
We prove the existence of regular optimal -invariant partitions, with an arbitrary number of components, for the Yamabe equation on a closed Riemannian manifold when is a compact group of isometries of with infinite orbits. To this aim, we study a weakly coupled competitive elliptic system of equations, related to the Yamabe equation. We show that this system has a least energy -invariant solution with nontrivial components and we show that the limit profiles of its components separate spatially as the competition parameter goes to , giving rise to an optimal partition. For the optimal partition obtained yields a least energy sign-changing -invariant solution to the Yamabe equation with precisely two nodal domains.
Citation: Mónica Clapp, Angela Pistoia. Yamabe systems and optimal partitions on manifolds with symmetries[J]. Electronic Research Archive, 2021, 29(6): 4327-4338. doi: 10.3934/era.2021088
[1] | Shiqiang Feng, Dapeng Gao . Existence of traveling wave solutions for a delayed nonlocal dispersal SIR epidemic model with the critical wave speed. Mathematical Biosciences and Engineering, 2021, 18(6): 9357-9380. doi: 10.3934/mbe.2021460 |
[2] | Rongjian Lv, Hua Li, Qiubai Sun, Bowen Li . Model of strategy control for delayed panic spread in emergencies. Mathematical Biosciences and Engineering, 2024, 21(1): 75-95. doi: 10.3934/mbe.2024004 |
[3] | Lin Zhao, Haifeng Huo . Spatial propagation for a reaction-diffusion SI epidemic model with vertical transmission. Mathematical Biosciences and Engineering, 2021, 18(5): 6012-6033. doi: 10.3934/mbe.2021301 |
[4] | Cheng-Cheng Zhu, Jiang Zhu . Spread trend of COVID-19 epidemic outbreak in China: using exponential attractor method in a spatial heterogeneous SEIQR model. Mathematical Biosciences and Engineering, 2020, 17(4): 3062-3087. doi: 10.3934/mbe.2020174 |
[5] | Jummy F. David, Sarafa A. Iyaniwura, Michael J. Ward, Fred Brauer . A novel approach to modelling the spatial spread of airborne diseases: an epidemic model with indirect transmission. Mathematical Biosciences and Engineering, 2020, 17(4): 3294-3328. doi: 10.3934/mbe.2020188 |
[6] | Yoichi Enatsu, Yukihiko Nakata . Stability and bifurcation analysis of epidemic models with saturated incidence rates: An application to a nonmonotone incidence rate. Mathematical Biosciences and Engineering, 2014, 11(4): 785-805. doi: 10.3934/mbe.2014.11.785 |
[7] | Hans F. Weinberger, Xiao-Qiang Zhao . An extension of the formula for spreading speeds. Mathematical Biosciences and Engineering, 2010, 7(1): 187-194. doi: 10.3934/mbe.2010.7.187 |
[8] | Wenhao Chen, Guo Lin, Shuxia Pan . Propagation dynamics in an SIRS model with general incidence functions. Mathematical Biosciences and Engineering, 2023, 20(4): 6751-6775. doi: 10.3934/mbe.2023291 |
[9] | Meng Zhao, Wan-Tong Li, Yang Zhang . Dynamics of an epidemic model with advection and free boundaries. Mathematical Biosciences and Engineering, 2019, 16(5): 5991-6014. doi: 10.3934/mbe.2019300 |
[10] | Xue Zhang, Shuni Song, Jianhong Wu . Onset and termination of oscillation of disease spread through contaminated environment. Mathematical Biosciences and Engineering, 2017, 14(5&6): 1515-1533. doi: 10.3934/mbe.2017079 |
We prove the existence of regular optimal -invariant partitions, with an arbitrary number of components, for the Yamabe equation on a closed Riemannian manifold when is a compact group of isometries of with infinite orbits. To this aim, we study a weakly coupled competitive elliptic system of equations, related to the Yamabe equation. We show that this system has a least energy -invariant solution with nontrivial components and we show that the limit profiles of its components separate spatially as the competition parameter goes to , giving rise to an optimal partition. For the optimal partition obtained yields a least energy sign-changing -invariant solution to the Yamabe equation with precisely two nodal domains.
