Review

Cannabis in the management of PTSD: a systematic review

  • Received: 17 February 2021 Accepted: 08 May 2021 Published: 13 May 2021
  • Introduction 

    Existing reviews exploring cannabis effectiveness have numerous limitations including narrow search strategies. We systematically explored cannabis effects on PTSD symptoms, quality of life (QOL), and return to work (RTW). We also investigated harm outcomes such as adverse effects and dropouts due to adverse effects, inefficacy, and all-cause dropout rates.

    Methods 

    Our search in MEDLINE, EMBASE, PsycInfo, CINAHL, Web of Science, CENTRAL, and PubMed databases, yielded 1 eligible RCT and 10 observational studies (n = 4672). Risk of bias (RoB) was assessed with the Cochrane risk of bias tool and ROBINS-I.

    Results 

    Evidence from the included studies was mainly based on non-randomized studies with no comparators. Results from unpooled, high RoB studies showed that cannabis was associated with a reduction in overall PTSD symptoms and improved QOL. Dry mouth, headaches, and psychoactive effects such as agitation and euphoria were the commonly reported adverse effects. In most studies, cannabis was well tolerated, but small proportions of patients experienced a worsening of PTSD symptoms.

    Conclusion 

    Evidence in the current study primarily stems from low quality and high RoB observational studies. Further RCTs investigating cannabis effects on PTSD treatment should be conducted with larger sample sizes and explore a broader range of patient-important outcomes.

    Citation: Yasir Rehman, Amreen Saini, Sarina Huang, Emma Sood, Ravneet Gill, Sezgi Yanikomeroglu. Cannabis in the management of PTSD: a systematic review[J]. AIMS Neuroscience, 2021, 8(3): 414-434. doi: 10.3934/Neuroscience.2021022

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  • Introduction 

    Existing reviews exploring cannabis effectiveness have numerous limitations including narrow search strategies. We systematically explored cannabis effects on PTSD symptoms, quality of life (QOL), and return to work (RTW). We also investigated harm outcomes such as adverse effects and dropouts due to adverse effects, inefficacy, and all-cause dropout rates.

    Methods 

    Our search in MEDLINE, EMBASE, PsycInfo, CINAHL, Web of Science, CENTRAL, and PubMed databases, yielded 1 eligible RCT and 10 observational studies (n = 4672). Risk of bias (RoB) was assessed with the Cochrane risk of bias tool and ROBINS-I.

    Results 

    Evidence from the included studies was mainly based on non-randomized studies with no comparators. Results from unpooled, high RoB studies showed that cannabis was associated with a reduction in overall PTSD symptoms and improved QOL. Dry mouth, headaches, and psychoactive effects such as agitation and euphoria were the commonly reported adverse effects. In most studies, cannabis was well tolerated, but small proportions of patients experienced a worsening of PTSD symptoms.

    Conclusion 

    Evidence in the current study primarily stems from low quality and high RoB observational studies. Further RCTs investigating cannabis effects on PTSD treatment should be conducted with larger sample sizes and explore a broader range of patient-important outcomes.



    In this paper, we consider the non-isentropic compressible Euler equations with a source term in the following Euler coordinate system:

    {ρt+(ρu)x=0,(ρu)t+(ρu2+p(ρ,S))x=βρ|u|αu,St+uSx=0, (1.1)

    whereρ,u,S andp(ρ,S) are the density, velocity, entropy and pressure of the considered gas, respectively. x[0,L] is the spatial variable, and L>0 is a constant denoting the duct's length. p(ρ,S)=aeSργ, with constants a>0 and γ>1. And, the term βρ|u|αu represents the source term with α,βR. Especially, the source term denotes friction when β<0.

    System (1.1) is equipped with initial data:

    (ρ,u,S)|t=0=(ρ0(x),u0(x),S0(x)), (1.2)

    and boundary conditions:

    (ρ,u,S)|x=0=(ρl(t),ul(t),Sl(t)). (1.3)

    If S=Const., the system (1.1) is the isentropic Euler equations with a source term. In the past few decades, the problems related to the isentropic compressible Euler equations with different kinds of source terms have been studied intensively. We refer the reader to [1,2,3,4,5,6,7,8,9,10] to find the existence and decay rates of small smooth (or large weak) solutions to Euler equations with damping. The global stability of steady supersonic solutions of 1-D compressible Euler equations with friction βρ|u|u was studied in [11]. For the singularity formation of smooth solutions, we can see [12,13,14,15] and the references therein. Moreover, the authors in [16] established the finite-time blow-up results for compressible Euler system with space-dependent damping in 1-D. Recently, time-periodic solutions have attracted much attention. However, most of these temporal periodic solutions are driven by the time-periodic external force; see [17,18] for examples. The first result on the existence and stability of time-periodic supersonic solutions triggered by boundary conditions was considered in [19]. Then, the authors of [20] studied the global existence and stability of the time-periodic solution of the isentropic compressible Euler equations with source term βρ|u|αu.

    If SConst., much less is known. In [21,22,23,24,25,26], the authors used characteristics analysis and energy estimate methods to study 1-D non-isentropic p-systems with damping in Lagrangian coordinates. Specifically, the global existence of smooth solutions for the Cauchy problem with small initial data has been investigated in [21,22]. The influence of the damping mechanism on the large time behavior of solutions was considered in [23,24]. For the results of the initial-boundary value problem, see [25,26]. The stability of combination of rarefaction waves with viscous contact wave for compressible Navier-Stokes equations with temperature-dependent transport coefficients and large data was obtained in [27]. As for the problems about non-isentropic compressible Euler equations with a vacuum boundary, we refer the reader to [28,29]. In [30,31,32], the relaxation limit problems for non-isentropic compressible Euler equations with source terms in multiple space dimensions were discussed.

    In this paper, we are interested in the dynamics of non-isentropic Euler equations with friction. Exactly speaking, we want to prove the global existence and stability of temporal periodic solutions around the supersonic steady state to non-isentropic compressible Euler equations with the general friction term βρ|u|αu for any α,βR. It is worth pointing out that the temporal periodic non-isentropic supersonic solution considered in this paper is driven by periodic boundary conditions.

    We choose the steady solution ˜W(x)=(˜ρ(x),˜u(x),˜S(x)) (with ˜u(x)>0) as a background solution, which satisfies

    {(˜ρ˜u)x=0,(˜ρ˜u2+p(˜ρ,˜S))x=β˜ρ˜uα+1,˜u˜Sx=0,(˜ρ,˜u,˜S)|x=0=(ρ,u,S0). (1.4)

    The equation (1.4)3 indicates that the static entropy in the duct must be a constant. That is, ˜S(x)=S0. Moreover, when (α,β) lies in different regions of R2, the source term β˜ρ˜uα+1 affects the movement of flow dramatically. We analyze the influence meticulously and gain the allowable maximal duct length for subsonic or supersonic inflow.

