Research article

Word-level dual channel with multi-head semantic attention interaction for community question answering

  • The semantic matching problem detects whether the candidate text is related to a specific input text. Basic text matching adopts the method of statistical vocabulary information without considering semantic relevance. Methods based on Convolutional neural networks (CNN) and Recurrent networks (RNN) provide a more optimized structure that can merge the information in the entire sentence into a single sentence-level representation. However, these representations are often not suitable for sentence interactive learning. We design a multi-dimensional semantic interactive learning model based on the mechanism of multiple written heads in the transformer architecture, which not only considers the correlation and position information between different word levels but also further maps the representation of the sentence to the interactive three-dimensional space, so as to solve the problem and the answer can select the best word-level matching pair, respectively. Experimentally, the algorithm in this paper was tested on Yahoo! and StackEx open-domain datasets. The results show that the performance of the method proposed in this paper is superior to the previous CNN/RNN and BERT-based methods.

    Citation: Jinmeng Wu, HanYu Hong, YaoZong Zhang, YanBin Hao, Lei Ma, Lei Wang. Word-level dual channel with multi-head semantic attention interaction for community question answering[J]. Electronic Research Archive, 2023, 31(10): 6012-6026. doi: 10.3934/era.2023306

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  • The semantic matching problem detects whether the candidate text is related to a specific input text. Basic text matching adopts the method of statistical vocabulary information without considering semantic relevance. Methods based on Convolutional neural networks (CNN) and Recurrent networks (RNN) provide a more optimized structure that can merge the information in the entire sentence into a single sentence-level representation. However, these representations are often not suitable for sentence interactive learning. We design a multi-dimensional semantic interactive learning model based on the mechanism of multiple written heads in the transformer architecture, which not only considers the correlation and position information between different word levels but also further maps the representation of the sentence to the interactive three-dimensional space, so as to solve the problem and the answer can select the best word-level matching pair, respectively. Experimentally, the algorithm in this paper was tested on Yahoo! and StackEx open-domain datasets. The results show that the performance of the method proposed in this paper is superior to the previous CNN/RNN and BERT-based methods.



    In this article, we study the following anisotropic singular p()-Laplace equation

    {Ni=1xi(|xiu|pi(x)2xiu)=f(x)uβ(x)+g(x)uq(x) in Ω,u>0 in Ω,u=0 on Ω, (1.1)

    where Ω is a bounded domain in RN (N3) with smooth boundary Ω; fL1(Ω) is a positive function; gL(Ω) is a nonnegative function; βC(¯Ω) such that 1<β(x)< for any x¯Ω; qC(¯Ω) such that 0<q(x)<1 for any x¯Ω; piC(¯Ω) such that 2pi(x)<N for any x¯Ω, i{1,...,N}.

    The differential operator

    Ni=1xi(|xiu|pi(x)2xiu),

    that appears in problem (1.1) is an anisotropic variable exponent p()-Laplace operator, which represents an extension of the p()-Laplace operator

    Ni=1xi(|xiu|p(x)2xiu),

    obtained in the case for each i{1,...,N}, pi()=p().

    In the variable exponent case, p(), the integrability condition changes with each point in the domain. This makes variable exponent Sobolev spaces very useful in modeling materials with spatially varying properties and in studying partial differential equations with non-standard growth conditions [1,2,3,4,5,6,7,8].

    Anisotropy, on the other hand, adds another layer of complexity, providing a robust mathematical framework for modeling and solving problems that involve complex materials and phenomena exhibiting non-uniform and direction-dependent properties. This is represented mathematically by having different exponents for different partial derivatives. We refer to the papers [9,10,11,12,13,14,15,16,17,18,19,20,21] and references for further reading.

    The progress in researching anisotropic singular problems with p()-growth, however, has been relatively slow. There are only a limited number of studies available on this topic in academic literature. We could only refer to the papers [22,23,24] that were published recently. In [22], the author studied an anisotropic singular problems with constant case p()=p but with a variable singularity, where existence and regularity of positive solutions was obtained via the approximation methods. In [23], the author obtained the existence and regularity results of positive solutions by using the regularity theory and approximation methods. In [24], the authors showed the existence of positive solutions using the regularity theory and maximum principle. However, none of these papers studied combined effects of variable singular and sublinear nonlinearities.

    We would also like to mention that the singular problems of the type

    {Δu=f(x)uβ in Ω,u>0 in Ω,u=0 on Ω, (1.2)

    have been intensively studied because of their wide applications to physical models in the study of non-Newtonian fluids, boundary layer phenomena for viscous fluids, chemical heterogenous catalysts, glacial advance, etc. (see, e.g., [25,26,27,28,29,30]).

    These studies, however, have mainly focused on the case 0<β<1, i.e., the weak singularity (see, e.g. [31,32,33,34,35,36]), and in this case, the corresponding energy functional is continuous.

    When β>1 (the strong singularity), on the other hand, the situation changes dramatically, and numerous challenges emerge in the analysis of differential equations of the type (1.2), where the primary challenge encountered is due to the lack of integrability of uβ for uH10(Ω) [37,38,39,40,41].

    To overcome these challenges, as an alternative approach, the so-called "compatibility relation" between f(x) and β has been introduced in the recent studies [37,40,42]. This method, used along with a constrained minimization and the Ekeland's variational principle [43], suggests a practical approach to obtain solutions to the problems of the type (1.2). In the present paper, we generalize these results to nonstandard p()-growth.