The spreading of communicable diseases is affected by many factors including infectious agents, modes of contact, and latent periods. Since different diseases may have distinctive features of infection, it is necessary to model the evolutionary of various diseases by different mathematical models. Following the pioneer work of Kermack and McKendrick [1], the total population is often classified into the susceptible (S), the infective (I), and the recovered (R), and the corresponding models are called SIR models. The contact pattern between the susceptible and the infective is often described by the incidence function. Nonlinear incidence functions have been utilized in many epidemic systems including the following SIR model [2]
(1.1) |
in which all the parameters are positive and describe the contact pattern, represents the constant death ratio and death rate and the constant recruitment rate. Here, the nonlinear incidence is partly due to the effect of media, government behavior. For some typical examples of and their biological backgrounds, we may refer to [2]. Clearly, some properties of this system can be obtained by only investigating
In epidemic models, time delay may reflect that a susceptible individual was attacked by the pathogen (by contacting an infective) at an earlier time but becomes infective after several days, which may be reflected by delayed effect of the infective. Since an ostensible susceptible may be infected one that may transmit the pathogen to other true susceptible, the delayed effect must be involved in some cases. When the delayed effect on latent periods is concerned in (1.1), Huang et al. [3] studied the following model
in which all the parameters are positive, reflects the latent period. By comparing [2,3], time delay may be harmless to the stability of the system but decrease the basic reproduction ratio, which indicates the nontrivial role of time delay. Moreover, the latent periods may be different, and distributed delays may be useful, see a model of hematopoiesis by Adimy et al. [4]. In particular, by assuming that each individual of the susceptible class has the same probability being infected, is in proportion to in many models in the above works.
Over a period of time there has been a growing awareness of the importance that includes a spatial aspect in constructing realistic models of biological systems, with a consequent development of both approximate and mathematically rigorous methods of analysis [5]. It is important to characterize the speed of spatial expansion of diseases [6,7,8], and the expansion speed may be a constant [9,Chapter 13]. In literature, many reaction-diffusion systems have been established to reflect the process [5]. Due to the deficiency of monotone semiflows in many epidemic models, the long time behavior of the initial value problems of epidemic models can not be studied by the theory of monotone semiflows [10], we may refer to Ducrot [11,12].
When both the spatial factor and delayed effect are involved in mathematical epidemiology, one important factor is the effect of nonlocal delays [13,14]. Here the nonlocal delay may reflect the history movement ability of the infective, which includes the cases of discrete delays and distributed delays [15,16]. De Mottoni et al. [17] studied the following model with spatial nonlocality
in which all the parameters are positive, is the spatial domain, is a nonnegative function. For more epidemic models with nonlocal delays, we refer to Ruan [16]. The purpose of this paper is to study diffusive epidemic models with nonlocal delays, nonlinear incidence rate and constant recruitment rate, during which the effect of time delay and spatial nonlocality will be also presented.