    Based on the steady solution, we are interested in two problems. The first one is, if ρl(t)ρ, ul(t)u, Sl(t)S0 and ρ0(x)˜ρ(x), u0(x)˜u(x), S0(x)S0 are small in some norm sense, can we obtain a classical solution of the problem described by (1.1)–(1.3) for [0,)×[0,L] while this classical solution remains close to the background solution? If the first question holds, our second one is whether the small classical solution is temporal-periodic as long as the inflow is time-periodic at the entrance of ducts?

    We use ˉW(t,x)=(ˉρ(t,x),ˉu(t,x),ˉS(t,x))=(ρ(t,x)˜ρ(x),u(t,x)˜u(x),S(t,x)S0) to denote the perturbation around the background solution, and, correspondingly,

    ˉW0(x)=(ˉρ0(x),ˉu0(x),ˉS0(x))=(ρ0(x)˜ρ(x),u0(x)˜u(x),S0(x)S0),
    ˉWl(t)=(ˉρl(t),ˉul(t),ˉSl(t))=(ρl(t)ρ,ul(t)u,Sl(t)S0),

    that is,

    t=0:{ρ0(x)=ˉρ0(x)+˜ρ(x),u0(x)=ˉu0(x)+˜u(x),0xL,S0(x)=ˉS0(x)+S0, (1.5)

    and

    x=0:{ρl(t)=ˉρl(t)+ρ,ul(t)=ˉul(t)+u,t0.Sl(t)=ˉSl(t)+S0. (1.6)

    The main conclusions of this article are as follows:

    Theorem 1.1. For any fixed non-sonic upstream state (ρ,u,S0) with ρρ=[(ρu)2aγeS0]1γ+1>0 and u>0, the following holds:

    1) There exists a maximal duct length Lm, which only depends on α,β,γ and (ρ,u,S0), such that the steady solution ˜W(x)=(˜ρ(x),˜u(x),S0) of the problem (1.1) exists in [0,L] for any L<Lm;

    2) The steady solution (˜ρ(x),˜u(x),S0) keeps the upstream supersonic/subsonic state and ˜ρ˜u=ρu>0;

    3) (˜ρ(x),˜u(x),S0)C2([0,L])<M0, where M0 is a constant only depending on α, β, γ, ρ, u, S0 and L;

    4) If β>0, α1 and the upstream is supersonic, the maximal duct length Lm can be infinite and a vacuum cannot appear in any finite place of ducts;

    5) When β>0, αγ and the upstream is subsonic, the maximal duct length Lm can also be infinite, and the flow cannot stop in any place of ducts.

    Theorem 1.2. Assume that the length of duct L<Lm and the steady flow is supersonic at the entrance of a duct, i.e., ρ<ρ=[(ρu)2aγeS0]1γ+1. Then, there are constants ε0 and K0 such that, if

    ˉW0(x)C1([0,L])=(ρ0(x)˜ρ(x),u0(x)˜u(x),S0(x)S0)C1([0,L])ε<ε0, (1.7)
    ˉWl(t)C1([0,+))=ρl(t)ρ,ul(t)u,Sl(t)S0C1([0,+))ε<ε0, (1.8)

    and the C0,C1 compatibility conditions are satisfied at point (0,0), there is a unique C1 solution W(t,x)=(ρ(t,x),u(t,x),S(t,x)) for the mixed initial-boundary value problems (1.1)–(1.3) in the domain G={(t,x)|t0,x[0,L]}, satisfying

    ˉW(t,x)C1(G)=ρ(t,x)˜ρ(x),u(t,x)˜u(x),S(t,x)S0C1(G)K0ε. (1.9)

    Remark 1.1. Since the flows at {x=L} are entirely determined by the initial data on x[0,L] and the boundary conditions on {x=0} under the supersonic conditions, we only need to present the boundary conditions on {x=0} in Theorem 1.2.

    If we further assume that the boundaries ρl(t),ul(t),Sl(t) are periodic, then the C1 solution obtained in Theorem 1.2 is a temporal periodic solution:

    Theorem 1.3. Suppose that the assumptions of Theorem 1.2 are fulfilled and the flow at the entrance x=0 is temporal-periodic, i.e., Wl(t+P)=Wl(t); then, the C1 solution W(t,x)=(ρ(t,x),u(t,x),S(t,x)) of the problem described by (1.1)(1.3) is also temporal-periodic, namely,

    W(t+P,x)=W(t,x) (1.10)

    for any t>T1 and x[0,L], where T1 is a constant defined in (4.3).

    The organization of this article is as follows. In the next section, we study the steady-state supersonic and subsonic flow. The wave decomposition for non-isentropic Euler equations is introduced in Section 3. In Section 4, based on wave decomposition, we prove the global existence and stability of smooth solutions under small perturbations around the steady-state supersonic flow. And, in Section 5, with the help of Gronwall's inequality, we obtain that the smooth supersonic solution is a temporal periodic solution, after a certain start-up time, with the same period as the boundary conditions.

    In this section, the steady-state flow is considered for some positive constants upstream (ρ,u,S0) on the left side. In [11], the authors considered the differential equation in which the Mach number varies with the length of the duct. In [20], the authors investigated the steady-state equation with sound speed and flow velocity. Different from the methods used in [11] and [20], and motivated by [33], we rewrite (1.4) as the equations related to momentum and density in this paper, namely,

    {˜mx=0,(˜m2˜ρ+p(˜ρ,S0))x=β˜mα+1˜ρα,(˜ρ,˜m)|x=0=(ρ,ρu), (2.1)

    where ˜m=˜ρ˜u represents momentum. The advantage of this method is that the vacuum and stagnant states can be considered. Now, we analyze this problem in three cases:

    Case 1: α1 and αγ.

    In this case, (2.1) becomes

    {˜m=const.=ρu,F1(˜ρ,˜m)x=β˜mα+1, (2.2)

    where

    F1(˜ρ,˜m)=˜m2α1˜ρα1+aγeS0γ+α˜ργ+α. (2.3)

    Then, we get

    F1(˜ρ,˜m)˜ρ=˜ρα(˜m2˜ρ2+aγeS0˜ργ1)=˜ρα2(˜ρ2p˜ρ˜m2). (2.4)

    Let G(˜ρ,˜m)=˜ρ2p˜ρ˜m2. For any fixed ˜m>0, we have that lim˜ρ0G(˜ρ,˜m)=˜m2<0. From the definition of p(˜ρ,S0), we obtain

    ˜ρ2p˜ρ is a strictly increasing function for˜ρ>0.

