tau) \leq s \bar \Psi(\tau), \qquad \mathrm{for} \quad 0 \leq s \leq 1 \quad \mathrm{and} \quad \tau \in [0, \infty).

    Combining the above with (2.3), Jensen's inequality and (6.2), we obtain, for any t > t_0 ,

    \begin{align*} \theta(t)& = -\frac{1}{\eta(t)}\int_{t_0}^t\eta(t)g'(s)\left\| \nabla u(t)-\nabla u(t-s)\right\|^2_2\\ &\geq\frac{1}{\eta(t)}\int_{t_0}^t\eta(t)\vartheta(s)\Psi(g(s))\left\| \nabla u(t)-\nabla u(t-s)\right\|^2_2\\ &\geq\frac{\vartheta(t)}{\eta(t)}\int_{t_0}^t \bar \Psi(\eta(t)g(s))\left\| \nabla u(t)-\nabla u(t-s))\right\|^2_2\\ &\geq\frac{\vartheta(t)}{\gamma} \bar{\Psi} \left( \gamma \int_{t_0}^t g(s)\left\| \nabla u(t)-\nabla u(t-s)\right\|^2_2\right). \end{align*}

    Then, for any t \geq t_0 , we have

    \begin{equation} \int_{t_0}^t g(s)\left\| \nabla (u(t)-u(t-s))\right\|^2_2 \leq \frac{1}{\gamma}\bar{\Psi}^{-1}\left(\frac{\gamma\theta(t)}{\vartheta(t)}\right), \ \forall t > t_0. \end{equation} (6.4)

    Combining (2.6), (5.28), (6.4) and using Lemma 2.9, we get, for any t\geq t_0 ,

    \begin{equation} \begin{aligned} & \mathcal{L}'(t) \leq -\beta_1 E(t) - c E'(t)+ c\int_{t_0}^t g(s)\left\| \nabla (u(t)-u(t-s))\right\|^2_2\\ & \quad \le -\beta_1 E(t) - c E'(t)+ \frac{c}{\gamma}\bar{\Psi}^{-1}\left(\frac{\gamma\theta(t)}{\vartheta(t)}\right). \end{aligned} \end{equation} (6.5)
    \begin{equation} \mathcal{F}'(t) \leq -\beta_1 E(t) + \frac{c}{\gamma} \bar{\Psi}^{-1} \left( \frac{\gamma \theta(t)}{\vartheta(t)}\right), \qquad \forall\, t \geq t_0, \end{equation} (6.6)

    where \mathcal{F}: = \mathcal{L}+cE . For {\varepsilon}_0 < r , we define

    \mathcal{F}_1(t) : = \bar \Psi'\left( \frac{{\varepsilon}_0E(t)}{E(0)} \right) \mathcal{F}(t), \qquad \forall\, t \geq t_0.

    Then, using the facts that E'\leq0 , \Psi' > 0 and \Psi'' > 0 , estimate (6.6) becomes

    \begin{eqnarray} \mathcal{F}_1'(t) & = & \frac{{\varepsilon}_0 E'(t)}{E(0)} \bar \Psi'\left(\frac{{\varepsilon}_0E(t)}{E(0)}\right) \mathcal{F}(t) + \bar \Psi'\left(\frac{{\varepsilon}_0E(t)}{E(0)}\right) \mathcal{F}'(t) \\ &\leq& - \beta_1 E(t)\bar \Psi'\left(\frac{{\varepsilon}_0E(t)}{E(0)}\right) + \frac{c}{\gamma}\bar \Psi'\left(\frac{{\varepsilon}_0E(t)}{E(0)}\right)\bar{\Psi}^{-1}\left(\frac{\gamma\theta(t)}{\vartheta(t)}\right), \quad \forall\, t \geq t_0. \end{eqnarray} (6.7)

