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Global boundedness in an attraction–repulsion Chemotaxis system with nonlinear productions and logistic source
Journal of Inequalities and Applications volume 2024, Article number: 130 (2024)
Abstract
This paper deals with the attraction–repulsion chemotaxis system with nonlinear productions and logistic source,
in a bounded domain \(\Omega \subset {{\mathbb{R}}^{n}}\) (\(n \ge 1 \)), subject to the homogeneous Neumann boundary conditions and initial conditions, where \(D,\Phi ,\Psi \in {{C}^{2}}[0,\infty )\) are nonnegative with \(D(s)\ge {{(s+1)}^{p}}\) for \(s\ge 0\), \(\Phi (s)\le \chi {{s}^{q}}\), \(\xi {{s}^{g}}\le \Psi (s) \le \zeta s^{j}\), \(s\ge {{s}_{0}}\), for \({{s}_{0}}>1\), the logistic source satisfies \(f(s)\le s(a-b{{s}^{d}})\), \(s>0\), \(f(0)\ge 0\), and the nonlinear productions for the attraction and repulsion chemicals are described via \(\alpha {{u}^{k}}\) and \(\gamma {{u}^{l}}\), respectively. When \(k=l=1\), it is known that this system possesses a globally bounded solution in some cases. However, there has been no work in the case \(k,l>0\). This paper develops the global boundedness of the solution to the system in some cases and extends the global boundedness criteria established by Tian, He, and Zheng (2016) for the attraction–repulsion chemotaxis system.
1 Introduction
In this paper, we consider the boundedness in the attraction–repulsion chemotaxis system
where \(\Omega \subset {{\mathbb{R}}^{n}} ( n \ge 1 )\) is a bounded domain with smooth boundary ∂Ω, \(\tau \in \{0,1\}\), ν denotes the outward normal vector to ∂Ω, and the parameters \(\alpha ,\beta ,\gamma ,\delta ,k,l>0\). The nonlinear nonnegative functions D, Φ, Ψ satisfy
with \(\chi ,\xi ,\zeta >0\) and \(p,q,g, j \in \mathbb{R}\). The logistic source \(f\in {{C}^{2}}[0,\infty )\) fulfills
where \(a,b,d>0\). In model (1.1) the functions u, v, and w represent the cell density and the concentrations of attractive and repulsive chemical substances, respectively. The productions of v and w in the model are both nonlinear of the forms \(\alpha {{u}^{k}}\) and \(\gamma {{u}^{l}}\). This would substantially affect the boundedness of solutions.
Model (1.1) is one of many types of the chemotaxis systems proposed by Keller and Segel [1] (for guidance on various variants, we refer to Hillen and Painter [2]). For the attraction–repulsion system with linear productions and logistic source, i.e.,
where \({{\tau }_{i}}\in \{0,1\}\) (\(i=1,2\)), in the case \({{\tau }_{1}}={{\tau }_{2}}=1\) with \(f(u)=u(a-bu)\), the global boundedness was established in [3–6]. Among them, Jin and Wang [5] dealt with the one-dimensional case. Also, the two- and three-dimensional settings were investigated by Jin and Liu [4] under the condition \(\chi =\xi \). Furthermore, in the case \({{\tau }_{1}}={{\tau }_{2}}=0\) with \(f(u)=u(a-bu)\) and \(a=b\), Salako and Shen [7] derived the global boundedness under some special conditions. Moreover, with \(f(u)\le u(a-bu)\), Zhang and Li [8] proved that the problem possesses a globally bounded classical solution if one of the following holds: (a) \(\alpha \chi -\gamma \xi \le b\); (b) \(n\le 2\); (c) \(\frac{n-2}{n}(\alpha \chi -\gamma \xi )\le b\) with \(n\ge 3\).
Lately, we turn our eyes into the chemotaxis system with nonlinear productions. Wang and Xiang [9] proved that for the chemotaxis system
with \(f(u)\le u(a-b{{u}^{d}})\) and \(k,d>0\), the solutions are globally bounded if either \(d>k\) or \(d=k\) with \(\frac{kn-2}{kn}\chi < b\). Moreover, Hong, Tian, and-Zheng [10] extended the above criteria for the attraction–repulsion system
where \(f(u)\le u(a-b{{u}^{d}})\), \(k,l,d>0\), \(k<\max \{l,d,\frac{2}{n}\}\) or \(k=\max \{l,d\}\ge \frac{2}{n}\) with the following assumptions: (a) \(k=l=d\), \(\frac{kn-2}{kn}(\alpha \chi -\gamma \xi )< b\); (b) \(k=l>d\), \(\alpha \chi -\gamma \xi <0\); (c) \(k=d>l\), \(\frac{kn-2}{kn}\alpha \chi < b\).