For simplicity, we firstly consider the initial value problem after scaling
(1.2) |
with
where In model (1.2), , denote the densities of susceptible and infective individuals at time and location , respectively, is a constant describing the spatial diffusive motility of the susceptible, represents the entering flux as well as the death rate of the individuals, is the death rates of infective, reflects the infection rate, is the recovery rate of the infective individuals, and the positive constant measures the saturation level, is a continuous bounded function. The nonlocal delayed term describes the interaction between the infected individuals at an earlier time at location and susceptible individuals at location at time which implies that only the susceptible individuals at location at the present time affect the change rate of the susceptible class although the contact leading to infection maybe occurred at location at an earlier time
Clearly, model (1.2) is a subsystem of the following SIR model
where denotes the removed individuals, are constants on spatial diffusion ratio and death rate of the removed, respectively. Clearly, after investigating (1.2), some properties of the class can be obtained (see. e.g., Li et al. [18,Section 5]) since
for any and we only study system (1.2) in this paper. These systems may model the evolutionary of the epidemic with nonlinear incidence rate and constant recruitment rate. For the dynamics in the corresponding functional differential equations with discrete or distribute delay, we may refer to Enatsu et al. [19], Huang et al. [3], in which the persistence and the extinction of were studied. In particular, by [3], we may find that the so-called basic reproduction ratio is
Recently, traveling wave solutions of different versions for (1.2) have been studied [18,20,21], in which these solutions take the form
for some and satisfy
By letting , such a solution indicates that at any fixed location , there was no infective long time ago ( iff ) while the infective and susceptible will coexist eventually ( iff ). However, from the viewpoint of initial value problems, these traveling wave solutions formulate that the infective individuals live in a habitat of infinite size at any fixed time. This contradicts to the outbreak of many diseases, during which the initial habitat of the infective individuals is finite, see a similar process in biological invasion by [22,23,24]. Motivated by this, we will study the corresponding initial value problem of (1.2) by the following index [25].
Definition 1.1. Assume that is a nonnegative function for . Then is called the spreading speed of if
a) for any given ;
b) for any given .
The spreading speeds of unknown functions governed by reaction-diffusion equations and other parabolic type systems have been widely studied since [25], and there are some important results for monotone semiflows [10,26,27,28,29] and nonmonotone scalar equations [30,31,32]. For noncooperative systems, Ducrot [11] estimated the asymptotic spreading in a predator-prey system of Holling-Tanner type, Ducrot [12] considered the spatial propagation of an epidemic model with recruitment rate and bilinear incidence rate, Lin et al. [33,34] studied the spreading speeds of two competitive invaders in competitive systems, Lin and Wang [35] and Pan [36] investigated the invasion speed of predators in a predator-prey system of Lotka-Volterra type. For coupled systems in [11,12,33,34,35,36], the comparison principle plays the crucial role.
In this paper, to focus on our main idea, we first study (1.2) by estimating the limit behavior of motivated by [35,36]. With the uniform boundedness of , we try to estimate by which we may obtain an auxiliary equation on . However, this equation involves the nonlocal delay [14,15,16,37] and does not generate monotone semiflows. Further by the smoothness of we obtain an auxiliary equation with quasimonotonicity, of which the spreading speed has been established. Then we obtain the spreading speed of Here, the spreading speed is coincident with the minimal wave speed of traveling wave solutions in some well studied cases. For example, when it just involves discrete delays, the spreading speed in this paper equals the minimal wave speed of traveling wave solutions in Li et al. [18].
Subsequently, we study the general model
(1.3) |
where is Lipscitz continuous. We also obtain the spreading speed of even if is not monotone, and the convergence of is established from the viewpoint of asymptotic spreading. Furthermore, to show the effect of time delay and spatial nonlocality and estimate the spreading speeds, we present some numerical examples.
The rest of this paper is organized as follows. In Section 2, we show some necessary preliminaries on reaction-diffusion systems with nonlocal delays. Section 3 is concerned with the spreading speed of in (1.2). We then consider the spreading speed in the general model (1.3) in Section 4, and show the convergence result of . To further illustrate our analysis results, we present some numerical results in Section 5. Finally, we provide a discussion on the epidemic backgrounds and mathematical conclusions.
In this section, we introduce some concepts and review some relevant results. Firstly, when a partial order in is concerned, it is the standard partial order in That is, if
then iff For the kernel function that is integrable, we make the following assumptions.
(J1)
(J2) for each fixed there exists such that
For we make the following assumptions.
(f) There exists such that is . and there exist positive constants such that
Besides by taking
as in (1.2), there are also many other functions satisfying (f), e.g., the following function
where By taking different parameters, it may be nonmonotone, the corresponding kinetic model was proposed and analyzed by Liu et al. [38], Xiao and Ruan [39]. By the above assumptions, we define
for each fixed with From (J1)-(J2) and (f), satisfies the following property.