    Recall that \bar \Psi is convex on (0, \infty) and let \bar \Psi^* be the convex conjugate of \bar \Psi in the sense of Young [48] such that

    \begin{equation} \bar \Psi^*(s) = s\big(\bar \Psi'\big)^{-1}(s)-\bar \Psi\left[\big(\bar \Psi'\big)^{-1}(s), \right] \forall s \in (0, \infty). \end{equation} (6.8)

    and satisfies the following generalized Young inequality

    \begin{equation} AB\leq\bar \Psi^*(A)+\bar \Psi(B), \forall A, B \in (0, \infty). \end{equation} (6.9)

    Then a combination of (2.7), (6.7)) and (6.9) with applying the generalized Young inequality over (0, \infty) with A = \bar \Psi'\left(\frac{{\varepsilon}_0 E(t)}{E(0)}\right) and B = \bar \Psi^{-1}\left(\frac{\gamma\theta(t)}{\vartheta(t)}\right),

    \begin{eqnarray*} \mathcal{F}_1'(t) &\leq& - \beta_1 E(t)\bar \Psi'\left(\frac{{\varepsilon}_0E(t)}{E(0)}\right) + \frac{c}{\gamma}\bar \Psi^*\left[\bar \Psi'\left(\frac{{\varepsilon}_0 E(t)}{E(0)}\right)\right] + \frac{c \theta(t)}{\vartheta(t)}\\ &\leq& - (\beta_1 E(0) - c {\varepsilon}_0)\frac{E(t)}{E(0)}\bar \Psi'\left(\frac{{\varepsilon}_0E(t)}{E(0)}\right) + c\frac{\theta(t)}{\vartheta(t)}, \qquad \forall\, t \geq t_0. \end{eqnarray*}

    Take {\varepsilon}_0 small enough, if needed, to obtain, for some positive constant \beta_1 ,

    \begin{eqnarray*} \mathcal{F}_1'(t) &\leq& -\beta_1\frac{E(t)}{E(0)}\bar \Psi'\left(\frac{{\varepsilon}_0E(t)}{E(0)}\right)+c\frac{\theta(t)}{\vartheta(t)}, \qquad \forall\, t \geq t_0. \end{eqnarray*}

    Multiplying both sides of the last inequality by \vartheta(t) and using {\varepsilon}_0\frac{E(t)}{E(0)} < r and inequality 6.3, we get

    \begin{eqnarray*} \label{e12s5} \vartheta(t) \mathcal{F}_1'(t) &\leq& - \beta_2\frac{E(t)}{E(0)}\Psi'\left(\frac{{\varepsilon}_0E(t)}{E(0)}\right)\vartheta(t)+c\theta(t) \notag\\ &\leq& -\beta_2\frac{E(t)}{E(0)}\Psi'\left(\frac{{\varepsilon}_0E(t)}{E(0)}\right)\vartheta(t)-c E'(t) , \qquad \forall\, t \geq t_0. \end{eqnarray*}

    Hence by setting \mathcal{F}_2 = \vartheta \mathcal{F}_1+cE , we obtain, for two constants \alpha_1, \alpha_2 > 0,

    \begin{equation} \alpha_1 \mathcal{F}_2(t)\le E(t)\le \alpha_2 \mathcal{F}_2, \quad \forall t\ge t_0 \end{equation} (6.10)

    and

    \begin{eqnarray} \mathcal{F}_2'(t) &\leq& - \beta_2\frac{E(t)}{E(0)}\Psi'\left(\frac{{\varepsilon}_0E(t)}{E(0)}\right)\vartheta(t), \quad \forall t\ge t_0. \end{eqnarray} (6.11)

    Now, let

    \Lambda(t): = \frac{\alpha_1 \mathcal{F}_2(t)}{E(0)}\ {\rm{and}}\ \Psi_2(\tau) = \tau \Psi^{\prime}({\varepsilon}_0 \tau),

    then we deduce from (A2) that \Psi_2, \Psi_2^{\prime} > 0 on (0, 1] , and from (6.10) and (6.11) that \Lambda\sim E and

    \begin{equation} -\frac{\Lambda^{\prime}(t)}{\Psi_2(\Lambda(t))}\ge \lambda_1\vartheta(t), \quad \forall t > t_0, \end{equation} (6.12)

    Integration over (t_0, t) , we get

    \begin{equation*} \int_{{\varepsilon}_0 \Lambda(t)}^{{\varepsilon}_0 \Lambda(t_0)}\frac{1}{s\Psi^{\prime}(s)}ds\ge \int_{t_0}^{t}\vartheta(s)ds, \quad \forall t > t_0. \end{equation*}

    Hence,

    \begin{equation*} E(t)\le \lambda_2 \Psi_0^{-1}\left(\lambda_1\int_{t_0}^{t}\vartheta(s)ds\right), \quad \forall t > t_0, \end{equation*}

    where \Psi_0 = \int_{t}^{r}\frac{1}{s\Psi'(s)}ds and \lambda_2 > 0.

