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Research article

Bayesian and non-Bayesian inferential approaches under lower-recorded data with application to model COVID-19 data

  • Received: 15 March 2022 Revised: 02 June 2022 Accepted: 08 June 2022 Published: 29 June 2022
  • MSC : 62N05, 62F10

  • In this article, estimation of the parameters as well as some lifetime parameters such as reliability and hazard rate functions for the Dagum distribution based on record statistics is obtained. Both Bayesian and non-Bayesian inferential approaches of the distribution parameters and reliability characteristics are discussed. Moreover, approximate confidence intervals for the parameters based on the asymptotic distribution of the maximum likelihood estimators are constructed. Besides, to construct the variances of the reliability and hazard rate functions the delta method is implemented. The Lindley's approximation and Markov chain Monte Carlo techniques are proposed to construct the Bayes estimates. To this end, the results of the Bayes estimates are obtained under both symmetric and asymmetric loss functions. Also, the corresponding highest posterior density credible intervals are constructed. A simulation study is utilized to assay and evaluate the performance of the proposed inferential approaches. Finally, a real data set of COVID-19 mortality rate is analyzed to illustrate the proposed methods of estimation.

    Citation: Rashad M. EL-Sagheer, Mohamed S. Eliwa, Khaled M. Alqahtani, Mahmoud El-Morshedy. Bayesian and non-Bayesian inferential approaches under lower-recorded data with application to model COVID-19 data[J]. AIMS Mathematics, 2022, 7(9): 15965-15981. doi: 10.3934/math.2022873

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  • In this article, estimation of the parameters as well as some lifetime parameters such as reliability and hazard rate functions for the Dagum distribution based on record statistics is obtained. Both Bayesian and non-Bayesian inferential approaches of the distribution parameters and reliability characteristics are discussed. Moreover, approximate confidence intervals for the parameters based on the asymptotic distribution of the maximum likelihood estimators are constructed. Besides, to construct the variances of the reliability and hazard rate functions the delta method is implemented. The Lindley's approximation and Markov chain Monte Carlo techniques are proposed to construct the Bayes estimates. To this end, the results of the Bayes estimates are obtained under both symmetric and asymmetric loss functions. Also, the corresponding highest posterior density credible intervals are constructed. A simulation study is utilized to assay and evaluate the performance of the proposed inferential approaches. Finally, a real data set of COVID-19 mortality rate is analyzed to illustrate the proposed methods of estimation.



    Gradient estimates are very powerful tools in geometric analysis. In 1970s, Cheng-Yau [3] proved a local version of Yau's gradient estimate (see [25]) for the harmonic function on manifolds. In [16], Li and Yau introduced a gradient estimate for positive solutions of the following parabolic equation,

    (Δq(x,t)t)u(x,t)=0, (1.1)

    which was known as the well-known Li-Yau gradient estimate and it is the main ingredient in the proof of Harnack-type inequalities. In [10], Hamilton proved an elliptic type gradient estimate for heat equations on compact Riemannian manifolds, which was known as the Hamilton's gradient estimate and it was later generalized to the noncompact case by Kotschwar [15]. The Hamilton's gradient estimate is useful for proving monotonicity formulas (see [9]). In [22], Souplet and Zhang derived a localized Cheng-Yau type estimate for the heat equation by adding a logarithmic correction term, which is called the Souplet-Zhang's gradient estimate. After the above work, there is a rich literature on extensions of the Li-Yau gradient estimate, Hamilton's gradient estimate and Souplet-Zhang's gradient estimate to diverse settings and evolution equations. We only cite [1,8,11,12,18,19,24,28,31] here and one may find more references therein.

    An important generalization of the Laplacian is the following diffusion operator

    ΔV=Δ+V,

    on a Riemannian manifold (M,g) of dimension n, where V is a smooth vector field on M. Here and Δ are the Levi-Civita connenction and Laplacian with respect to metric g, respectively. The V-Laplacian can be considered as a special case of V-harmonic maps introduced in [5]. Recall that on a complete Riemannian manifold (M,g), we can define the -Bakry-Émery Ricci curvature and m-Bakry-Émery Ricci curvature as follows [6,20]

    RicV=Ric12LVg, (1.2)
    RicmV=RicV1mnVV, (1.3)

    where mn is a constant, Ric is the Ricci curvature of M and LV denotes the Lie derivative along the direction V. In particular, we use the convention that m=n if and only if V0. There have been plenty of gradient estimates obtained not only for the heat equation, but more generally, for other nonlinear equations concerning the V-Laplacian on manifolds, for example, [4,13,20,27,32].