Lemma 2.1. There exists a constant such that
(R1) has no real roots if
(R2) if then has positive real roots.
Evidently, we see that time delay and spatial nonlocality may affect the threshold a similar conclusion was reported by Li et al. [40] (we may refer to a recent paper by Li and Pan [41] and references cited therein for the traveling wave solutions of delayed models). To further quantificationally illustrate the role, we first consider the case of discrete delay such that
and
in which Let be the threshold depending on then we have
and
That is, the time delay may decrease the threshold, we also refer to Zou [42]. On the other hand, to quantificationally show the effect of spatial nonlocality, we consider a simple nonlocal case with
and so
Let be the threshold depending on then
and
For this type of kernels, we say the nonlocality is stronger if is larger, so the spatial nonlocality may increase the threshold, which will be further illustrated by numerical simulations.
Let
for any bounded and continuous function Then by the theory of abstract functional differential equations with application to delayed reaction-diffusion systems [43,44,45,46], we have the following existence and uniqueness of mild solutions.
Lemma 2.2. (1.3) admits a mild solution such that
and takes the form
for and any given If then are uniformly continuous in In particular, if admits nonempty compact support in (1.2), then
Moreover, if such that
then implies that is the classical solution of (1.3) in the sense of partial derivatives.
The local existence of mild solutions is ensured by the theory of analytic semigroups as well as abstract functional differential equations [43,47], and the global existence is guaranteed due to the existence of positive invariant regions because of the existence of .
In addition, the proof depends on the comparison principle and asymptotic spreading of the following equation with nonlocal delays
(2.1) |
where all the other parameters are the same as those in (f) and is a positive continuous function satisfying
for some By results in Martin and Smith [47], Ruan and Wu [43], (2.1) satisfies the following comparison principle.
Lemma 2.3. Let hold and be nondecreasing. Assume that a continuous function satisfies
and
for and any given Then
Furthermore, results by Liang and Zhao [10], Yi et al. [48] imply the following spreading property even if is not monotone for all .
Lemma 2.4. Let be the unique mild solution of (2.1) with for some . Then for any given satisfies and for any given satisfies
In this section, we establish the main results of (1.2). In particular, we take in this section, admits nonempty compact support and
(3.1) |
with some The following is the main result of this section.
Theorem 3.1. Assume that is defined by (1.2). Then for any given satisfies
(3.2) |
and for any given satisfies
(3.3) |
Proof. By Lemma 2.2, we have
which implies that
(3.4) |
for all Further by Lemmas 2.3 and 2.4, we obtain (3.2).
We now prove (3.3) for any fixed . Since it involves long time behavior, we assume that is large and is uniformly continuous in . Define then Lemma 2.2 indicates that
Therefore, if is smooth enough, then it satisfies
and similarly, we can verify that
where
for any bounded and continuous function
Returning to the equation of we have
with
In what follows, we prove the following claim.
(C) For any there exists such that
(3.5) |
if is large.
From Lemmas 2.3 and 2.4, (C) implies that
by selecting and fixing small enough, which implies what we wanted.
Subsequently, we verify (3.5) for any fixed . If
then (3.5) is true. Otherwise, let and be large enough such that
(3.6) |
Firstly, we fix such that
For such a fixed we further select such that
which is admissible since
Further choose sufficiently small such that
So we obtain
for any and (3.6) implies
(3.7) |
The left side of (3.7) is
for any By the convergence in (J1) and (J2), if (independent on ) are large enough, then
(3.8) |
and we now fix constants
Note that are uniformly continuous and uniformly bounded for then (3.8) implies that we can choose constants
such that
here depends on and is independent of Again by the uniform continuity of and convergence of we fix depending on such that
for some
and the uniform continuity further implies that
From the equation of we see that
for any By the property of semigroup, we also have
for any So for any given if
then we have
By what we have done, satisfying (3.6) lead to
where is uniform for any such that (3.6) holds. Again by the uniform boundedness of and
we obtain the existence of which is also independent on once (3.7) is true and The proof is complete.