    The paper is organized as follows. In Section 2, we provide some fundamental information for the theory of variable Sobolev spaces since it is our work space. In Section 3, first we obtain the auxiliary results. Then, we present our main result and obtain a positive solution to problem (1.1). In Section 4, we provide an example to illustrate our results in a concrete way.

    We start with some basic concepts of variable Lebesgue-Sobolev spaces. For more details, and the proof of the following propositions, we refer the reader to [1,2,44,45].

    C+(¯Ω)={p;pC(¯Ω),infp(x)>1, for all x¯Ω}.

    For pC+(¯Ω) denote

    p:=infx¯Ωp(x)p(x)p+:=supx¯Ωp(x)<.

    For any pC+(¯Ω), we define the variable exponent Lebesgue space by

    Lp()(Ω)={uu:ΩR is measurable,Ω|u(x)|p(x)dx<},

    then, Lp()(Ω) endowed with the norm

    |u|p()=inf{λ>0:Ω|u(x)λ|p(x)dx1},

    becomes a Banach space.

    Proposition 2.1. For any uLp()(Ω) and vLp()(Ω), we have

    Ω|uv|dxC(p,(p))|u|p()|v|p()

    where Lp(x)(Ω) is the conjugate space of Lp()(Ω) such that 1p(x)+1p(x)=1.

    The convex functional Λ:Lp()(Ω)R defined by

    Λ(u)=Ω|u(x)|p(x)dx,

    is called modular on Lp()(Ω).

    Proposition 2.2. If u,unLp()(Ω) (n=1,2,...), we have

    (i) |u|p()<1(=1;>1)Λ(u)<1(=1;>1);

    (ii) |u|p()>1|u|pp()Λ(u)|u|p+p();

    (iii) |u|p()1|u|p+p()Λ(u)|u|pp();

    (iv) limn|un|p()=0limnΛ(un)=0;limn|un|p()=limnΛ(un)=.

    Proposition 2.3. If u,unLp()(Ω) (n=1,2,...), then the following statements are equivalent:

    (i) limn|unu|p()=0;

    (ii) limnΛ(unu)=0;

    (iii) unu in measure in Ω and  limnΛ(un)=Λ(u).

    The variable exponent Sobolev space W1,p()(Ω) is defined by

    W1,p()(Ω)={uLp()(Ω):|u|Lp()(Ω)},

    with the norm

    u1,p()=|u|p()+|u|p(),

    or equivalently

    u1,p()=inf{λ>0:Ω(|u(x)λ|p(x)+|u(x)λ|p(x))dx,1}

    for all uW1,p()(Ω).

    As shown in [46], the smooth functions are in general not dense in W1,p()(Ω), but if the variable exponent pC+(¯Ω) is logarithmic Hölder continuous, that is

    |p(x)p(y)|Mlog(|xy|),for allx,yΩ such that|xy|12, (2.1)

    then the smooth functions are dense in W1,p()(Ω) and so the Sobolev space with zero boundary values, denoted by W1,p()0(Ω), as the closure of C0(Ω) does make sense. Therefore, the space W1,p()0(Ω) can be defined as ¯C0(Ω)1,p()=W1,p()0(Ω), and hence, uW1,p()0(Ω) iff there exists a sequence (un) of C0(Ω) such that unu1,p()0.

    As a consequence of Poincaré inequality, u1,p() and |u|p() are equivalent norms on W1,p()0(Ω) when pC+(¯Ω) is logarithmic Hölder continuous. Therefore, for any uW1,p()0(Ω), we can define an equivalent norm u such that

    u=|u|p().

    Proposition 2.4. If 1<pp+<, then the spaces Lp()(Ω) and W1,p()(Ω) are separable and reflexive Banach spaces.

    Proposition 2.5. Let qC(¯Ω). If 1q(x)<p(x) for all x¯Ω, then the embedding W1,p()(Ω)Lq()(Ω) is compact and continuous, where

    p(x)={Np(x)Np(x),ifp(x)<N,+,ifp(x)N.

    Finally, we introduce the anisotropic variable exponent Sobolev spaces.

    Let us denote by p:¯ΩRN the vectorial function p()=(p1(),...,pN()) with piC+(¯Ω), i{1,...,N}. We will use the following notations.

    Define P+,PRN as

    P+=(p+1,...,p+N),  P=(p1,...,pN),

    and P++,P+,PR+ as

    P++=max{p+1,...,p+N},P+=max{p1,...,pN}, P=min{p1,...,pN}, 

    Below, we use the definitions of the anisotropic variable exponent Sobolev spaces as given in [12] and assume that the domain ΩRN satisfies all the necessary assumptions given in there.

    The anisotropic variable exponent Sobolev space is defined by

    W1,p()(Ω)={uLP++(Ω):xiuLpi()(Ω), i{1,...,N}},

    which is associated with the norm

    uW1,p()(Ω)=|u|P++()+Ni=1|xiu|pi().

    W1,p()(Ω) is a reflexive Banach space under this norm.

    The subspace W1,p()0(Ω)W1,p()(Ω) consists of the functions that are vanishing on the boundary, that is,

    W1,p()0(Ω)={uW1,p()(Ω):u=0onΩ},

    We can define the following equivalent norm on W1,p()0(Ω)

    up()=Ni=1|xiu|pi().

    since the smooth functions are dense in W1,p()0(Ω), as the variable exponent piC+(¯Ω), i{1,...,N} is logarithmic Hölder continuous.

