The effects of contract mechanisms between the government and private hospitals on the social utility

In this work, we deal with a real healthcare system, in which public and private hospitals with different characteristics co-exist. While public hospitals have lower costs, they also suffer from long waiting times, diminishing the perceived quality of care for patients. Conversely, private hospitals, with their higher fees, offer shorter waiting periods, resulting in a more favorable perception of quality. A balanced healthcare system could offer societal benefits. Pricing strategies greatly influence a patient's hospital selection. For instance, reduced fees in private hospitals attract more patients, consequently reducing overcrowding in public facilities and elevating the overall quality of services provided. This study aims to develop pricing models to foster a balanced and socially advantageous healthcare system. Within this system, private hospital pricing is determined through contract mechanisms with the government. Thus, we delve into the ramifications of various contract models between the government and private hospitals on social utility. Our findings underscore the communal advantages of contract mechanisms. Furthermore, we generalize the proposed models to be applicable to similar systems.info:eu-repo/semantics/publishedVersio

Longitudinal metabolomics analysis reveals the acute effect of cysteine and NAC included in the combined metabolic activators

Growing evidence suggests that the depletion of plasma NAD+ and glutathione (GSH) may play an important role in the development of metabolic disorders. The administration of Combined Metabolic Activators (CMA), consisting of GSH and NAD+ precursors, has been explored as a promising therapeutic strategy to target multiple altered pathways associated with the pathogenesis of the diseases. Although studies have examined the therapeutic effect of CMA that contains N-acetyl-L-cysteine (NAC) as a metabolic activator, a system-wide comparison of the metabolic response to the administration of CMA with NAC and cysteine remains lacking. In this placebo-controlled study, we studied the acute effect of the CMA administration with different metabolic activators, including NAC or cysteine with/without nicotinamide or flush free niacin, and performed longitudinal untargeted-metabolomics profiling of plasma obtained from 70 well-characterized healthy volunteers. The time-series metabolomics data revealed the metabolic pathways affected after the administration of CMAs showed high similarity between CMA containing nicotinamide and NAC or cysteine as metabolic activators. Our analysis also showed that CMA with cysteine is well-tolerated and safe in healthy individuals throughout the study. Last, our study systematically provided insights into a complex and dynamics landscape involved in amino acid, lipid and nicotinamide metabolism, reflecting the metabolic responses to CMA administration containing different metabolic activators

The Healing Effects of Autologous Mucosal Grafts in Experimentally Injured Rabbit Maxillary Sinuses

Objectives Healing processes of the nose and paranasal sinuses are quite complex, and poorly understood. In this study, we aimed to compare the effect of mucosal autologous grafts on the degenerated rabbit maxillary sinus mucosa with spontaneous wound healing. It is hypothesized that mucosal grafts will enhance ciliogenesis and improve the morphology of regenerated cilia. Methods Ten female New Zealand rabbits were included in the study. They underwent external maxillary sinus surgery through a transcutaneous approach. A total of 20 maxillary sinuses were randomly divided into 2 groups: ‘spontaneous healing group’ and ‘autologous graft group.’ The animals were sacrificed at the 14th day after the surgery. Scanning electron microscope (SEM), and light microscope were used for the evaluation. Results Cellular composition of the graft group is better than the spontaneous healing group. The graft group had larger areas covered with ciliary epithelium than the spontaneous healing group, and the mean length of the cilias were also longer. Additionally, there were wider cilia with abnormal morphology areas in the spontaneous healing group. Conclusion In our opinion, covering of the denuded areas with a graft improves re-epithelization, and may prevent the early complications after sinus surgeries

AN AUTOMATED MULTI-OBJECTIVE INVIGILATOR-EXAM ASSIGNMENT SYSTEM

This paper is concerned with the invigilator-exam assignment problem. A web-based Automated Invigilator Assignment System (AIAS), consists of a mathematical model; a database storing the information and web-based user interfaces is constructed to solve the problem by providing an environment for a practical usage. The core of the system is the mathematical model developed for obtaining the exact solution. We conclude the paper by presenting a real-life problem solved by the proposed approach.Invigilator assignment, multi-objective programming, web-based automated assignment system

An incremental piecewise linear classifier based on polyhedral conic separation

In this paper, a piecewise linear classifier based on polyhedral conic separation is developed. This classifier builds nonlinear boundaries between classes using polyhedral conic functions. Since the number of polyhedral conic functions separating classes is not known a priori, an incremental approach is proposed to build separating functions. These functions are found by minimizing an error function which is nonsmooth and nonconvex. A special procedure is proposed to generate starting points to minimize the error function and this procedure is based on the incremental approach. The discrete gradient method, which is a derivative-free method for nonsmooth optimization, is applied to minimize the error function starting from those points. The proposed classifier is applied to solve classification problems on 12 publicly available data sets and compared with some mainstream and piecewise linear classifiers. © 2014, The Author(s)

A sharp augmented Lagrangian-based method in constrained non-convex optimization

In this paper, a novel sharp Augmented Lagrangian-based global optimization method is developed for solving constrained non-convex optimization problems. The algorithm consists of outer and inner loops. At each inner iteration, the discrete gradient method is applied to minimize the sharp augmented Lagrangian function. Depending on the solution found the algorithm stops or updates the dual variables in the inner loop, or updates the upper or lower bounds by going to the outer loop. The convergence results for the proposed method are presented. The performance of the method is demonstrated using a wide range of nonlinear smooth and non-smooth constrained optimization test problems from the literature

ICF: An algorithm for large scale classification with conic functions

Incremental Conic Functions (ICF) algorithm is developed for solving classification problems based on mathematical programming. This algorithm improves previous version of conic function-based classifier construction in terms of computational speed. Furthermore, the incremental step avoids the a-priori knowledge of number of sub-classes (which is a necessary parameter in the clustering step of this classification algorithm). Test results show that ICF is, on the average almost 3-times faster than previous versions without sacrificing accuracy. Python 2.7 implementation and software explanations are provided. Keywords: Polyhedral conic functions, Mathematical programming, Classification, Machine learnin

An incremental clustering algorithm based on hyperbolic smoothing

Clustering is an important problem in data mining. It can be formulated as a nonsmooth, nonconvex optimization problem. For the most global optimization techniques this problem is challenging even in medium size data sets. In this paper, we propose an approach that allows one to apply local methods of smooth optimization to solve the clustering problems. We apply an incremental approach to generate starting points for cluster centers which enables us to deal with nonconvexity of the problem. The hyperbolic smoothing technique is applied to handle nonsmoothness of the clustering problems and to make it possible application of smooth optimization algorithms to solve them. Results of numerical experiments with eleven real-world data sets and the comparison with state-of-the-art incremental clustering algorithms demonstrate that the smooth optimization algorithms in combination with the incremental approach are powerful alternative to existing clustering algorithms

Research University Identity, Quality Problems in PhD and Residency Education and Search of Contemporary University in Turkey

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