    In [7], Chen and Zhao proved Li-Yau type gradient estimates and Souplet-Zhang type gradient estimates for positive solutions to a general parabolic equation

    (ΔVq(x,t)t)u(x,t)=A(u(x,t)) (1.4)

    on M×[0,T] with m-Bakry-Émery Ricci tensor bounded below, where q(x,t) is a function on M×[0,T] of C2 in x-variables and C1 in t-variable, and A(u) is a function of C2 in u. In the present paper, by studying the evolution of quantity u13 instead of lnu, we derive localised Hamilton type gradient estimates for |u|u. Most previous studies cited in the paper give the gradient estimates for |u|u. The main theorems are below.

    Theorem 1.1. Let (Mn,g) be a complete Riemannian manifold with

    RicmV(m1)K1

    for some constant K1>0 in B(¯x,ρ), some fixed point ¯x in M and some fixed radius ρ. Assume that there exists a constant D1>0 such that u(0,D1] is a smooth solution to the general parabolic Eq (1.4) in Q2ρ,T1T0=B(¯x,2ρ)×[T0,T1], where T1>T0. Then there exists a universal constant c(n) that depends only on n so that

    |u|uc(n)D1((m1)K1ρ+2m1ρ2+1tT0+maxQρ,T1T0|q|23)12+3D1((m1)K1+maxQρ,T1T0|q|2min{0,minQρ,T1T0(A(u)A(u)2u)})12 (1.5)

    in Qρ2,T1T0 with tT0.

    Remark 1.1. Hamilton [10] first got this gradient estimate for the heat equation on a compact manifold. We also have Hamilton type estimates if we assume that RicV(m1)K1 for some constant K1>0, and notice that RicV(m1)K1 is weak than RicmV(m1)K1. Since we do not have a good enough V-Laplacian comparison for general smooth vector field V, we need the condition that |V| is bounded in this case. Nevertheless, when V=f, we can use the method given in [23] to obtain all results in this paper, without assuming that |V| is bounded.

    If q=0 and A(u)=aulnu, where a is a constant, then following the proof of Theorem 1.1 we have

    Corollary 1.2. Let (Mn,g) be a complete Riemannian manifold with

    RicmV(m1)K1

    for some constant K1>0 in B(¯x,ρ), some fixed point ¯x in M and some fixed radius ρ. Assume that u is a positive smooth solution to the equation

    tu=ΔVuaulnu (1.6)

    in Q2ρ,T1T0=B(¯x,2ρ)×[T0,T1], where T1>T0.

    (1) When a>0, assuming that 1uD1 in Q2ρ,T1T0, there exists a constant c=c(n) such that

    |u|ucD1(4(m1)2K1ρ2+2m1ρ+1tT0+|2(m1)K12a|12) (1.7)

    in Qρ2,T1T0 with tT0.

    (2) When a<0, assuming that 0<uD1 in Q2ρ,T1T0, there exists a constant c=c(n) such that

    |u|ucD1(4(m1)2K1ρ2+2m1ρ+1tT0+|2(m1)K1a(2+lnD1)|12) (1.8)

    in Qρ2,T1T0 with tT0.

    Using the corollary, we get the following Liouville type result.

    Corollary 1.3. Let (Mn,g) be a complete Riemannian manifold with RicmV(m1)K1 for some constant K1>0. Assume that u is a positive and bounded solution to the Eq (1.6) and u is independent of time.

    (1) When a>0, assume that 1uD1. If a=(m1)K1, then u1.

    (2) When a<0, assume that 0<uexp{2+2(m1)K1a}, then u does not exist.

    Remark 1.2. When V=0, ΔV and RicmV become Δ and Ric, respectively. It is clear that Corollary 1.2–1.3 generalize Theorem 1.3 and Corollary 1.1 in [14].