    The space W1,p()0(Ω) is also a reflexive Banach space (for the theory of the anisotropic Sobolev spaces see, e.g., the monographs [2,47,48] and the papers [12,15]).

    Throughout this article, we assume that

    Ni=11pi>1, (2.2)

    and define PR+ and P,R+ by

    P=NNi=11pi1, P,=max{P+,P}.

    Proposition 2.6. [[15], Theorem 1] Suppose that ΩRN(N3) is a bounded domain with smooth boundary and relation (2.2) is fulfilled. For any qC(¯Ω) verifying

    1<q(x)<P,forallx¯Ω,

    the embedding

    W1,p()0(Ω)Lq()(Ω),

    is continuous and compact.

    We define the singular energy functional J:W1,p()0(Ω)R corresponding to equation (1.1) by

    J(u)=ΩNi=1|xiu|pi(x)pi(x)dxΩg(x)|u|q(x)+1q(x)+1dx+Ωf(x)|u|1β(x)β(x)1dx.

    Definition 3.1. A function u is called a weak solution to problem (1.1) if uW1,p()0(Ω) such that u>0 in Ω and

    Ω[Ni=1|xiu|pi(x)2xiuxiφ[g(x)uq(x)+f(x)uβ(x)]φ]dx=0, (3.1)

    for all φW1,p()0(Ω).

    Definition 3.2. Due to the singularity of J on W1,p()0(Ω), we apply a constrained minimization for problem (1.1). As such, we introduce the following constrains:

    N1={uW1,p()0(Ω):Ω[Ni=1|xiu|pi(x)g(x)|u|q(x)+1f(x)|u|1β(x)]dx0},

    and

    N2={uW1,p()0(Ω):Ω[Ni=1|xiu|pi(x)g(x)|u|q(x)+1f(x)|u|1β(x)]dx=0}.

    Remark 1. N2 can be considered as a Nehari manifold, even though in general it may not be a manifold. Therefore, if we set

    c0:=infuN2J(u),

    then one might expect that c0 is attained at some uN2 (i.e., N2) and that u is a critical point of J.

    Throughout the paper, we assume that the following conditions hold:

    (A1) β:¯Ω(1,) is a continuous function such that 1<ββ(x)β+<.

    (A2) q:¯Ω(0,1) is a continuous function such that 0<qq(x)q+<1 and q++1β.

    (A3) 2PP++<P for almost all x¯Ω.

    (A4) fL1(Ω) is a positive function, that is, f(x)>0 a.e. in Ω.

    (A5) gL(Ω) is a nonnegative function.

    Lemma 3.3. For any uW1,p()0(Ω) satisfying Ωf(x)|u|1β(x)dx<, the functional J is well-defined and coercive on W1,p()0(Ω).

    Proof. Denote by I1,I2 the indices sets I1={i{1,2,...,N}:|xiu|pi()1} and I2={i{1,2,...,N}:|xiu|pi()>1}. Using Proposition 2.2, it follows

    |J(u)|1PNi=1Ω|xiu|pi(x)dx|g|q++1Ω|u|q(x)+1dx+1β1Ωf(x)|u|1β(x)dx1P(iI1|xiu|Ppi()+iI2|xiu|P++pi())|g|q++1min{|u|q++1q(x)+1,|u|q+1q(x)+1}+1β1Ωf(x)|u|1β(x)dx1P(Ni=1|xiu|P++pi()+iI1|xiu|Ppi())|g|q++1min{|u|q++1q(x)+1,|u|q+1q(x)+1}+1β1Ωf(x)|u|1β(x)dx1P(Ni=1|xiu|P++pi()+N)|g|q++1min{|u|q++1q(x)+1,|u|q+1q(x)+1}+1β1Ωf(x)|u|1β(x)dx (3.2)

    which shows that J is well-defined on W1,p()0(Ω).

    Applying similar steps and using the generalized mean inequality for Ni=1|xiu|Ppi() gives

    J(u)1P++Ni=1Ω|xiu|pi(x)dx|g|q+1Ω|u|q(x)+1dx+1β+1Ωf(x)|u|1β(x)dx1P++(iI1|xiu|P++pi()+iI2|xiu|Ppi())|g|q+1Ω|u|q(x)+1dx+1β+1Ωf(x)|u|1β(x)dxNP++(uPp()NP1)|g|q+1uq++1p()+1β+1Ωf(x)|u|1β(x)dx (3.3)

    That is, J is coercive (i.e., J(u) as up()), and bounded below on W1,p()0(Ω).

    Next, we provide a-priori estimate.

    Lemma 3.4. Assume that (un)N1 is a nonnegative minimizing sequence for the minimization problem limnJ(un)=infN1J. Then, there are positive real numbers δ1,δ2 such that

    δ1unp()δ2

    Proof. We assume by contradiction that there exists a subsequence (un) (not relabelled) such that un0 in W1,p()0(Ω). Thus, we can assume that unp()<1 for n large enough, and therefore, |xiun|Lpi()<1. Then, using Proposition 2.2, we have

    ΩNi=1|xiun|pi(x)dxNi=1|xiun|pipi()Ni=1|xiun|Ppi() (3.4)

    We recall the following elementary inequality: for all r,s>0 and m>0 it holds

    rm+smK(r+s)m (3.5)

    where K:=max{1,21m}. If we let r=|x1un|PLp1(), s=|x2un|PLp2() and m=P in (3.5), it reads

    |x1un|PLp1()+|x2un|PLp2()K(|x1un|Lp1()+|x2un|Lp2())P (3.6)

    where K=max{1,21P}=1. Applying this argument to the following terms in the sum Ni=1|xiun|Ppi() consecutively leads to