    Thus, when ˜ρ+, G(˜ρ,˜m)+. Then, there exists ρ=[(ρu)2aγeS0]1γ+1>0 such that G(ρ,˜m)=0 (i.e., (ρ)2p˜ρ(ρ)=˜m2). That is, when ˜ρ=ρ, the fluid velocity is equal to the sound speed (i.e., ˜u=˜c=p˜ρ=aγeS02˜ργ12). Therefore, we have

    F1(˜ρ,˜m)˜ρ=˜ρα2(p˜ρ˜ρ2˜m2)<0p˜ρ˜ρ2<˜m2 (2.5)

    and

    F1(˜ρ,˜m)˜ρ=˜ρα2(p˜ρ˜ρ2˜m2)>0p˜ρ˜ρ2>˜m2. (2.6)

    We conclude that F1(˜ρ,˜m)˜ρ<0 for ˜ρ<ρ and F1(˜ρ,˜m)˜ρ>0 for ˜ρ>ρ. Furthermore, we have

    lim˜ρ0F1(˜ρ,˜m)=0,lim˜ρ+F1(˜ρ,˜m)=+,F1(ρ,˜m)<0,forα>1; (2.7)
    lim˜ρ0F1(˜ρ,˜m)=+,lim˜ρ+F1(˜ρ,˜m)=+,F1(ρ,˜m)>0,forγ<α<1; (2.8)

    and

    lim˜ρ0F1(˜ρ,˜m)=+,lim˜ρ+F1(˜ρ,˜m)=0,F1(ρ,˜m)<0,forα<γ. (2.9)

    Then, for any fixed ˜m=ρu>0, according to different regions of αR, we draw the graphs of F1(˜ρ,˜m). See Figure 1 below.

    Figure 1.  Plot of ˜ρF1(˜ρ,m).

    Integrating (2.2)2 over (0,x), we obtain

    F1(˜ρ(x),˜m)F1(ρ,˜m)=β˜mα+1x. (2.10)

    If β<0, by (2.10), F1(˜ρ,˜m) will decrease as the length of ducts increases, until it arrives at the minimum F1(ρ,˜m), no matter whether the upstream is supersonic (i.e., ρ<ρ) or subsonic (i.e., ρ>ρ). Therefore, we get the maximal length of ducts

    Lm=1β[u1α1α+aγeS0γ+αργ1uα1+(aγeS0)1αγ+1(ρu)(1α)(γ1)γ+1(1α11γ+α)] (2.11)

    for a supersonic or subsonic flow before it gets choked, which is the state where the flow speed is equal to the sonic speed.

    However, if β>0, α>1 and the upstream is supersonic (i.e., ρ<ρ), by (2.7), (2.10) and Figure 1 (i), we know that ˜ρ is decreasing as duct length x increases. Then, we get the maximal length of ducts

    Lm=1β(u1αα1aγeS0γ+αργ1uα1) (2.12)

    for a supersonic flow before it reaches the vacuum state. If γ<α<1 or α<γ, by (2.8)–(2.10) and Figure 1(ii) and (iii), ˜ρ is decreasing as the duct length x increases for supersonic upstream, too. But, the vacuum will never occur for any duct length L.

    Moreover, if β>0, α<γ and the upstream is subsonic (i.e., ρ>ρ), combining (2.9), (2.10) with Figure 1(iii), ˜ρ is increasing as the duct length x increases. At the same time, F1(˜ρ,˜m) is increasing and approaching its supremum 0. Then, we get the maximal length of the duct Lm, which is still as shown in (2.12). When L>Lm, the fluid velocity is zero, that is, the fluid stagnates in a finite place. While, if γ<α<1 or α>1, again, by (2.7), (2.8), (2.10) and Figure 1(i) and (ii), ˜ρ is also increasing as the duct length x increases, but F1(˜ρ,˜m) goes to infinity as ˜ρ grows. In this case, although the fluid is slowing down, it does not stagnate at any finite place.

    Case 2: α=1.

    Now, (2.2) turns into

    {˜m=ρu,F2(˜ρ,˜m)x=β˜m2, (2.13)

    where

    F2(˜ρ,˜m)=˜m2ln˜ρ+aγeS0γ+1˜ργ+1.

    And, we get

    lim˜ρ0F2(˜ρ,˜m)=+,lim˜ρ+F2(˜ρ,˜m)=+, (2.14)
    F2(˜ρ,˜m)˜ρ=˜ρ(˜m2˜ρ2+aγeS0˜ργ1), (2.15)

    and

    F2(˜ρ(x),˜m)F2(ρ,˜m)=β˜m2x. (2.16)

    Similarly, the function F2(˜ρ(x),˜m) gets its minimum at point ˜ρ=ρ. If β<0, combining (2.14) with (2.16), we get the maximal length of ducts

    Lm=1β(γ+1)(lnρ1γu2aγeS0+aγeS0ργ1u21) (2.17)

    for a supersonic or subsonic flow before it gets choked. While, if β>0, the flow remains in its entrance state for any duct length L>0, no matter whether it is supersonic or subsonic.

    Case 3: α=γ.

    In this case, (2.1) changes into

    {˜m=ρu,F3(˜ρ,˜m)x=β˜m1γ, (2.18)

    where

    F3(˜ρ,˜m)=˜m21+γ˜ργ1+aγeS0ln˜ρ.

    Then, we have

    lim˜ρ0F3(˜ρ,˜m)=+,lim˜ρ+F3(˜ρ,˜m)=+, (2.19)
    F3(˜ρ,˜m)˜ρ=˜ργ(˜m2˜ρ2+aγeS0˜ργ1), (2.20)

    and

    F3(˜ρ(x),˜m)F3(ρ,˜m)=β˜m1γx. (2.21)

    Similar to the other two cases, the function F3(˜ρ(x),˜m) gets its minimum at point ˜ρ=ρ. If β<0, by (2.19) and (2.21), we obtain the maximal length of ducts

    Lm=1β(1+γ)[uγ+1+aγeS0(ρu)γ1ln(aγeS01ργ1u2)] (2.22)

    for a supersonic or subsonic flow before it gets choked. While, if β>0, again, by (2.19) and (2.21), the flow also keeps the upstream supersonic or subsonic state for any duct length L>0.