Remark 3.2. From (3.4) and Lemma 2.4, we see that
implies
That is, the sign of determines the persistence and extinction of which is similar to the case in the corresponding functional differential systems. Therefore, the basic reproduction ratio of the corresponding functional differential systems may determine the failure or propagation of the disease, and also may affect the spreading speed if the ratio is larger than 1.
In this section, we first study the spreading speed and then estimate the convergence of in (1.3), in which satisfies (f). The first result on spreading speed is formulated as follows.
Theorem 4.1. is the spreading speed of if satisfies (3.1).
Proof. Due to the proof of Theorem 3.1, we just give a sketch. Firstly, we define
then there exists such that
and is nondecreasing such that
Therefore, satisfies
for any So for any given satisfies
Further define
then there exists such that
and
So satisfies
for any Similar to that in Section 3, we obtain
for any given The proof is complete.
Theorems 3.1 and 4.1 imply that the infective individuals successfully invade the habitat of the susceptible. We now estimate the limit behavior of Firstly, we consider (1.3) when satisfies
(4.1) |
and make the following assumption.
(C) Assume that (4.1) holds. Then
where is the unique positive spatially homogeneous steady state of (1.3).
Remark 4.2. In some cases, (C) is true. For example, if is monotone such that and (1.3) with (4.1) is persistent, further define
then the persistence implies that
By dominated convergence theorem, we have
If these inequalities imply , then (C) is true by applying the dominated convergence theorem in the corresponding integral equations [18].
Now, we formulate the limit behavior of defined by (1.3) if satisfies (3.1).
Theorem 4.3. Assume that there exist such that
and if then
for any If (C) holds, then
which holds for any given
Proof. We prove that for any given there exists such that
(4.2) |
by the idea in [49]. Firstly, by Theorem 4.1, there exist such that
Then (4.2) is true if we can prove that for any large enough, there exists independent on such that
(4.3) |
since
when is large enough.
Let be the solution of (1.3) with initial value satisfying
Then (C) implies that there exists such that
Let
then the boundedness indicates that there exists satisfying
for any Then satisfy
where is defined by
with
Let be a fixed constant (clarified later) such that
and
Let be large and be small such that
of which the admissibility is clear by the existence of Define a continuous function
for which implies that
Then we have
for any and so
Then we fix such that
and for any such that
we have (4.3), so for (4.2). The proof is complete.
In this section, we shall illustrate the analytic conclusion by some numerical examples. Due to Theorem 3.1, we simulate the dynamics in a large spatial interval and take the following boundary conditions
Moreover, is defined by
Firstly, we consider (1.2) without nonlocal delay and taking
(5.1) |
With these parameters, we see that
and We now show the numerical results as follows.
From Figures 1 and 2, we see that almost invades and almost decreases at a constant speed. To further show the invasion speed of , we present the following Figure 3 on the distribution at by which we see that the invasion speed is close to
We now consider the effect of time delay in the following model
(5.2) |
such that
When we show the graphs of by the following Figures 4 and 5, from which we see that is close to 1.
The evolution of with is presented by Figures 6 and 7.
To estimate the invasion speed with different , we give the distribution of by Figures 8 and 9, by which we see the role of time delay.
To show the effect of nonlocality, we consider
(5.3) |
and
We first show the graph of as follows when by Figures 10 and 11.
Comparing Figures 4 and 5 with Figures 10-11, we see that the nonlocality increases the invasion speed. We we see that is close to from the following Figure 12.
Although is close to due to the role of spatial nonlocality. The evolution of with is presented as follows.
To further show the effect of spatial nonlocality, we also simulate by by the following Figures 15 and 16.
