Citation: Anju Usman Singh. Dysbiosis, small intestinal bacterial overgrowth and biofilms in autism and chronic illness[J]. AIMS Molecular Science, 2018, 5(2): 160-165. doi: 10.3934/molsci.2018.2.160
[1] | Bo Sun, Ming Wei, Binbin Jing . Optimal model for the aircraft arrival and departure scheduling problem with fuzzy runway incursion time. Mathematical Biosciences and Engineering, 2021, 18(5): 6724-6738. doi: 10.3934/mbe.2021334 |
[2] | Ming Wei, Ligang Zhao, Zhijian Ye, Binbin Jing . An integrated optimization mode for multi-type aircraft flight scheduling and routing problem. Mathematical Biosciences and Engineering, 2020, 17(5): 4990-5004. doi: 10.3934/mbe.2020270 |
[3] | Bin Deng, Ran Ding, Jingfeng Li, Junfeng Huang, Kaiyi Tang, Weidong Li . Hybrid multi-objective metaheuristic algorithms for solving airline crew rostering problem with qualification and language. Mathematical Biosciences and Engineering, 2023, 20(1): 1460-1487. doi: 10.3934/mbe.2023066 |
[4] | Zilong Zhuang, Zhiyao Lu, Zizhao Huang, Chengliang Liu, Wei Qin . A novel complex network based dynamic rule selection approach for open shop scheduling problem with release dates. Mathematical Biosciences and Engineering, 2019, 16(5): 4491-4505. doi: 10.3934/mbe.2019224 |
[5] | Yafei Li, Yuxi Liu . Multi-airport system flight slot optimization method based on absolute fairness. Mathematical Biosciences and Engineering, 2023, 20(10): 17919-17948. doi: 10.3934/mbe.2023797 |
[6] | Bin Wang, Fagui Liu . Task arrival based energy efficient optimization in smart-IoT data center. Mathematical Biosciences and Engineering, 2021, 18(3): 2713-2732. doi: 10.3934/mbe.2021138 |
[7] | Shirin Ramezan Ghanbari, Behrouz Afshar-Nadjafi, Majid Sabzehparvar . Robust optimization of train scheduling with consideration of response actions to primary and secondary risks. Mathematical Biosciences and Engineering, 2023, 20(7): 13015-13035. doi: 10.3934/mbe.2023580 |
[8] | Santiago Iturriaga, Jonathan Muraña, Sergio Nesmachnow . Bio-inspired negotiation approach for smart-grid colocation datacenter operation. Mathematical Biosciences and Engineering, 2022, 19(3): 2403-2423. doi: 10.3934/mbe.2022111 |
[9] | Jianguo Duan, Mengting Wang, Qinglei Zhang, Jiyun Qin . Distributed shop scheduling: A comprehensive review on classifications, models and algorithms. Mathematical Biosciences and Engineering, 2023, 20(8): 15265-15308. doi: 10.3934/mbe.2023683 |
[10] | Yingjia Tan, Bo Sun, Li Guo, Binbin Jing . Novel model for integrated demand-responsive transit service considering rail transit schedule. Mathematical Biosciences and Engineering, 2022, 19(12): 12371-12386. doi: 10.3934/mbe.2022577 |
We consider the initial boundary value problem of the following porous elastic system with nonlinear or linear weak damping terms and nonlinear source terms
$ {utt−μuxx−bϕx+g1(ut)=f1(u,ϕ), x∈(0,L), t∈[0,T),ϕtt−δϕxx+bux+ξϕ+g2(ϕt)=f2(u,ϕ), x∈(0,L), t∈[0,T),u(x,0)=u0(x), ut(x,0)=u1(x), x∈(0,L),ϕ(x,0)=ϕ0(x), ϕt(x,0)=ϕ1(x), x∈(0,L),u(0,t)=u(L,t)=ϕ(0,t)=ϕ(L,t)=0, t∈[0,T), $ | (1.1) |
where $ u(x, t) $ and $ \phi(x, t) $ are the displacement of the solid elastic material and the volume fraction, respectively, $ \mu, \ b, \ \delta $ and $ \xi $ are coefficients with physical meaning satisfying
$ \mu > 0, \ b\neq0, \ \delta > 0, \ \xi > 0 \ \text{and}\ \mu\xi > b^2, $ |
$ u_0, \ u_1, \phi_0 $ and $ \phi_1 $ are given initial data, and the assumptions of weak damping terms $ g_1, \ g_2 $ and nonlinear source terms $ f_1, \ f_2 $ will be given in Section 2 by Assumption 2.1 and Assumption 2.2, respectively.
In the physical view, elastic solid with voids is an important extension of the classical elasticity theory. It allows the processing of porous solids in which the matrix material is elastic and the interstices are void of material (see [8,20] and references therein). Porous media reflects the properties of many materials in the real world, including rocks, soil, wood, ceramics, pressed powder, bones, natural gas hydrates and so on. Due to the diversity of porous media and its special physical properties, such models were widely applied in the past few decades in the petroleum industry, engineering, etc (see [1,12,13,16,17,19]).
As mathematical efforts, Goodman and Cowin [2,8] established the continuum theory and the variational principle of granular materials. Then Nunziato and Cowin [3,18] developed the linear and nonlinear theories of porous elastic materials. In recent years, the study of the porous elastic system also attracted a lot of attention [5,6,7,21,22]. We particularly mention that Freitas et.al. in [5] studied the problem (1.1) and proved the global existence and finite time blowup of solutions. Especially, they built up the continuous dependence on initial data of the local solution in the following version
$ ˆE(t)≤eC0tˆE(0), C0>0, $ | (1.2) |
which can also be extended to the global solution with the same form. By denoting $ z = (u, \phi) $ and $ \tilde{z} = (\tilde{u}, \tilde{\phi}) $ the global solutions to problem (1.1) corresponding to the initial data $ z_{0} $, $ z_{1} $ and $ \tilde{z}_{0} $, $ \tilde{z}_{1} $, respectively, $ \widehat{E}(0) $ is the distance of two sets of different initial data
$ z_0, \tilde{z}_0 \in V: = {H_{0}^1(0, L)}\times {H_{0}^1(0, L)}, $ |
and
$ z_{1}, \tilde{z}_{1} \in {L^2(0, L)}\times {L^2(0, L)}, $ |
that is
$ ˆE(0):=12‖z1−˜z1‖22+12‖z0−˜z0‖2V, $ |
and $ \widehat{E}(t) $ is the distance of solutions induced by these two sets of different initial data
$ ˆE(t):=12‖zt−˜zt‖22+12‖z−˜z‖2V. $ |
The growth estimate (1.2) indicates that the growth of the distance of solutions $ \widehat{E}(t) $ is bounded by an exponential growth bound with time $ t $. In other words, as the time $ t $ goes to infinity, the distance of solutions $ \widehat{E}(t) $ of the system is bounded by a very large bound, by which it is hard to explain the solutions $ z $ and $ \tilde{z} $ of such a dissipative system with the initial data $ z_0, z_1 $ and $ \tilde{z}_0, \tilde{z}_1 $, respectively, as both of them are expected to decay to zero as the time $ t $ goes to infinity. Hence, the estimate on the growth of the distance of solutions $ \widehat{E}(t) $ is proposed to be improved to reflect the decay properties with time $ t $ to be consistent with the dissipative behavior of the system. To achieve this, the efforts in the present paper are illustrated by two new continuous dependence results on the initial data for the global-in-time solution. Especially, it is found that the system with the linear damping term behaves differently from that with the nonlinear damping term. Hence in the present paper, we adopt two different estimate strategies to deal with the problem and derive two different conclusions:
$ ({\rm{i}}) $ For the linear damping case, i.e., $ g_1(u_t) $ and $ g_2(\phi_t) $ take the linear form and satisfy Assumption 2.1, we have
$ ˆE(t)≤C1(ˆE(0)+C2(ˆE(0))a2)ρe−C3t, $ | (1.3) |
where the positive constants $ C_1, C_2, C_3, a, \rho $ are independent of initial data.
$ ({\rm{ii}}) $ For the nonlinear damping case, i.e., $ g_1(u_t) $ and $ g_2(\phi_t) $ take the nonlinear form and satisfy Assumption 2.1, we have
$ ˆE(t)≤C5(ˆE(0)+C6(ˆE(0))b02)κe−C7t, $ | (1.4) |
where $ 0 < \kappa < 1 $, and the positive constants $ C_5, C_6, C_7, b_0 $ are dependent of initial data.
By observing (1.3) and (1.4), we find that these two continuous dependence results can reasonably reflect the decay property of the dissipative system (1.1). The difference between (1.3) and (1.4) is that the parameters in (1.3) do not depend on the initial data, while the parameters in (1.4) depend on the initial data. Hence although (1.3) and (1.4) are in the similar form, we present and prove them separately.
Additionally, to develop the finite time blowup of the solution to problem (1.1) at the arbitrary positive initial energy level derived in [22], we estimate the lower bound of the blowup time in the present paper for the nonlinear weak damping case by noticing that the linear weak damping case was discussed in [22]. For more relative works on the blowup of solutions to the hyperbolic equations at high initial energy, please refer to [10,11,14,15,25]. We can also refer to [9,23,24] for the works about the blowup of solutions to parabolic equations.
The rest of the present paper is organized as follows. In Section 2, we give some notations, assumptions about damping terms and source terms, and functionals and manifolds for the potential well theory. In Section 3, we deal with the continuous dependence on initial data of the global solution for the linear weak damping case. In Section 4, we establish the continuous dependence on initial data of the global solution for the nonlinear weak damping case. In Section 5, we estimate the lower bound of blowup time at the arbitrarily positive initial energy level for the nonlinear weak damping case.