    ΩNi=1|xiun|pi(x)dxNi=1|xiun|pipi()Ni=1|xiun|Ppi()(Ni=1|xiun|pi())PunPp() (3.7)

    Now, using (3.7) and the reversed Hölder's inequality, we have

    (Ωf(x)1/βdx)β(Ω|un|dx)1βΩf(x)|un|1βdxΩf(x)|un|1β(x)dx (3.8)

    By the assumption, (un)N1. Thus, using (3.8) and Proposition 2.2 leads to

    (Ωf(x)1/βdx)β(Ω|un|dx)1βΩf(x)|un|1βdxunPp()|g|q+1unq++10 (3.9)

    Considering the assumption (A2), this can only happen if Ω|un|dx, which is not possible. Therefore, there exists a positive real number δ1 such that unp()δ1.

    Now, let's assume, on the contrary, that unp()>1 for any n. We know, by the coerciveness of J, that the infimum of J is attained, that is, <m:=infuW1,p()0(Ω)J(u). Moreover, due to the assumption limnJ(un)=infN1J, (J(un)) is bounded. Then, applying the same steps as in (3.3), it follows

    Cunp()+J(un)NP++(unPp()NP1)|g|q+1unq++1p()+1β+1Ωf(x)|un|1β(x)dx

    for some constant C>0. If we drop the nonnegative terms, we obtain

    Cunp()+J(un)1P++(unPp()NP1N)|g|q+1uq++1p()

    Dividing the both sides of the above inequality by unq++1p() and passing to the limit as n leads to a contradiction since we have q+1<P. Therefore, there exists a positive real number δ2 such that unp()δ2.

    Lemma 3.5. N1 is closed in W1,p()0(Ω).

    Proof. Assume that (un)N1 such that unˆu(strongly) in W1,p()0(Ω). Thus, un(x)ˆu(x) a.e. in Ω, and xiunxiˆu in Lpi()(Ω) for i=1,2,...,N. Then, using Fatou's lemma, it reads

    Ω[Ni=1|xiun|pi(x)g(x)|un|q(x)+1f(x)|un|1β(x)]dx0lim infn[ΩNi=1|xiun|pi(x)dx]Ωg(x)|ˆu|q(x)+1dxlim infn[Ωf(x)|un|1β(x)dx]

    and hence,

    Ω[Ni=1|xiˆu|pi(x)g(x)|ˆu|q(x)+1f(x)|ˆu|1β(x)]dx0

    which means ˆuN1. N1 is closed in W1,p()0(Ω).

    Lemma 3.6. For any uW1,p()0(Ω) satisfying Ωf(x)|u|1β(x)dx<, there exists a unique continuous scaling function uW1,p()0(Ω)(0,):ut(u) such that t(u)uN2, and t(u)u is the minimizer of the functional J along the ray {tu:t>0}, that is, inft>0J(tu)=J(t(u)u).

    Proof. Fix uW1,p()0(Ω) such that Ωf(x)|u|1β(x)dx<. For any t>0, the scaled functional, J(tu), determines a curve that can be characterized by

    Φ(t):=J(tu),t[0,). (3.10)

    Then, for a t[0,), tuN2 if and only if

    Φ(t)=ddtΦ(t)|t=t(u)=0. (3.11)

    First, we show that Φ(t) attains its minimum on [0,) at some point t=t(u).

    Considering the fact 0<Ωf(x)|u|1β(x)dx<, we will examine two cases for t.

    For 0<t<1:

    Φ(t)=J(tu)tP++P++Ni=1Ω|xiu|pi(x)dxtq+1q+1Ωg(x)|u|q(x)+1dx+t1ββ+1Ωf(x)|u|1β(x)dx:=Ψ0(t)

    Then, Ψ0:(0,1)R is continuous. Taking the derivative of Ψ0 gives

    Ψ0(t)=tP++1Ni=1Ω|xiu|pi(x)dxtqΩg(x)|u|q(x)+1dx+(1ββ+1)tβΩf(x)|u|1β(x)dx (3.12)

    It is easy to see from (3.12) that Ψ0(t)<0 when t>0 is small enough. Therefore, Ψ0(t) is decreasing when t>0 is small enough. In the same way,

    Φ(t)=J(tu)tPPNi=1Ω|xiu|pi(x)dxtq++1q++1Ωg(x)|u|q(x)+1dx+t1β+β1Ωf(x)|u|1β(x)dx:=Ψ1(t)

    Then, Ψ1:(0,1)R is continuous. Taking the derivative of Ψ1 gives

    Ψ1(t)=tP1Ni=1Ω|xiu|pi(x)dxtq+Ωg(x)|u|q(x)+1dx+(1β+β+1)tβ+Ωf(x)|u|1β(x)dx (3.13)

    But (3.13) also suggests that Ψ1(t)<0 when t>0 is small enough. Thus, Ψ1(t) is decreasing when t>0 is small enough. Therefore, since Ψ0(t)Φ(t)Ψ1(t) for 0<t<1, Φ(t) is decreasing when t>0 is small enough.