    To sum up, we draw the following conclusion from the above analysis:

    Lemma 2.1. If ρρ>0,u>0,c=(aγeS0)1γ+1(ρu)γ1γ+1>0 and the duct length L<Lm, where Lm is the maximal allowable duct length given in (2.11), (2.12), (2.17) and (2.22), then the Cauchy problem (1.4) admits a unique smooth positive solution (˜ρ(x),˜u(x),S0) which satisfies the following properties:

    1) 0<ρ<˜ρ(x)<ρ and c<˜u(x)<u, \quad if β<0 and ρ<ρ;

    2) 0<ρ<˜ρ(x)<ρ and u<˜u(x)<c, \quad if β<0 and ρ>ρ;

    3) 0<˜ρ(x)<ρ and c<u<˜u(x)<+, \quad if β>0 and ρ<ρ;

    4) 0<ρ<˜ρ(x)<+ and 0<˜u(x)<u<c, \quad if β>0 and ρ>ρ;

    5) ˜ρ˜u=ρu;

    6) (˜ρ(x),˜u(x),S0)C2([0,L])<M0, where M0 is a constant only depending on α, β, γ, ρ, u, S0 and L.

    Remark 2.1. The following is worth pointing out:

    1) When β>0 and the upstream is supersonic, a vacuum can occur at the finite place for α>1, while a vacuum will never happen in any finite ducts for α1;

    2) When β>0 and the upstream is subsonic, fluid velocity can be zero at the finite place for α<γ, while the movement of fluid will never stop in the duct for αγ;

    3) For the case of β=0, we refer the reader to [19] for details.

    Thus, from Lemma 2.1 and Remark 2.1, we can directly get Theorem 1.1.

    In order to answer the two problems proposed in the introduction, we introduce a wave decomposition for system (1.1) in this section. Here, we choose the steady supersonic solution ˜W(x)=(˜ρ(x),˜u(x),˜S(x)) (with ˜u(x)>0) as the background solution, which satisfies (1.4). For system (1.1), the corresponding simplification system has the form

    {ρt+ρxu+ρux=0,ut+uux+aγeSργ2ρx+aeSργ1Sx=βuα+1,St+uSx=0. (3.1)

    Let us denote W(t,x)=ˉW(t,x)+˜W(x), where ˉW=(ˉρ,ˉu,ˉS) is the perturbation around the background solution. Substituting

    ρ(t,x)=ˉρ(t,x)+˜ρ(x),u(t,x)=ˉu(t,x)+˜u(x),S(t,x)=ˉS(t,x)+S0 (3.2)

    into (3.1) yields

    {ˉρt+uˉρx+ρˉux+˜ρxˉu+˜uxˉρ+˜u˜ρx+˜ρ˜ux=0,ˉut+uˉux+ˉu˜ux+˜ux˜u+aγeSργ2(ˉρx+˜ρx)+aeSργ1ˉSx=β(ˉu+˜u)α+1,¯St+uˉSx=0. (3.3)

    Combining this with (1.4), system (3.3) can be simplified as

    {ˉρt+uˉρx+ρˉux=˜uxˉρ˜ρxˉu,ˉut+uˉux+aγeSργ2ˉρx+aeSργ1ˉSx=Θ(ρ,˜ρ,S,S0)eˉSˉρ˜ρx˜uxˉug(u,˜u)ˉu,¯St+uˉSx=0, (3.4)

    where Θ(ρ,˜ρ,S,S0)eˉSˉρ=aγ(eSργ2eS0˜ργ2) and g(u,˜u)ˉu=β[(ˉu+˜u)α+1˜uα+1]. g(u,˜u) can be represented as follows:

    g(u,˜u)=β(α+1)10(θˉu+˜u)αdθ.

    Obviously, system (3.4) can be expressed as the following quasi-linear equations:

    ˉWt+A(W)ˉWx+H(˜W)ˉW=0, (3.5)

    where

    A(W)=(uρ0aγeSργ2uaeSργ100u), (3.6)
    H(˜W)=(˜ux˜ρx0Θ(ρ,˜ρ,S,˜S)eˉS˜ρx˜ux+g(u,˜u)0000). (3.7)

    Through simple calculations, the three eigenvalues of system (3.5) are

    λ1(W)=uc,λ2(W)=u,λ3(W)=u+c, (3.8)

    where c=aγeS2ργ12. The three right eigenvectors ri(W)(i=1,2,3) corresponding to λi(i=1,2,3) are

    {r1(W)=1ρ2+c2(ρ,c,0),r2(W)=1ρ2+γ2(ρ,0,γ),r3(W)=1ρ2+c2(ρ,c,0). (3.9)

    The left eigenvectors li(W)(i=1,2,3) satisfy

    li(W)rj(W)δij,ri(W)ri(W)1,(i,j=1,2,3), (3.10)

    where δij represents the Kroneckeros symbol. It is easy to get the expression for li(W) as follows:

    {l1(W)=ρ2+c22(ρ1,c1,0),l2(W)=ρ2+γ22(ρ1,0,γ1),l3(W)=ρ2+c22(ρ1,c1,0). (3.11)

    Besides, li(W) and ri(W) have the same regularity.

    Let

    μi=li(W)ˉW,ϖi=li(W)ˉWx,μ=(μ1,μ2,μ3),ϖ=(ϖ1,ϖ2,ϖ3); (3.12)

    then,

    ˉW=3k=1μkrk(W),ˉWx=3k=1ϖkrk(W). (3.13)

    Noticing (3.5) and (3.12), we have

    dμidit=d(li(W)ˉW)dit=d(ˉW)ditli(W)ˉW+λi(W)˜Wli(W)ˉWli(W)H(˜W)ˉW, (3.14)

    where

    li(W)=(W1(li(W))W2(li(W))W3(li(W))). (3.15)

    By using (3.5) and (3.13), we get

    d(ˉW)dit=ˉWt+λi(W)(ˉW)x=3k=1(λi(W)λk(W))ϖkrk(W)H(˜W)ˉW. (3.16)

    Thus, noting (li(W)rj(W))=0 and li(W)rj(W)=li(W)rj(W), we get

    dμidit=μit+λi(W)μix=3j,k=1Φijk(W)ϖjμk+3j,k=1˜Φijk(W)μjμk3k=1˜˜Φik(W)μk, (3.17)

    where

    Φijk(W)=(λj(W)λi(W))li(W)Wrj(W)rk(W),˜Φijk(W)=li(W)H(˜W)Wrj(W)rk(W),˜˜Φik(W)=λi(W)li(W)˜WWrk(W)+li(W)H(˜W)rk(W), (3.18)

    and

    Φiik(W)0,k=1,2,3. (3.19)