We denote the $ L^{2} $-inner product by
$ (u, v): = \int_{0}^{L}{uv}{\rm d}x, $ |
and the norm of $ L^{p}(0, L) $ by
$ \|u\|_{p}: = \left( \int_{0}^{L}|u|^{p}{\rm d}x \right)^{\frac{1}{p}}. $ |
As we are dealing with the system of two equations, for $ z = (u, \phi) $ and $ \hat{z} = (\hat{u}, \hat{\phi}) $, we introduce
$ (z, \hat{z}): = (u, \hat{u})+(\phi, \hat{\phi}) $ |
and
$ ‖z‖p:=(‖u‖pp+‖ϕ‖pp)1p. $ | (2.1) |
Further, we consider the Hilbert space
$ V = {H_{0}^1(0, L)}\times {H_{0}^1(0, L)} $ |
with inner products given by
$ (z,ˆz)V:=∫L0(μuxˆux+δϕxˆϕx+ξϕˆϕ+b(uxˆϕ+ϕˆux))dx $ | (2.2) |
for $ z = (u, \phi) $, $ \hat{z} = (\hat{u}, \hat{\phi}) $, where $ \mu $, $ \delta $, $ \xi $, $ b $ are the coefficients of the terms in the equations in problem (1.1). Therefore, we have
$ ‖z‖2V:=∫L0(μu2x+δϕ2x+ξϕ2+2buxϕ)dx. $ | (2.3) |
The norm $ \|z\|_{V} $ is equivalent to the corresponding usual norm on $ V $, i.e., $ {H_{0}^1(0, L)}\times {H_{0}^1(0, L)} $, introduced in [20]. For $ 1 < q < +\infty $, we define
$ Rq:=supz∈V∖{0}‖z‖qq‖z‖qV, $ | (2.4) |
which means
$ ‖z‖qq≤Rq‖z‖qV $ | (2.5) |
for $ z\in V $. Here, due to $ H^{1}_{0}(0, L)\hookrightarrow L^{q}(0, L) $ for $ 1 < q < +\infty $, we see $ 0 < R_{q} < +\infty $. And we denote
$ \mathcal{F}(z): = (f_{1}(u, \phi), f_{2}(u, \phi)) $ |
and
$ \mathcal{G}(z_{t}): = (g_{1}(u_{t}), g_{2}(\phi_{t})), $ |
where $ f_{j}(u, \phi) $, $ j = 1, 2 $, are the source terms, and $ g_{1}(u_{t}) $ and $ g_{2}(\phi_{t}) $ are the damping terms in the equations in problem (1.1).
We give the following assumptions about damping terms, i.e., $ g_{1}(u_{t}) $ and $ g_{2}(\phi_{t}) $, and source terms, i.e., $ f_{j}(u, \phi) $, $ j = 1, 2 $, in the equations in problem (1.1).
Assumption 2.1. (Damping terms) Let $ g_{1}, g_{2}: \mathbb{R}\rightarrow \mathbb{R} $ be continuous, monotone increasing functions with $ g_{1}(0) = g_{2}(0) = 0 $. In addition, there exist positive constants $ \alpha > 0 $ and $ \beta > 0 $ such that
${\rm{(i)}}$ for $ |s|\geq1 $
$ α|s|m+1≤g1(s)s≤β|s|m+1, m≥1; $ | (2.6) |
and
$ α|s|r+1≤g2(s)s≤β|s|r+1, r≥1; $ | (2.7) |
${\rm{(ii)}}$ for $ |s| < 1 $
$ α|s|ˆm≤|g1(s)|≤β|s|ˆm, ˆm≥1; $ | (2.8) |
and
$ α|s|ˆr≤|g2(s)|≤β|s|ˆr, ˆr≥1. $ | (2.9) |
Assumption 2.2. (Source terms) For the functions $ f_{j}\in C^{1}(\mathbb{R}^{2}) $, $ j = 1, 2 $, there exists a positive constant $ C $ such that
$ |∇fj(η)|≤C(|η1|p−1+|η2|p−1+1), p>1. $ | (2.10) |
where $ \eta = (\eta_{1}, \eta_{2})\in\mathbb{R}^{2} $, $ f_{j}(\eta) = f_{j}(\eta_{1}, \eta_{2}) $, $ j = 1, 2 $, and
$ ∇fj:=(∂fj∂η1,∂fj∂η2). $ |
There exists a nonnegative function $ F\in C^{2}(\mathbb{R}^{2}) $ satisfying
$ ∇F=F $ | (2.11) |
and
$ F(λη)=λp+1F(η) $ | (2.12) |
for all $ \lambda > 0 $, where $ F(\eta) = F(\eta_{1}, \eta_{2}) $ and
$ ∇F:=(∂F∂η1,∂F∂η2). $ | (2.13) |
According to [5], Assumption 2.2 implies that there exists a constant $ M > 0 $ such that
$ F(z)≤M(|u|p+1+|ϕ|p+1). $ | (2.14) |
Next, we recall some functionals and manifolds for the potential well theory. We recall the potential energy functional
$ J(z):=12‖z‖2V−∫L0F(z)dx $ | (2.15) |
and the Nehari functional
$ I(z):=‖z‖2V−(p+1)∫L0F(z)dx. $ |
The energy functional is defined as
$ E(z(t),zt(t)):=12‖zt‖22+J(z). $ | (2.16) |
And the Nehari manifold is defined as
$ N:={z∈V∖{0}| I(z)=0}. $ |
Then we can define the depth of the potential well
$ d:=infz∈NJ(z). $ |
By above, we introduce the stable manifold
$ W:={z∈V| J(z)<d, I(z)>0}∪{0}. $ |
Next, since we need to apply the decay rate of the energy in investigating continuous dependence on the initial data of the solution, we recall the following notations used in the investigation of the decay rate of the energy in [5]
$ ˆd:=sups∈[0,+∞)M(s)=M(s0)=p−12(p+1)((p+1)MRp+1)−2p−1, $ | (2.17) |
where
$ M(s):=12s2−MRp+1sp+1, $ | (2.18) |
and $ \mathcal{M}(s) $ attains the maximum value at
$ s0:=((p+1)MRp+1)−1p−1. $ | (2.19) |
Here, Proposition 2.11 in [5] shows the fact $ \hat{d}\leq d $.
In this section, we consider the model equations in (1.1) with the linear weak damping terms, i.e., $ r = m = \hat{r} = \hat{m} = 1 $. First, we need the following decay result of the energy.
Lemma 3.1. (Decay of the energy) Let Assumption 2.1 and Assumption 2.2 hold with $ r = m = \hat{r} = \hat{m} = 1 $. For any $ 0 < \sigma < 1 $, if $ \mathcal{E}(z_{0}, z_{1}) < \sigma \hat{d} $ and $ z_{0}\in W $, then one has
$ E(z(t),zt(t))<K0e−λ0t $ | (3.1) |
for $ t > 0 $, where $ \lambda_{0} $ and $ K_{0} $ will be defined in the proof.
Proof. We define
$ H(t):=E(z(t),zt(t))+ε(z,zt), $ |
where $ \varepsilon > 0 $. Here, according to Cauchy-Schwartz inequality, Young inequality, and (2.5), we have
$ H(t)≤E(z(t),zt(t))+ε‖z‖2‖zt‖2≤E(z(t),zt(t))+ε2‖z‖22+ε2‖zt‖22≤E(z(t),zt(t))+ε2R2‖z‖2V+ε2‖zt‖22≤E(z(t),zt(t))+εmax{R2,1}(12‖z‖2V+12‖zt‖22) $ | (3.2) |
and
$ H(t)≥E(z(t),zt(t))−ε‖z‖2‖zt‖2≥E(z(t),zt(t))−εmax{R2,1}(12‖z‖2V+12‖zt‖22). $ | (3.3) |
According to Theorem 2.12(ⅳ) in [5], we know
$ 12‖z‖2V+12‖zt‖22≤p+1p−1E(z(t),zt(t)), $ | (3.4) |
which means that (3.2) and (3.3) turn to
$ H(t)≤E(z(t),zt(t))+εmax{R2,1}(p+1)p−1E(z(t),zt(t)) $ | (3.5) |
and
$ H(t)≥E(z(t),zt(t))−εmax{R2,1}(p+1)p−1E(z(t),zt(t)). $ | (3.6) |
According to (3.5) and (3.6), we know
$ α1E(z(t),zt(t))≤H(t)≤α2E(z(t),zt(t)), $ | (3.7) |
where
$ \alpha_{1}: = 1-\frac{\varepsilon\max\{R_{2}, 1\}(p+1)}{p-1} $ |
and
$ \alpha_{2}: = 1+\frac{\varepsilon\max\{R_{2}, 1\}(p+1)}{p-1}. $ |
We calculate the derivative of the auxiliary functional $ H(t) $ with respect to time $ t $ as
$ H′(t)=ddtE(z(t),zt(t))+ε‖zt‖22+ε(ztt,z). $ | (3.8) |
In (3.8), we have
$ ddtE(z(t),zt(t))=12ddt‖zt‖22+12ddt‖z‖2V+∫L0ddtF(z)dx=12ddt(‖ut‖22+‖ϕt‖22)+12∫L0ddt(μu2x+δϕ2x+ξϕ2+2buxϕ)dx+∫L0ddtF(z)dx=∫L0(ututt+ϕtϕtt)dx+∫L0(μuxuxt+δϕxϕxt+ξϕϕt+buxtϕ+buxϕt)dx+∫L0∇F(z)⋅ztdx. $ | (3.9) |
Here, the notation $ \nabla F $ is defined by (2.13). Thus, according to (2.11), we know $ \nabla F(z) = \mathcal{F}(z) $, which means (3.9) turns to
$ ddtE(z(t),zt(t))=∫L0(ututt+ϕtϕtt)dx+∫L0(μuxuxt+δϕxϕxt+ξϕϕt+buxtϕ+buxϕt)dx+∫L0F(z)⋅ztdx=∫L0(ututt+ϕtϕtt)dx+∫L0(μuxuxt+δϕxϕxt+ξϕϕt+buxtϕ+buxϕt)dx+∫L0(f1(u,ϕ)ut+f2(u,ϕ)ϕt)dx=∫L0(ututt+ϕtϕtt)dx+∫L0(μuxuxt+δϕxϕxt+ξϕϕt+buxϕt)dx−∫L0butϕxdx+∫L0(f1(u,ϕ)ut+f2(u,ϕ)ϕt)dx=∫L0(ututt+μuxuxt−butϕx−f1(u,ϕ)ut)dx+∫L0(ϕtϕtt+δϕxϕxt+buxϕt+ξϕϕt−f2(u,ϕ)ϕt)dx. $ | (3.10) |
Testing the both sides of the first equation in (1.1) by $ u_{t} $ and integrating both sides over $ [0, L] $, we have
$ ∫L0(ututt+μuxuxt−butϕx−f1(u,ϕ)ut)dx=−∫L0g1(ut)utdx. $ | (3.11) |
And testing the both sides of the second equation in (1.1) by $ \phi_{t} $ and integrating both sides over $ [0, L] $, we have
$ ∫L0(ϕtϕtt+δϕxϕxt+buxϕt+ξϕϕt−f2(u,ϕ)ϕt)dx=−∫L0g2(ϕt)ϕtdx. $ | (3.12) |
By substituting (3.11) and (3.12) into (3.10), we have
$ ddtE(z(t),zt(t))=−∫L0g1(ut)utdx−∫L0g2(ϕt)ϕtdx. $ | (3.13) |