    Case 1: \Psi is linear. Combining (2.3), (2.6) and (5.34), then for some \gamma_1 > 0 , we have

    \begin{equation} \begin{aligned} &\vartheta(t) \mathcal{L}'(t) \leq -\gamma_1\vartheta(t)E(t) + c\vartheta(t)(g\circ \nabla u)(t)+c\vartheta(t) \bigg[-E'(t)\bigg]^{m_1-1}\\ & \quad \le -\gamma_1\vartheta(t)E(t) - c E'(t)+c\vartheta(t) \bigg[-E'(t)\bigg]^{m_1-1}, \quad \forall t > t_0. \end{aligned} \end{equation} (6.13)

    Letting \mathcal{L}_1: = \vartheta \mathcal{L}+cE\sim E , multiplying both sides of the above estimate by E^k , with k = \frac{2-m_1}{m_1-1} and applying Young's inequality, we obtain

    \begin{equation*} E^k(t) \mathcal{L}_{1}^{\prime}(t)\le -(\gamma_1-\epsilon)\vartheta(t)E^{k+1}(t)-cE^{\prime}(t), \quad \forall t > t_0. \end{equation*}

    Set \mathcal{L}_2: = E^k \mathcal{L}_1+cE \sim E , take \epsilon small enough and use the fact E'\leq 0 we get, for some \gamma_2, \gamma_3 > 0,

    \begin{equation*} \mathcal{L}_2^{\prime}(t)\le -\gamma_2 \vartheta(t)E^{k+1}(t)\le -\gamma_3 \vartheta(t) \mathcal{L}_2^{k+1}(t), \quad \forall t\ge t_0. \end{equation*}

    Now, we integrate over (t_0, t) and use \mathcal{L} \sim E, to get,

    \begin{equation*} E(t)\le C\left(\int_{t_0}^{t}\vartheta(s)ds\right)^{1-m_1}, \quad \forall t\ge t_0. \end{equation*}

    Case 2: \Psi is nonlinear. We define the following functional

    \eta_1(t) : = \frac{\gamma_0}{(t-t_0)^{2-m_1}}\int_{t_0}^t \left\| \nabla u(t)-\nabla u(t-s)\right\|^2_2ds, \quad\forall\, t \geq t_0.

    Thanks to (5.37), we can pick \gamma_0 small enough so that \eta_1(t) < 1 . Then, for any t\ge t_0, we have

    \begin{align*} \theta_1(t)& = -\frac{1}{\eta_1(t)}\int_{t_0}^t\eta_1(t)g'(s) \left\| \nabla u(t)-\nabla u(t-s)\right\|^2_2 ds\\ &\geq\frac{1}{\eta_1(t)}\int_{t_0}^t\eta_1(t)\vartheta(s)\Psi(g(s)) \left\| \nabla u(t)-\nabla u(t-s)\right\|^2_2ds\\ &\geq\frac{\vartheta(t)}{\eta_1(t)}\int_{t_0}^t \bar{\Psi}(\eta_1(t)g(s)) \left\| \nabla u(t)-\nabla u(t-s)\right\|^2_2 ds\\ &\geq\frac{(t-t_0)^{{2-m_1}}\vartheta(t)}{\gamma}\bar{\Psi}\left( \frac{\gamma}{(t-t_0)^{2-m_1}} \int_{t_0}^t g(s)\left\| \nabla u(t)-\nabla u(t-s)\right\|^2_2 ds\right), \end{align*}

    which gives

    \begin{equation} \int_{t_0}^t g(s) \left\| \nabla u(t)-\nabla u(t-s)\right\|^2_2ds\le \frac{1}{\gamma_0}(t-t_0)^{2-m_1} \bar{\Psi}^{-1} \left(\frac{\gamma_0\theta_1(t)}{\vartheta(t)(t-t_0)^{2-m_1}}\right). \end{equation} (6.14)

