Research article Special Issues

Analysis and Bayesian estimation of a model for Chikungunya dynamics with relapse: An outbreak in Acapulco, Mexico

  • Chikungunya is a vector-borne viral disease transmitted by Aedes aegypti and Aedes albopictus mosquitoes. It does not have any specific treatment, and there is no vaccine. Recent epidemiological data have indicated that a relapse of the infection can occur within three months of the initial infection; however, until now, mathematical models for the spread of the disease have not considered this factor. We propose a mathematical model for the transmission of the Chikungunya virus that considers relapse. We calculated the basic reproductive number (R0) of the disease by using the next-generation operator method. We proved the existence of a forward bifurcation. We determined the existence and the global stability of the equilibrium points by using the Lyapunov function method. We fitted the model to data from an outbreak in 2015 in Acapulco, Mexico to estimate the model parameters and R0 with the Bayesian approach via a Hamiltonian Monte Carlo method. In the local sensitivity analysis, we found that the fraction of infected individuals who become asymptomatic has a strong impact on the basic reproductive number and makes some control measures insufficient. The impact of the fraction of infected individuals who become asymptomatic should be considered in Chikungunya control strategies.

    Citation: María Guadalupe Vázquez-Peña, Cruz Vargas-De-León, Jorge Fernando Camacho-Pérez, Jorge Velázquez-Castro. Analysis and Bayesian estimation of a model for Chikungunya dynamics with relapse: An outbreak in Acapulco, Mexico[J]. Mathematical Biosciences and Engineering, 2023, 20(10): 18123-18145. doi: 10.3934/mbe.2023805

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  • Chikungunya is a vector-borne viral disease transmitted by Aedes aegypti and Aedes albopictus mosquitoes. It does not have any specific treatment, and there is no vaccine. Recent epidemiological data have indicated that a relapse of the infection can occur within three months of the initial infection; however, until now, mathematical models for the spread of the disease have not considered this factor. We propose a mathematical model for the transmission of the Chikungunya virus that considers relapse. We calculated the basic reproductive number (R0) of the disease by using the next-generation operator method. We proved the existence of a forward bifurcation. We determined the existence and the global stability of the equilibrium points by using the Lyapunov function method. We fitted the model to data from an outbreak in 2015 in Acapulco, Mexico to estimate the model parameters and R0 with the Bayesian approach via a Hamiltonian Monte Carlo method. In the local sensitivity analysis, we found that the fraction of infected individuals who become asymptomatic has a strong impact on the basic reproductive number and makes some control measures insufficient. The impact of the fraction of infected individuals who become asymptomatic should be considered in Chikungunya control strategies.



    Domain theory [1], which is a mathematical foundation of theoretical computer science, was put forward by Scott in the late 1960s. As an important content of domain theory, Dedekind-MacNeille completion (also called the normal completion), has been studied by many researchers [2,3,4].

    Quantitative domain theory ([5,6,7,8,9]), which is regarded as the deep combination of denotational semantics of domain theory and the method of measurement, forms a new research field of domain theory. Its essence is to find a kind of model structure which can be calculated. As an important part of quantitative domain theory, the completions have also developed rapidly, and many researchers are devoted to studying the completions. Wagner [9] discussed the enriched Dedekind-MacNeille completion. Bělohlávek [10] discussed the Dedekind-MacNeille completion from the aspect of fuzzy concept lattice. Xie, Zhang and Fan [11] studied the Dedekind-MacNeille completion from the aspect of fuzzy poset. Wang and Zhao characterized the Dedekind-MacNeille completion from the aspect of the category [12]. Ma and Zhao studied the Dedekind-MacNeille completion based on a complete residuated lattice and obtain the full reflective subcategory of the category of fuzzy poset and fuzzy precontinuous in a certain morphism [13]. Halaš and Lihová characterized weakly cut-stable map by the 1st-order language [14]. In this paper, we study weakly cut-stable map based on a complete residuated lattice, that is, fuzzy weakly cut-stable map. Furthermore, we prove the extension property of fuzzy weakly cut-stable map. Following this, it is explored the conditions under which the extension map to be fuzzy order isomorphism.