    For t>1: Following the same arguments shows that Ψ0(t)>0 and Ψ1(t)>0 when t>1 is large enough, and therefore, both Ψ0(t) and Ψ1(t) are increasing. Thus, Φ(t) is increasing when t>1 is large enough. In conclusion, since Φ(0)=0, Φ(t) attains its minimum on [0,) at some point, say t=t(u). That is, ddtΦ(t)|t=t(u)=0. Then, t(u)uN2 and inft>0J(tu)=J(t(u)u).

    Next, we show that scaling function t(u) is continuous on W1,p()0(Ω).

    Let unu in W1,p()0(Ω){0}, and tn=t(un). Then, by the definition, tnunN2. Defined in this way, the sequence tn is bounded. Assume on the contrary that tn (up to a subsequence). Then, using the fact tnunN2 it follows

    ΩNi=1|xitnun|pi(x)dxΩg(x)|tnun|q(x)+1dx=Ωf(x)|tnun|1β(x)dxtPnΩNi=1|xiun|pi(x)dxtq+1nΩg(x)|un|q(x)+1dxt1βnΩf(x)|un|1β(x)dx

    which suggests a contradiction when tn. Hence, sequence tn is bounded. Therefore, there exists a subsequence tn (not relabelled) such that tnt0, t00. On the other hand, from Lemma 3.4, tnunp()δ1>0. Thus, t0>0 and t0uN2. By the uniqueness of the map t(u), t0=t(u), which concludes the continuity of t(u). In conclusion, for any W1,p()0(Ω) satisfying Ωf(x)|u|1β(x)dx<, the function t(u) scales uW1,p()0(Ω) continuously to a point such that t(u)uN2.

    Lemma 3.7. Assume that (un)N1 is the nonnegative minimizing sequence for the minimization problem limnJ(un)=infN1J. Then, there exists a subsequence (un) (not relabelled) such that unu (strongly) in W1,p()0(Ω).

    Proof. Since (un) is bounded in W1,p()0(Ω) and W1,p()0(Ω) is reflexive, there exists a subsequence (un), not relabelled, and uW1,p()0(Ω) such that

    unu (weakly) in W1,p()0(Ω),

    unu in Ls()(Ω), 1<s(x)<P,, for all x¯Ω,

    un(x)u(x) a.e. in Ω.

    Since the norm p() is a continuous convex functional, it is weakly lower semicontinuous. Using this fact along with the Fatou's lemma, and Lemma 3.4, it reads

    infN1J=limnJ(un)lim infn[ΩNi=1|xiun|pi(x)pi(x)dx]Ωg(x)|u|q(x)+1q(x)+1dx+lim infn[Ωf(x)|un|1β(x)β(x)1dx]ΩNi=1|xiu|pi(x)pi(x)dxΩg(x)|u|q(x)+1q(x)+1dx+Ωf(x)|u|1β(x)β(x)1dx=J(u)J(t(u)u)infN2JinfN1J (3.14)

    The above result implies, up to subsequences, that

    limnunp()=up(). (3.15)

    Thus, (3.15) along with unu in W1,p()0(Ω) show that unu in W1,p()0(Ω).

    The following is the main result of the present paper.

    Theorem 3.8. Assume that the conditions (A1)(A5) hold. Then, problem (1.1) has at least one positive W1,p()0(Ω)-solution if and only if there exists ¯uW1,p()0(Ω) satisfying Ωf(x)|¯u|1β(x)dx<.

    Proof. (): Assume that the function uW1,p()0(Ω) is a weak solution to problem (1.1). Then, letting u=φ in Definition (3.1) gives

    Ωf(x)|u|1β(x)dx=ΩNi=1|xiu|pi(x)dxΩg(x)|u|q(x)+1dxuPMp()|g||u|qMq(x)+1uPMp()<,

    where PM:=max{P,P++} and qM:=max{q,q+}, changing according to the base.

    (): Assume that there exists ¯uW1,p()0(Ω) such that Ωf(x)|¯u|1β(x)dx<. Then, by Lemma 3.6, there exists a unique number t(¯u)>0 such that t(¯u)¯uN2.

    The information we have had about J so far and the closeness of N1 allow us to apply Ekeland's variational principle to the problem infN1J. That is, it suggests the existence of a corresponding minimizing sequence (un)N1 satisfying the following:

    (E1) J(un)infN1J1n,

    (E2) J(un)J(ν)1nunνp(),νN1.

    Due to the fact J(|un|)=J(un), it is not wrong to assume that un0 a.e. in Ω. Additionally, considering that (un)N1 and following the same approach as it is done in the () part, we can obtain that Ωf(x)|un|1β(x)dx<. If all this information and the assumptions (A1), (A2) are taken into consideration, it follows that un(x)>0 a.e. in Ω.

    The rest of the proof is split into two cases.

    Case Ⅰ: (un)N1N2 for n large.

    For a function φW1,p()0(Ω) with φ0, and t>0, we have

    0<(un(x)+tφ(x))1β(x)un(x)1β(x)a.e. inΩ.