    Using (2.6), (5.34), (6.14) and Lemma 2.9, then for any t\geq t_0 , we get

    \begin{equation} \begin{array}{l} \mathcal{L}'(t) \leq -\gamma_4 E(t) - c E'(t)+ \frac{c}{\gamma_0}(t-t_0)^{2-m_1} \bar{\Psi}^{-1} \left(\frac{\gamma_0\theta_1(t)}{\vartheta(t)(t-t_0)^{2-m_1}}\right)+c \bigg[-E'(t)\bigg]^{m_1-1}. \end{array} \end{equation} (6.15)

    Thus, (6.15) becomes

    \begin{equation} \mathcal{F}'(t) \leq -\gamma_4 E(t) + \frac{c(t-t_0)^{{2-m_1}}}{\gamma_0}\bar{\Psi}^{-1}\left(\frac{\gamma_0\theta_1(t)}{(t-t_0)^{{2-m_1}}\vartheta(t)}\right)+c\bigg[-E'(t)\bigg]^{m_1-1}, \qquad \forall\, t \geq t_0, \end{equation} (6.16)

    where \mathcal{F}: = \mathcal{L}+cE\sim E .

    For 0 < {\varepsilon}_1 < r , we shall define

    \mathcal{F}_1(t) : = \bar \Psi'\left(\frac{{\varepsilon}_1}{(t-t_0)^{{2-m_1}}} .\frac{E(t)}{E(0)} \right) \mathcal{F}(t), \qquad \forall\, t \geq t_0.

    Using (2.7), (6.16), the assumption (A1) , and the generalized Young inequality, then for any t > t_0, we have