Next, we use Assumption 2.1 to deal with (3.13). In Assumption 2.1, for $ |s|\geq1 $, according to (2.6) with $ m = 1 $ and (2.7) with $ r = 1 $, we know that
$ α|s|2≤gj(s)s≤β|s|2, j=1,2. $ | (3.14) |
Then taking the absolute value of (3.14) gives
$ α|s|≤|gj(s)|≤β|s|, j=1,2. $ | (3.15) |
For $ |s| < 1 $, according to (2.8) with $ \hat{m} = 1 $ and (2.9) with $ \hat{r} = 1 $, we know that (3.15) also holds. Meanwhile, since $ g_{1}(0) = g_{2}(0) = 0 $ and $ g_{j}(s) $, $ j = 1, 2 $, are assumed to be the increasing functions, for $ j = 1, 2 $, we know $ g_{j}(s) > 0 $ for $ s > 0 $ and $ g_{j}(s) < 0 $ for $ s < 0 $, which gives $ g_{j}(s)s\geq0 $, $ j = 1, 2 $, for $ s\in \mathbb{R} $. Thus, we have
$ ∫L0g1(ut)utdx+∫L0g2(ϕt)ϕtdx=∫L0|g1(ut)ut|dx+∫L0|g2(ϕt)ϕt|dx≥α‖ut‖22+α‖ϕt‖22=α‖zt‖22, $ |
which makes (3.13) turn to
$ ddtE(z(t),zt(t))≤−α‖zt‖22. $ | (3.16) |
We deal with the term $ \varepsilon\left(z_{tt}, z\right) $ in (3.8). Testing the both sides of the first equation in problem (1.1) by $ u $ and integrating both sides over $ [0, L] $, we have
$ (utt,u)=−μ‖ux‖22−b(ux,ϕ)−(g1(ut),u)+(f1(u,ϕ),u). $ | (3.17) |
And testing the both sides of the second equation in problem (1.1) by $ \phi $ and integrating both sides over $ [0, L] $, we have
$ (ϕtt,ϕ)=−δ‖ϕx‖22−b(ux,ϕ)−ξ‖ϕ‖22−(g2(ϕt),ϕ)+(f2(u,ϕ),ϕ). $ | (3.18) |
By (3.17) plus (3.18), we have
$ (ztt,z)=−∫L0(μu2x+δϕ2x+ξϕ2+2buxϕ)dx−(g1(ut),u)−(g2(ϕt),ϕ)+(f1(u,ϕ),u)+(f2(u,ϕ),ϕ)=−‖ϕ‖2V−(G(zt),z)+(F(z),z)≤−‖ϕ‖2V+|(G(zt),z)|+(F(z),z). $ | (3.19) |
According to (3.16) and (3.19), we know that (3.8) turns to
$ H′(t)≤−α‖zt‖22+ε‖zt‖22−ε‖z‖2V+ε|(G(zt),z)|+ε(F(z),z). $ | (3.20) |
Next, we deal with the term $ \varepsilon\left|\left(\mathcal{G}(z_{t}), z\right)\right| $ in (3.20). By using (3.15) and Hölder inequality, we know
$ |(G(zt),z)|=|(g1(ut),u)+(g2(ϕt),ϕ)|≤|(g1(ut),u)|+|(g2(ϕt),ϕ)|≤∫L0|g1(ut)||u|dx+∫L0|g2(ϕt)||ϕ|dx≤β∫L0|ut||u|dx+β∫L0|ϕt||ϕ|dx≤β‖ut‖2‖u‖2+β‖ϕt‖2‖ϕ‖2≤2β‖zt‖2‖z‖2. $ | (3.21) |
Then, We deal with $ \varepsilon\left(\mathcal{F}(z), z\right) $ in (3.20). Here, we first need to give
$ F(z)⋅z=(p+1)F(z). $ | (3.22) |
For all $ \lambda > 0 $, taking the derivative of both sides of (2.12) with respect to $ \lambda $, we know
$ ddλF(λz)=∇F(λz)⋅z=ddλλp+1F(z)=(p+1)λpF(z), $ | (3.23) |
where $ \nabla F $ is defined by (2.13). By taking $ \lambda = 1 $ in (3.23) and using (2.11), we obtain (3.22). According to (3.22) and (2.14), we have
$ (F(z),z)=∫L0F(z)⋅zdx=(p+1)∫L0F(z)dx≤(p+1)M‖z‖p+1p+1. $ | (3.24) |
By using (2.5), (3.24) turns to
$ (F(z),z)≤(p+1)MRp+1‖z‖p+1V=(p+1)MRp+1‖z‖p−1V‖z‖2V. $ | (3.25) |
Then, we estimate the term $ \|z\|^{p-1}_{V} $ in (3.25). According to Theorem 2.12 (ⅱ) in [5], we know $ z(t)\in W $ for $ t > 0 $. By using $ I(z(t)) > 0 $, i.e., $ z(t)\in W $, we have
$ (p+1)∫L0F(z(t))dx<‖z(t)‖2V, $ |
which means
$ J(z(t))=12‖z(t)‖2V−∫L0F(z(t))dx>12‖z(t)‖2V−1p+1‖z(t)‖2V=p−12(p+1)‖z(t)‖2V. $ | (3.26) |
Meanwhile, according to (3.16), i.e.,
$ \frac{{\rm d}}{{\rm d}t}\mathcal{E}(z(t), z_{t}(t))\leq0, $ |
we have $ \mathcal{E}(z(t), z_{t}(t))\leq\mathcal{E}(z_{0}, z_{1}) $. Thus, we know
$ p−12(p+1)‖z(t)‖2V≤J(z(t))≤E(z(t),zt(t))≤E(z0,z1), $ | (3.27) |
i.e.,
$ ‖z(t)‖p−1V≤(2(p+1)p−1E(z0,z1))p−12, $ |
for $ t > 0 $, which implies that (3.25) turns to
$ (F(z),z)≤(p+1)MRp+1(2(p+1)p−1E(z0,z1))p−12‖z‖2V. $ | (3.28) |
Due to $ \mathcal{E}(z_{0}, z_{1}) < \sigma \hat{d} $ being assumed, we know that (3.28) turns to
$ (F(z),z)≤σp−12‖z‖2V, $ | (3.29) |
where $ \hat{d} $ is defined by (2.17). Substituting (3.21) and (3.29) into (3.20), we have
$ H′(t)≤−α‖zt‖22+ε‖zt‖22+εσp−12‖z‖2V−ε‖z‖2V+2εβ‖zt‖2‖z‖2. $ | (3.30) |
By using Young inequality for $ \delta_{0} > 0 $ and inequality (2.5) for $ q = 2 $, we know that (3.30) turns to
$ H′(t)≤−α‖zt‖22+ε‖zt‖22+εσp−12‖z‖2V−ε‖z‖2V+εβδ0‖zt‖22+εβδ0R2‖z‖2V=−(α−ε−εβδ0)‖zt‖22−ε(1−σp−12−βδ0R2)‖z‖2V. $ | (3.31) |
In (3.31), we choose $ \delta_{0} > 0 $ to make $ 1-\sigma^{\frac{p-1}{2}}-\beta\delta_{0} R_{2} > 0 $ hold, where $ 1-\sigma^{\frac{p-1}{2}} > 0 $ due to $ \sigma\in(0, 1) $. Then, we select $ \varepsilon > 0 $ such that $ \alpha-\varepsilon-\frac{\varepsilon\beta}{\delta_{0}} > 0 $ and
$ \alpha_{1} = 1-\frac{\varepsilon\max\{R_{2}, 1\}(p+1)}{p-1} > 0. $ |
To deal with (3.31), we first have
$ (α−ε−εβδ0)‖zt‖22+ε(1−σp−12−βδ0R2)‖z‖2V=2(α−ε−εβδ0)12‖zt‖22+2ε(1−σp−12−βδ0R2)12‖z‖2V≥min{2(α−ε−εβδ0),2ε(1−σp−12−βδ0R2)}(12‖zt‖22+12‖z‖2V). $ | (3.32) |
According to Theorem 2.12 (ⅳ) in [5], (3.32) turns to
$ (α−ε−εβδ0)‖zt‖22+ε(1−σp−12−βδ0R2)‖z‖2V≥min{2(α−ε−εβδ0),2ε(1−σp−12−βδ0R2)}E(z(t),zt(t)). $ | (3.33) |
Due to (3.7), i.e., $ H(t)\leq \alpha_{2}\mathcal{E}(z(t), z_{t}(t)) $, (3.33) turns to
$ (α−ε−εβδ0)‖zt‖22+ε(1−σp−12−βδ0R2)‖z‖2V≥min{2(α−ε−εβδ0),2ε(1−σp−12−βδ0R2)}α2H(t). $ | (3.34) |
Thus, we know that (3.31) implies
$ H′(t)≤−λ0H(t), $ | (3.35) |
where
$ λ0:=min{2(α−ε−εβδ0),2ε(1−σp−12−βδ0R2)}α2. $ | (3.36) |
By using Gronwall's inequality, (3.35) gives
$ H(t)≤e−λ0tH(0). $ | (3.37) |
According to (3.7), (3.37), and the assumptions $ \mathcal{E}(z_{0}, z_{1}) < \sigma\hat{d} $ and $ 0 < \sigma < 1 $, we have
$ E(z(t),zt(t))≤α2E(z0,z1)α1e−λ0t<α2σˆdα1e−λ0t<K0e−λ0t, $ | (3.38) |
where
$ K0:=α2ˆdα1. $ | (3.39) |
Theorem 3.2. (Continuous dependence on initial data for linear weak damping case) Let Assumption 2.1 and Assumption 2.2 hold with $ r = m = \hat{r} = \hat{m} = 1 $. For any $ 0 < \sigma < 1 $, suppose $ \mathcal{E}(z_{0}, z_{1}) < \sigma \hat{d} $, $ z_{0}\in W $, $ \mathcal{E}(\tilde{z}_{0}, \tilde{z}_{1}) < \sigma \hat{d} $ and $ \tilde{z}_{0}\in W $. Let $ z = (u, \phi) $ and $ \tilde{z} = (\tilde{u}, \tilde{\phi}) $ be the global solutions to problem (1.1) with the initial data $ z_{0} $, $ z_{1} $, and $ \tilde{z}_{0} $, $ \tilde{z}_{1} $, respectively. Then one has
$ ˆE(t)≤C1(ˆE(0)+C2(ˆE(0))a2)ρe−C3t, $ | (3.40) |
where
$ C1:=(1+C4eC4λ0(p−1)λ0(p−1))ρ(4(p+1)K0p−1)1−ρ,C2:=2a2Nλ1,C3:=λ0(1−ρ),C4:=43CR124R124(p−1)(2(p+1)K0p−1)p−1,0<a<min{2λ0ˉMC+λ0,1},0<ρ<1,$ | (3.41) |
$ \lambda_{0} $ and $ K_{0} $ are defined by (3.36) and (3.39), respectively, $ R_{4(p-1)} $ is the best embedding constant defined in (2.4) taking $ q = 4(p-1) $,
$ λ1:=λ0(2−a)−aˉMC2, $ |
$ N:=21−aC(2K0)2−a2+23−aCR122(2(p+1)K0p−1)12(2K0)1−a2, $ |
and
$ ˉM:=max{23252R124(2R4(p−1)(2(p+1)σˆdp−1)2(p−1)+L)12,1}. $ | (3.42) |
Proof. We denote $ w: = z-\tilde{z} $. According to the proof of Theorem 2.5 in [5], we notice that
$ ˆE(t)≤ˆE(0)+∫t0∫L0(F(z(τ))−F(˜z(τ)))wt(τ)dxdτ $ | (3.43) |
holds by Assumption 2.1 and Assumption 2.2. In the following, we shall finish this proof by considering the following two steps. In Step $ \rm{I} $, we shall derive a similar estimate of the growth of $ \widehat{E}(t) $ to (135) in [5]. As we build this estimate for the global solution instead of the local solution treated in [5], we have to rebuild all the necessary estimates based on the conditions for global existence theory.