    Therefore, using (A1), (A2) gives

    Ωf(x)(un+tφ)1β(x)dxΩf(x)u1β(x)ndxΩNi=1|xiun|pi(x)dxΩg(x)uq(x)+1ndx< (3.16)

    Then, when t>0 is small enough in (3.16), we obtain

    Ωf(x)(un+tφ)1β(x)dxΩNi=1|xi(un+tφ)|pi(x)dxΩg(x)(un+tφ)q(x)+1dx (3.17)

    which means that ν:=un+tφN1. Now, using (E2), it reads

    1ntφp()J(un)J(ν)=ΩNi=1|xiun|pi(x)pi(x)dxΩNi=1|xi(un+tφ)|pi(x)pi(x)dxΩg(x)uq(x)+1nq(x)+1dx+Ωg(x)(un+tφ)q(x)+1q(x)+1dx+Ωf(x)u1β(x)nβ(x)1dxΩf(x)(un+tφ)1β(x)β(x)1dx

    Dividing the above inequality by t and passing to the infimum limit as t0 gives

    lim inft0φp()n+lim inft0[ΩNi=1[|xi(un+tφ)|pi(x)|xiun|pi(x)]tpi(x)dx]:=I1lim inft0[Ωg(x)[(un+tφ)q(x)+1uq(x)+1n]t(q(x)+1)dx]:=I2lim inft0[Ωf(x)[(un+tφ)1β(x)u1β(x)n]t(1β(x))dx]:=I3

    Calculation of I1,I2 gives

    I1=ddt(ΩNi=1|xi(un+tφ)|pi(x)pi(x)dx)|t=0=ΩNi=1|xiun|pi(x)2xiunxiφdx (3.18)

    and

    I2=ddt(Ωg(x)(un+tφ)q(x)+1q(x)+1dx)|t=0=Ωg(x)uq(x)nφdx. (3.19)

    For I3: Since for t>0 it holds

    u1β(x)n(x)(un(x)+tφ(x))1β(x)0,a.e. inΩ

    we can apply Fatou's lemma, that is,

    I2=lim inft0Ωf(x)[(un+tφ)1β(x)u1β(x)n]t(1β(x))dxΩlim inft0f(x)[(un+tφ)1β(x)u1β(x)n]t(1β(x))dxΩf(x)uβ(x)nφdx (3.20)

    Now, substituting I1,I2,I3 gives

    φp()n+ΩNi=1|xiun|pi(x)2xiunxiφdxΩg(x)uq(x)nφdxΩf(x)uβ(x)nφdx

    From Lemma 3.7, we know that unu in W1,p()0(Ω). Thus, also considering Fatou's lemma, we obtain

    ΩNi=1|xiu|pi(x)2xiuxiφdxΩg(x)(u)q(x)φdxΩf(x)(u)β(x)φdx0, (3.21)

    for any φW1,p()0(Ω) with φ0. Letting φ=u in (3.21) shows clearly that uN1.

    Lastly, from Lemma 3.7, we can conclude that

    limnJ(un)=J(u)=infN2J,

    which means

    uN2,(witht(u)=1) (3.22)

    Case Ⅱ: There exists a subsequence of (un) (not relabelled) contained in N2.

    For a function φW1,p(x)0(Ω) with φ0, t>0, and unN2, we have

    Ωf(x)(un+tφ)1β(x)dxΩf(x)u1β(x)ndx=ΩNi=1|xiu|pi(x)dxΩg(x)uq(x)+1ndx<, (3.23)

    and hence, there exists a unique continuous scaling function, denoted by θn(t):=t(un+tφ)>0, corresponding to (un+tφ) so that θn(t)(un+tφ)N2 for n=1,2,.... Obviously, θn(0)=1. Since θn(t)(un+tφ)N2, we have

    0=ΩNi=1|xiθn(t)(un+tφ)|pi(x)dxΩg(x)(θn(t)(un+tφ))q(x)+1dxΩf(x)(θn(t)(un+tφ))1β(x)dxΩNi=1|xiθn(t)(un+tφ)|pi(x)dxθqM+1n(t)Ωg(x)(un+tφ)q(x)+1dxθ1βmn(t)Ωf(x)(un+tφ)1β(x)dx, (3.24)

    and

    0=ΩNi=1|xiun|pi(x)dxΩg(x)uq(x)+1ndxΩf(x)u1β(x)ndx. (3.25)

    where βm:=min{β,β+}. Then, using (3.24) and (3.25) together gives

    0[(q++1)[θn(0)+τ1(θn(t)θn(0))]qmΩg(x)(un+tφ)q(x)+1dx(1βm)[θn(0)+τ2(θn(t)θn(0))]βmΩf(x)(un+tφ)1β(x)dx](θn(t)θn(0))+ΩNi=1|xiθn(t)(un+tφ)|pi(x)dxΩNi=1|xi(un+tφ)|pi(x)dx+ΩNi=1|xi(un+tφ)|pi(x)dxΩNi=1|xiun|pi(x)dx[Ωg(x)(un+tφ)q(x)+1dxΩg(x)uq(x)+1ndx][Ωf(x)(un+tφ)1β(x)dxΩf(x)u1β(x)ndx] (3.26)

    for some constants τ1,τ2(0,1). To proceed, we assume that θn(0)=ddtθn(t)|t=0[,]. In case this limit does not exist, we can consider a subsequence tk>0 of t such that tk0 as k.

    Next, we show that θn(0).

    Dividing the both sides of (3.26) by t and passing to the limit as t0 leads to

    0[PΩNi=1|xiun|pi(x)dx+(βm1)Ωf(x)u1β(x)ndx(q++1)Ωg(x)uq(x)+1ndx]θn(0)+PΩNi=1|xiun|pi(x)2xiunxiφdx(q++1)Ωg(x)uq(x)nφdx+(βm1)Ωf(x)uβ(x)nφdx (3.27)

    or

    0[(Pq+1)ΩNi=1|xiun|pi(x)dx+(βm+q+)Ωf(x)u1β(x)ndx]θn(0)+PΩNi=1|xiun|pi(x)2xiunxiφdx(q++1)Ωg(x)uq(x)nφdx+(βm1)Ωf(x)uβ(x)nφdx (3.28)

    which, along with Lemma 3.4, concludes that θn(0)<, and hence, θn(0)¯c, uniformly in all large n.