Recently, Chiyo, Yokota, and Mizukami [11, 12] obtained some interesting results for a fully parabolic attraction–repulsion chemotaxis system with signal-dependent sensitivity.
Concerning the attraction–repulsion chemotaxis system (1.1), our main results are the following theorems.
Theorem 1
Let \(\tau = 0, D,\Phi ,\Psi \) and f satisfy (1.2)–(1.6) with nonnegative initial data \({{u}_{0}}\in C(\bar{\Omega })\) and \({{v}_{0}} \in {{W}^{1,\sigma }}(\bar{\Omega })\) (\(\sigma >n\)).
(i) If \(q+k<\max \{g+l,d+1,\frac{2}{n}+p+1\}\), then Eq. (1.1) admits a globally bounded solution.
(ii) Assume \(q+k=\max \{g+l,d+1\}\ge \tfrac{2}{n}+p+1\) and there exist \({{b}_{0}}\), \({{\theta }_{0}}\) such that one of the following assumptions holds:
(a) \(q+k=g+l=d+1\) with b and γξ sufficiently large such that \(b + \gamma \xi \theta _{0} > 4b_{0}\);
(b) \(q+k=g+l>d+1\) with γξ sufficiently large such that \(\gamma \xi \theta _{0} > 4b_{0}\);
(c) \(q+k=d+1>g+l\) with b sufficiently large such that \(b > 4b_{0}\).
Then the solution of Eq. (1.1) is globally bounded.
Theorem 2
Let \(\tau = 1, D,\Phi ,\Psi \), and f satisfy (1.2)–(1.6) with nonnegative initial data \({{u}_{0}}\in C(\bar{\Omega })\) and \({{v}_{0}},{{w}_{0}}\in {{W}^{1,\sigma }}(\bar{\Omega })\) (\(\sigma >n\)).
(i) If \(q+k,g+l<\max \{d+1,\frac{2}{n}+p+1\}\), then Eq. (1.1) admits a globally bounded solution.
(ii) Assume that \(q+k=d+1\) and \(q+k,g+l\ge \tfrac{2}{n}+p+1\) and that there exist \({{b}_{1}},{{b}_{2}},{{b}_{3}},{{\theta }_{1}},{{\theta }_{2}}>0\) such that one of the following assumptions holds:
(a) \(q+k=d+1=g+l\) with b sufficiently large such that \(\frac{b-\xi {{\theta }_{2}}}{\chi {{\theta }_{1}}}>1+{{b}_{1}}\) and \(\frac{b-\chi {{\theta }_{1}}}{\xi {{\theta }_{2}}}>1+{{b}_{2}}\);
(b) \(q+k=d+1>g+l\) with b sufficiently large such that \(\frac{b}{\chi {{\theta }_{1}}}>2+{{b}_{3}}\).
Then the solution of Eq. (1.1) is globally bounded.
Remark 1
Model (1.1) includes four mechanisms (a nonlinear diffusion, attraction, repulsion, and logistic source) and two nonlinear productions (components v and w). The behavior of the solution is determined by the interaction among them. It is known that besides the attraction and corresponding production, all the other benefit the global boundedness of solutions.
Remark 2
Theorem 1 illustrates how the nonlinear exponents \(p,q,g,d,k,l>0\) influence the evolution of solutions. More precisely, if the attraction is dominated by one of the other mechanisms (\(q+k< \max \{g+l,d+1,\frac{2}{n}+p+1\}\)), then the solution will be globally bounded. Under the balance situations with \(q+k=\max \{g+l,d+1\}\) and \(q+k\ge \tfrac{2}{n}+p+1\), the solution boundedness will be determined by some related coefficients. Furthermore, Theorem 1 extends the criteria for global boundedness established by Tian, He, and Zheng [13] for the attraction–repulsion chemotaxis system.