    The remainder of this paper is organized as follows. In Section 2, we review the basic definitions and results which are used in the rest of the paper. In Section 3, we propose the definitions of fuzzy weakly lower (upper) cut-stable map, fuzzy weakly lower (upper) cut-continuous map, and fuzzy weakly cut-preserving map. Furthermore, we discuss the extension property of fuzzy weakly cut-stable map. In Section 4, we explore the conditions under which the extension map to be fuzzy order isomorphism. Finally, we provide conclusions in Section 5.

    This section is devoted to providing a review of some key concepts of domain theory and fuzzy set theory.

    Definition 2.1. ([15]) A residuated lattice is an algebraic structure L= (L; , , , , 0, 1) of type (2, 2, 2, 2, 0, 0) such that the following conditions hold.

    (1) (L; , , 0, 1) is a bounded lattice with the least element 0 and the greatest element 1;

    (2) (L; , 1) is a commutative monoid with the identity 1;

    (3) L satisfies the adjointness property, i.e.  x, y, zL, xyz iff xyz.

    A residuated lattice is called complete if the underlying lattice is complete. In this paper, if no otherwise specified, a complete residuated lattice is always denoted by L.

    Definition 2.2. ([16,17]) A fuzzy poset is a pair (X,e) such that X is a set and e:X×XL is a map, which satisfies the following conditions for all x,y,zX,

    (1) e(x,x)=1 (reflexivity);

    (2) e(x,y)e(y,z)e(x,z) (transitivity);

    (3) e(x,y)=e(y,x)=1 implies x=y (antisymmetry).

    For a set X, LX denotes the set of all fuzzy subsets of X, that is, the set of all maps from X to L. For λL, we use λX to denote the constant map with the value λ. For CX,

    χC(x)={1,  xC,0,  otherwises.

    Obviously, λX and χC(x) are the fuzzy subsets of X.

    Definition 2.3. ([16,17]) Let (X,e) be a fuzzy poset and ALX. An element x0X is called a supremum (resp., infimum) of A, in symbols x0=A (resp., x0=A), if the follwoing conditions hold.

    (1)  xX,A(x)e(x,x0) (resp., xX,A(x)e(x0,x));

    (2)  yX, xX(A(x)e(x,y))e(x0,y) (resp., yX, xX(A(x)e(y,x))e(y,x0)).

    Theorem 2.4. ([16,17]) Let (X,e) be a fuzzy poset and ALX,x0X. Then the following statements are equivalent:

    (1) x0=A (x0=A);

    (2) e(x0,x)=yX(A(y)e(y,x)) (e(x,x0)=yX(A(y)e(x,y))) for all xX.

    Proposition 2.5. ([16,17]) Let (X,e) be a fuzzy poset. Then (X,e) is a fuzzy complete lattice iff A exists for all ALX iff \ A exists for all ALX.

    Definition 2.6. ([18]) Let f:XY be a map. The Zadeh forward powerset operator fL:LXLY and the Zadeh backward powerset operator fL:LYLX are, respectively, defined by fL(A)(y)=f(x)=yA(x) for all ALX,yY and fL(B)=Bf for all BLY.

    Definition 2.7. ([11]) Let (X,e) be a fuzzy poset and ALX. Define Al,Au as follows:  xX, Al(x)=xX(A(x)e(x,x)), Au(x)=xX(A(x)e(x,x)).

    Proposition 2.8. ([10]) (The Dedekind-MacNeille completion) Given a fuzzy poset (X,e), if A,BLX, A=Bl,B=Au, then the pair (A,B) is called a fuzzy cut and Au, Bl are usually called fuzzy upper cut and fuzzy lower cut, respectively. The collection of all fuzzy cuts, ordered by e((A,B),(C,D))=sub(A,C)=sub(D,B), is a fuzzy complete lattice, called the Dedekind-MacNeille completion of X. The Dedekind-MacNeille completion of X is also denoted by DML(X) or N(X). That is to say, DML(X)={(A,B)A,BLX,A=Bl,B=Au}.