    \begin{equation} \begin{aligned} & \mathcal{F}_1'(t) = \Big[\frac{{\varepsilon}_1}{(t-t_0)^{{2-m_1}}}.\frac{E'(t)}{E(0)}-\frac{(2-m_1){\varepsilon}_1}{(t-t_0)^{3-m_1}}.\frac{E(t)}{E(0)}\Big] \bar \Psi''\left(\frac{{\varepsilon}_1}{(t-t_0)^{{2-m_1}}} .\frac{E(t)}{E(0)}\right) \mathcal{F}(t) \\ & \quad + \bar \Psi'\left(\frac{{\varepsilon}_1}{(t-t_0)^{{2-m_1}}} .\frac{E(t)}{E(0)}\right) \mathcal{F}'(t) \\ &\leq \bar \Psi'\left(\frac{{\varepsilon}_1}{(t-t_0)^{{2-m_1}}}.\frac{E(t)}{E(0)}\right) \mathcal{F}'(t)\\ & \leq -\gamma_4 E(t)\bar \Psi'\left(\frac{{\varepsilon}_1}{(t-t_0)^{{2-m_1}}} .\frac{E(t)}{E(0)}\right) +c\bar \Psi'\left(\frac{{\varepsilon}_1}{(t-t_0)^{{2-m_1}}} .\frac{E(t)}{E(0)}\right)\bigg[-E'(t)\bigg]^{m_1-1}\\ & \quad + \frac{(t-t_0)^{{2-m_1}}}{\gamma_0}\bar{\Psi}^{-1}\left(\frac{\gamma_0\theta_1(t)}{(t-t_0)^{{2-m_1}}\vartheta(t)}\right)\bar \Psi'\left(\frac{{\varepsilon}_1}{(t-t_0)^{{2-m_1}}} .\frac{E(t)}{E(0)}\right)\\ &\leq - \gamma_4 E(t)\bar \Psi'\left(\frac{{\varepsilon}_1}{(t-t_0)^{{2-m_1}}} .\frac{E(t)}{E(0)}\right) + \frac{c(t-t_0)^{{2-m_1}}}{\gamma_0}\bar \Psi^*\left[\bar \Psi'\left(\frac{{\varepsilon}_1}{(t-t_0)^{{2-m_1}}} .\frac{E(t)}{E(0)}\right)\right] \\ & \quad +c \frac{ \theta_1(t)}{\vartheta(t)}+c\bar \Psi'\left(\frac{{\varepsilon}_1}{(t-t_0)^{{2-m_1}}} .\frac{E(t)}{E(0)}\right)\bigg[-E'(t)\bigg]^{m_1-1}.\\ &\leq - \gamma_4 E(t)\bar \Psi'\left(\frac{{\varepsilon}_1}{(t-t_0)^{{2-m_1}}} .\frac{E(t)}{E(0)}\right) + c{\varepsilon}_1\frac{E(t)}{E(0)}\bar \Psi'\left(\frac{{\varepsilon}_1}{(t-t_0)^{{2-m_1}}} .\frac{E(t)}{E(0)}\right) \\ & \quad + c\frac{ \theta_1(t)}{\vartheta(t)}+c\bar \Psi'\left(\frac{{\varepsilon}_1}{(t-t_0)^{{2-m_1}}} .\frac{E(t)}{E(0)}\right)\bigg[-E'(t)\bigg]^{m_1-1}\\ &\le - (\gamma_4 E(0) - c{\varepsilon}_1 )\frac{E(t)}{E(0)}\bar \Psi'\left(\frac{{\varepsilon}_1}{(t-t_0)^{{2-m_1}}} .\frac{E(t)}{E(0)}\right) +c \frac{ \theta_1(t)}{\vartheta(t)}\\ & \quad +c\bar \Psi'\left(\frac{{\varepsilon}_1}{(t-t_0)^{{2-m_1}}} .\frac{E(t)}{E(0)}\right)\bigg[-E'(t)\bigg]^{m_1-1}\\ &\le - \gamma_5 \frac{E(t)}{E(0)}\bar \Psi'\left(\frac{{\varepsilon}_1}{(t-t_0)^{{2-m_1}}} .\frac{E(t)}{E(0)}\right) + c\frac{ \theta_1(t)}{\vartheta(t)}\\ & \quad +c\bar \Psi'\left(\frac{{\varepsilon}_1}{(t-t_0)^{{2-m_1}}} .\frac{E(t)}{E(0)}\right)\bigg[-E'(t)\bigg]^{m_1-1}, \end{aligned} \end{equation} (6.17)

    where \gamma_5 > 0. Multiplying the last inequality by \vartheta(t) and using (6.3), then for any t > t_0, we obtain

    \begin{equation*} \begin{aligned} &\vartheta(t) \mathcal{F}_1'(t)\le - \gamma_5 E(t)\vartheta(t)\bar \Psi'\left(\frac{{\varepsilon}_1}{(t-t_0)^{{2-m_1}}} .\frac{E(t)}{E(0)}\right) -cE'(t)\\ & \quad +c\vartheta(t)\bar \Psi'\left(\frac{{\varepsilon}_1}{(t-t_0)^{{2-m_1}}} .\frac{E(t)}{E(0)}\right)\big(-E'(t)\big)^{{m_1-1}}. \end{aligned} \end{equation*}

    By setting \mathcal{F}_2: = \vartheta \mathcal{F}_1+cE , we get, for any t > t_0,

    \begin{equation*} \begin{aligned} & \mathcal{F}_2'(t)\le - \gamma_5 E(t)\vartheta(t)\bar \Psi'\left(\frac{{\varepsilon}_1}{(t-t_0)^{{2-m_1}}} .\frac{E(t)}{E(0)}\right)\\ & \quad +c\bar \Psi'\left(\frac{{\varepsilon}_1}{(t-t_0)^{{2-m_1}}} .\frac{E(t)}{E(0)}\right)\big(-E'(t)\big)^{{m_1-1}}. \end{aligned} \end{equation*}

