668 research outputs found

    high-order proximal point algorithm for the monotone variational inequality problem and its application

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    The proximal point algorithm (PPA) has been developed to solve the monotone variational inequality problem. It provides a theoretical foundation for some methods, such as the augmented Lagrangian method (ALM) and the alternating direction method of multipliers (ADMM). This paper generalizes the PPA to the ppth-order (p‚Č•1p\geq 1) and proves its convergence rate O(1/kp/2)O \left(1/k^{p/2}\right) . Additionally, the ppth-order ALM is proposed based on the ppth-order PPA. Some numerical experiments are presented to demonstrate the performance of the ppth-order ALM

    A linearly convergent method for solving high-order proximal operator

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    Recently, various high-order methods have been developed to solve the convex optimization problem. The auxiliary problem of these methods shares the general form that is the same as the high-order proximal operator proposed by Nesterov. In this paper, we present a linearly convergent method to solve the high-order proximal operator based on the classical proximal operator. In addition, some experiments are performed to demonstrate the performance of the proposed method

    The role of the peripheral system dysfunction in the pathogenesis of sepsis-associated encephalopathy

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    Sepsis is a condition that greatly impacts the brain, leading to neurological dysfunction and heightened mortality rates, making it one of the primary organs affected. Injury to the central nervous system can be attributed to dysfunction of various organs throughout the entire body and imbalances within the peripheral immune system. Furthermore, central nervous system injury can create a vicious circle with infection-induced peripheral immune disorders. We collate the pathogenesis of septic encephalopathy, which involves microglial activation, programmed cell death, mitochondrial dysfunction, endoplasmic reticulum stress, neurotransmitter imbalance, and blood‚Äďbrain barrier disruption. We also spotlight the effects of intestinal flora and its metabolites, enterocyte-derived exosomes, cholinergic anti-inflammatory pathway, peripheral T cells and their cytokines on septic encephalopathy

    Optimasi Portofolio Resiko Menggunakan Model Markowitz MVO Dikaitkan dengan Keterbatasan Manusia dalam Memprediksi Masa Depan dalam Perspektif Al-Qur`an

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    Risk portfolio on modern finance has become increasingly technical, requiring the use of sophisticated mathematical tools in both research and practice. Since companies cannot insure themselves completely against risk, as human incompetence in predicting the future precisely that written in Al-Quran surah Luqman verse 34, they have to manage it to yield an optimal portfolio. The objective here is to minimize the variance among all portfolios, or alternatively, to maximize expected return among all portfolios that has at least a certain expected return. Furthermore, this study focuses on optimizing risk portfolio so called Markowitz MVO (Mean-Variance Optimization). Some theoretical frameworks for analysis are arithmetic mean, geometric mean, variance, covariance, linear programming, and quadratic programming. Moreover, finding a minimum variance portfolio produces a convex quadratic programming, that is minimizing the objective function √į√į¬•with constraints√į √į √į¬• ¬• √įand√į¬ī√į¬• = √į. The outcome of this research is the solution of optimal risk portofolio in some investments that could be finished smoothly using MATLAB R2007b software together with its graphic analysis

    Measurement of the top quark forward-backward production asymmetry and the anomalous chromoelectric and chromomagnetic moments in pp collisions at ‚ąös = 13 TeV