    Since {(A,B) A,BLX,A=Bl,B=Au} is isomorphic to {A ALX,A=Aul}, the Dedekind-MacNeille completion of X can also be denoted by {A ALX,A=Aul}, that is to say, N(X)={A ALX,A=Aul}.

    Let (X,e) be a fuzzy poset and xX. Define two maps ιx, μx:XL by ιx(y)=e(y,x), μx(y)=e(x,y) for all yX. Clearly, we have  ιx= μx=x and the pair (ιx,μx) is a fuzzy cut of X.

    Lemma 2.9. ([10,13]) Let (X,e) be a fuzzy poset and A,BLX. Then

    (1) AAul and AAlu;

    (2) sub(A,B)sub(Bu,Au) and sub(A,B)sub(Bl,Al);

    (3) sub(A,B)sub(Aul,Bul) and sub(A,B)sub(Alu,Blu);

    (4) Au=Aulu and Al=Alul.

    Theorem 2.10. ([14]) Let P,Q be posets. For a mapping f:PQ there exists a (unique) weakly complete lattice homomorphism f:N(P)N(Q) extending f if and only if f is weakly cut-stable.

    In this section, we propose the definition of fuzzy weakly cut-stable map and discuss the extension theorem of fuzzy weakly cut-stable map.

    Definition 3.1. Let (X,eX) and (Y,eY) be fuzzy posets and f:XY be a map. Then f is called fuzzy weakly lower (upper) cut-stable if for all ALX, when Au0X,(fL(Au))l=(fL(A))ul (when Al0X, (fL(Al))u=(fL(A))lu), and when Au=0X,(fL(A))u=(fL(1X))u (when Al=0X, (fL(A))l=(fL(1X))l). If f is both fuzzy weakly lower and upper cut-stable, then f is called fuzzy weakly cut-stable.

    For simplicity, we denote (fL(A)) as fL(A).

    Definition 3.2. Let (X,eX),(Y,eY) be fuzzy posets and f:XY be a map. f is called fuzzy weakly lower (upper) cut-continuous if  ALX,A0X, fL(Aul)fL(A)ul(fL(Alu)fL(A)lu). If f is both fuzzy weakly lower and upper cut-continuous, then f is called fuzzy weakly cut-continuous.

    Example 3.3. The identity mapping on a fuzzy poset is fuzzy weakly cut-continuous.

    Definition 3.4. Let (X,eX),(Y,eY) be fuzzy posets, f:XY a map. f is called fuzzy weakly cut-preserving if for all fuzzy cut (A,B) of X, and A,B0X, (fL(B)l,fL(A)u) is a fuzzy cut of Y.

    Example 3.5. For the fuzzy poset (L,eL), define f:LLL as follows ALL,f(A)=A, then f is fuzzy weakly cut-preserving.

    Obversely, by Lemma 2.9, (fL(B)l,fL(A)u) is a fuzzy cut of Y is equivalent to fL(A)ul=fL(B)l or fL(B)lu=fL(A)u. Next, we explore the relationships among these maps.

    Proposition 3.6. If f is fuzzy weakly lower (upper) cut-stable, then f is fuzzy weakly cut-preserving. Conversely, if f:XY is fuzzy weakly (lower, upper) cut-continuous and fuzzy weakly cut-preserving, then it is fuzzy weakly (lower, upper) cut-stable.

    Proof. Suppose that f:XY is fuzzy weakly lower cut-stable map. If  (A,B)DML(X),A,B0X, then Au=B,Bl=A. Therefore, fL(B)l=fL(Au)l=fL(A)ul. Hence, f is fuzzy weakly cut-preserving.