Step Ⅰ: Global estimate of $ \widehat{E}(t) $ for global solution.
We estimate the term $ \int_{0}^{t}\int_{0}^{L}\left(\mathcal{F}(z(\tau))-\mathcal{F}(\tilde{z}(\tau))\right) w_{t}(\tau){\rm d}x{\rm d}\tau $ in (3.43) as follows
$ ∫L0(F(z(t))−F(˜z(t)))⋅wtdx=∫L0(f1(z)−f1(˜z))(ut−˜ut)dx+∫L0(f2(z)−f2(˜z))(ϕt−˜ϕt)dx≤∫L0|f1(z)−f1(˜z)||ut−˜ut|dx+∫L0|f2(z)−f2(˜z)||ϕt−˜ϕt|dx. $ | (3.44) |
Here, according to the proof of Lemma 3.2 in [5], we notice that (2.10) in Assumption 2.2 gives
$ |fj(z)−fj(˜z)|≤C|z−˜z|(|u|p−1+|˜u|p−1+|ϕ|p−1+|˜ϕ|p−1+1), j=1,2, $ | (3.45) |
which means (3.44) turns to
$ ∫L0(F(z(t))−F(˜z(t)))⋅wtdx≤∫L0C|z−˜z|(|u|p−1+|˜u|p−1+|ϕ|p−1+|˜ϕ|p−1+1)|ut−˜ut|dx⏟:=A1+∫L0C|z−˜z|(|u|p−1+|˜u|p−1+|ϕ|p−1+|˜ϕ|p−1+1)|ϕt−˜ϕt|dx⏟:=A2. $ | (3.46) |
Next, we deal with $ A_{1} $ and $ A_{2} $ separately. For $ A_{1} $, by Hölder inequality and Young inequality, we have
$ A1≤C(∫L0|z−˜z|2(|u|p−1+|˜u|p−1+|ϕ|p−1+|˜ϕ|p−1+1)2dx)12(∫L0|ut−˜ut|2dx)12≤C2∫L0|z−˜z|2(|u|p−1+|˜u|p−1+|ϕ|p−1+|˜ϕ|p−1+1)2dx+C2∫L0|ut−˜ut|2dx. $ | (3.47) |
By the similar process, we can deal with $ A_{2} $ as
$ A2≤C2∫L0|z−˜z|2(|u|p−1+|˜u|p−1+|ϕ|p−1+|˜ϕ|p−1+1)2dx+C2∫L0|ϕt−˜ϕt|2dx. $ | (3.48) |
According to (3.47), (3.48) and Hölder inequality, we know that (3.46) turns to
$ ∫L0(F(z(t))−F(˜z(t)))⋅wtdx≤C∫L0|z−˜z|2(|u|p−1+|˜u|p−1+|ϕ|p−1+|˜ϕ|p−1+1)2dx+C2‖wt‖22≤C(∫L0|z−˜z|4dx)12(∫L0(|u|p−1+|˜u|p−1+|ϕ|p−1+|˜ϕ|p−1+1)4dx)12+C2‖wt‖22. $ | (3.49) |
In (3.49), by noticing $ z = (u, \phi) $, $ \tilde{z} = (\tilde{u}, \tilde{\phi}) $, we see that
$ (∫L0|z−˜z|4dx)12=(∫L0((|u−˜u|2+|ϕ−˜ϕ|2)12)4dx)12=(∫L0(|u−˜u|4+|ϕ−˜ϕ|4+2|u−˜u|2|ϕ−˜ϕ|2)dx)12=(∫L0(|u−˜u|4+|ϕ−˜ϕ|4)dx+∫L02|u−˜u|2|ϕ−˜ϕ|2dx)12. $ | (3.50) |
By using Hölder inequality and Young inequality, we know (3.50) turns to
$ (∫L0|z−˜z|4dx)12≤(∫L0(|u−˜u|4+|ϕ−˜ϕ|4)dx+2‖u−˜u‖24‖ϕ−˜ϕ‖24)12≤(2‖u−˜u‖44+2‖ϕ−˜ϕ‖44)12=212‖z−˜z‖24. $ | (3.51) |
Next, we deal with $ \int_{0}^{L}(|u|^{p-1}+|\tilde{u}|^{p-1}+|\phi|^{p-1}+|\tilde{\phi}|^{p-1}+1)^{4}{\rm d}x $ in (3.49). For $ k_{1} $, $ k_{2} $, $ k_{3} $, $ k_{4} $, $ k_{5}\geq0 $, we have
$ (k1+k2+k3+k4+k5)4≤(5max{k1,k2,k3,k4,k5})4=54max{k41,k42,k43,k44,k45}≤54(k41+k42+k43+k44+k45). $ |
From above observation, we have
$ ∫L0(|u|p−1+|˜u|p−1+|ϕ|p−1+|˜ϕ|p−1+1)4dx≤54∫L0(|u|4(p−1)+|˜u|4(p−1)+|ϕ|4(p−1)+|˜ϕ|4(p−1)+1)dx. $ | (3.52) |
According to (3.51) and (3.52), (3.49) turns to
$ ∫L0(F(z)−F(˜z))⋅wtdx≤C212‖z−˜z‖24(54∫L0(|u|4(p−1)+|˜u|4(p−1)+|ϕ|4(p−1)+|˜ϕ|4(p−1)+1)dx)12+C2‖wt‖22=C21252‖z−˜z‖24(∫L0(|u|4(p−1)+|ϕ|4(p−1))dx+∫L0(|˜u|4(p−1)+|˜φ|4(p−1))dx+L)12+C2‖wt‖22=C21252‖z−˜z‖24(‖z‖4(p−1)4(p−1)+‖˜z‖4(p−1)4(p−1)+L)12+C2‖wt‖22. $ | (3.53) |
By using (2.5), we know that (3.53) turns to
$ ∫L0(F(z)−F(˜z))⋅wtdx≤C21252R124‖z−˜z‖2V(R4(p−1)‖z‖4(p−1)V+R4(p−1)‖˜z‖4(p−1)V+L)12+C2‖wt‖22. $ | (3.54) |
According to (3.27) and the assumptions $ \mathcal{E}(z_{0}, z_{1}) < \sigma \hat{d} $ and $ \mathcal{E}(\tilde{z}_{0}, \tilde{z}_{1}) < \sigma \hat{d} $, we have
$ ‖z‖2V<2(p+1)σˆdp−1 $ | (3.55) |
and
$ ‖˜z‖2V<2(p+1)σˆdp−1. $ | (3.56) |
Substituting (3.55) and (3.56) into (3.54), we have
$ ∫L0(F(z)−F(˜z))⋅wtdx≤C21252R124(2R4(p−1)(2(p+1)σˆdp−1)2(p−1)+L)12‖w‖2V+C2‖wt‖22≤ˉMC(12‖wt‖22+12‖w‖2V)=ˉMCˆE(t). $ | (3.57) |
Due to (3.57), we know
$ ∫t0∫L0(F(z(τ))−F(˜z(τ)))⋅wtdxdτ≤ˉMC∫t0ˆE(τ)dτ. $ | (3.58) |
Substituting (3.58) into (3.43), we have
$ ˆE(t)≤ˆE(0)+ˉMC∫t0ˆE(τ)dτ. $ | (3.59) |
Then, by a variation of Gronwall's inequality (see Appendix), we have
$ ˆE(t)≤ˆE(0)eˉMCt. $ | (3.60) |
As the growth estimate (3.60) we derived in Step $ \rm{I} $ does not reflect the decay of the solution, we shall deal with the decay terms and the non-decay terms separately in Step $ \rm{II} $ to upgrade the results obtained in Step $ \rm{I} $, i.e., (3.60), by giving an improved estimate to reflect the dissipative property of the system (1.1).
Step Ⅱ: Decay estimate of $ \widehat{E}(t) $.