    We can obtain a global estimate from Theorem 1.1 by taking ρ0.

    Corollary 1.4. Let (Mn,g) be a complete Riemannian manifold with RicmV(m1)K1 for some constant K1>0. u is a positive smooth solution to the general parabolic Eq (1.4) on Mn×[T0,T1]. Suppose that uD1 on Mn×[T0,T1]. We also suppose that

    |A(u)A(u)2u|D2,|q|2D3,|q|23D4

    on Mn×[T0,T1]. Then there exists a universal constant c that depends only on n so that

    |u|uc(n)D1(1tT0+D4)12+3D1((m1)K1+D3+D2)12 (1.9)

    in Mn×[T0,T1] with tT0.

    Let A(u)=a(u(x,t))β in Corollary 1.4, we obtain Hamilton type gradient estimates for bounded positive solutions of the equation

    (ΔVq(x,t)t)u(x,t)=a(u(x,t))β,aR,β(,0][12,+). (1.10)

    Corollary 1.5. Let (Mn,g) be a complete Riemannian manifold with RicmV(m1)K1 for some constant K1>0. u is a positive smooth solution to (1.10) on Mn×[T0,T1]. Suppose that uD1 on Mn×[T0,T1]. We also suppose that

    |q|2D3,|q|23D4

    on Mn×[T0,T1]. Then in Mn×[T0,T1] with tT0, there exists a universal constant c that depends only on n so that

    |u|uc(n)D1(1tT0+D4)12+3D1((m1)K1+D3+Λ0)12, (1.11)

    where

    Λ0={0,a0,β12,a(β12)Dβ11,a0,β12,0,a0,β0,a(12β)(minMn×[T0,T1]u)β1,a0,β0.

    In the next part, our result concerns gradient estimates for positive solutions of

    (Δtq(x,t)t)u(x,t)=A(u(x,t)) (1.12)

    on (Mn,g(t)) with the metric evolving under the geometric flow:

    tg(t)=2S(t), (1.13)

    where Δt depends on t and it denotes the Laplacian of g(t), and S(t) is a symmetric (0,2)-tensor field on (Mn,g(t)). In [31], Zhao proved localised Li-Yau type gradient estimates and Souplet-Zhang type gradient estimates for positive solutions of (1.12) under the geometric flow (1.13). In this paper, we have the following localised Hamilton type gradient estimates for positive solutions to the general parabolic Eq (1.12) under the geometric flow (1.13).

    Theorem 1.6. Let (Mn,g(t))t[0,T] be a complete solution to the geometric flow (1.13) on Mn with

    Ricg(t)K2g(t),|Sg(t)|g(t)K3

    for some K2, K3>0 on Qρ,T=B(¯x,ρ)×[0,T]. Assume that there exists a constant L1>0 such that u(0,L1] is a smooth solution to the general parabolic Eq (1.12) in Q2ρ,T. Then there exists a universal constant c(n) that depends only on n so that

    |u|uc(n)L1(K2ρ+1ρ2+1t+K3+maxQρ,T|q|23)12+3L1(K2+K3+maxQρ,T|q|2min{0,minQρ,T(A(u)A(u)2u)})12 (1.14)

    in Qρ2,T.

    Remark 1.3. Recently, some Hamilton type estimates have been achieved to positive solutions of

    (Δtqt)u=au(lnu)α

    under the Ricci flow in [26], and for

    (Δtqt)u=pub+1

    under the Yamabe flow in [29], where p, qC2,1(Mn×[0,T]), b is a positive constant and a,α are real constants. Our results generalize many previous well-known gradient estimate results.

    The paper is organized as follows. In Section 2, we provide a proof of Theorem 1.1 and a proof of Corollary 1.3 and Corollary 1.5. In Section 3, we study gradient estimates of (1.12) under the geometric flow (1.13) and give a proof of Theorem 1.6.

    We first give some notations for the convenience of writing throughout the paper. Let h:=u13 and ˆA(h):=A(u)3u23. Then ˆAh=A(u)2A(u)3u. To prove Theorem 1.1 we need two basic lemmas. First, we derive the following lemma.