Remark 3
Theorem 2 also illustrates how the nonlinear exponents \(p,q,g,d,k,l>0\) influence the evolution of solutions. More precisely, if the attraction and repulsion are dominated by one of the other mechanisms (\(q+k,g+l<\max \{d+1,\frac{2}{n}+p+1\}\)), then the solution will be globally bounded. Under the balance situations with \(q+k=d+1\) and \(q+k,g+l\ge \tfrac{2}{n}+p+1\), the solution boundedness will be determined by some related coefficients. However, in two cases, \(g+l>q+k\ge d+1\text{ and} g+l=q+k>d+1\), we have not found a satisfactory way to explain the behavior of the solution.
2 Preliminaries
In this section, we introduce some results on the local solutions, some integral estimates, and the maximal Sobolev regularity.
Lemma 1
(See [13, Lemma 2.1]) Let \(\Omega \subset {{\mathbb{R}}^{n}} (n\ge 1)\) be a bounded domain with smooth boundary, \(\tau =0\), and let D, Φ, Ψ, and f satisfy (1.2)–(1.6). Then for nonnegative \({{u}_{0}}\in {{C}^{0}}(\bar{\Omega })\) and \({{v}_{0}} \in {{W}^{1,\sigma }}(\Omega ) (\sigma \ge n)\), there exist nonnegative functions \(u,v,w \in C^{0} (\bar{\Omega} \times [0,{T}_{\max}))\cap {{C}^{2,1}}( \bar{\Omega} \times (0,{T}_{\max})) \) with \({{T}_{\max }}\in (0,\infty ]\) that classically solve (1.1) in \(\Omega \times (0,T_{\max})\). Moreover, if \({{T}_{\max}}<\infty \), then
The proof is similar to that of Lemma 1.1 in [14].
Lemma 2
Let \(\Omega \subset {{\mathbb{R}}^{n}} (n\ge 1)\) be a bounded domain with smooth boundary, \(\tau =1\), let D, Φ, Ψ, and f satisfy (1.2)–(1.6), and let \({{u}_{0}}\in {{C}^{0}}(\bar{\Omega })\) and \({{v}_{0}},{{w}_{0}}\in {{W}^{1,\infty }}(\Omega )\) be nonnegative with \({{u}_{0}} \not \equiv 0\). Then there exist a maximal \({{T}_{\max }}\in (0,\infty ]\) and a uniquely determined triplet \((u,v,w)\) of nonnegative functions
that classically solve (1.1) in \(\Omega \times (0,{T}_{\max})\). Moreover, if \({{T}_{\max}}<\infty \), then
Some basic properties are derived as follows.
Lemma 3
[10] Let \((u,v,w)\) be a solution to (1.1) ensured by Lemma 1. Then for any \(l, \eta > 0\) and \(\theta > 1\), there is \(c_{0} = c_{0}(\eta ,\theta ,l) > 0\) such that
Moreover,
Next, we prove a variation of the maximal Sobolev regularity. The idea is inspired by [10, Lemma 4.1] and the work presented in [15].
Lemma 4
Let \(\sigma >1\). Consider the following equation:
for any \({{\varsigma }_{0}}\in {{W}^{2,\sigma }}(\Omega )\) (\(\sigma >n\)), \(\frac{\partial {{\varsigma }_{0}}}{\partial \nu }=0\) on ∂Ω, and all \(h\in {{L}^{\sigma }} ( (0,T);{{L}^{\sigma }}(\Omega ) )\). Then it has a unique solution
Moreover, if \({{t}_{0}}\in [0,T)\), \(\varsigma (\cdot ,{{t}_{0}})\in {{W}^{2,\sigma }} (\sigma >n) \textit{ with }\frac{\partial {{\varsigma }_{0}}}{\partial \nu }=0\), then there exists \({{C}_{\sigma }}>0\) such that
Proof
Let \(\bar{H }(x,t)={{e}^{\beta t}}\varsigma (x,t)\). We have
By the standard Sobolev regularity there exists \({{C}_{\sigma }}>0\) such that
and thus
For any \({{t}_{0}}>0\), replacing \(\varsigma (t)\) by \(\varsigma (t+{{t}_{0}})\), we get
□
Given \({{t}_{0}}\in (0,{{T}_{\max }})\) with \({{t}_{0}}\le 1\), from the regularity principle stated by Lemma 1, we know that \(u(\cdot ,{{t}_{0}}),v(\cdot ,{{t}_{0}}) \in {{C}^{2}}(\bar{\Omega })\) with \(\frac{\partial v(\cdot ,{{t}_{0}})}{\partial \nu }=0\) on ∂Ω. So we can pick \(\bar{M_{1}}>0\) such that
Similarly, by Lemma 2 we know that \(u(\cdot ,{{t}_{0}}),v(\cdot ,{{t}_{0}}),w(\cdot ,{{t}_{0}})\in {{C}^{2}}( \bar{\Omega })\) with \(\frac{\partial v(\cdot ,{{t}_{0}})}{\partial \nu }, \frac{\partial w(\cdot ,{{t}_{0}})}{\partial \nu }=0\) on ∂Ω. So we can pick \(\bar{M_{2}}>0\) such that
3 Proof of Theorem 1
In this section, we deal with the parabolic–parabolic–elliptic case (with \(\tau = 0\)) to prove Theorem 1. For simplicity, the variable of integration in an integral will be omitted without ambiguity; e.g., we write the integral \(\int _{\Omega }{f(x)\,dx}\) as \(\int _{\Omega }{f(x)}\). Hereafter, \({{c}_{i}}\), \(i=1,2,3, \dots \), denote generic constants, which may change from one line to another.