According to (3.46), we have
$ ∫L0(F(z(t))−F(˜z(t)))⋅wtdx≤∫L0C|z−˜z|(|u|p−1+|˜u|p−1+|ϕ|p−1+|˜ϕ|p−1)|ut−˜ut|dx⏟:=A3+∫L0C|z−˜z|(|u|p−1+|˜u|p−1+|ϕ|p−1+|˜ϕ|p−1)|ϕt−˜ϕt|dx⏟:=A4+∫L0C|z−˜z||ut−˜ut|dx+∫L0C|z−˜z||ϕt−˜ϕt|dx. $ | (3.61) |
By the similar process dealing with $ A_{1} $ and $ A_{2} $, we can treat $ A_{3} $ and $ A_{4} $ as
$ A3≤C2∫L0|z−˜z|2(|u|p−1+|˜u|p−1+|ϕ|p−1+|˜ϕ|p−1)2dx+C2∫L0|ut−˜ut|2dx $ | (3.62) |
and
$ A4≤C2∫L0|z−˜z|2(|u|p−1+|˜u|p−1+|ϕ|p−1+|˜ϕ|p−1)2dx+C2∫L0|ϕt−˜ϕt|2dx. $ | (3.63) |
By the similar process of obtaining (3.54), i.e.,
$ A1+A2≤C21252R124‖z−˜z‖2V(R4(p−1)‖z‖4(p−1)V+R4(p−1)‖˜z‖4(p−1)V+L)12+C2‖wt‖22, $ |
we can use (3.62) and (3.63) to give
$ A3+A4≤C21242R124R124(p−1)‖z−˜z‖2V(‖z‖4(p−1)V+‖˜z‖4(p−1)V)12+C2‖wt‖22. $ | (3.64) |
Due to (3.26), (2.16) and Lemma $ 3.1 $, we know
$ 12‖zt‖22+p−12(p+1)‖z‖2V≤E(z(t),zt(t))<K0e−λ0t $ | (3.65) |
and
$ 12‖˜zt‖22+p−12(p+1)‖˜z‖2V≤E(˜z(t),˜zt(t))<K0e−λ0t. $ | (3.66) |
According to (3.65) and (3.66), we have
$ ‖z‖4(p−1)V<(2(p+1)p−1K0)2(p−1)e−2λ0(p−1)t $ |
and
$ ‖˜z‖4(p−1)V<(2(p+1)p−1K0)2(p−1)e−2λ0(p−1)t, $ |
which mean
$ (‖z‖4(p−1)V+‖˜z‖4(p−1)V)12<212(2(p+1)p−1K0)p−1e−λ0(p−1)t. $ | (3.67) |
By substituting (3.67) into (3.64), we obtain
$ A3+A4≤C4e−λ0(p−1)t12‖z−˜z‖2V+C2‖zt−˜zt‖22≤C4e−λ0(p−1)t(12‖z−˜z‖2V+12‖zt−˜zt‖22)+C2‖zt−˜zt‖22. $ | (3.68) |
Substituting (3.68) into (3.61) and using Hölder inequality and (2.5), we have
$ ∫L0(F(z(t))−F(˜z(t)))⋅wtdx≤C4e−λ0(p−1)tˆE(t)+C2‖zt−˜zt‖22+∫L0C|z−˜z||ut−˜ut|dx+∫L0C|z−˜z||ϕt−˜ϕt|dx≤C4e−λ0(p−1)tˆE(t)+C2‖zt−˜zt‖22+C‖z−˜z‖2‖ut−˜ut‖2+C‖z−˜z‖2‖ϕt−˜ϕt‖2≤C4e−λ0(p−1)tˆE(t)+C2‖zt−˜zt‖22+2C‖z−˜z‖2‖zt−˜zt‖2≤C4e−λ0(p−1)tˆE(t)+C2‖zt−˜zt‖22+2CR122‖z−˜z‖V‖zt−˜zt‖2. $ | (3.69) |
According to (3.60), we know
$ ‖zt−˜zt‖2≤(2ˆE(0)eˉMCt)12, $ |
i.e.,
$ ‖zt−˜zt‖a2≤(2ˆE(0))a2eaˉMCt2 $ | (3.70) |
for $ 0 < a < 1 $. Meanwhile, combining (3.65) and (3.66), we also have
$ ‖zt−˜zt‖2≤‖zt‖2+‖˜zt‖2≤2(2K0)12e−λ02t, $ | (3.71) |
i.e.,
$ ‖zt−˜zt‖1−a2≤21−a(2K0)1−a2e−λ0(1−a)2t, $ | (3.72) |
and
$ ‖z−˜z‖V≤‖z‖V+‖˜z‖V≤2(2(p+1)K0p−1)12e−λ02t. $ | (3.73) |
Combining (3.70), (3.71) and (3.72), we have
$ ‖zt−˜zt‖22=‖zt−˜zt‖2‖zt−˜zt‖a2‖zt−˜zt‖1−a2≤22−a(2K0)2−a2(2ˆE(0))a2e−λ0(2−a)−aˉMC2t. $ | (3.74) |
We choose $ 0 < a < \min\left\{\frac{2\lambda_{0}}{\bar{M}C+\lambda_{0}}, 1\right\} $ such that
$ λ0(2−a)−aˉMC>0 $ | (3.75) |
in (3.74). Meanwhile, according to (3.70), (3.72) and (3.73), we notice that
$ ‖z−˜z‖V‖zt−˜zt‖2=‖z−˜z‖V‖zt−˜zt‖a2‖zt−˜zt‖1−a2≤22−a(2(p+1)K0p−1)12(2K0)1−a2(2ˆE(0))a2e−λ0(2−a)−aˉMC2t. $ | (3.76) |
Due to (3.74) and (3.76), we see that (3.69) turns to
$ ∫L0(F(z(t))−F(˜z(t)))⋅wtdx≤C4e−λ0(p−1)tˆE(t)+21−aC(2K0)2−a2(2ˆE(0))a2e−λ0(2−a)−aˉMC2t+23−aCR122(2(p+1)K0p−1)12(2K0)1−a2(2ˆE(0))a2e−λ0(2−a)−aˉMC2t. $ | (3.77) |
By substituting (3.77) into (3.43), we obtain
$ ˆE(t)≤ˆE(0)+C4∫t0e−λ0(p−1)τˆE(τ)dτ+(2ˆE(0))a2D, $ | (3.78) |
where
$ D:=N∫t0e−λ1τdτ=Nλ1−Nλ1e−λ1t. $ | (3.79) |
Here, according to (3.79), we notice that $ D\leq\frac{N}{\lambda_{1}} $, which means that (3.78) turns to
$ ˆE(t)≤ˆE(0)+(2ˆE(0))a2Nλ1+C4∫t0e−λ0(p−1)τˆE(τ)dτ, $ | (3.80) |
i.e.,
$ e−λ0(p−1)tˆE(t)≤e−λ0(p−1)t(ˆE(0)+(2ˆE(0))a2Nλ1)+C4e−λ0(p−1)t∫t0e−λ0(p−1)τˆE(τ)dτ. $ | (3.81) |
We define
$ F(t):=∫t0e−λ0(p−1)τˆE(τ)dτ. $ | (3.82) |
Thus, we can rewrite (3.81) as
$ F′(t)≤e−λ0(p−1)t(ˆE(0)+(2ˆE(0))a2Nλ1)+C4e−λ0(p−1)tF(t). $ | (3.83) |
By applying Gronwall's inequality, (3.83) gives
$ F(t)≤(ˆE(0)+(2ˆE(0))a2Nλ1)eC4∫t0e−λ0(p−1)τdτ∫t0e−λ0(p−1)τdτ=(ˆE(0)+(2ˆE(0))a2Nλ1)eC4λ0(p−1)(1−e−λ0(p−1)t)1−e−λ0(p−1)tλ0(p−1)≤(ˆE(0)+(2ˆE(0))a2Nλ1)eC4λ0(p−1)λ0(p−1), $ |
which means (3.80) turns to
$ ˆE(t)≤(ˆE(0)+(2ˆE(0))a2Nλ1)(1+C4eC4λ0(p−1)λ0(p−1)). $ | (3.84) |
For $ 0 < \rho < 1 $, according to (3.84), we have
$ ˆE(t)=ˆE(t)ρˆE(t)1−ρ≤(ˆE(0)+(2ˆE(0))a2Nλ1)ρ(1+C4eC4λ0(p−1)λ0(p−1))ρˆE(t)1−ρ. $ | (3.85) |
Here, by using Young inequality, we know
$ ˆE(t)1−ρ=(12‖zt−˜zt‖22+12‖z−˜z‖2V)1−ρ≤(12(‖zt‖2+‖˜zt‖2)2+12(‖z‖V+‖˜z‖V)2)1−ρ=(12‖zt‖22+‖zt‖2‖˜zt‖2+12‖˜zt‖22+12‖z‖2V+‖z‖V‖˜z‖V +12‖˜z‖2V)1−ρ≤(‖zt‖22+‖˜zt‖22+‖z‖2V+‖˜z‖2V)1−ρ $ | (3.86) |
According to (3.65) and (3.66), we know
$ p−12(p+1)(‖zt‖22+‖z‖2V)<K0e−λ0t $ | (3.87) |
and
$ p−12(p+1)(‖˜zt‖22+‖˜z‖2V)<K0e−λ0t. $ | (3.88) |
By substituting (3.87) and (3.88) into (3.86), we have
$ ˆE(t)1−ρ≤(4(p+1)K0p−1)1−ρe−λ0(1−ρ)t, $ |
which means that (3.85) turns to (3.40).
In this section, we consider the continuous dependence of the global solution on the initial data for the nonlinear weak damping case of the model equations in problem (1.1) by supposing that $ m\geq1 $, $ r\geq1 $, and $ \hat{m} = \hat{r} = 1 $ in Assumption 2.1, which means that the weak damping terms $ g_j(s) $, $ j = 1, 2 $, take the nonlinear form for $ |s|\geq1 $ and linear form for $ |s| < 1 $. These conditions are applied to improve the estimate (1.2) and reflect the decay property of (1.1), which was clearly clarified in Corollary 2.14 in [5], that is, the condition $ \hat{m} = \hat{r} = 1 $ is necessary to obtain the exponential decay of the energy, which helps to get the exponential decay, and the absence of such linear condition can only lead to the polynomial decay of the energy. Hence although we discuss the nonlinear weak damping case here, we still need to assume that the terms $ g_j(s) $, $ j = 1, 2 $, take the linear form for $ |s| < 1 $.