    Lemma 2.1. Let (Mn,g) be a complete Riemannian manifold with RicmV(m1)K1 for some constant K1>0. u is a positive smooth solution to the general parabolic Eq (1.4) in Q2ρ,T1T0. If h:=u13, and μ:=h|h|2, then we have

    (ΔVt)μ4h3μ22h1h,μ2(m1)K1μ+qμ23h32|q|μ+2ˆAhμ+h1ˆA(h)μ. (2.1)

    Proof. Since h:=u13, by a simple computation, we can derive the following equation from (1.4):

    (ΔVt)h=2h1|h|2+qh3+ˆA(h). (2.2)

    By direct computations, we have

    iμ=|h|2ih+2hijhjh,

    and

    ΔVμ=Δμ+V,μ=2h|2h|2+2hiijhjh+42h(h,h)+|h|2Δh+2hijhjhVi+V,h|h|2=2h|2h|2+2hΔh,h+2hRic(h,h)+42h(h,h)+|h|2ΔVh+2hijhjhVi=2h|2h|2+2hΔh,h+2hRicV(h,h)+2hjViihjh+42h(h,h)+|h|2ΔVh+2hijhjhVi=2h|2h|2+2hΔVh,h2h(jViihjh+ijhjhVi)+2hRicV(h,h)+2hjViihjh+42h(h,h)+|h|2ΔVh+2hijhjhVi=2h|2h|2+2hΔVh,h+2hRicV(h,h)+42h(h,h)+|h|2ΔVh. (2.3)

    By the following fact:

    0(mnmnΔhnm(mn)h,V)2=(1n1m)(Δh)22mh,VΔh+(1mn1m)h,V2=1n(Δh)21m((Δh)2+2h,VΔh+h,V2)+1mnh,V2|2h|21m(ΔVh)2+1mnh,V2,

    it yields

    |2h|21m(ΔVh)21mnh,V2. (2.4)

    Plugging (2.4) into (2.3), we have

    ΔVμ2h(1m(ΔVh)21mnh,V2)+2hΔVh,h+2hRicV(h,h)+42h(h,h)+|h|2ΔVh=2mh(ΔVh)2+2hRicmV(h,h)+2hΔVh,h+42h(h,h)+|h|2ΔVh. (2.5)

    The partial derivative of μ with respect to t is given by

    tμ=|h|2th+2hi(th)ih=|h|2th+2hi(ΔVh+2h1|h|2qh3ˆA(h))ih=|h|2th+2hΔVh,h+82h(h,h)4h1|h|42qh|h|232h2q,h32hˆAh|h|2. (2.6)

    It follows from (2.2), (2.5) and (2.6) that

    (ΔVt)μ=2mh(ΔVh)2+2hRicmV(h,h)42h(h,h)+|h|2(ΔVt)h+4h1|h|4+2qh3|h|2+2h2q,h3+2hˆAh|h|2=2mh(ΔVh)2+2hRicmV(h,h)42h(h,h)+|h|2(2h1|h|2+qh3+ˆA(h))+4h1|h|4+2qh3|h|2+2h2q,h3+2hˆAh|h|2=2mh(ΔVh)2+2hRicmV(h,h)42h(h,h)+2h1|h|4+qh|h|2+2h2q,h3+2hˆAh|h|2+ˆA(h)|h|22(m1)K1h|h|242h(h,h)+2h1|h|4+qh|h|2+2h2q,h3+2hˆAh|h|2+ˆA(h)|h|2. (2.7)

    Note that

    42h(h,h)=2h1|h|42h1h,(h|h|2)=2h3μ22h1h,μ. (2.8)

    Therefore,

    (ΔVt)μ2(m1)K1h|h|2+4h3μ22h1h,μ+qh|h|2+2h2q,h3+2hˆAh|h|2+ˆA(h)|h|22(m1)K1μ+4h3μ22h1h,μ+qμ23h32|q|μ+2ˆAhμ+h1ˆA(h)μ, (2.9)

    which is the desired estimate.

    The following cut-off function will be used in the proof of Theorem 1.1 (see [2,16,22,30]).