    Multiplying the above inequality by E^n , \left(n = \frac{2-m_1}{m_1-1}\right), and using Young's inequality, then for some \gamma_6 , we have

    \begin{equation*} \begin{aligned} & E^n(t) \mathcal{F}_2'(t)\le -\left(\frac{\gamma_5}{E(0)}-c{\varepsilon}\right)E^{n+1}(t)\bar \Psi'\left(\frac{{\varepsilon}_1}{(t-t_0)^{{2-m_1}}} .\frac{E(t)}{E(0)}\right) \\ & \quad +c({\varepsilon})\bar \Psi'\left(\frac{{\varepsilon}_1}{(t-t_0)^{{2-m_1}}} .\frac{E(t)}{E(0)}\right)\big(-E'(t)\big)\\ &\le -\left(\frac{\gamma_5}{E(0)}-c{\varepsilon}\right) \vartheta(t)E^{\frac{2-m_1}{m_1-1}}(t)\bar \Psi'\left(\frac{{\varepsilon}_1}{(t-t_0)^{2-m_1}} .\frac{E(t)}{E(0)}\right)-cE^{\prime}(t). \end{aligned} \end{equation*}

    Let \mathcal{F}_3 = E^n \mathcal{F}_2+cE and choose {\varepsilon} small enough, then for a constant \gamma_6 > 0 , we get

    \begin{equation} \mathcal{F}'_3(t)\le -\gamma_6\vartheta(t)\left(\frac{E(t)}{E(0)}\right)^{n+1}\bar \Psi'\left(\frac{{\varepsilon}_1}{(t-t_0)^{{2-m_1}}} .\frac{E(t)}{E(0)}\right). \end{equation} (6.18)

    We deduce from \lim_{t\to \infty}{\frac{1}{(t-t_0)^{2-m_1}}} = 0 , that, there exists t_1 > t_0 such that \frac{1}{(t-t_0)^{2-m_1}} < 1 for any t\ge t_1 , which implies

    \begin{equation} \vartheta(t)\Big(\frac{E(t)}{E(0)}\Big)^{n+1} \Psi'\left(\frac{{\varepsilon}_1}{(t-t_0)^{{2-m_1}}} .\frac{E(t)}{E(0)}\right)\le -c \mathcal{F}'_3(t), \quad \forall t > t_1. \end{equation} (6.19)

    Integrating (6.19) over (t_1, t) yields

    \begin{equation} \int_{t_1}^{t} \left(\frac{E(t)}{E(0)}\right)^{n+1} \Psi'\left(\frac{{\varepsilon}_1}{(s-t_0)^{{2-m_1}}} .\frac{E(s)}{E(0)}\right)\vartheta(s)ds \le -\int_{t_1}^{t} \mathcal{F}'_3(s)ds\le c \mathcal{F}'_3(t_1). \end{equation} (6.20)

    Since \Psi'' > 0 and E' \leq 0 , it follows that the map

    t\longmapsto\left( \frac{E(t)}{E(0)}\right)^{n+1} \Psi'\left(\frac{{\varepsilon}_1}{(t-t_0)^{{2-m_1}}} .\frac{E(t)}{E(0)}\right)

    is non-increasing. Therefore, we get

    \begin{equation} \begin{aligned} \left( \frac{E(t)}{E(0)}\right)^{n+1} \Psi'\left(\frac{{\varepsilon}_1}{(t-t_0)^{{2-m_1}}} .\frac{E(t)}{E(0)}\right)\int_{t_1}^{t}\vartheta(s)ds \le c \mathcal{F}'_3(t_1) \quad \forall t > t_1. \end{aligned} \end{equation} (6.21)

    Multiplying (6.21) by \bigg(\frac{{\varepsilon}_1}{(t-t_0)^{2-m_1}}\bigg)^{n+1} and setting \Psi_1(\tau): = \tau^{n+1}\Psi^{\prime}(\tau) , which is strictly increasing, we obtain, for \lambda_1, \lambda_2 > 0,

    \begin{equation} E(t) \leq {\lambda}_2(t-t_0)^{2-m_1} \Psi_1^{-1}\left[\left({\lambda}_1(t-t_0)^{\frac{m_1-2}{m_1-1}}\int_{t_1}^t\vartheta(s)ds\right)^{-1}\right], \qquad\forall\, t > t_1, \end{equation} (6.22)

    This completes the proof.