    Conversely, let f be fuzzy weakly lower cut-continuous and fuzzy weakly cut-preserving.  0XALX, when Au0X, (Aul,Au)DML(X), since f is fuzzy weakly cut-preserving, we have (fL(Au)l,fL(Aul)u)DML(Y), then fL(Au)l=fL(Aul)ul. As fL(Aul)fL(A)ul, we have fL(A)ul=fL(A)ululfL(Aul)ul=fL(Au)l.  yY,

    fL(Au)(y)=xX,f(x)=yAu(x)  =xX,f(x)=yx1X(A(x1)e(x1,x))  xX,f(x)=yx1X(A(x1)e(f(x1),f(x)))  =x1X(A(x1)e(f(x1),y))  =y1Y(fL(A)(y1)e(y1,y))  =fL(A)u(y).

    Hence, fL(Au)fL(A)u, fL(Au)lfL(A)ul. Therefore, fL(Au)l=fL(A)ul.

    When Au=0X, fL(A)fL(1X)=fL(Aul)fL(A)ul. Hence, fL(A)ufL(1X)u=fL(Aul)ufL(A)ulu=fL(A)u, that is, fL(A)u=fL(1X)u.

    Therefore, f:XY is fuzzy weakly lower cut-stable map. Other cases can be proved in a similar manner.

    Proposition 3.7. If f is fuzzy weakly cut-preserving or fuzzy weakly cut-continuous, then f is fuzzy order-preserving.

    Proof. Let f:XY be fuzzy weakly cut-preserving. Since  xX,(ιx,μx) is a fuzzy cut of X and ιx,μx0X, it holds that (fL(μx)l,fL(ιx)u) is a fuzzy cut of Y. Hence, fL(μx)fL(μx)lu=fL(ιx)u, we have μxfL(fL(ιx)u).  x,yX, eX(x,y)=μx(y)fL(fL(ιx)u)(y)=fL(ιx)u(f(y))=zY(fL(ιx)(z)eY(z,f(y)))= zY((f(x)=zeX(x,x))eY(z,f(y)))=xX(eX(x,x)eY(f(x),f(y)))eY(f(x),f(y)). Therefore, we have that f is fuzzy order-preserving. Next we prove if f is fuzzy weakly cut-continuous, then f is fuzzy order-preserving.

    Firstly,  zY,(χf(x))ul(z)=z1Y((χf(x))u(z1)e(z,z1))=z1Y((z2Yχf(x)(z2)e(z2,z1))e(z,z1))= z1Y(f(x),z1)e(z,z1))=e(z,f(x))=ιf(x)(z).

    Secondly, χf(x)=fL(χx),  zY, if z=f(x), then (χf(x))(z)=1=x1X,f(x1)=zχx(x1)=fL(χx)(z). If zf(x), then (χf(x))(z)=0=x1X,f(x1)=zχx(x1)=fL(χx)(z).

    Finally,  x,yX,

    e(f(x),f(y))=ιf(y)(f(x))  =(χf(y))ul(f(x))  =(fL(χy))ul(f(x))  fL((χy)ul)(f(x))  =fL(ιy)(f(x))  =zX,f(z)=f(x)ιy(z)  e(x,y).

    By Propositions 3.6 and 3.7, we have every fuzzy weakly lower (upper) cut-stable map is fuzzy order-preserving. Next, we show the extension property of the fuzzy weakly cut-stable map.

    Let X, Y be fuzzy posets, f:XY is a map. If  0XALX, f(A)=fL(A),f(A) =fL(A), then f is called a fuzzy weakly complete homomorphism.

    Theorem 3.8. Let X and Y be fuzzy posets. Then f:XY is fuzzy weakly cut-stable if and only if there exists a unique fuzzy weakly complete homomorphism f:\ N(X)N(Y) extending f.

    Proof. (Necessity) Suppose that f:XY is fuzzy weakly cut-stable. Define f:N(X)N(Y) by  AN(X). If A0X, then f(Aul)=fL(A)ul. If A=0X, then f(Aul)=fL(1X)l.