    Lemma 2.2. Fix T0, T1R and T0<T1. Given τ(T0,T1], there exists a smooth function ¯Ψ:[0,+)×[T0,T1]R satisfying the following requirements.

    1). The support of ¯Ψ(s,t) is a subset of [0,ρ]×[T0,T1], and 0¯Ψ1 in [0,ρ]×[T0,T1].

    2). The equalities ¯Ψ(s,t)=1 in [0,ρ2]×[τ,T1] and ¯Ψs(s,t)=0 in [0,ρ2]×[T0,T1].

    3). The estimate |t¯Ψ|¯CτT0¯Ψ12 is satisfied on [0,+]×[T0,T1] for some ¯C>0, and ¯Ψ(s,T0)=0 for all s[0,+).

    4). The inequalities Cb¯Ψbρ¯Ψs0 and |2¯Ψs2|Cb¯Ψbρ2 hold on [0,+]×[T0,T1] for every b(0,1) with some constant Cb that depends on b.

    Throughout this section, we employ the cut-off function Ψ:Mn×[T0,T1]R by

    Ψ(x,t)=¯Ψ(r(x),t),

    where r(x):=d(x,¯x) is the distance function from some fixed point ¯xMn.

    From Lemma 2.1, we have

    (ΔVt)(Ψμ)=μ(ΔVt)Ψ+Ψ(ΔVt)μ+2μ,Ψμ(ΔVt)Ψ+2μ,Ψ2Ψh1h,μ+Ψ[2(m1)K1μ+4h3μ223h32|q|μ+qμ+2ˆAhμ+h1ˆA(h)μ]=μ(ΔVt)Ψ+2ΨΨ,(Ψμ)2|Ψ|2Ψμ2h1h,(Ψμ)+2h1μh,Ψ+Ψ[2(m1)K1μ+4h3μ223h32|q|μ+qμ+2ˆAhμ+h1ˆA(h)μ]. (2.10)

    For fixed τ(T0,T1], let (x1,t1) be a maximum point for Ψμ in Qρ,τT0. Obviously at (x1,t1), we have the following facts: (Ψμ)=0, ΔV(Ψμ)0, and t(Ψμ)0. It follows from (2.10) that at such point

    0h3μ(ΔVt)Ψ2h3|Ψ|2Ψμ2h32μ32|Ψ|+Ψ[2(m1)K1h3μ+4μ223h92|q|μ+qμh3+2h3ˆAhμ+h2ˆA(h)μ]. (2.11)

    In other words, we have just proved that

    4Ψμ2h3μ(ΔVt)Ψ+2h32μ32|Ψ|+23h92|q|μΨ+2h3|Ψ|2Ψμ+Ψμ[2(m1)K1h3qh32h3ˆAhh2ˆA(h)] (2.12)

    at (x1,t1).

    Next, to realize the theorem, it suffices to bound each term on the right-hand side of (2.12). To deal with ΔVΨ(x1,t1), we divide the arguments into two cases.

    Case 1. If d(¯x,x1)<ρ2, then it follows from Lemma 2.2 that Ψ(x,t)=1 around (x1,t1) in the space direction. Therefore, ΔVΨ(x1,t1)=0.

    Case 2. Suppose that d(¯x,x1)ρ2. Since RicmV(m1)K1, we can apply the generalized Laplace comparison theorem (see Corollary 3.2 in [20]) to get

    ΔVr(m1)K1coth(K1r)(m1)(K1+1r).

    Using the generalized Laplace comparison theorem and Lemma 2.2, we have

    ΔVΨ=¯ΨrΔVr+2¯Ψr2|r|2C1/2Ψ12ρ(m1)(K1+2ρ)C1/2Ψ12ρ2

    at (x1,t1), which agrees with Case 1. Therefore, we have

    h3μ(ΔVt)Ψ=uμ(ΔVt)Ψ(C1/2Ψ12ρ(m1)(K1+2ρ)+C1/2Ψ12ρ2+¯CΨ12τT0)uμcD1Ψ12μ((m1)K1ρ+2m1ρ2+1τT0)12Ψμ2+cD21((m1)K1ρ+2m1ρ2+1τT0)2 (2.13)

    for some universal constant c>0. Here we used Lemma 2.2, 0Ψ1 and Cauchy's inequality.