Proof of Theorem 1
We first prove that for any \(r>1\), there is \(c=c(r)>0\) such that
Without loss of generality, suppose \(r>\max \{2,1-q,1-g,1-p, 1-j \}\) and assume that \(\nabla u \cdot \nabla v > 0\) and \(\nabla u \cdot \nabla w > 0\). Taking \({{u}^{r-1}}\) as a test function for the first equation of (1.1), we have
and, combining it with the third equation of (1.1),
By Young’s inequality, for any \(\varepsilon > 0\), there exists \(c_{1} = c_{1}(r, \varepsilon )\) such that
and combining this with (2.1) and letting \(\eta =\frac{\varepsilon }{2{{c}_{1}}}\), we get
where \({{c}_{2}}={{c}_{2}}(r,\varepsilon )>0\). By Young’s inequality,
and thus
Case 1: \(q+k<\max \{g+l,d+1,\frac{2}{n}+p+1\}\).
Let \(q+k< d+1\). By Young’s inequality, for any \({{\eta }_{1}}>0\), there is \({{c}_{3}}={{c}_{3}}(r,{{\eta }_{1}})>0\) such that
where \(\sigma _{1} = \frac{r+d}{k}\). Taking \(\varepsilon =\frac{\gamma \xi (r-1)}{r+g-1}\) in (3.3), we get
where \({{c}_{4}}={{c}_{2}}+{{c}_{3}}>0\). By Young’s inequality,
where \({{c}_{5}}={{c}_{5}}(r)>0\). Thus there exists \({{c}_{6}}={{c}_{4}}+{{c}_{5}}>0\) such that
and applying the variation-of-constants formula, we have
where \({{c}_{7}}=\frac{1}{r}{{e}^{\beta {{\sigma }_{1}}{{t}_{0}}}}\int _{ \Omega }{{{u}^{r}}(\cdot ,{{t}_{0}})}+ \frac{{{c}_{6}}}{\beta {{\sigma }_{1}}}(1+{{e}^{\beta {{\sigma }_{1}}{{t}_{0}}}})\), which is independent of t. By (2.2) this yields that
and thus
which gives (3.1) by taking \({{\eta }_{1}}= \frac{b}{4({{c}_{{{\sigma }_{1}}}}{{\alpha }^{{{\sigma }_{1}}}})}\).
Let \(q+k< g+l\). By Young’s inequality, for any \({{\eta }_{2}}>0\), there is \({{c}_{8}}={{c}_{8}}(r,{{\eta }_{2}})>0\) such that
By (3.3) with \(\varepsilon =\frac{\gamma \xi (r-1)}{4(r+g-1)}\) we have
where \({{c}_{9}}={{c}_{2}}+{{c}_{8}}>0\) and \({{\sigma }_{2}}=\frac{r+g+l-1}{k}\). Since \(g+l>d+1>0\), there is \({{c}_{10}}={{c}_{10}}(r)>0\) such that
Similarly to (3.4), we have
where \({{c}_{12}}=\frac{1}{r}{{e}^{\beta {{\sigma }_{2}}{{t}_{0}}}}\int _{ \Omega }{{{u}^{r}}(\cdot ,{{t}_{0}})}+ \frac{{{c}_{11}}}{\beta {{\sigma }_{2}}}(1+{{e}^{\beta {{\sigma }_{2}}{{t}_{0}}}})\) independent of t, and \(c_{11} = c_{9} + c_{10} > 0\). Then (3.1) follows by taking \({{\eta }_{2}}= \frac{\gamma \xi (r-1)}{8(r+g-1){{c}_{{{\sigma }_{2}}}}{{\alpha }^{{{\sigma }_{2}}}}}\).