    (1) f is well-defined.  A,BLX, if A,B0X, Aul=Bul, then Au=Bu. When Au=Bu0X, fL(A)ul=fL(Au)l=fL(Bu)l=fL(B)ul. When Au=Bu=0X, fL(A)ul=fL(1X)ul=fL(B)ul. If A0X,B=0X, then Aul=0ulX. Therefore, Au=1X, fL(A)ul=fL(Au)l=fL(1X)l. Hence f(Aul)=f(Bul). Similarly, B0X,A=0X, f(Aul)=f(Bul). If A=B=0X, clearly we have f(Aul)=f(Bul).

    (2) f is a fuzzy weakly complete homomorphism.  ΦLN(X), Φ0N(X). Firstly, we show (ϕN(X)Φ(ϕ)fL(ϕ))ul=(ϕN(X)Φ(ϕ)(fL(ϕ))ul)ul.  φN(Y),

    sub((ϕN(X)Φ(ϕ)fL(ϕ))ul,φ)=sub(ϕN(X)Φ(ϕ)fL(ϕ),φ)  =yY(ϕN(X)Φ(ϕ)fL(ϕ)(y)φ(y))  =ϕN(X)yY(Φ(ϕ)fL(ϕ)(y)φ(y))  =ϕN(X)yY(Φ(ϕ)(fL(ϕ)(y)φ(y)))  =ϕN(X)(Φ(ϕ)sub(fL(ϕ),φ))  =ϕN(X)(Φ(ϕ)sub((fL(ϕ))ul,φ))  =sub((ϕN(X)Φ(ϕ)fL(ϕ)ul),φ)  =sub((ϕN(X)Φ(ϕ)fL(ϕ)ul)ul,φ).

    Therefore, (ϕN(X)Φ(ϕ)fL(ϕ))ul=(ϕN(X)Φ(ϕ)(fL(ϕ))ul)ul.

    By [17], we have that N(X) is complete lattice, and Φ=ϕN(X)Φ(ϕ)ϕ=(ϕN(X)Φ(ϕ)ϕ)ul.

    f(Φ)=f((ϕN(X)Φ(ϕ)ϕ)ul)  =(fL(ϕN(x)Φ(ϕ)ϕ))ul  =(ϕN(X)Φ(ϕ)fL(ϕ))ul  =(ϕN(X)Φ(ϕ)(fL(ϕ))ul)ul  =(ϕN(X)Φ(ϕ)f(ϕ))ul  =(ψN(Y)(ϕN(X),f(ϕ)=ψΦ(ϕ)ψ))ul  =(ψN(Y)((f)L(Φ)(ψ)ψ))ul  =(f)L(Φ).

    So, f(Φ)=(f)L(Φ). Similarly we can show  ΦLN(X), Φ0N(X), f(Φ)=(f)L(Φ). Hence, f is a fuzzy weakly complete homomorphism.

    (3) Commutativity.  xX,

    fιX(x)=f(ιx)  =f(ιulx)  =fL(ιx)ul  =ιf(x)  =ιYf(x).

    (4) f is unique. Assume that there is g:N(X)N(Y) such that gιX=ιYf.

     ϕN(X),

    g(ϕ)=g((ιX)L(ϕ))  =gL((ιX)L(ϕ))  =(ιYf)L(ϕ)  =(f)L((ιX)L(ϕ))  =f((ιX)L(ϕ))  =f(ϕ).

    (Sufficiency) Assume that there is a fuzzy weakly complete homomorphism f:XY such that fιX=ιYf.  0XALX. If Au0X, then (ιX)L(Au)0N(X).

    fL(Au)l=ιY(fL(Au))  =(ιYf)L(Au)  =(fιX)L(Au)  =(f)L((ιX)L(Au))  =f((ιX)L(Au))  =f((ιX)L(A))  =(fιX)L(A)  =(ιYf)L(A)  =(ιY)LfL(A)  =fL(A)ul.

