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We define a positive constant M ¯ as follows: M ¯ = max i ∈ N { sup s ∈ [ − τ i, 0 ] | Y i ( s ) | }.
Before the design procedure, we define a positive constant as follows: tau_{k}=big| h_{k}^big| ^{2},quad k=0,1,2, ldots,n.
To state our first result, we define a positive constant A p by A p : = C 1 p − 1 ( C 1 C 0 ) p − 1 ≥ 1, (2). which is equal to 1 in the case of A ( x, y ) = | y | p − 2 y (i.e., the case of the p-Laplacian) because we can choose C 0 = C 1 = p − 1.
We define a positive constant M as follows: M = max i j ∈ J { sup s ∈ ( − ∞, 0 ] Y i j ( s ) }. Let K be a positive number such that Y i j ( t ) ≤ M < M + 1 = K for all t ∈ ( − ∞, 0 ], i j ∈ J. (3.11).
Define a positive constant by Gamma_{0}:=max_{tin I} int_{0}^{1} G t, s),ds=frac{beta delta +alpha delta +alpha gamma /2}{rho }. (2.8).
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Throughout the present paper, M is defined as a positive constant.
where is a probability density function defined on (see [9, 10]) and induces an invertible operator defined on and there exists a positive constant and such that and.
where D is a positive constant defined in Lemma 2.2.
Let be nonnegative sequences defined on, and let be a positive constant.
end{aligned} By Lemma 3.4 there exist a point (omega_{k+1}inpartial H(z_{k+1},z_{k})) defined as in (15) and a positive constant (C_{2}>0) such that Vert omega_{k+1} Vert leq C_{2} bigl( Vert z_{k+1}-z_{k} Vert + Vert z_{k}-z_{k-1} Vert bigr).
For a positive constant M, define v_{M}(x)=minbigl{ u(x),Mbigr} and choose (v=v_{M}^{kp+1}) ((kge0)) as a test function in (2.1).
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Since I tried Ludwig back in 2017, I have been constantly using it in both editing and translation. Ever since, I suggest it to my translators at ProSciEditing.

Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com