    Similarly, we have from (3.10) and (3.13) that

    dϖidit=d(li(W)ˉWx)dit=3k=1ϖkd(li(W))ditrk(W)+li(W)d(ˉWx)dit, (3.20)

    and

    d(li(W))ditrk(W)=li(W)d(rk(W))dit=3s=1li(W)(rk(W))Wsd(Ws)dit=3s=1Cksi(W)(dˉWsdit+d˜Wsdit), (3.21)

    where Cksi(W)=li(W)(rk(W))Ws. It is concluded from (3.16) that

    d(ˉWs)dit=3j=1(λi(W)λj(W))ϖjrjs(W)H(˜W)ˉW. (3.22)

    Therefore,

    3k=1ϖkd(li(W))ditrk(W)=3j,k,s=1ϖkCksi(λj(W)λi(W))ϖjrjs(W)3k,s=1Cksiλi˜Wsxϖk+3k,s=1CksiϖkH(˜W)ˉW. (3.23)

    Then,

    li(W)dˉWxdit=li(W)(ˉWxt+A(W)ˉWxx)=3k,s=1li(W)(A(W))Ws(ˉWs+˜Ws)xϖkrkli(W)(H(˜W)ˉW)x, (3.24)

    where we used (3.5). By differentiating

    A(W)rk(W)=λk(W)rk(W)

    with respect to Ws and multiplying the result by li(W), we get

    li(W)(A(W))Wsrk=li(W)(λk)Wsrk+li(W)λk(rk)Wsli(W)A(W)(rk)Ws=(λk)Wsδik+(λkλi)Cksi(W). (3.25)

    Thus,

    dϖidit=3k=1ϖkd(li(W))ditrk(W)+li(W)d(ˉWx)dit=3j,k=1Υijk(W)ϖjϖk+3j,k=1˜Υijk(W)ϖkli(W)H(˜W)xˉW, (3.26)

    where

    Υijk(W)=(λj(W)λk(W))li(W)Wrk(W)rj(W)Wλk(W)rj(W)δik,˜Υijk(W)=λk(W)li(W)Wrk(W)˜W+li(W)WrkH(˜W)rjμj(W)Wλk(W)δik˜Wli(W)H(˜W)rk(W).

    In view of Lemma 2.1, it is clear that the term H(˜W)x in (3.26) is meaningful.

    For the convenience of the later proof, we can rewrite system (3.5) as

    ˉWx+A1(W)ˉWt+A1(W)H(˜W)ˉW=0 (3.27)

    by swapping the variables t and x. Here, we represent the eigenvalues, left eigenvectors and right eigenvectors of the matrix A1(W) as ˆλi, ˆli(W) and ˆri(W),i=1,2,3, respectively.

    Let

    ˆμi=ˆli(W)ˉW,ˆϖi=ˆli(W)ˉWt,ˆμ=(ˆμ1,ˆμ2,ˆμ3),ˆϖ=(ˆϖ1,ˆϖ2,ˆϖ3). (3.28)

    Similar to the above arguments, we can get similar results by combining (3.27) and (3.28):

    dˆμidit=ˆμix+ˆλi(W)ˆμit=3j,k=1ˆΦijk(W)ˆϖjˆμk+3j,k=1ˆ˜Φijk(W)ˆμjˆμk3k=1ˆ˜˜Φik(W)ˆμk, (3.29)

    with

    ˆΦijk(W)=(ˆλj(W)ˆλi(W))ˆli(W)Wˆrj(W)ˆrk(W),ˆ˜Φijk(W)=ˆλj(W)ˆli(W)H(˜W)Wˆrj(W)ˆrk(W),ˆ˜˜Φik(W)=ˆli(W)˜WWˆrk(W)+ˆλi(W)ˆli(W)H(˜W)ˆrk(W),

    and

    dˆϖidit=ˆϖix+ˆλi(W)ˆϖit=3j,k=1ˆΥijk(W)ˆϖjˆϖk+3j,k=1ˆ˜Υijk(W)ˆϖkˆli(W)(A1H(˜W))tˉW, (3.30)

    where

    ˆΥijk(W)=(ˆλj(W)ˆλk(W))ˆli(W)Wˆrk(W)ˆrj(W)Wˆλk(W)ˆrj(W)δik,ˆ˜Υijk(W)=ˆli(W)Wˆrk(W)˜W+ˆli(W)Wˆrk(W)A1H(˜W)ˆrjˆμj(W)ˆli(W)A1(W)H(˜W)ˆrk(W).

    The wave decomposition for the initial data

    ˉW(t,x)|t=0=ˉW0(x)=(ˉρ0(x),ˉu0(x),ˉS0(x))

    and boundary conditions

    ˉW(t,x)|x=0=ˉWl(t)=(ˉρl(t),ˉul(t),ˉSl(t))

    have the following form:

    μ0=(μ10,μ20,μ30),ϖ0=(ϖ10,ϖ20,ϖ30),ˆμl=(ˆμ1l,ˆμ2l,ˆμ3l),ˆϖl=(ˆϖ1l,ˆϖ2l,ˆϖ3l), (3.31)
    μl=(μ1l,μ2l,μ3l),ϖl=(ϖ1l,ϖ2l,ϖ3l), (3.32)

    with

    μi0=li(W0)¯W0,ϖi0=li(W0)x(ˉW0),ˆμil=ˆli(Wl)ˉWl,ˆϖil=ˆli(Wl)t(ˉWl), (3.33)
    μil=li(Wl)¯Wl,ϖil=li(Wl)x(ˉWl), (3.34)

    where

    W0=(ρ0,u0,S0),Wl=(ρl,ul,Sl).

    In this section, based on wave decomposition, we prove the global existence and stability of smooth solutions under small perturbations around the steady-state supersonic flow in region G={(t,x)|t0,x[0,L]}. The initial data and boundary conditions satisfy the compatibility conditions at point (0, 0) (see [11]).

    In order to verify Theorem 1.2, we first establish a uniform prior estimate of the supersonic classical solution. That is, we assume that

    |μi(t,x)|Kε,|ϖi(t,x)|Kε,(t,x)G,i=1,2,3, (4.1)

    when

    (ˉρ0,ˉu0,ˉS0)C1([0,L])<ε,(ˉρl,ˉul,ˉSl)C1([0,+))<ε, (4.2)

    where ε is a suitably small positive constant. Here and hereafter, K, Ki and Ki are constants that depend only on L, ε, (˜ρ,˜u,S0))C2([0,L]) and T1, defined by

    T1=mint0,x[0,L]i=1,2,3Lλi(W(t,x))>0. (4.3)

    Here, λ1, λ2 and λ3 are the three eigenvalues of system (3.5). Combining (3.9) and (3.13), (4.1) means

    |ˉW(t,x)|Kε,|ˉWx(t,x)|Kε,(t,x)G. (4.4)

    In what follows, we will show the validity of the hypothesis given by (4.1).