    Next, we show that θn(0).

    First, we apply Ekeland's variational principle to the minimizing sequence (un)N2(N1). Thus, letting ν:=θn(t)(un+tφ) in (E2) gives

    1n[|θn(t)1|unp()+tθn(t)φp()]J(un)J(θn(t)(un+tφ))=ΩNi=1|xiun|pi(x)pi(x)dxΩg(x)uq(x)+1nq(x)+1dx+Ωf(x)u1β(x)nβ(x)1dxΩNi=1|xiθn(t)(un+tφ)|pi(x)pi(x)dx+Ωg(x)[θn(t)(un+tφ)]q(x)+1q(x)+1dxΩf(x)[θn(t)(un+tφ)]1β(x)β(x)1dxΩNi=1|xiun|pi(x)pi(x)dxΩNi=1|xiθn(t)(un+tφ)|pi(x)pi(x)dxΩg(x)uq(x)+1nq(x)+1dx+Ωg(x)[θn(t)(un+tφ)]q(x)+1q(x)+1dx1β1ΩNi=1|xiθn(t)(un+tφ)|pi(x)dx (3.29)

    If we use Lemma 3.4 to manipulate the norm u+tφp(), the integral in the last line of (3.29) can be written as follows

    1β1ΩNi=1|xiθn(t)(un+tφ)|pi(x)dxθPMn(t)β1ΩNi=1|xi(un+tφ)|pi(x)dxθPMn(t)β1un+tφPMp()2P++1θPMn(t)CPM(δ2)φPMp()β1t (3.30)

    Then,

    1n[|θn(t)1|unp()+tθn(t)φp()]+ΩNi=1[|xi(un+tφ)|pi(x)|xiun|pi(x)]pi(x)dx+2P++1θPMn(t)CPM(δ2)φPMp()β1t[(1q+1)[θn(0)+τ1(θn(t)θn(0))]qmΩg(x)(un+tφ)q(x)+1dx](θn(t)θn(0))ΩNi=1[|xiθn(t)(un+tφ)|pi(x)|xi(un+tφ)|pi(x)]pi(x)dx+1q+1Ωg(x)[(un+tφ)q(x)+1uq(x)+1n]dx (3.31)

    Dividing by t and passing to the limit as t0 gives

    1nφp()+2P++1θPMn(t)CPM(δ2)φPMp()β1[(1+1q+1)ΩNi=1|xiun|pi(x)dx1q+1Ωf(x)u1β(x)ndxunp()nsgn[θn(t)1]]θn(0)ΩNi=1|xiun|pi(x)2xiunxiφdx+Ωg(x)uq(x)ndx (3.32)

    which concludes that θn(0). Thus, θn(0)c_ uniformly in large n.

    In conclusion, there exists a constant, C0>0 such that |θn(0)|C0 when nN0,N0N.

    Next, we show that uN2.

    Using (E2) again, we have

    1n[|θn(t)1|unp()+tθn(t)φp()]J(un)J(θn(t)(un+tφ))=ΩNi=1|xiun|pi(x)pi(x)dxΩg(x)uq(x)+1nq(x)+1dx+Ωf(x)u1β(x)nβ(x)1dxΩNi=1|xiθn(t)(un+tφ)|pi(x)pi(x)dx+Ωg(x)[θn(t)(un+tφ)]q(x)+1q(x)+1dxΩf(x)[θn(t)(un+tφ)]1β(x)β(x)1dx=ΩNi=1|xi(un+tφ)|pi(x)pi(x)dx+ΩNi=1|xiun|pi(x)pi(x)dxΩf(x)(un+tφ)1β(x)β(x)1dx+Ωf(x)u1β(x)nβ(x)1dxΩNi=1|xiθn(t)(un+tφ)|pi(x)pi(x)dx+ΩNi=1|xi(un+tφ)|pi(x)pi(x)dxΩf(x)[θn(t)(un+tφ)]1β(x)β(x)1dx+Ωf(x)(un+tφ)1β(x)β(x)1dxΩg(x)[θn(t)(un+tφ)]q(x)+1q(x)+1dxΩg(x)(un+tφ)q(x)+1q(x)+1dxΩg(x)uq(x)+1nq(x)+1dx+Ωg(x)(un+tφ)q(x)+1q(x)+1dx (3.33)

    Dividing by t and passing to the limit as t0 gives

    1n[|θn(0)|unp()+φp()]ΩNi=1|xiun|pi(x)2xiunxiφdx+Ωf(x)uβ(x)nφdx+Ωg(x)uq(x)nφdx[ΩNi=1|xiun|pi(x)dx+Ωg(x)uq(x)+1ndx+Ωf(x)u1β(x)ndx]θn(0)=ΩNi=1|xiun|pi(x)2xiunxiφdx+Ωg(x)uq(x)nφdx+Ωf(x)uβ(x)nφdx (3.34)

    If we consider that |θn(0)|C0 uniformly in n, we obtain that Ωf(x)uβ(x)ndx<. Therefore, for n it reads

    ΩNi=1|xiu|pi(x)2xiuxiφdxΩg(x)(u)q(x)φdxΩf(x)(u)β(x)φdx0 (3.35)

    for all φW1,p()0(Ω), φ0. Letting φ=u in (3.35) shows clearly that uN1.