    On the other hand, by Young's inequality and Lemma 2.2, we obtain

    2h32μ32|Ψ|=2Ψ34μ32u12|Ψ|Ψ3412Ψμ2+cD21|Ψ|4Ψ312Ψμ2+cD211ρ4, (2.14)
    23Ψh92|q|μ=23Ψ14μ12u32Ψ34|q|12Ψμ2+cu2Ψ|q|4312Ψμ2+cD21Ψ|q|43, (2.15)
    2|Ψ|2Ψh3μ=2|Ψ|2Ψ32Ψ12uμ2D1|Ψ|2Ψ32Ψ12μ12Ψμ2+cD21|Ψ|4Ψ312Ψμ2+cD21ρ4 (2.16)

    and

    Ψμ[2(m1)K1h3qh32h3ˆAhh2ˆA(h)]=Ψ12μΨ12u[2(m1)K1q2ˆAhh1ˆA(h)]12Ψμ2+12Ψu2[2(m1)K1q2ˆAhh1ˆA(h)]212Ψμ2+D212Ψ[2(m1)K1q2ˆAhh1ˆA(h)]2. (2.17)

    Now, we plug (2.13)–(2.17) into (2.12) to get

    (Ψμ)2(x1,t1)(Ψμ2)(x1,t1)cD21((m1)K1ρ+2m1ρ2+1τT0+|q|23)2+D21((m1)K1+|q|2min{0,minQρ,T1T0(ˆAh+12h1ˆA(h))})2cD21((m1)K1ρ+2m1ρ2+1τT0+maxQρ,T1T0|q|23)2+D21((m1)K1+maxQρ,T1T0|q|2min{0,minQρ,T1T0(A(u)A(u)2u)})2. (2.18)

    The finally, since Ψ(x,τ)=1 in B(¯x,ρ2), it follows from (2.18) that

    μ(x,τ)Ψμ(x1,t1)cD1((m1)K1ρ+2m1ρ2+1τT0+maxQρ,T1T0|q|23)+D1((m1)K1+maxQρ,T1T0|q|2min{0,minQρ,T1T0(A(u)A(u)2u)}). (2.19)

    Since τ(T0,T1] is arbitrary and μ=|u|29u, we have

    |u|ucD1((m1)K1ρ+2m1ρ2+1tT0+maxQρ,T1T0|q|23)12+3D1((m1)K1+maxQρ,T1T0|q|2min{0,minQρ,T1T0(A(u)A(u)2u)})12 (2.20)

    in Qρ2,T1T0. We complete the proof.

    Proof of Corollary 1.3.

    (1) When a>0, for a=(m1)K1, using the inequality (1.7), we have

    |u|ucD1(4(m1)2K1ρ2+2m1ρ+1tT0). (2.21)

    Letting ρ+, t+ in (2.21), we get u is a constant. Using ΔVuaulnu=0, we get u=1.

    (2) When a<0, for D1=exp{2+2(m1)K1a}, using the inequality (1.8), we have

    |u|ucD1(4(m1)2K1ρ2+2m1ρ+1tT0). (2.22)

    Letting ρ+, t+ in (2.22), we get u is a constant. Using ΔVuaulnu=0, we get u=1, but 0<uD1=exp{2+2(m1)K1a}<1. So u does not exist.

    Proof of Corollary 1.5.

    Let

    Λ:=min{0,minMn×[T0,T1](a(β12)uβ1)}.

    From Corollary 1.4, we just have to compute Λ. By the definition, we have

    Λ0={0,a0,β12,a(β12)Dβ11,a0,β12,0,a0,β0,a(12β)(minMn×[T0,T1]u)β1,a0,β0.

    In this section, we consider positive solutions of the nonlinear parabolic Eq (1.12) on (Mn,g) with the metric evolving under the geometric flow (1.13). To prove Theorem 1.6, we follow the procedure used in the proof of Theorem 1.1.

    We first derive a general evolution equation under the geometric flow.

