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A new definition of the filled function is presented in this paper. Based on the definition, a new filled function is presented, and a global optimization algorithm is developed. The implementation of the algorithm on several test problems is reported with satisfactory numerical results. The numerical experiments further show that the algorithm may solve higher dimensional global optimization problems. [ABSTRACT FROM AUTHOR]

For the nonconvex quadratic programming problem, a new linear programming relaxation bound-and-reduce algorithm is proposed and its convergence is proved. In this algorithm, a new hyper-rectangle partition technique and a new linear programming relaxation tactics are used. At the same time, the hyper-rectangular reduction method is used to raise its convergent speed. The numerical results demonstrate the effectiveness and feasibility of the proposed algorithm. [ABSTRACT FROM AUTHOR]

Abstract: In this paper, by solving the relaxed quasiconcave programming problem in outcome space, a new global optimization algorithm for convex multiplicative programming is presented. Two kinds of techniques are employed to establish the algorithm. The first one is outer approximation technique which is applied to shrink relaxation area of quasiconcave programming problem and to compute appropriate feasible points and to raise the capacity of bounding. And the other one is branch and bound technique which is used to guarantee global optimization. Some numerical results are presented to demonstrate the effectiveness and feasibility of the proposed algorithm. [Copyright &y& Elsevier]

Abstract: This paper presents an outcome-space finite algorithm for solving linear multiplicative programming, in each iteration of which a convex quadratic programming is only solved. In the paper, we give a global optimization condition on a class of multiplicative programming problems and prove that the proposed algorithm is finite terminative and gain a global optimal solution of the former problem when it stops. It can be shown by the numerical results that the proposed algorithm is effective and the computational results can be gained in short time. [Copyright &y& Elsevier]

Abstract: The paper presents a new rectangle branch-and-reduce approach for solving nonconvex quadratic programming problems, in which a new lower approximate linear functions of the quadratic function over an n-rectangle is given to determine a lower bound of the global optimal value of the original problem over each rectangle, and a simple two-partition technique on rectangle is used, as well as the tactics on reducing and deleting subrectangles is used to accelerate the convergence of the proposed algorithm. The proposed algorithm is proved to be convergent and shown to be effective with numerical results. [Copyright &y& Elsevier]

Abstract: In this paper a class of augmented Lagrangians is considered, for solving equality constrained nonlinear optimization problems via unconstrained minimization techniques. This class of augmented Lagrangians is obtained by multiplying the penalty term on the first order necessary optimality condition in a class of augmented Lagrangians of Di Pillo and Grippo by a penalty parameter. Under suitable assumptions, the exactly corresponding relationship is established between the solution of the original constrained problem and the unconstrained minimization of this class of augmented Lagrangians on the product space of problem variables and multipliers for sufficiently large but finite values of penalty parameters. Therefore, a solution of the original constrained problem and the corresponding values of the Lagrange multipliers can be found by performing a single unconstrained minimization of an augmented Lagrangian on the product space of problem variables and multipliers. In particular, for quadratic programming problems with equality constraints, the optimizer is obtained by minimizing a quadratic function on the expanded space. [Copyright &y& Elsevier]

Abstract: In this paper a deterministic global optimization algorithm is proposed for locatingthe global minimum of the generalized geometric programming (GGP) problem. By utilizing an exponential variable transformation and some other techniques the initial nonconvex problem (GGP) is reduced to a typical reverse convex programming (RCP). Then a linear relaxation of problem (RCP) is obtained based on the famous arithmetic-geometric mean inequality and the linear upper bound of the reverse constraints inside some hyperrectangle region. The proposed branch and bound algorithm is convergent to the global minimum through the successive refinement of the linear relaxation of the feasible region of the objective function and the solutions of a series of linear optimization problems. And finally the numerical experiment is given to illustrate the feasibility and the robust stability of the present algorithm. [Copyright &y& Elsevier]

Abstract: In this paper, a new discrete filled function method is proposed for finding a global minimizer of integer programming problems. Only one parameter is included in the proposed filled function and it does not need to be adjusted further when it is taken as large as possible; moreover, the current local minimizer obtained by minimizing the proposed filled function will be one of the local minimizers of the original problem and it is better than the minimizers found previously. Thus it is not necessary to use a local search method to the original function. As a result, the computation cost of the proposed discrete filled function method is relatively low. Numerical results demonstrate the effectiveness of the proposed method. [Copyright &y& Elsevier]

• Cardiomyocyte contributes to elevation of Dectin-1 expression post-MI. • Silencing Dectin-1 improves cardiac remodeling and function in the ischemic heart. • Dectin-1 aggravates MI induced cardiac dysfunction by partially activating NF- κ B/NLRP3 axis. The myocardial inflammatory response is a consequence of myocardial infarction (MI), which may deteriorate cardiac remodeling and lead to dysfunction in the heart post-MI. Dectin-1 is a c-type lectin, which has been shown to regulate innate immune responses to pathogens. However, the role of Dectin-1 in the heart diseases remains largely unknown. In this study, we aimed to investigate the effects of Dectin-1 on cardiac remodeling post-MI. We found that cardiac Dectin-1 mRNA and protein expressions were significantly elevated in C57BL/6 mice after MI. In vitro , hypoxia induced cardiomyocyte injury in parallel with increased Dectin-1 protein expression. Knockdown of Dectin-1 remarkably attenuated cardiomyocyte death under hypoxia and lipopolysaccharide (LPS) stimulation. In vivo administration of adeno-associated virus serotype 9 mediated silencing of Dectin-1, which significantly decreased cardiac fibrosis, dilatation, and improved cardiac function in the mice post-MI. At the molecular level, downregulation of Dectin-1 dramatically suppressed up-regulation of nuclear factor-κB (NF-κB), nucleotide-binding oligomerization domain-like receptor family pyrin domain-containing 3 (NLRP3), and the inflammatory genes involved in fibrogenesis and cardiac remodeling after MI. Furthermore, treatment with BAY11-7082, an inhibitor of NF-κB, repressed the activation of NF-κB, and attenuated LPS induced elevation of NLRP3 and cell death in cardiomyocytes. Collectively, upregulation of Dectin-1 in cardiomyocytes post-MI contributes to cardiac remodeling and cardiac dysfunction at least partially by activating NF-κB and NLRP3. This study identified Dectin-1 as a promising therapeutic target for ischemic heart disease. [ABSTRACT FROM AUTHOR]