Theorem 4.1. (Continuous dependence on initial data for nonlinear weak damping case) Let Assumption 2.1 and Assumption 2.2 hold with $ \hat{r} = \hat{m} = 1 $, $ \mathcal{E}(z_{0}, z_{1}) < \mathcal{M}(s_0-\nu) $, $ \mathcal{E}(\tilde{z}_{0}, \tilde{z}_{1}) < \mathcal{M}(s_0-\nu) $, $ \|z_{0}\|_{V}\leq s_{0}-\nu $, and $ \|\tilde{z}_{0}\|_{V}\leq s_{0}-\nu $ for some $ \nu > 0 $. Let $ z = (u, \phi) $ and $ \tilde{z} = (\tilde{u}, \tilde{\phi}) $ are the global solutions to the problem (1.1) with the initial data $ z_{0} $, $ z_{1} $, and $ \tilde{z}_{0} $, $ \tilde{z}_{1} $, respectively, where $ \mathcal{M} $ and $ s_{0} $ are defined in (2.18) and (2.19), respectively. Then one has
$ ˆE(t)≤C5(ˆE(0)+C6(ˆE(0))b02)κe−C7t, $ | (4.1) |
where
$ 0<κ<1,C5:=(1+C8TeC8Tθ0(p−1)θ0(p−1))κ(4(p+1)eθ+˜θˆdp−1)1−κ,C6:=2b02N1λ2,C7:=θ0(1−κ)T,C8:=43R124R124(p−1)C(2(p+1)ˆdp−1eθ+˜θ)p−1,θ0:=θ+˜θ−|θ−˜θ|2=min{θ,˜θ}, $ | (4.2) |
and $ \theta > 0 $, $ \tilde{\theta} > 0 $, and $ T > 0 $ satisfy
$ E(z(t),zt(t))≤eθE(z0,z1)e−θTt $ | (4.3) |
and
$ E(˜z(t),˜zt(t))≤e˜θE(˜z0,˜z1)e−˜θTt, $ | (4.4) |
$ b0:=θ0θ0+ˉMCT, $ | (4.5) |
$ \bar{M} $ is defined in (3.42),
$ N1:=(8eθ+˜θˆd)2−b02C2+2CR122(8eθ+˜θˆd)1−b02(8(p+1)p−1eθ+˜θˆd)12, $ |
and
$ λ2:=θ0(2−b0)2T−b0ˉMC2=θ0(2−b0)−b0ˉMCT2T. $ |
Proof. Due to Corollary 2.14 in [5], for any $ T > 0 $, we know that there exist $ \theta $ and $ \tilde{\theta} $ to make (4.3) and (4.4) hold, where $ \theta $ is dependent on $ \mathcal{E}(z_{0}, z_{1}) $ and $ T $, and $ \tilde{\theta} $ is dependent on $ \mathcal{E}(\tilde{z}_{0}, \tilde{z}_{1}) $ and $ T $. According to Proposition 2.11 in [5], the assumptions $ \mathcal{E}(z_{0}, z_{1}) < \mathcal{M}(s_0-\nu) $, $ \|z_{0}\|_{V}\leq s_{0}-\nu $, and $ \mathcal{E}(\tilde{z}_{0}, \tilde{z}_{1}) < \mathcal{M}(s_0-\nu) $, $ \|\tilde{z}_{0}\|_{V}\leq s_{0}-\nu $ give $ z_{0}\in W $ and $ \tilde{z}_{0}\in W $, respectively. Here $ \mathcal{M}(s_0-\nu) < \hat{d} $ can be observed according to (2.17). Thus, we know (3.26) also holds. According to these facts and (2.16), we have
$ 12‖zt‖22+p−12(p+1)‖z‖2V<E(z(t),zt(t))≤eθE(z0,z1)e−θTt<eθˆde−θTt, $ | (4.6) |
and
$ 12‖˜zt‖22+p−12(p+1)‖˜z‖2V<E(˜z(t),˜zt(t))≤e˜θE(˜z0,˜z1)e−˜θTt<e˜θˆde−˜θTt. $ | (4.7) |
Due to (4.2), we know that (4.6) and (4.7) turn to
$ 12‖zt‖22+p−12(p+1)‖z‖2V<eθˆde−θTt<eθ+˜θˆde−θ0Tt $ | (4.8) |
and
$ 12‖˜zt‖22+p−12(p+1)‖˜z‖2V<e˜θˆde−˜θTt<eθ+˜θˆde−θ0Tt, $ | (4.9) |
respectively. According to (4.8) and (4.9), we have
$ ‖z‖4(p−1)V<(2(p+1)ˆdp−1eθ+˜θ)2(p−1)e−2θ0(p−1)Tt $ |
and
$ ‖˜z‖4(p−1)V<(2(p+1)ˆdp−1eθ+˜θ)2(p−1)e−2θ0(p−1)Tt, $ |
which mean
$ (‖z‖4(p−1)V+‖˜z‖4(p−1)V)12<(2(p+1)ˆdp−1eθ+˜θ)p−1212e−θ0(p−1)Tt. $ | (4.10) |
Next, we need to use the estimate (3.64) to continue this proof. More precisely, by substituting (4.10) into (3.64), we obtain
$ A3+A4≤C8e−θ0(p−1)Tt12‖z−˜z‖2V+C2‖wt‖22≤C8e−θ0(p−1)Tt(12‖z−˜z‖2V+12‖zt−˜zt‖22)+C2‖wt‖22. $ | (4.11) |
By substituting (4.11) into (3.61) and the similar process of obtaining (3.69), we have
$ ∫L0(F(z(t))−F(˜z(t)))⋅wtdx≤C8e−θ0(p−1)TtˆE(t)+C2‖wt‖22+2C‖z−˜z‖2‖zt−˜zt‖2≤C8e−θ0(p−1)TtˆE(t)+C2‖wt‖22+2CR122‖z−˜z‖V‖zt−˜zt‖2. $ | (4.12) |
According to (3.60), we know
$ ‖zt−˜zt‖2≤(2ˆE(0)eˉMCt)12, $ |
i.e.,
$ ‖zt−˜zt‖b02≤(2ˆE(0))b02eb0ˉMCt2, $ | (4.13) |
where $ b_0 $ is defined by (4.5). Meanwhile, combining (4.8) and (4.9), we know
$ ‖zt−˜zt‖2≤‖zt‖2+‖˜zt‖2≤(8eθ+˜θˆd)12e−θ02Tt, $ | (4.14) |
i.e.,
$ ‖zt−˜zt‖1−b02≤(8eθ+˜θˆd)1−b02e−θ0(1−b0)2Tt. $ | (4.15) |
and
$ ‖z−˜z‖V≤‖z‖V+‖˜z‖V≤(8(p+1)p−1eθ+˜θˆd)12e−θ02Tt, $ | (4.16) |
where $ b_0 > 0 $ and $ 1-b_0 > 0 $ are ensured by (4.5). According to (4.13), (4.14) and (4.15), we have
$ ‖zt−˜zt‖22=‖zt−˜zt‖2‖zt−˜zt‖b02‖zt−˜zt‖1−b02≤(2ˆE(0))b02(8eθ+˜θˆd)2−b02e−(θ0(2−b0)2T−b0ˉMC2)t. $ | (4.17) |
According to (4.5), we have
$ 0<b0<2θ0θ0+ˉMCT, $ | (4.18) |
i.e.,
$ θ0(2−b0)2T−b0ˉMC2>0 $ |
in (4.17). Meanwhile, according to (4.13), (4.15) and (4.16), we notice that
$ ‖z−˜z‖V‖zt−˜zt‖2=‖z−˜z‖V‖zt−˜zt‖b02‖zt−˜zt‖1−b02≤(2ˆE(0))b02(8eθ+˜θˆd)1−b02(8(p+1)p−1eθ+˜θˆd)12 e−(θ0(2−b0)2T−b0ˉMC2)t. $ | (4.19) |
Due to (4.17) and (4.19), we know that (4.12) turns to
$ ∫L0(F(z(t))−F(˜z(t)))⋅wtdx≤C8e−θ0(p−1)TtˆE(t)+(2ˆE(0))b02(8eθ+˜θˆd)2−b02Ce−(θ0(2−b0)2T−b0ˉMC2)t2+2CR122(2ˆE(0))b02(8eθ+˜θˆd)1−b02(8(p+1)p−1eθ+˜θˆd)12e−(θ0(2−b0)2T−b0ˉMC2)t. $ | (4.20) |
By substituting (4.20) into (3.43), we obtain
$ ˆE(t)≤ˆE(0)+C8∫t0e−θ0(p−1)TτˆE(τ)dτ+(2ˆE(0))b02D1, $ | (4.21) |
where
$ D1:=N1∫t0e−λ2τdτ=N1λ2−N1λ2e−λ2t. $ | (4.22) |
Here, according to (4.22), we notice that $ D_{1}\leq\frac{N_{1}}{\lambda_{2}} $, which means that (4.21) turns to
$ ˆE(t)≤ˆE(0)+(2ˆE(0))b02N1λ2+C8∫t0e−θ0(p−1)TτˆE(τ)dτ, $ | (4.23) |
i.e.,
$ e−θ0(p−1)TtˆE(t)≤e−θ0(p−1)Tt(ˆE(0)+(2ˆE(0))b02N1λ2)+C8e−θ0(p−1)Tt∫t0e−θ0(p−1)TτˆE(τ)dτ. $ | (4.24) |
By similar process of obtaining (3.84), we have
$ ˆE(t)≤(ˆE(0)+(2ˆE(0))b02N1λ2)(1+C8TeC8Tθ0(p−1)θ0(p−1)). $ | (4.25) |
For $ 0 < \kappa < 1 $, according to (4.25), we know
$ ˆE(t)=ˆE(t)κˆE(t)1−κ≤(ˆE(0)+(2ˆE(0))b02N1λ2)κ(1+C8TeC8Tθ0(p−1)θ0(p−1))κˆE(t)1−κ. $ | (4.26) |
By the similar process of obtaining (3.86), we have
$ ˆE(t)1−κ≤(‖zt‖22+‖˜zt‖22+‖z‖2V+‖˜z‖2V)1−κ. $ | (4.27) |
According to (4.8) and (4.9), we know
$ p−12(p+1)(‖zt‖22+‖z‖2V)<eθ+˜θˆde−θ0Tt $ | (4.28) |
and
$ p−12(p+1)(‖˜zt‖22+‖˜z‖2V)<eθ+˜θˆde−θ0Tt. $ | (4.29) |
By substituting (4.28) and (4.29) into (4.27), we have
$ ˆE(t)1−κ≤(4(p+1)eθ+˜θˆdp−1)1−κe−θ0(1−κ)Tt, $ |
which means that (4.26) turns to (4.1).
The finite time blowup at the positive initial energy level was established for the linear weak damping case and nonlinear weak damping case in [22], and for the linear weak damping case, the lower and upper bounds of the blowup time were also estimated there. Hence in this section, we shall estimate the lower bound of the blowup time at the positive initial energy level for the nonlinear weak damping case.