    Lemma 3.1. ([21]) Suppose the metric evolves by (1.13). Then for any smooth function f, we have

    (|f|2)t=2S(f,f)+2f,(ft).

    Next, we derive the following lemma in the same fashion of Lemma 2.1.

    Lemma 3.2. Let (Mn,g(t))t[0,T] be a complete solution to the geometric flow (1.13) and u be a smooth positive solution to the nonlinear parabolic Eq (1.12) in Q2ρ,T. Suppose that there exists positive constants K2 and K3, such that

    Ricg(t)K2g(t),|Sg(t)|g(t)K3

    in Qρ,T. If h:=u13, and μ:=h|h|2, then in Qρ,T, we have

    (Δtt)μ4h3μ24h1h,μ23h32|q|μ2(K2+K3)μ+qμ+h1ˆA(h)μ+2ˆAhμ. (3.1)

    Proof. Since u is a solution to the nonlinear parabolic Eq (1.12), the function h=u13 satisfies

    (Δtt)h=2h1|h|2+qh3+ˆA(h). (3.2)

    As in the proof of Lemma 2.1, we have that

    Δtμ=2h|2h|2+2hΔth,h+2hRic(h,h)+42h(h,h)+|h|2Δth.

    On the other hand, by the equation tg(t)=2S(t), we have

    tμ=|h|2th+2hi(th)ih2hS(f,f)=|h|2th+2hi(Δth+2h1|h|2qh3ˆA(h))ih2hS(f,f)=|h|2th+2hΔth,h+82h(h,h)4h1|h|42qh|h|232h2q,h32hˆAh|h|22hS(f,f). (3.3)

    Therefore,

    (Δtt)μ=2h|2h|242h(h,h)+2h1|h|4+2h2q,h3+2hRic(h,h)+2hS(h,h)+qh|h|2+2hˆAh|h|2+ˆA(h)|h|282h(h,h)2h(K2+K3)|h|223h2|h||q|+(qh+2hˆAh+ˆA(h))|h|2=4h3μ24h1h,μ23h32|q|μ2(K2+K3)μ+qμ+h1ˆA(h)μ+2ˆAhμ, (3.4)

    where we used (2.8), the assumption on bound of Ric+S and

    h|2h|2+22h(h,h)+h1|h|4=|h2h+dhdhh|20.

    The proof is complete.

    Finally, we employ the cut-off function Ψ:Mn×[T0,T1]R, with T0=0, T1=T, by

    Ψ(x,t)=¯Ψ(r(x,t),t),

    where r(x,t):=dg(t)(x,¯x) is the distance function from some fixed point ¯xMn with respect to the metric g(t).

    To prove Theorem 1.6, we follows the same procedure used previously to prove Theorem 1.1; hence in view of Lemma 3.2,

    (Δtt)(Ψμ)μ(Δtt)Ψ+2ΨΨ,(Ψμ)2|Ψ|2Ψμ4h1h,(Ψμ)+4h1μh,Ψ+Ψ[2(K2+K3)μ+4h3μ223h32|q|μ+qμ+2ˆAhμ+h1ˆA(h)μ]. (3.5)

    For fixed τ(0,T], let (x2,t2) be a maximum point for Ψμ in Qρ,τ:=B(¯x,ρ)×[0,τ]Qρ,T. It follows from (3.5) that at such point

    0h3μ(Δtt)Ψ2h3|Ψ|2Ψμ4h32μ32|Ψ|+Ψ[2(K2+K3)μh3+4μ223h92|q|μ+qμh3+2h3ˆAhμ+h2ˆA(h)μ]. (3.6)

    At (x2,t2), making use of (3.6), we further obtain

    4Ψμ2h3μ(Δtt)Ψ+4h32μ32|Ψ|+23h92|q|μΨ+2h3|Ψ|2Ψμ+Ψμ[2(K2+K3)h3qh32h3ˆAhh2ˆA(h)]. (3.7)

    Next, we need to bound each term on the right-hand side of (3.7). To deal with ΔtΨ(x2,t2), we divide the arguments into two cases:

    Case 1: r(x2,t2)<ρ2. In this case, from Lemma 2.2, it follows that Ψ(x,t)=1 around (x2,t2) in the space direction. Therefore, Δt2Ψ(x2,t2)=0.