    We give numerical simulations in this section to support our theoretical results in Theorems 4.1 and 4.2. We use the conservative Lax-Wendroff strategy presented in [49] to demonstrate the decay of two tests. To discretize the system (1.1) , we use a second-order finite difference method (FDM) in time and space for the space-time domain \Omega\times (0, T) = [0, 1]\times (0, 25) . The mixed boundary conditions in the system (1.1) could be viewed as a Dirichlet boundary condition on one hand and a Neuman boundary condition on the other. Let for instance, u_0(x) = x and u_1(x) = 1-x. Then, the condition

    \frac{\partial u}{\partial n}-\int_0^t g(t-s) \frac{\partial u}{\partial n} ds+\vert u_t \vert^{m(x)-2} u_t = \vert u \vert^{q(x)-2} u , \quad in \quad \Gamma_1 \times (0, T)

    will apply to the following two tests:

    TEST 1: In the first test, we set m(x) = q(x) = 2 . We use the boundary condition at x = 1 (the term u_1 will be vanish at x = 1 , while the right-hand side condition will have a nonzero starting value).

    TEST 2: In the second numerical test, we examine the case m(x) \neq 2 and q(x) \neq 2 for all x\in[0, 1] . We use the boundary at x = 0 (the term u_1 term will not vanish at x = 0 and the right hand side condition will be canceled). For this, we use the functions m(x) = q(x) = 2+\dfrac{1}{1+x} for all x\in [0, 1] .

    To check that the implemented method and the run code are numerically stable, we use \Delta{t} < 0.5\Delta x , satisfying the stability condition according to the Courant-Friedrichs-Lewy (CFL) inequality, where \Delta t = 0.0025 represents the time step and \Delta x = 0.01 the spatial step. The spatial interval [0, 1] is subdivided into 100 subintervals, whereas the temporal interval [0, T] = [0, 25] is deduced from the stability condition above. We run our code for 10,000 time steps using the following initial conditions:

    \begin{equation*} u(x, 0) = x(1-x)\;\mathrm{and}\; u_t(x, 0) = 0, \quad {\rm{in}}\ [0, 1]. \label{InSol1} \end{equation*}

    In Tests 1 and 2, we demonstrated the decay under the initial and boundary conditions. The plots in Figure 1 show the temporal wave evolution in cross sections. The three cross sections are taken at x = 0.75, 1.5, 2.25 (see Figure 1. The corresponding energies given by the "modified" equation (3.1) are presented in Figure 2. The damping behavior is well seen in both tests. The result shown in Figure 2 is equally important. As a result, the similarity decrease for the energy decay rates obtained in Test 1 and Test 2 can be clearly observed. We normalized the output by dividing the maximums value in order to compare the asymptotic convergence of the energy.

    Figure 1.  The behavioral decay of the solution wave (left: TEST 1, right: TEST 2).
    Figure 2.  The energy functions (left: TEST 1, right: TEST 2).

    Finally, it should be stressed that our intention focuses is to show the energy decay represented in Figure 2. However, we remarked that there are some similarities in the energy decay behavior. Both functions have at least a polynomial decay. This is due to the initial conditions used for the problem. We believe that, for other choices of the initial solution, we could obtain a clear difference between the outputs of the energy function.

    In this work, we considered a viscoelastic wave equation with boundary damping and variable exponents. We first proved the existence of global solutions and then we established optimal and general decay estimates depending on the behavior of the relaxation function and the nature of the variable exponent nonlinearity. We finally end our paper with some numerical illustrations. Working with variable exponents in the boundary is totally different from the earlier results and of much challenging. We compared our results with other related results and showed that our results improved and extended some earlier results in the literature.

    The authors appreciate the continued assistance of King Fahd University of Petroleum and Minerals (KFUPM) and the University of Sharjah. The authors also thank the referees for their very careful reading and valuable comments. This work is funded by KFUPM, Grant No. #SB201012.

    The authors declare that there is no conflict of interest regarding the publication of this paper.



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