Clearly, although in Figures 6 and 7, the spreading speed is close to that in Figures 6 and 7, which indicates the role of spatial nonlocality.
To show the role of spatial nonlocality, we fix and take and compare the distribution. From the following Figures 17 and 18, we see that the stronger nonlocality implies larger spreading threshold.
Finally, different from that in the monotone model (5.1), we consider the following system without comparison principle
(5.4) |
Clearly, the spreading speed of (5.4) is the same as that in (5.1), and the following figures imply the spreading speed of is close to 2.
The spatial spreading of epidemic models attracts much attention since it greatly affects the human behavior in modern days. In population dynamics, there are many works on the study of spatial dynamics of epidemic models. Since the interesting works of [7,8], the threshold of spatial spreading of epidemic models has been widely studied. Thus the analysis of parameters dependence of propagation threshold may show the factors on disease spreading and control. In this paper, we have shown the effect of time delay and spatial nonlocality by theoretical analysis and numerical simulations. But it is difficult to change the latent periods in many cases. Due to our analysis, the spatial movement of the infective in history may increase the spreading speed of the disease, and it is reasonable to restrain the spatial movement of potential infective individuals to control some diseases. The recipe has been utilized in controlling many disease including SARS.
As we have mentioned in Section 1, the traveling wave solutions can not well illustrate the outbreak of some diseases, of which the initial prevalent district is small. To model the feature, asymptotic spreading is a suitable index. Comparing with the traveling wave solutions, there are a few results on the asymptotic spreading of nonmonotone epidemic models. In this paper, we obtained the spreading speed in a class of epidemic models. In fact, the methodology in this work can be extended to more general systems. For example,
in which is admissible and kernel functions may be different, may be a function including Under proper assumptions, we could estimate the spreading speed of
The spreading speed in this paper equals the minimal wave speed of traveling wave solutions in some known results. For some models similar to (2.1), it has been proven that the traveling wave solutions with minimal wave speed is stable in the sense of weighted functional spaces, see [51,52] and references cited therein. Therefore, it is possible to understand the dynamics of the corresponding initial value problems by traveling wave solutions. In this paper, we show a rough speed on the branch Very likely, the shape of spreading of governed by (1.2) can be approximated by the shape of traveling wave solutions with minimal wave speed in proper weighted functional spaces.
We are grateful to three referees and Professor Shigui Ruan for their valuable comments. Lin was supported by NSF of China (11731005) and Fundamental Research Funds for the Central Universities (lzujbky-2018-113), Yan was supported by NSF of China (61763024) and Foundation of a Hundred Youth Talents Training Program of Lanzhou Jiaotong University (152022).
The authors declare no conflict of interest in this paper.
[1] |
The second Yamabe invariant. J. Funct. Anal. (2006) 235: 377-412. ![]() |
[2] | Problémes isopérimétriques et espaces de Sobolev. J. Differ. Geom. (1976) 11: 573-598. |
[3] |