    This means, as with the Case Ⅰ, that we have

    uN2 (3.36)

    By taking into consideration the results (3.21), (3.22), (3.35), and (3.36), we infer that uN2 and (3.35) holds, in the weak sense, for both cases. Additionally, since u0 and u0, by the strong maximum principle for weak solutions, we must have u(x)>0almost everywhere inΩ.

    Next, we show that uW1,p()0(Ω) is a weak solution to problem (1.1).

    For a random function ϕW1,p()0(Ω), and ε>0, let φ=(u+εϕ)+=max{0,u+εϕ}. We split Ω into two sets as follows:

    Ω={xΩ:u(x)+εϕ(x)0}, (3.37)

    and

    Ω<={xΩ:u(x)+εϕ(x)<0}. (3.38)

    If we replace φ with (u+εϕ) in (3.35), it follows

    0ΩNi=1|xiu|pi(x)2xiuxiφdxΩ[g(x)(u)q(x)+f(x)(u)β(x)]φdx=ΩNi=1|xiu|pi(x)2xiuxi(u+εϕ)dxΩ[g(x)(u)q(x)(u)+f(x)(u)β(x)](u+εϕ)dx=ΩΩ<[Ni=1|xiu|pi(x)2xiuxi(u+εϕ)[g(x)(u)q(x)+f(x)(u)β(x)](u+εϕ)]dx=ΩNi=1|xiu|pi(x)dx+εΩNi=1|xiu|pi(x)2xiuxiϕdxΩf(x)(u)1β(x)dxεΩf(x)(u)β(x)ϕdxΩg(x)(u)q(x)+1dxεΩg(x)(u)q(x)ϕdxΩ<[Ni=1|xiu|pi(x)2xiuxi(u+εϕ)[g(x)(u)q(x)+f(x)(u)β(x)](u+εϕ)]dx (3.39)

    Since uN2, we have

    0ε[ΩNi=1|xiu|pi(x)2xiuxiϕ[g(x)(u)q(x)+f(x)(u)β(x)]ϕ]dxεΩ<Ni=1|xiu|pi(x)2xiuxiϕdx+εΩ<g(x)(u)q(x)ϕdx+εΩ<f(x)(u)β(x)ϕdx (3.40)

    Dividing by ε and passing to the limit as ε0, and considering that |Ω<|0 as ε0 gives

    ΩNi=1|xiu|pi(x)2xiuxiϕdxΩg(x)(u)q(x)ϕdxΩf(x)(u)β(x)ϕdx,ϕW1,p()0(Ω) (3.41)

    However, since the function ϕW1,p()0(Ω) is chosen randomly, it follows that

    ΩNi=1|xiu|pi(x)2xiuxiϕdxΩg(x)(u)q(x)ϕdx=Ωf(x)(u)β(x)ϕdx (3.42)

    which concludes that uW1,p()0(Ω) is a weak solution to problem (1.1).

    Suppose that

    {g(x)=ekcos(|x|),andf(x)=(1|x|)kβ(x),xB1(0)RN,k>0.

    Then equation (1.1) becomes

    {Ni=1xi(|xiu|pi(x)2xiu)=(1|x|)kβ(x)uβ(x)+ekcos(|x|)uq(x) in B1(0),u>0 in B1(0),u=0 on B1(0). (4.1)

    Theorem 4.1. Assume that the conditions (A1)(A3) hold. If 1<β+<1+k+1α and α>1/2, then, problem (4.1) has at least one positive W1,p()0(B1(0))-solution.

    Proof. Function f(x)=(1|x|)kβ(x)(1|x|)kβ is clearly non-negative and bounded above within the unit ball B1(0) since |x|<1. Hence, f(x)L1(B1(0)).

    Now, let's choose ¯u=(1|x|)α. Since ¯u is also non-negative and bounded within B(0,1), it is in ¯uLP++(B(0,1)). Indeed,

    Ni=1B1(0)((1|x|)α)pi(x)dxN[B1(0)((1|x|)α)Pdx+B1(0)((1|x|)α)P++dx]<.

    Next, we show that xi¯uLpi()(B1(0)) for i{1,...,N}. Fix i{1,...,N}. Then

    xi(1|x|)α=α(1|x|)α1xi|x|

    Considering that xB1(0), we obtain

    B1(0)|xi(1|x|)α|pi(x)dxαPMB1(0)(1|x|)(α1)Pdx

    Therefore,

    Ni=1B1(0)|xi(1|x|)α|pi(x)dxNαPMNi=1B(0,1)(1|x|)(α1)Pdx<

    if α>P1P. Thus, xi¯uLpi()(B1(0)) for i{1,...,N}, and as a result, ¯uW1,p()0(B1(0)).

    Finally, we show that B(0,1)(1|x|)k(1|x|)α(1β(x))β(x)dx<. Then,

    B1(0)(1|x|)k(1|x|)α(1β(x))β(x)dx1βB1(0)(1|x|)k+α(1β+)dx<.

    Thus, by Theorem 3.8, problem (4.1) has at least one positive W1,p()0(B1(0))-solution.

    The author declares he has not used Artificial Intelligence (AI) tools in the creation of this article.

    This work was supported by Athabasca University Research Incentive Account [140111 RIA].

    The author declares there is no conflict of interest.



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