    If Au=0X, fL(A)ul=(ιY)L(fL(A))=(f)L((ιX)L(A))=f((ιX)L(A))=f(Aul)=f(0lX)=f(1X) =f((ιX)L(1X))=(fιX)L(1X)=(ιYf)L(1X)=(ιY)LfL(1X)=fL(1X)ul.

    Hence, fL(A)ul=fL(1X)ul. Therefore, f is fuzzy weakly lower cut-stable. Similarly, f is also fuzzy weakly upper cut-stable.

    In this section, we explore the conditions under which the extension map to be fuzzy order isomorphism.

    Definition 4.1. Let (X,e) be a fuzzy poset, AX. If  xX, there exists ϕLA such that μx=ϕu, then we call (X,e) fuzzy A-dense.

    Next we give an example of fuzzy A-dense.

    Example 4.2. Let X={0,a,b,c}, L={0,12,1} and =, the fuzzy order eX is defined as follows:

    Let A={0,a,b}X, we can show 0X, there exists ϕ=χ0LA such that μ0=ϕu. aX, there exists ϕ=χ{0,a}LA such that μa=ϕu. bX, there exists ϕ=χ{0,b}LA such that μb=ϕu. cX, there exists ϕ=χ{0,c}LA such that μc=ϕu. This shows that (X,eX) is fuzzy A-dense.

    Proposition 4.3. Let (X,e) and (Y,e) be fuzzy posets. If f is fuzzy weakly cut-stable, then f is surjective iff Y is fuzzy f(X)-dense and (fL(1X))l=1lY.

    Proof. (Necessity) Suppose that f is surjective.

    (1) By the definition of f, (fL(1X))l=f(0ulX).

    (2) (fL(1X))l=1lY. Since  yY,

    (fL(1X))l(y)=zY(fL(1X)(z)e(y,z))  =zY((xX,f(x)=z1X(x))e(y,z))  =xXe(y,f(x)).

    Thus,

    1lY(y)=zY(1Y(z)e(y,z))  =zYe(y,z)  xXe(y,f(x))  =(fL(1X))l(y).

    Conversely, we need to show (fL(1X))l1lY.  zY,ιzN(Y), as f is surjective, there exists AN(X) such that f(Aul)=ιz,ιz=f(Aul)f(0ulX)=(fL(1X))l. Thus 1lY(y)=zY1Y(z)e(y,z)=zYιz(y)(fL(1X))l. Therefore, (fL(1X))l=1lY.

     yY, since f is surjective, there exists AN(X) such that f(Aul)=ιy=(ιy)ul. If A0X, then f(Aul)=(fL(A))ul=(fL(A)f(X))ul, we have μy=(fL(A)f(X))u. If A=0X, then f(Aul)=(fL(1X))l=(1Y)l, we have μy=1Y=0uY=0Yuf(Y). Thus Y is fuzzy f(X)-dense.

    (Sufficiency) Let Y be fuzzy f(X)-dense and (fL(1X))l=(1Y)l. First we need to show  yY, ιy has preimage. Since Y is fuzzy f(X)-dense, there exists BLf(X) such that μy=Bu. By BLf(X), fL(B)LX. If fL(B)0X, notice that  yY,fL(fL(B))(y)=xX,f(x)=yfL(B)(x)=xX,f(x)=yB(f(x))=B(y), we have fL(fL(B))=B, then f(fL(B)ul)=(fL(fL(B)))ul=Bul=μly=ιy.

    If fL(B)=0X, notice that  yY,

    fL(0X)u(y)=zYfL(0X)(z)e(z,y)  =xX(xX,f(x)=z0X(x))e(z,y)  =1  =1Y(y).

    We have (1Y)l=fL(0X)ul, then

    f(fL(B)ul)=f(1lX)  =fL(1lX)  =(1Y)l  =fL(0X)ul  =μly  =ιy.

    Therefore, (fL(B))ul is the preimage of ιy.

    Suppose that BN(Y). The above tells us that  yY, there exists ByLf(X) such thatf((fL(By))ul)=ιy. Having B=yYB(y)χy implies that Bul=(yYB(y)χy)ul. Define ΦLN(X), yY.