Bifurcation in a multicomponent system of nonlinear Schrödinger equations. J. Fixed Point Theory Appl. (2013) 13: 37-50. ![]() |
[4] |
A sign-changing solution for a superlinear Dirichlet problem. Rocky Mountain J. Math. (1997) 27: 1041-1053. ![]() |
[5] |
Segregated nodal domains of two-dimensional multispecies Bose-Einstein condensates. Phys. D (2004) 196: 341-361. ![]() |
[6] |
Positive least energy solutions and phase separation for coupled Schrödinger equations with critical exponent: Higher dimensional case. Calc. Var. Partial Differential Equations (2015) 52: 423-467. ![]() |
[7] |
M. Clapp and J. C. Fernández, Multiplicity of nodal solutions to the Yamabe problem, Calc. Var. Partial Differential Equations, 56 (2017), 22pp. doi: 10.1007/s00526-017-1237-2
![]() |
[8] |
M. Clapp and A. Pistoia, Existence and phase separation of entire solutions to a pure critical competitive elliptic system, Calc. Var. Partial Differential Equations, 57 (2018), 20pp. doi: 10.1007/s00526-017-1283-9
![]() |
[9] | M. Clapp and A. Pistoia, Fully nontrivial solutions to elliptic systems with mixed couplings, arXiv: 2106.01637, (2021). |
[10] | M. Clapp, A. Pistoia and H. Tavares, Yamabe systems, optimal partitions and nodal solutions to the Yamabe equation, Preprint, arXiv: 2106.00579, 2021. |
[11] |
Phase separation, optimal partitions and nodal solutions to the Yamabe equation on the sphere. Int. Math. Res. Not. (2021) 2021: 3633-3652. ![]() |
[12] |
M. Clapp and A. Szulkin, A simple variational approach to weakly coupled competitive elliptic systems, Nonlinear Differential Equations Appl., 26 (2019), 21pp. doi: 10.1007/s00030-019-0572-8
![]() |
[13] |
Nehari's problem and competing species systems. Ann. Inst. H. Poincaré Anal. Non Linéaire (2002) 19: 871-888. ![]() |
[14] |
A variational problem for the spatial segregation of reaction-diffusion systems. Indiana Univ. Math. J. (2005) 54: 779-815. ![]() |
[15] |
Large energy entire solutions for the Yamabe equation. J. Differential Equations (2011) 251: 2568-2597. ![]() |
[16] | Torus action on Sn and sign-changing solutions for conformally invariant equations. Ann. Sc. Norm. Super. Pisa Cl. Sci. (2013) 12: 209-237. |
[17] |
On a conformally invariant elliptic equation on . Comm. Math. Phys. (1986) 107: 331-335. ![]() |
[18] |
Stability for strongly coupled critical elliptic systems in a fully inhomogeneous medium. Anal. PDE (2009) 2: 305-359. ![]() |
[19] |
Low energy nodal solutions to the Yamabe equation. J. Differential Equations (2020) 268: 6576-6597. ![]() |
[20] |
A non-variational system involving the critical Sobolev exponent. The radial case. J. Anal. Math. (2019) 138: 643-671. ![]() |
[21] |
Entire nonradial solutions for non-cooperative coupled elliptic system with critical exponents in . J. Differential Equations (2014) 256: 3463-3495. ![]() |
[22] |
Liouville type theorems for positive solutions of elliptic system in . Comm. Partial Differential Equations (2008) 33: 263-284. ![]() |
[23] | E. Hebey, Introduction à l'analyse non linéaire sur les variétés, Diderot, Paris, 1997. |
[24] |
Sobolev spaces in the presence of symmetries. J. Math. Pures Appl. (1997) 76: 859-881. ![]() |
[25] | The conjectures on conformal transformations of Riemannian manifolds. J. Differential Geometry (1971/72) 6: 247-258. |
[26] |
The principle of symmetric criticality. Comm. Math. Phys. (1979) 69: 19-30. ![]() |
[27] |
M. Struwe, Variational Methods. Applications to Nonlinear Partial Differential Equations and Hamiltonian Systems, 2 edition, Ergebnisse der Mathematik und ihrer Grenzgebiete, 34. Springer-Verlag, Berlin, 1996. doi: 10.1007/978-3-662-03212-1