    Case 2: r(x2,t2)ρ2. Since Ricg(t)(n1)K2, the Laplace comparison theorem (see [17]) implies that

    Δtr(n1)K2coth(K2r)(n1)(K2+1r).

    Then, it follows that

    ΔtΨ=¯ΨrΔtr+2¯Ψr2|r|2C1/2Ψ12ρ(n1)(K2+2ρ)C1/2Ψ12ρ2

    at (x2,t2), which agrees with Case 1.

    Next, we estimate tΨ. xB(¯x,ρ), let γ:[0,a]Mn be a minimal geodesic connecting x and ¯x at time t[0,T]. Then, we have

    |tr(x,t)|g(t)=|ta0|˙γ(s)|g(t)ds|g(t)12a0||˙γ(s)|1g(t)tg(˙γ(s),˙γ(s))|g(t)dsK3r(x,t)K3ρ.

    Thus, together with Lemma 2.2, we find that

    tΨ|t¯Ψ|g(t)+|¯Ψ|g(t)|tr|g(t)¯CΨ1/2τ+C1/2K3Ψ1/2. (3.8)

    Therefore, we have

    h3μ(Δtt)Ψ=uμ(Δtt)Ψ(C1/2Ψ12ρ(n1)(K2+2ρ)+C1/2Ψ12ρ2+¯CΨ1/2τ+C1/2K3Ψ1/2)uμcL1Ψ12μ(K2ρ+1ρ2+1τ+K3)12Ψμ2+cL21(K2ρ+1ρ2+1τ+K3)2 (3.9)

    at (x2,t2) for some universal constant c>0 that depends only on n. By similar computations as in the proof of Theorem 1.1, we arrive at

    4h32μ32|Ψ|Ψμ2+2cL211ρ4, (3.10)
    23Ψh92|q|μ12Ψμ2+cL21Ψ|q|43, (3.11)
    2|Ψ|2Ψh3μ12Ψμ2+cL21ρ4 (3.12)

    and

    Ψμ[2(K2+K3)h3qh32h3ˆAhh2ˆA(h)]12Ψμ2+L212Ψ[2(K2+K3)+|q|min{0,minQρ,T(2ˆAh+h1ˆA(h))}]2. (3.13)

    Plugging (3.9)–(3.13) into (3.6), we get

    (Ψμ)2(x2,t2)(Ψμ2)(x2,t2)cL21(K2ρ+1ρ2+1τ+K3+|q|23)2+L21(K2+K3+|q|2min{0,minQρ,T(ˆAh+12h1ˆA(h))})2cL21(K2ρ+1ρ2+1τ+K3+maxQρ,T|q|23)2+L21(K2+K3+maxQρ,T|q|2min{0,minQρ,T(A(u)A(u)2u)})2. (3.14)

    Note that Ψ(x,τ)=1 when d(x,¯x)<ρ2, it follows from (2.18) that

    μ(x,τ)Ψμ(x2,t2)cL1(K2ρ+1ρ2+1τ+K3+maxQρ,T|q|23)+L1(K2+K3+maxQρ,T|q|2min{0,minQρ,T(A(u)A(u)2u)}). (3.15)

    Since τ(0,T] is arbitrary and μ=|u|29u, we have

    |u|ucL1(K2ρ+1ρ2+1τ+K3+maxQρ,T|q|23)12+3L1(K2+K3+maxQρ,T|q|2min{0,minQρ,T(A(u)A(u)2u)})12 (3.16)

    in Qρ2,T.

    We complete the proof.

    Remark 3.1. We also obtain the corresponding applications similar to Corollary 1.4 and Corollary 1.5, which we will not write them down here.

    The author would like to thank the referee for helpful suggestion which makes the paper more readable. This work was supported by NSFC (Nos. 11971415, 11901500), Henan Province Science Foundation for Youths (No.212300410235), and the Key Scientific Research Program in Universities of Henan Province (No.21A110021) and Nanhu Scholars Program for Young Scholars of XYNU (No. 2019).

    The author declares no conflict of interest.



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