Let \(q+k<\frac{2}{n}+p+1\). Without loss of generality, we suppose \(q+k\ge \max \{g+l,d+1\}\). Take \({{(u+1)}^{r+1}}\) as a test function for the first equation in (1.1). Similarly, to obtain (3.2), we have
and then
By Young’s inequality we have
Similarly, replacing u in the second equation of (1.1) by \(u + 1\) to obtain (3.3), we have
Taking \(\varepsilon =\frac{\gamma \xi (r-1)}{r+g-1}\), we further have
By the Gagliardo–Nirenberg inequality there exist \({c}_{13}={c}_{13}(r)>0\) and \({c}_{14}={c}_{14}(r)>0\) such that
where \(z={ ( \frac{n(r+p)}{2}-\frac{n(r+p)}{2(r+q+k-1)} )} / { ( 1-\frac{n}{2}+\frac{n(r+p)}{2} )} \in (0,1)\).
Now let \(q+k<\frac{2}{n}+p+1\). Then \(\frac{2(r+q+k-1)}{r+p}z\le 2\). By Young’s inequality, for any \(\bar{\eta }>0\),
where \({{c}_{15}}={{c}_{15}}(r,\bar{\eta })>0\). Thus
where \(c_{16}=c_{2} +c_{15} > 0\) and \({{\sigma }_{3}}=\frac{r+q+k-1}{k}\). Applying the variation-of-constants formula and (2.2), we have
where \({{c}_{17}}=c_{17}(r,\bar{\eta})\). This gives (3.1) with η̄ small enough.
Case 2: \(q+k=\max \{g+l,d+1\}\) and \(q+k\ge \frac{2}{n}+p+1\).
(a) Let \(q+k=g+l=d+1\). By (3.3) we have
By Young’s inequality, for any \(\eta _{3}>0\), there exists \({{c}_{18}}={{c}_{18}}(r,{{\eta }_{3}})>0\) such that
and thus we get
where \(c_{19}=c_{2}+c_{18}\). By Young’s inequality,
where \(c_{20}=c_{20}(r)>0\). Then
where \(c_{21}=c_{19}+c_{20}\). Applying the variation-of-constants formula and (2.2), we have
where \({{c}_{22}}=c_{22}(r,\varepsilon )\). Let
Then we can choose ε and \(\eta _{3}\) small enough such that \(\frac{1}{4} ( b+\gamma \xi {{\theta }_{0}} )- \varepsilon -{{b}_{0}}>0\), provided that \(b+\gamma \xi {{\theta }_{0}}>4{{b}_{0}}\), and, consequently, (3.1) is true.
(b) Let \(q+k=g+l>d+1\). Then (3.3) becomes
Following the same arguments as those for getting (3.7), we can find \(c_{23}=c_{23}(r,\varepsilon )>0\) such that
Then we can choose ε and \(\eta _{3}\) small enough such that \(\frac{1}{4} \gamma \xi {{\theta }_{0}} -\varepsilon -{{b}_{0}}>0\), provided that \(\gamma \xi {{\theta }_{0}}>4{{b}_{0}}\), and thus (3.1) is true.
(c) Let \(q+k=d+1>g+l\). Taking \(\varepsilon =\tfrac{\gamma \xi (r-1)}{r+g-1}\), by (3.3) we have
Following the same arguments as those for getting (3.7), we can find \(c_{24}=c_{24}(r)>0\) such that
Then we can choose \(\eta _{3}\) small enough such that \(\frac{1}{4} b -{{b}_{0}}>0\), provided that \(b>4{{b}_{0}}\), and hence (3.1) is proved.