    Let x=xj(t)(j=1,2,3) be the characteristic curve of λj that passes through (0, 0):

    dxj(t)dt=λj(W(t,xj(t))),xj(0)=0. (4.5)

    Since λ3(W)>λ2(W)>λ1(W), we have that x=x3(t) lies below x=x2(t) and x=x2(t) lies below x=x1(t). In what follows, we divide domain G={(t,x)|t0,x[0,L]} into several different regions.

    Region 1: The region G1={(t,x)0tT1,0xL,xx3(t)}.

    For any point (t,x)G1, integrating the i-th equation in (3.17) along the i-th characteristic curve about t from 0 to t, we have

    |μi(t,x(t))|=|μi(0,bi)|+t03j,k=1|Φijk(W)ϖjμk|dτ+t03j,k=1|˜Φijk(W)μjμk|dτ+t03k=1|˜˜Φik(W)μk|dτ|μi0(bi)|+K1t0|μ(τ,x(τ))|dτ,i=1,2,3, (4.6)

    where we have used (4.3) and (4.4) and assumed that the line intersects the x axis at (0,bi). Similarly, integrating the i-th equation in (3.26) along the i-th characteristic curve and assuming that the line intersects the x axis at (0,bi) again, we get

    |ϖi(t,x(t))|=|ϖi(0,bi)|+t03j,k=1|Υijk(W)ϖjϖk|dτ+t03j,k=1|˜Υijk(W)ϖk|dτ+t0|li(W)H(˜W)xˉW|dτ|ϖi0(bi)|+K2t0|ϖ(τ,x(τ))|dτ+t0[12|˜uxxρc(ΘeˉS˜ρx)xc˜ρxxρ±˜uxx±gx(u,˜u)||μ1|+12|˜uxxρc(ΘeˉS˜ρx)x+c˜ρxxρ˜uxxgx(u,˜u)||μ3|]dτ|ϖi0(bi)|+K2t0|ϖ(τ,x(τ))|dτ+K2t0|μ(τ,x(τ))|dτ,i=1,3, (4.7)

    and

    |ϖ2(t,x(t))|=|ϖ2(0,b2)|+t03j,k=1|Υijk(W)ϖjϖk|dτ+t03j,k=1|˜Υijk(W)ϖk|dτ+t0|l2(W)H(˜W)xˉW|dτ|ϖ20(b2)|+K3t0|ϖ(τ,x(τ))|dτ+t0[ρ2+γ22ρ2+c2(|˜uxxc˜ρxxρ||μ1|+|˜uxx+c˜ρxxρ||μ3|)]dτ|ϖ20(b2)|+K3t0|ϖ(τ,x(τ))|dτ+K3t0|μ(τ,x(τ))|dτ, (4.8)

    where Θ=Θ(ρ,˜ρ,S,S0). Adding (4.6)–(4.8) together, for any i=1,2,3, and using Gronwall's inequality, one gets

    |μ(t,x)|+|ϖ(t,x)|eK4T1(μ0C0([0,L])+ϖ0C0([0,L])). (4.9)

    Due to the boundedness of T1, the arbitrariness of (t,x)G1 and (4.9), it holds that

    max(t,x)G1{|μ(t,x)|+|ϖ(t,x)|}K(μ0C0([0,L])+ϖ0C0([0,L])). (4.10)

    Region 2: The region G2={(t,x)t0,0xL,0xx1(t)}.

    We make the change of variables t and x. For any point (t,x)G2, integrating (3.29) along the i-th characteristic curve about x, it follows that

    |ˆμi(t(x),x)||ˆμil(ti)|+K5x0|ˆμ(t(ς),ς)|dς,i=1,2,3, (4.11)

    where we assumed that the line intersects the t axis at the point (ti,0). Similarly, repeating the above procedure for (3.30), we get

    |ˆϖi(t(x),x)||ˆϖil(ti)|+K6x0|ˆϖ(t(ς),ς)|dς+K6x0|ˆμ(t(ς),ς)|dς,i=1,2,3. (4.12)

    Summing up (4.11) and (4.12) for i = 1, 2, 3 and applying Gronwall's inequality, we obtain

    max(t,x)G2{|ˆμ(t,x)|+|ˆϖ(t,x)|}K(ˆμlC0([0,+))+ˆϖlC0([0,+))),(t,x)G2, (4.13)

    where we exploit the arbitrariness of (t,x)G2.

    Region 3: The region G3={(t,x)0tT1,0xL,x2(t)xx3(t)}.

    For any point (t,x)G3, integrating the 1st and 2nd equations in (3.17) and (3.26) along the 1st and 2nd characteristic curve, we get

    |μ1(t,x(t))||μ10(x1)|+K7t0|μ(τ,x(τ))|dτ, (4.14)
    |ϖ1(t,x(t))||ϖ10(x1)|+K8t0|ϖ(τ,x(τ))|dτ+t0[12|2˜uxxρc(ΘeˉS˜ρx)xc˜ρxxρ+gx(u,˜u)||μ1|+12|ρc(ΘeˉS˜ρx)x+c˜ρxxρgx(u,˜u)||μ3|]dτ|ϖ10(x1)|+K8t0|ϖ(τ,x(τ))|dτ+K8t0|μ(τ,x(τ))|dτ, (4.15)
    |μ2(t,x(t))||μ20(x2)|+K9t0|μ(τ,x(τ))|dτ, (4.16)

    and

    |ϖ2(t,x(t))||ϖ20(x2)|+K10t0|ϖ(τ,x(τ))|dτ+K10t0|μ(τ,x(τ))|dτ, (4.17)

    where we assumed that the line intersects the x axis at points (0,x1) and (0,x2), respectively. Similarly, integrating the 3rd equations in (3.17) and (3.26) along the 3rd characteristic curve, one has

    |μ3(t,x(t))||μ3l(t3)|+K11tt3|μ(τ,x(τ))|dτ|μ3l(t3)|+K11t0|μ(τ,x(τ))|dτ, (4.18)

    and

    |ϖ3(t,x(t))||ϖ3l(t3)|+K12tt3|ϖ(τ,x(τ))|dτ+tt3[12|ρc(ΘeˉS˜ρx)xc˜ρxxρgx(u,˜u)||μ1|+12|2˜uxx+ρc(ΘeˉS˜ρx)x+c˜ρxxρ+gx(u,˜u)||μ3|]dτ|ϖ3l(t3)|+K12t0|ϖ(τ,x(τ))|dτ+K12t0|μ(τ,x(τ))|dτ, (4.19)

    where the point (t3,0) is the intersection of the line and the t axis.