![]() |
[28] |
Hölder bounds and regularity of emerging free boundaries for strongly competing Schrödinger equations with nontrivial grouping. Nonlinear Anal. (2016) 138: 388-427. ![]() |
[29] |
Best constant in Sobolev inequality. Ann. Mat. Pura Appl. (1976) 110: 353-372. ![]() |
[30] |
M. Willem, Minimax Theorems, Progress in Nonlinear Differential Equations and their Applications, 24. Birkhäuser Boston, Inc., Boston, MA, 1996. doi: 10.1007/978-1-4612-4146-1
![]() |
1. | Piotr Skórka, Beata Grzywacz, Dawid Moroń, Magdalena Lenda, Abdallah M. Samy, The macroecology of the COVID-19 pandemic in the Anthropocene, 2020, 15, 1932-6203, e0236856, 10.1371/journal.pone.0236856 | |
2. | Fuzhen Wu, Dongfeng Li, Minimal wave speed of a diffusive SIR epidemic model with nonlocal delay, 2019, 12, 1793-5245, 1950081, 10.1142/S1793524519500815 | |
3. | Guo Lin, Yibin Niu, Shuxia Pan, Shigui Ruan, Spreading Speed in an Integrodifference Predator–Prey System without Comparison Principle, 2020, 82, 0092-8240, 10.1007/s11538-020-00725-y | |
4. | Xinjian Wang, Guo Lin, Shigui Ruan, Spreading speeds and traveling wave solutions of diffusive vector-borne disease models without monotonicity, 2023, 153, 0308-2105, 137, 10.1017/prm.2021.76 | |
5. | Shuxia Pan, Asymptotic spreading in a delayed dispersal predator-prey system without comparison principle, 2019, 27, 2688-1594, 89, 10.3934/era.2019011 | |
6. | Shuo Zhang, Guo Lin, Propagation dynamics in a diffusive SIQR model for childhood diseases, 2022, 27, 1531-3492, 3241, 10.3934/dcdsb.2021183 | |
7. | Xinjian Wang, Guo Lin, Spreading speeds in two reaction–diffusion models for Polio disease, 2023, 118, 10075704, 107009, 10.1016/j.cnsns.2022.107009 | |
8. | Guo Lin, Shuxia Pan, Xueying Wang, Spreading Speed of a Cholera Epidemic Model in a Periodic Environment, 2023, 22, 1575-5460, 10.1007/s12346-023-00753-8 | |
9. | Xinjian Wang, Guo Lin, Shigui Ruan, Spatial propagation in a within‐host viral infection model, 2022, 149, 0022-2526, 43, 10.1111/sapm.12490 | |
10. | Shuo Zhang, Zhaosheng Feng, Guo Lin, Asymptotic Spreading for a Diffusive Chemostat System in Space-Time Periodic Environment, 2022, 1040-7294, 10.1007/s10884-022-10216-4 | |
11. | Yahui Wang, Xinjian Wang, Guo Lin, Propagation thresholds in a diffusive epidemic model with latency and vaccination, 2023, 74, 0044-2275, 10.1007/s00033-022-01935-1 | |
12. | Liang Zhang, Spatial propagation phenomena for a diffusive epidemic model with vaccination, 2023, 74, 0044-2275, 10.1007/s00033-023-02098-3 | |
13. | Shuang‐Ming Wang, Liang Zhang, Spatiotemporal propagation of a time‐periodic reaction–diffusion SI epidemic model with treatment, 2024, 152, 0022-2526, 342, 10.1111/sapm.12646 | |
14. | Guo Lin, Xinjian Wang, Xiao-Qiang Zhao, Propagation phenomena of a vector-host disease model, 2024, 378, 00220396, 757, 10.1016/j.jde.2023.10.016 | |
15. | Guo Lin, Propagation dynamics in epidemic models with two latent classes, 2024, 01672789, 134509, 10.1016/j.physd.2024.134509 | |
16. | Wanxia Shi, Spreading speeds for a reaction-diffusion HIV/AIDS epidemic model with education campaigns, 2024, 0, 1531-3492, 0, 10.3934/dcdsb.2024158 | |
17. | Haiqin Zhao, Da An, Spreading speed for a diffusive foot-and-mouth disease model, 2025, 2025, 2731-4235, 10.1186/s13662-025-03930-y | |
18. | Liang Zhang, Zhi-Cheng Wang, Spatial propagation phenomena for diffusive SIS epidemic models, 2025, 423, 00220396, 240, 10.1016/j.jde.2024.12.039 |