Theorem 5.1. (Lower bound of blowup time for positive initial energy and nonlinear weak damping case) Let Assumption 2.1 and Assumption 2.2 hold, and $ \mathcal{E}(z_{0}, z_{1})\geq 0 $. Suppose $ z(x, t) $ is the solution to problem (1.1). If $ z(x, t) $ blows up at a finite time $ T_{0} $, then we have the estimate of blowup time
$ T_{0} \geq \int_{G(0)}^\infty\frac{1}{C_{9}y^{p}+C_{10}y+C_{11}}{\rm d}y, $ |
where
$ C9:=(p+1)R2p22p−2Mp,C10:=(p+1)M,C11:=(p+1)E(z0,z1)+(p+1)R2p22p−2(E(z0,z1))p, $ |
and
$ G(0): = \|z_{0}\|^{p+1}_{p+1}. $ |
Proof. Let $ z = (u, \phi) $ be a weak solution to problem (1.1). We suppose that such solution blows up at a finite time $ T_{0} $. Our goal is to obtain an estimate of the lower bound of $ T_{0} $.
For $ t\in [0, T_{0}) $, we define
$ G(t):=‖z(t)‖p+1p+1=‖u(t)‖p+1p+1+‖ϕ(t)‖p+1p+1, $ | (5.1) |
then, by Hölder inequality and Young inequality, we have
$ G′(t)=(p+1)∫L0|u|p−1uutdx+(p+1)∫L0|ϕ|p−1ϕϕtdx≤(p+1)∫L0|u|p|ut|dx+(p+1)∫L0|ϕ|p|ϕt|dx≤(p+1)‖u‖p2p‖ut‖2+(p+1)‖ϕ‖p2p‖ϕt‖2≤p+12(‖u‖2p2p+‖ut‖22+‖ϕ‖2p2p+‖ϕt‖22)=p+12(‖z‖2p2p+‖zt‖22). $ | (5.2) |
Next task is to estimate the terms in the last line of (5.2). By (2.14) and (2.16), we obtain
$ E(z(t),zt(t))=12‖zt‖22+12‖z‖2V−∫L0F(z(t))dx≥12‖zt‖22+12‖z‖2V−M∫L0(|u|p+1+|ϕ|p+1)dx=12‖zt‖22+12‖z‖2V−M‖z‖p+1p+1. $ | (5.3) |
According to (3.16), we know
$ E(z(t),zt(t))≤E(z0,z1), t∈[0,T0), $ | (5.4) |
where $ \mathcal{E}(z_{0}, z_{1})\geq 0 $. We notice that (5.3) and (5.4) give
$ ‖zt‖22+‖z‖2V≤2E(z0,z1)+2MG(t), $ | (5.5) |
which means
$ ‖z‖2V≤2E(z0,z1)+2MG(t), $ | (5.6) |
and
$ ‖zt‖22≤2E(z0,z1)+2MG(t). $ | (5.7) |
Combining (2.5) and (5.6), we see
$ ‖z‖2p2p≤R2p(2E(z0,z1)+2MG(t))p. $ | (5.8) |
By substituting (5.7) and (5.8) into (5.2), we have
$ G′(t)≤(p+1)R2p2(2E(z0,z1)+2MG(t))p+(p+1)(E(z0,z1)+MG(t)). $ | (5.9) |
We consider the function $ h(x): = x^{p}, x > 0, p > 1 $. Since $ h^{''}(x) = p(p-1)x^{p-2} > 0 $, $ h(x) $ is a convex function. Thus it gives that
$ h \left( \frac{\tilde{k}_{1}+\tilde{k}_{2}}{2} \right) \leq \frac{1}{2}h(\tilde{k}_{1})+\frac{1}{2}h(\tilde{k}_{2}), \ \ \tilde{k}_1, \tilde{k}_2\geq 0, $ |
that is to say
$ (\tilde{k}_{1}+\tilde{k}_{2})^{p}\leq 2^{p-1}(\tilde{k}_{1}^{p}+\tilde{k}_{2}^{p}). $ |
Then, due to $ \mathcal{E}(z_{0}, z_{1})\geq0 $ and $ G(t)\geq0 $, we can get
$ (2E(z0,z1)+2MG(t))p≤2p−1((2E(z0,z1))p+(2MG(t))p), $ | (5.10) |
which means that (5.9) turns to
$ G′(t)≤(p+1)R2p22p−2Mp(G(t))p+(p+1)MG(t)+(p+1)E(z0,z1)+(p+1)R2p22p−2(E(z0,z1))p, $ |
i.e.,
$ G′(t)C9(G(t))p+C10G(t)+C11≤1. $ | (5.11) |
Recalling the assumption that the solution of problem (1.1) blows up in finite time $ T_{0} $, we have
$ limt→T0G(t)=limt→T0‖z(t)‖p+1p+1=∞. $ | (5.12) |
Then, integrating both sides of (5.11) on $ (0, T_{0}) $ and combining (5.12), we get
$ \int_{G(0)}^\infty\frac{1}{C_{9}y^{p}+C_{10}y+C_{11}}{\rm d}y\leq T_{0}. $ |
Thus, the proof of Theorem 5.1 is completed.
In Sept Ⅰ of the proofs of Theorem $ 3.2 $, by the classical form of Gronwall's inequality (integral form) shown in Appendix B.2 of [4], we know that (3.59) gives
$ ˆE(t)≤ˆE(0)(1+ˉMCteˉMCt). $ | (6.1) |
In (6.1), the growth order of the distance of the solutions, i.e., $ \widehat{E}(t) $, is controlled by the product of an exponential function and a polynomial function, which is higher than that in (1.2) established for the local solution. In Sept Ⅱ of the proofs of Theorem $ 3.2 $, in order to build the growth estimate of $ \widehat{E}(t) $ in the same form as (1.2) for the global solution, i.e., (3.60), we need the following variation of Gronwall's inequality.
Proposition 6.1. For a nonnegative, summable function $ \zeta(t) $ on $ [0, \bar{T}] $ with satisfying
$ ζ(t)≤ˉC1∫t0ζ(τ)dτ+ˉC2 $ | (6.2) |
for the constants $ \bar{C}_{1}, \bar{C}_{2}\geq0 $, one has
$ ζ(t)≤ˉC2eˉC1t $ | (6.3) |
for a.e. $ 0\leq t\leq \bar{T} $.
Proof. We use the similar idea of proving the classical form of Gronwall's inequality shown by Appendix B in [4] to give the proofs. We first define the auxiliary function
$ χ(t):=e−ˉC1t∫t0ζ(τ)dτ. $ | (6.4) |
By direct calculation, we have
$ χ′(t)=e−ˉC1t(ζ(t)−ˉC1∫t0ζ(τ)dτ). $ | (6.5) |
Substituting (6.2) into (6.5), we have
$ χ′(t)≤e−ˉC1tˉC2, $ |
which means
$ ∫t0χ′(τ)dτ≤∫t0e−ˉC1τˉC2dτ, $ |
i.e.,
$ χ(t)≤ˉC2ˉC1(1−e−ˉC1t). $ | (6.6) |
According to (6.4) and (6.6), we have
$ ∫t0ζ(τ)dτ≤ˉC2ˉC1(eˉC1t−1). $ | (6.7) |
Substituting (6.7) into (6.2), we obtain (6.3).
The authors declare they have not used Artificial Intelligence (AI) tools in the creation of this article.
Runzhang Xu was supported by the National Natural Science Foundation of China (12271122) and the Fundamental Research Funds for the Central Universities. Chao Yang was supported by the Ph.D. Student Research and Innovation Fund of the Fundamental Research Funds for the Central Universities (3072022GIP2403).
The authors declare there is no conflict of interest.