    Φ(ψ)={B(y),  ψ=(fL(By))ul,0,  otherwises.

    Notice that (yYB(y)ιy)ul=(yYB(y)χy)ul.  zY,

    (yYB(y)ιy)u(z)=z1Y((yYB(y)ιy(z1))e(z1,z))  =yY(B(y)e(y,z))  =Bu(z)  =z1Y(B(z1)e(z1,z))  =z1Y(yY(B(y)χy(z1))e(z1,z))  =(yYB(y)χy)u(z).
    f(Φ)=(f)L(Φ)  =(ϕN(Y)(f)L(Φ)(ϕ)ϕ)ul  =(ϕN(Y)(ψN(X),f(ψ)=ϕΦ(ψ))ϕ)ul  =(ψN(X)Φ(ψ)f(ψ))ul  =(yYB(y)(fL(By))ul)ul  =(yYB(y)ιy)ul  =(yYB(y)χy)ul  =Bul  =B.

    Theorem 4.4. Let f:(X,e)(Y,e) be fuzzy weakly cut-stable. Then f is fuzzy order isomorphism if and only if e(f(x),f(y))e(x,y) for all x,yX, Y is fuzzy f(X)-dense and (fL(1X))l=1lY.

    Proof. (Necessity) Let f be fuzzy order isomorphism.  x,yX,e(f(x),f(y))=sub(ιf(x),ιf(y)) =sub(f(ιx),f(ιy))sub(ιx,ιy)=e(x,y).

    (Sufficiency) By Proposition 4.3, we have that f is surjective, we only need to show f is order embedding. That is  A,BLX,sub(f(Aul),f(Bul))sub(Aul,Bul).

    If A=0X, obviously. If A0X, when B0X,

    sub(f(Aul),f(Bul))=sub(fL(A)ul,fL(B)ul)sub(fL(B)u,fL(A)u)=(yYfL(B)u(y)fL(A)u(y)=yY(z1YfL(B)(z1)e(z1,y))(z2YfL(A)(z2)e(z2,y))=yY(x1YB(x1)e(f(x1),y))(x2XA(x2)e(f(x2),y))xX(x1XB(x1)e(f(x1),f(x)))(x2XA(x2)e(f(x2),f(x)))xX(x1XB(x1)e(x1,x))(x2XA(x2)e(x2,x))=sub(Bu,Au)sub(Aul,Bul).

    When B=0X, notice that

    sub(1Y,fL(A)u)=yY(1fL(A)u(y))  =yY(zYfL(A)(z)e(z,y))  =yY(xXA(x)e(f(x),y))  x1X(xXA(x)e(f(x),f(x1)))  x1X(1X(x1)(xXA(x)e(x,x1)))  =x1X(1X(x1)Au(x1))  =sub(1X,Au)  sub(Aul,1lX).

    Therefore,

    sub(f(Aul),f(Bul))=sub(fL(A)ul,fL(1X)l)  =sub(fL(A)ul,1lY)  sub(1Y,fL(A)u)  sub(Aul,1lX)  =sub(Aul,Bul).

    In this paper, we proposed the definitions of fuzzy weakly lower (upper) cut-stable map, fuzzy weakly lower (upper) cut-continuous map, and fuzzy weakly cut-preserving map. Furthermore, we obtained the equivalent characterization and the extension property of fuzzy weakly cut-stable map. In addition, we showed that the extension map of the fuzzy weakly cut-stable map was fuzzy order isomorphism under some conditions.

    The authors express their gratitude to the anonymous reviewers and editor for their careful reading of the manuscript and for many valuable remarks and suggestions.

    This work was supported by the National Natural Science Foundation of China (Grant Nos.12001413), Natural Science Basic Research Program of Shaanxi (No.2019JQ-869 and No.2021JQ763) and Scientific Research Project of Education Department of Shaanxi Province (No.20JK0640 and No.19JK0317)

    The authors declare that there is no conflicts of interest regarding this manuscript.



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