    Since the boundary data are small enough, we sum up (4.14)(4.19) and apply Gronwall's inequality to obtain the following:

    max(t,x)G3{|μ(t,x)|+|ϖ(t,x)|}K(μ0C0([0,L])+ϖ0C0([0,L])+μlC0([0,+))+ϖlC0([0,+))), (4.20)

    where we exploit the arbitrariness of (t,x)G3.

    Region 4: The region G4={(t,x)0tT1,0xL,x1(t)xx2(t)}.

    For any point (t,x)G4, integrating the 1st equations in (3.17) and (3.26) along the 1st characteristic curve, we get

    |μ1(t,x(t))||μ10(x1)|+K13t0|μ(τ,x(τ))|dτ, (4.21)

    and

    |ϖ1(t,x(t))||ϖ10(x1)|+K14t0|ϖ(τ,x(τ))|dτ+K14t0|μ(τ,x(τ))|dτ, (4.22)

    where we assumed that the line intersects the x axis at (0,x1). Similarly, integrating the 2nd and 3rd equations in (3.17) and (3.26) along the 2nd and 3rd characteristic curve, one has

    |μ2(t,x(t))||μ2l(t2)|+K15t0|μ(τ,x(τ))|dτ, (4.23)
    |ϖ2(t,x(t))||ϖ2l(t2)|+K16t0|ϖ(τ,x(τ))|dτ+K16t0|μ(τ,x(τ))|dτ, (4.24)
    |μ3(t,x(t))||μ3l(t3)|+K17t0|μ(τ,x(τ))|dτ, (4.25)

    and

    |ϖ3(t,x(t))||ϖ3l(t3)|+K18t0|ϖ(τ,x(τ))|dτ+K18t0|μ(τ,x(τ))|dτ, (4.26)

    where the line intersects the t axis at points (t2,0) and (t3,0), respectively.

    Noticing that the boundary data are small enough, we sum (4.21)(4.26) and then apply Gronwall's inequality to obtain

    max(t,x)G4{|μ(t,x)|+|ϖ(t,x)|}K(μ0C0([0,L])+ϖ0C0([0,L])+μlC0([0,+))+ϖlC0([0,+))), (4.27)

    where we exploit the arbitrariness of (t,x)G4.

    From (4.10), (4.13), (4.20) and (4.27), we have proved that the assumption of (4.1) is reasonable. Therefore, we have obtained a uniform C1 a priori estimate for the classical solution. Thanks to the classical theory in [34], we further obtain the global existence and uniqueness of C1 solutions (see [11,35,36,37,38,39]) for problems (1.1)–(1.3). This proves Theorem 1.2.

    In this section, we show that the smooth supersonic solution W(t,x)=(ρ(t,x),u(t,x),S(t,x)) is temporal-periodic with a period P>0, after a certain start-up time T1, under the temporal periodic boundary conditions. Here, we have assumed that Wl(t+P)=Wl(t) with P>0.

    For system (1.1), Riemann invariants ξ, η and ζ are introduced as follows:

    ξ=u2γ1c,η=S,ζ=u+2γ1c. (5.1)

    Then, system (1.1) can be transformed into the following form:

    {ξt+λ1(ξ,ζ)ξx=β(ξ2+ζ2)α+1+γ116γ(ζξ)2ηx,ηt+λ2(ξ,ζ)ηx=0,ζt+λ3(ξ,ζ)ζx=β(ξ2+ζ2)α+1+γ116γ(ζξ)2ηx, (5.2)

    where

    λ1=uc=γ+14ξ+3γ4ζ,λ2=u=12(ξ+ζ),λ3=u+c=3γ4ξ+γ+14ζ

    are three eigenvalues of system (1.1). For supersonic flow (i.e., u>c), we know that λ3>λ2>λ1>0. Obviously, (1.2)–(1.3) can be written as

    ξ(0,x)=ξ0(x),η(0,x)=η0(x),ζ(0,x)=ζ0(x),0xL, (5.3)
    ξ(t,0)=ξl(t),η(t,0)=ηl(t),ζ(t,0)=ζl(t),t0, (5.4)

    where ξl(t+P)=ξl(t),ηl(t+P)=ηl(t) and ζl(t+P)=ζl(t) with P>0.

    We swap t and x so that the problem described by (5.2)–(5.4) takes the following form:

    {ξx+1λ1ξt=1λ1[β(ξ2+ζ2)α+1+γ116γ(ζξ)2ηx],ηx+1λ2ηt=0,ζx+1λ3ζt=1λ3[β(ξ2+ζ2)α+1+γ116γ(ζξ)2ηx],ξ(t,0)=ξl(t),η(t,0)=ηl(t),ζ(t,0)=ζl(t), (5.5)

    where t>0 and x[0,L]. Next, we set

    V=(ξ˜ξ,η˜η,ζ˜ζ),Λ(t,x)=(1λ1(ξ(t,x),ζ(t,x))0001λ2(ξ(t,x),ζ(t,x))0001λ3(ξ(t,x),ζ(t,x))); (5.6)

    then, the Cauchy problem (5.5) can be simplified as follows:

    Vx+Λ(t,x)Vt=Λ(t,x)(β(ξ2+ζ2)α+1+γ116γ(ζξ)2ηx0β(ξ2+ζ2)α+1+γ116γ(ζξ)2ηx)(1˜λ1[β(˜ξ2+˜ζ2)α+1+γ116γ(˜ζ˜ξ)2˜η]01˜λ3[β(˜ξ2+˜ζ2)α+1+γ116γ(˜ζ˜ξ)2˜η]), (5.7)

    where

    ˜ξ=˜u2γ1˜c,˜η=˜S,˜ζ=˜u+2γ1˜c,˜λ1=λ1(˜ξ,˜ζ)=γ+14˜ξ+3γ2˜ζ,˜λ2=λ2(˜ξ,˜ζ)=12˜ξ+12˜ζ,˜λ3=λ3(˜ξ,˜ζ)=3γ4˜ξ+γ+14˜ζ.