[1] |
Cryan JF, Dinan TG (2012) Mind-altering microorganisms: The impact of the gut microbiota on brain and behaviour. Nat Rev Neurosci 13: 701–712. doi: 10.1038/nrn3346
![]() |
[2] |
Borre YE, Moloney RD, Clarke G, et al. (2014) The impact of microbiota on brain and behavior: Mechanisms & therapeutic potential. Adv Exp Med Biol 817: 373–403. doi: 10.1007/978-1-4939-0897-4_17
![]() |
[3] | Diagnostic and Statistical Manual of Mental Disorders (DSM-V), 2013. American Psychiatric Association, 189: 4189. |
[4] |
Siniscalco D, Cirillo A, Bradstreet JJ, et al. (2013) Epigenetic findings in autism: New perspectives for therapy. Int J Environ Res Public Health 10: 4261–4273. doi: 10.3390/ijerph10094261
![]() |
[5] | Frye RE, Slattery J, Macfabe DF, et al. (2015) Approaches to studying and manipulating the enteric microbiome to improve autism symptoms. Microb Ecol Health Dis 26: 26878. |
[6] | De Magistris L, Picardi A, Siniscalco D, et al. (2013) Antibodies against food antigens in patients with autistic spectrum disorders. BioMed Res Int 2013: 729349. |
[7] |
Mcelhanon BO, Mccracken C, Karpen S, et al. (2014) Gastrointestinal symptoms in autism spectrum disorder: A meta-analysis. Pediatrics 133: 872–883. doi: 10.1542/peds.2013-3995
![]() |
[8] |
Adams JB, Johansen LJ, Powell LD, et al. (2011) Gastrointestinal flora and gastrointestinal status in children with autism-comparisons to typical children and correlation with autism severity. BMC Gastroenterol 11: 22. doi: 10.1186/1471-230X-11-22
![]() |
[9] |
Nikolov RN, Bearss KE, Lettinga J, et al. (2009) Gastrointestinal symptoms in a sample of children with pervasive developmental disorders. J Autism Dev Disord 39: 405–413. doi: 10.1007/s10803-008-0637-8
![]() |
[10] |
Iovene MR, Bombace F, Maresca R, et al. (2017) Intestinal dysbiosis and Yeast Isolation in Stool of Subjects with Autism Spectrum Disorders. Mycopathologia 182: 349–363. doi: 10.1007/s11046-016-0068-6
![]() |
[11] | Siniscalco D (2014) Gut bacteria-brain axis in autism. Autism 4: e124. |
[12] |
Kranich J, Maslowski KM, Mackay CR (2011) Commensal flora and the regulation of inflammatory and autoimmune responses. Semin Immunol 23: 139–145. doi: 10.1016/j.smim.2011.01.011
![]() |
[13] |
Macfarlane S, Macfarlane GT (2006) Composition and metabolic activities of bacterial biofilms colonizing food residues in the human gut. Appl Environ Microbiol 72: 6204–6211. doi: 10.1128/AEM.00754-06
![]() |
[14] |
Liu Y, Fatheree NY, Mangalat N, et al. (2010) Human-derived probiotic Lactobacillus reuteri strains differentially reduce intestinal inflammation. Am J Physiol Gastrointest Liver Physiol 299: G1087–G1096. doi: 10.1152/ajpgi.00124.2010
![]() |
[15] | Fateh R, Iravani S, Frootan M, et al. (2011) Synbiotic preparation in men suffering from functional constipation: A randomised controlled trial. Swiss Med Wkly 141: w13239. |
[16] |
Vuong HE, Hsiao EY (2017) Emerging Roles for the Gut Microbiome in Autism Spectrum Disorder. Biol Psychiatry 81: 411–423. doi: 10.1016/j.biopsych.2016.08.024
![]() |
[17] |
Strati F, Cavalieri D, Albanese D, et al. (2017) New evidences on the altered gut microbiota in autism spectrum disorders. Microbiome 5: 24. doi: 10.1186/s40168-017-0242-1
![]() |
[18] |
Finegold SM, Molitoris D, Song Y, et al. (2002) Gastrointestinal microflora studies in late-onset autism. Clin Infect Dis 35: S6–S16. doi: 10.1086/341914
![]() |
[19] | Wang L, Christophersen CT, Sorich MJ, et al. (2013) Increased abundance of Sutterella spp. and Ruminococcus torques in feces of children with autism spectrum disorder. Mol Autism 4: 42. |
[20] | Williams BL, Hornig M, Parekh T, et al. (2012) Application of novel PCR-based methods for detection, quantitation, and phylogenetic characterization of Sutterella species in intestinal biopsy samples from children with autism and gastrointestinal disturbances. MBio 3: 54–64. |
[21] |
Kang DW, Park JG, Ilhan ZE, et al. (2013) Reduced incidence of Prevotella and other fermenters in intestinal microflora of autistic children. PLoS One 8: e68322. doi: 10.1371/journal.pone.0068322
![]() |
[22] |
Ding HT, Taur Y, Walkup JT (2017) Gut microbiota and autism: Key concepts and findings. J Autism Dev Disord 47: 480–489. doi: 10.1007/s10803-016-2960-9
![]() |
[23] |
Frye RE, Nankova B, Bhattacharyya S, et al. (2017) Modulation of immunological pathways in autistic and neurotypical lymphoblastoid cell lines by the enteric microbiome metabolite propionic acid. Front Immunol 8: 1670. doi: 10.3389/fimmu.2017.01670
![]() |
[24] | Shaw W (2010) Increased urinary excretion of a 3-(3-hydroxyphenyl)-3-hydroxypropionic acid (HPHPA), an abnormal phenylalanine metabolite of Clostridia spp. in the gastrointestinal tract, in urine samples from patients with autism and schizophrenia. Nutr Neurosci 13: 135–143. |
[25] |
Wang L, Yu YM, Zhang YQ, et al. (2018) Hydrogen breath test to detect small intestinal bacterial overgrowth: A prevalence case-control study in autism. Eur Child Adolesc Psychiatry 27: 233–240. doi: 10.1007/s00787-017-1039-2
![]() |
[26] |
Adike A, DiBaise JK (2018) Small Intestinal Bacterial Overgrowth: Nutritional Implications, Diagnosis, and Management. Gastroenterol Clin North Am 47: 193–208. doi: 10.1016/j.gtc.2017.09.008
![]() |
[27] |
House SA, Goodman DC, Weinstein SJ, et al. (2016) Prescription use among children with autism spectrum disorders in Northern New England: Intensity and small area variation. J Pediatr 169: 277–283. doi: 10.1016/j.jpeds.2015.10.027
![]() |
[28] |
Rana SV, Bhardwaj SB (2008) Small intestinal bacterial overgrowth. Scand J Gastroenterol 43: 1030–1037. doi: 10.1080/00365520801947074
![]() |
[29] | Quera PR, Quigley EM, Madrid SAM (2005) Small intestinal bacterial overgrowth. An update. Rev Med Chile 133: 1361–1370. |
[30] |
Gatta L, Scarpignato C (2017) Systematic review with meta-analysis: Rifaximin is effective and safe for the treatment of small intestine bacterial overgrowth. Aliment Pharmacol Ther 45: 604–616. doi: 10.1111/apt.13928
![]() |
[31] | Kwiatkowski L, Rice E, Langland J (2017) Integrative treatment of chronic abdominal bloating and pain associated with overgrowth of small intestinal bacteria: A case report. Altern Ther Health Med 23: 56–61. |
[32] |
Kernien JF, Snarr BD, Sheppard DC, et al. (2018) The interface between fungal biofilms and innate immunity. Front Immunol 8: 1968. doi: 10.3389/fimmu.2017.01968
![]() |
[33] |
Anwar H, Dasgupta MK, Costerton JW (1990) Testing the susceptibility of bacteria in biofilms to antibacterial agents. Antimicrob Agents Chemother 34: 2043–2046. doi: 10.1128/AAC.34.11.2043
![]() |
[34] | Høiby N, Bjarnsholt T, Moser C, et al. (2015) ESCMID guideline for the diagnosis and treatment of biofilm infections 2014. Clin Microbiol Infect 1: 1–25. |
[35] |
Smith A, Buchinsky FJ, Post JC (2011) Eradicating chronic ear, nose, and throat infections: A systematically conducted literature review of advances in biofilm treatment. Otolaryngol Head Neck Surg 144: 338–347. doi: 10.1177/0194599810391620
![]() |
[36] |
Slobodníková L, Fialová S, Rendeková K, et al. (2016) Antibiofilm activity of plant polyphenols. Molecules 21: 1717. doi: 10.3390/molecules21121717
![]() |
[37] |
Li XH, Lee JH (2017) Antibiofilm agents: A new perspective for antimicrobial strategy. J Microbiol 55: 753–766. doi: 10.1007/s12275-017-7274-x
![]() |
[38] |
de Magistris L, Familiari V, Pascotto A, et al. (2010) Alterations of the intestinal barrier in patients with autism spectrum disorders and in their first-degree relatives. J Pediatr Gastroenterol Nutr 51: 418–424. doi: 10.1097/MPG.0b013e3181dcc4a5
![]() |
[39] | Wan MLY, Ling KH, El-Nezami H, et al. (2018) Influence of functional food components on gut health. Crit Rev Food Sci Nutr 2018: 1–10. |
[40] |
Laparra JM, Sanz Y (2010) Interactions of gut microbiota with functional food components and nutraceuticals. Pharmacol Res 61: 219–225. doi: 10.1016/j.phrs.2009.11.001
![]() |
1. | Zin Win Thu, Dasom Kim, Junseok Lee, Woon-Jae Won, Hyeon Jun Lee, Nan Lao Ywet, Aye Aye Maw, Jae-Woo Lee, Multivehicle Point-to-Point Network Problem Formulation for UAM Operation Management Used with Dynamic Scheduling, 2022, 12, 2076-3417, 11858, 10.3390/app122211858 | |
2. | Jiaming Su, Minghua Hu, Yingli Liu, Jianan Yin, A Large Neighborhood Search Algorithm with Simulated Annealing and Time Decomposition Strategy for the Aircraft Runway Scheduling Problem, 2023, 10, 2226-4310, 177, 10.3390/aerospace10020177 | |
3. | Ben Tian, Zhaogang Xie, Wei Peng, Jun Liu, Application Analysis of Multi-Intelligence Optimization Decision-Making Method in College Students’ Ideological and Political Education System, 2022, 2022, 1939-0122, 1, 10.1155/2022/8999757 | |
4. | Jian Yang, Xuejun Huang, Intelligent Planning Modeling and Optimization of UAV Cluster Based on Multi-Objective Optimization Algorithm, 2022, 11, 2079-9292, 4238, 10.3390/electronics11244238 | |
5. | Jun Tang, Wanting Qin, Qingtao Pan, Songyang Lao, A Deep Multimodal Fusion and Multitasking Trajectory Prediction Model for Typhoon Trajectory Prediction to Reduce Flight Scheduling Cancellation, 2024, 35, 1004-4132, 666, 10.23919/JSEE.2024.000042 | |
6. | Yingli Liu, Minghua Hu, Jiaming Su, Estimation Distributed Algorithm to Aid Aircraft Runway Scheduling Problem, 2023, 2491, 1742-6588, 012007, 10.1088/1742-6596/2491/1/012007 | |
7. | Hao Jiang, Weili Zeng, Wenbin Wei, Xianghua Tan, A bilevel flight collaborative scheduling model with traffic scenario adaptation: An arrival prior perspective, 2024, 161, 03050548, 106431, 10.1016/j.cor.2023.106431 | |
8. | Xiuhua Teng, Li Wang, Ruipeng Yu, Qichen Wu, Jun Qin, Wenjin Yu, 2024, Analysis of obstacle superelevation in airport clearance area based on Cesium, 9781510672949, 58, 10.1117/12.3024498 | |
9. | Wentao Zhou, Jinlin Wang, Longtao Zhu, Yi Wang, Yulong Ji, Flight Arrival Scheduling via Large Language Model, 2024, 11, 2226-4310, 813, 10.3390/aerospace11100813 | |
10. | Philipp Zeunert, Efficient Aircraft Arrival Sequencing Given Airport Gate Assignment, 2023, 31, 2380-9450, 184, 10.2514/1.D0350 | |
11. | Jingheng Zhang, Minghua Wang, Haochen Shi, Yingzhuo Zhang, 2023, Dynamic Optimal Scheduling Model of Multi Runway Flight Arrival and Departure Based on Improved Genetic Algorithm, 979-8-3503-1331-4, 203, 10.1109/ICNETIC59568.2023.00049 | |
12. | Chaoyu Xia, Yi Wen, Minghua Hu, Hanbing Yan, Changbo Hou, Weidong Liu, Microscopic-Level Collaborative Optimization Framework for Integrated Arrival-Departure and Surface Operations: Integrated Runway and Taxiway Aircraft Sequencing and Scheduling, 2024, 11, 2226-4310, 1042, 10.3390/aerospace11121042 | |
13. | Kejia Chen, Tengkuan Situ, Yunfei Fang, An improved multi-objective restart variable neighborhood search algorithm for aircraft sequencing problem with complex interdependent runways, 2025, 127, 09696997, 102807, 10.1016/j.jairtraman.2025.102807 |