If \(\nabla u \cdot \nabla v < 0\) and \(\nabla u \cdot \nabla w > 0\), then similarly to (3.2), we derive
Combining THIS with the third equation of (1.1), we have
By Young’s inequality, for any \(\varepsilon > 0\), there exists \(c_{25} = c_{25}(r, \varepsilon )\) such that
Combining this with (2.1) and letting \(\eta =\frac{\varepsilon }{2{{c}_{25}}}\), we get
where \({{c}_{26}}={{c}_{26}}(r,\varepsilon )>0\). Thus
Taking \(\varepsilon =\frac{\gamma \xi (r-1)}{r+g-1}\), by (3.3) we derive (3.1).
If \(\nabla u \cdot \nabla v > 0\) and \(\nabla u \cdot \nabla w < 0\), then we have
Similarly to the case where \(\nabla u \cdot \nabla v > 0\) and \(\nabla u \cdot \nabla w > 0\), we derive (3.1).
If \(\nabla u \cdot \nabla v < 0\) and \(\nabla u \cdot \nabla w < 0\), then we have
Similarly to the case where \(\nabla u \cdot \nabla v < 0\) and \(\nabla u \cdot \nabla w > 0\), we derive (3.1).
We have proved claim (3.1) for all cases of Theorem 1.
Furthermore, by a standard Alikakos–Moser iteration [16] and (2.3) we get that
with some \(C>0\).
The boundedness of v can be obtained by the standard parabolic regularity theory.
By Lemma 1 we conclude \({T}_{\max } = \infty \). □
4 Proof of Theorem 2
In this section, we deal with the fully parabolic case (with \(\tau = 1\)) to prove Theorem 2.
Proof of Theorem 2
Just as in the proof of Theorem 1, we first claim that for any \(r>1\), there exists \(c=c(r)>0\) such that (3.1) holds for some cases. Without loss of generality, suppose \(r>\max \{2,1-q,1-g,1-p, 1-j \}\) and assume that \(\nabla u \cdot \nabla v > 0\) and \(\nabla u \cdot \nabla w > 0\).
Case 1: \(q+k,g+l<\max \{d+1,\frac{2}{n}+p+1\}\).
Let \(q+k< d+1\), \(g+l< d+1\). By (3.2) and Young’s inequality we have
Then, by Young’s inequality again, for any \({{\eta }_{4}}>0\) and \({{\eta }_{5}}>0\), we have
with \({{c}_{27}}={{c}_{27}}(r)>0\), \({{c}_{ 28}}={{c}_{28}}(r)>0\). Together with (3.2), this gives
where \({{\sigma }_{4}}=\frac{r+d}{k}\), \({{\sigma }_{5}}= \frac{r+d}{l}\), and \({{c}_{29}}={{c}_{27}}+{{c}_{ 28}}>0\). By Young’s inequality we have
with \({{c}_{30}}={{c}_{30}}(r)>0\). Thus
for \({{c}_{31}}={{c}_{29}}+{{c}_{ 30}}>0\). Applying the variation-of-constants formula, we have
where \({{c}_{32}}={{e}^{ ( \beta {{\sigma }_{4}}+ \delta {{\sigma }_{5}} ){{t}_{0}}}}\frac{1}{r}\int _{ \Omega }{{{u}^{r}}(\cdot ,{{t}_{0}})}+ \frac{{{c}_{31}}}{\beta {{\sigma }_{4}}+\delta {{\sigma }_{5}}}(1+{{e}^{ ( \beta {{\sigma }_{4}}+\delta {{\sigma }_{5}} ){{t}_{0}}}})\). Then by the maximal Sobolev regularity (Lemma 2) we get
This gives (3.1) by taking \({{\eta }_{4}}= \frac{b}{8({{c}_{{{\sigma }_{4}}}}{{\alpha }^{{{\sigma }_{4}}}})}\) and \({{\eta }_{5}}= \frac{b}{8({{c}_{{{\sigma }_{5}}}}{{\alpha }^{{{\sigma }_{5}}}})}\).
Now let \(q+k <\frac{2}{n}+p+1\text{ and }g+l<\frac{2}{n}+p+1\). Without loss of generality, suppose \(q+k\ge \max \{g+l,d+1\}\). By (3.5) and Young’s inequality we have
and thus, replacing u in the second and third equations of (1.1) by \(u+1\), we have
By (3.6) we have
where \({{\sigma }_{6}}=\frac{r+q+k-1}{k}\) and \({{\sigma }_{7}}=\frac{r+g+l-1}{l}\). Applying the variation-of-constants formula and (2.2), we have
with \({{c}_{33}}={{c}_{33}}(r,\bar{\eta })>0\). Letting η̄ small enough, we obtain (3.1).