    According to

    ρ˜ρC1(G)+u˜uC1(G)+S˜SC1(G)<K0ε

    and (5.1), we can easily obtain

    ξ(t,x)˜ξ(x)C1(G)+η(t,x)˜η(x)C1(G)+ζ(t,x)˜ζ(x)C1(G)<J1ε, (5.8)

    where the constant J1(>0) depends solely on ˜ρ,˜u,γ and L.

    In order to prove that W(t+P,x)=W(t,x), for any t>T1 and x[0,L], we first prove that the following conclusions hold:

    ξ(t+P,x)=ξ(t,x),η(t+P,x)=η(t,x),ζ(t+P,x)=ζ(t,x),t>T1,x[0,L], (5.9)

    where T1 is the start-up time, which is defined in (4.3).

    Let

    N(t,x)=V(t+P,x)V(t,x);

    then, according to (5.7), we obtain

    {Nx+Λ(t,x)Nt=R(t,x),N(t,0)=0,t>0, (5.10)

    where

    R(t,x)=Λ(t+P,x)(β(ξ(t+P,x)2+ζ(t+P,x)2)α+1+(γ1)(ζ(t+P,x)ξ(t+P,x))2ηx(t+P,x)16γ0β(ξ(t+P,x)2+ζ(t+P,x)2)α+1+(γ1)(ζ(t+P,x)ξ(t+P,x))2ηx(t+P,x)16γ)Λ(t,x)(β(ξ(t,x)2+ζ(t,x)2)α+1+(γ1)(ζ(t,x)ξ(t,x))2ηx(t,x)16γ0β(ξ(t,x)2+ζ(t,x)2)α+1+(γ1)(ζ(t,x)ξ(t,x))2ηx(t,x)16γ)[Λ(t+P,x)Λ(t,x)]Vt(t+P,x). (5.11)

    Using the continuity of λi(i=1,2,3) and (5.8), after some calculations, we obtain the following estimates:

    |Vt(t+P,x)|J2ε, (5.12)
    |ξ(t+P,x)+ζ(t+P,x)|J3, (5.13)
    |Λ(t,x)|J4, (5.14)
    |Λ(t+P,x)Λ(t,x)|J5|N(t,x)|, (5.15)
    |Λt(ξ(t,x),η(t,x))|J6ε, (5.16)

    and

    |R(t,x)||Λ(t,x)|(J7|β||N(t,x)|+γ116γJ8J9|N(t,x)|0J7|β||N(t,x)|+γ116γJ8J9|N(t,x)|)+|Λ(t+P,x)Λ(t,x)|((J32)α+1|β|+γ116J23J80(J32)α+1|β|+γ116J23J8)+|Λ(t+P,x)Λ(t,x)||Vt(t+P,x)|J10|N(t,x)|, (5.17)

    where the constants Ji(i=2,,10) depend only on ˜ρ,˜u,γ and L.

    In the above calculation, we have used

    |(ξ(t+P,x)2+ζ(t+P,x)2)α+1(ξ(t,x)2+ζ(t,x)2)α+1|=|uα+1(t+P,x)uα+1(t,x)|=|u(t+P,x)u(t,x)||(α+1)||10[u(t,x)+θ(u(t+P,x)u(t,x))]αdθ|J7|N(t,x)|,forα1;
    |(ξ(t+P,x)2+ζ(t+P,x)2)α+1(ξ(t,x)2+ζ(t,x)2)α+1|=0J7|N(t,x)|,forα=1.

    Now, fix a point (t,x) with t>T1 and 0<x<L. Let Γ1:t=ˇt1(x) and Γ3:t=ˇt3(x) be two characteristic curves passing through point (t,x), that is,

    dˇt1dx=1λ1(ξ(ˇt1,x),ζ(ˇt1,x)),ˇt1(x)=t, (5.18)

    and

    dˇt3dx=1λ3(ξ(ˇt3,x),ζ(ˇt3,x)),ˇt3(x)=t, (5.19)

    where x[0,x]. Since λ3(W)>λ1(W), Γ1 lies below Γ3. Set

    Ψ(x)=12ˇt3(x)ˇt1(x)|N(t,x)|2dt, (5.20)

    where 0x<x. According to the definition of T1, and combining t>T1 and 0xL, we obtain that (ˇt1(0),ˇt3(0))(0,+). Then, it follows from (5.10) that N(t,0)0. Thus, Ψ(0)=0.

    Taking the derivative of Ψ(x) with regard to x gives

    Ψ(x)=ˇt3(x)ˇt1(x)N(t,x)Nx(t,x)dt+12|N(ˇt3(x),x)|21λ3(ξ(ˇt3(x),x),ζ(ˇt3,x))12|N(ˇt1(x),x)|21λ1(ξ(ˇt1(x),x),ζ(ˇt1(x),x))ˇt3(x)ˇt1(x)N(t,x)Λ(t,x)Nt(t,x)dt+ˇt3(x)ˇt1(x)N(t,x)R(t,x)dt+12N(t,x)Λ(t,x)N(t,x)|t=ˇt3(x)t=ˇt1(x)=12ˇt3(x)ˇt1(x)[(N(t,x)Λ(t,x)N(t,x))tN(t,x)Λt(t,x)N(t,x)]dt+ˇt3(x)ˇt1(x)N(t,x)R(t,x)dt+12N(t,x)Λ(t,x)N(t,x)|t=ˇt3(x)t=ˇt1(x)=12ˇt3(x)ˇt1(x)N(t,x)Λt(t,x)N(t,x)dt+ˇt3(x)ˇt1(x)N(t,x)R(t,x)dt(J6ε+2J10)Ψ(x), (5.21)

    where we used (5.16) and (5.17).

    Therefore, using Gronwall's inequality, we obtain that Ψ(x)0. In addition, according to the continuity of Ψ(x), we obtain that Ψ(x)=0; then, N(t,x)=0. Using the arbitrariness of (t,x), we get

    N(t,x)0,t>T1,x[0,L].

    Thus, (5.9) holds. Then, from (5.1) and c=aγeS2ργ12, it follows that

    W(t+P,x)=W(t,x)

    for any t>T1 and x[0,L], where T1 is the start-up time defined in (4.3). This proves Theorem 1.3.

    The authors declare they have not used Artificial Intelligence (AI) tools in the creation of this article.

    This work was supported in part by the Natural Science Foundation of China Grant No. 12101372, No. 12271310, and the Natural Science Foundation of Shandong Province Grant No. ZR2022MA088.

    The authors declare there is no conflict of interest.



    Conflict of interest



    The authors declare no conflict of interest.

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