Case 2: \(q+k=d+1\) and \(q+k,g+l\ge \frac{2}{n}+p+1\).
(a) Let \(q+k=d+1=g+l\). Similarly to (4.1), by Young’s inequality and (3.2) we have
and thus
where \({{\theta }_{1}}={{\theta }_{1}}(r,q)=\frac{r-1}{r+q-1}\) and \({{\theta }_{2}}={{\theta }_{2}}(r,g)=\frac{r-1}{r+g-1}\). By Young’s inequality we have
with \({{c}_{34}}={{c}_{34}}(r)>0\). We directly have
Applying the variation-of-constants formula, we get
where \({{c}_{35}}={{e}^{ ( \beta {{\sigma }_{7}}+ \delta {{\sigma }_{5}} ){{t}_{0}}}}\frac{1}{r}\int _{ \Omega }{{{u}^{r}}(\cdot ,{{t}_{0}})}+ \frac{{{c}_{34}}}{\beta {{\sigma }_{7}}+\delta {{\sigma }_{5}}}(1+{{e}^{ ( \beta {{\sigma }_{7}}+\delta {{\sigma }_{5}} ){{t}_{0}}}})\). According to (2.2), we obtain
where
Choosing b large enough such that \(\frac{1}{4} ( b-\chi {{\theta }_{1}}-\xi {{\theta }_{2}} )-\chi {{\theta }_{1}}{{C}_{{{\sigma }_{7}}}}{{\alpha }^{{{ \sigma }_{7}}}}>0\) and \(\frac{1}{4} ( b-\chi {{\theta }_{1}}-\xi {{\theta }_{2}} )-\xi {{\theta }_{2}}{{C}_{{{\sigma }_{5}}}}{{\gamma }^{{{ \sigma }_{5}}}}>0\), under the conditions \(\frac{b-\xi {{\theta }_{2}}}{\chi {{\theta }_{1}}}>1+{{b}_{1}}\) and \(\frac{b-\chi {{\theta }_{1}}}{\xi {{\theta }_{2}}}>1+{{b}_{2}}\), we can derive (3.1).
(b) Let \(q+k=d+1>g+l\). By Young’s inequality we have
By Young’s inequality and (3.2), for any \({{\eta }_{6}}>0\), we have
where \(c_{36} = c_{36}(r) > 0\). Thus
By Young’s inequality we have
where \({{c}_{37}}={{c}_{37}}(r)>0\). We have
where \(c_{38} = c_{36} + c_{ 37} > 0\). Applying the variation-of-constants formula, we get
where \({{c}_{39}}={{e}^{ ( \beta {{\sigma }_{7}}+ \delta {{\sigma }_{5}} ){{t}_{0}}}}\frac{1}{r}\int _{ \Omega }{{{u}^{r}}(\cdot ,{{t}_{0}})}+ \frac{{{c}_{38}}}{\beta {{\sigma }_{7}}+\delta {{\sigma }_{5}}}(1+{{e}^{ ( \beta {{\sigma }_{7}}+\delta {{\sigma }_{5}} ){{t}_{0}}}})\). Combining this with (2.2), we get
where
Choosing \({{\eta }_{6}}\) sufficiently small and b sufficiently large, we can ensure that \(\frac{b}{\chi {{\theta }_{1}}}>2+{{b}_{3}}\) and \(b>2\chi {{\theta }_{1}}\). This guarantees the derivation of (3.1).
We have established the \(L^{r}\)-boundedness (3.1) for certain cases. From this, employing a standard Alikakos–Moser iteration [16] and (2.4), we deduce
with some \(C>0\). The boundedness can be derived using the standard parabolic regularity theory. This, in conjunction with Lemma 2, establishes Theorem 2. □
Data availability
Data sharing not applicable to this paper as no data sets were generated or analyzed during the current study.
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Wang, R., Yan, L. Global boundedness in an attraction–repulsion Chemotaxis system with nonlinear productions and logistic source. J Inequal Appl 2024, 130 (2024). https://doi.org/10.1186/s13660-024-03195-1
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DOI: https://doi.org/10.1186/s13660-024-03195-1