714 research outputs found

    Mcmc- Based Optimization And Application

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    In the thesis, we study the theory of Markov Chain Monte Carlo (MCMC) and its application in statistical optimization. The MCMC method is a class of evolutionary algorithms for generating samples from given probability distributions. In the thesis, we first focus on the methods of slice sampling and simulated annealing. While slice sampling has a merit to generate samples based on the underlying distribution with adjustable step size, simulated annealing can facilitate samples to jump out of local optima and converge quickly to the global optimum. With this MCMC method, we then solve two practical optimization problems. The first problem is image transmission over varying channels. Existing work in media transmission generally assumes that channel condition is stationary. However, communication channels are often varying with time in practice. Adaptive design needs frequent feedback for channel updates, which is often impractical due to the complexity and delay. In this application, we design an unequal error protection scheme for image transmission over noisy varying channels based on MCMC. First, the problem cost function is mapped into a multi-variable probability distribution. Then, with the “detailed balance , MCMC is used to generate samples from the mapped stationary distribution so that the optimal solution is the one that gives the lowest data distortion. We also show that the final rate allocation designed with this method works better than a conventional design that considers the mean value of the channel. In the second application, we consider a terminal-location-planning problem for intermodal transportation systems. With a given number of potential locations, it needs to find the most appropriate number of terminals and their locations to provide the economically most efficient operation when multiple service pairs exist simultaneously. The problem also has an inherent issue that for a particular planning, the optimal route paths must be determined for the co-existing service pairs. To solve this NP-hard problem, we design a MCMC-based two-layer method. The lower-layer is an optimal routing design for all service pairs given a particular planning that considers both efficiency and fairness. The upper-layer is finding the optimal planning based on MCMC with the stationary distribution that is mapped from the cost function. The effectiveness of this method is demonstrated through computer simulations and comparison with one state-of-the-art method. The work of this thesis has shown that a MCMC-method, consisting of both slice sampling and simulated annealing, can be successfully applied to solving practical optimization problems. Particularly, the method has advantages in dealing with high-dimensional problems with large searching spaces

    Report on Provider-Client Interaction From 68 Methadone Maintenance Clinics in China.

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    Provider-client interaction is an integral of clinical practice and central to the delivery of high-quality medical care. This article examines factors related to the provider-client interaction in the context of methadone maintenance treatment (MMT). Data were collected from 68 MMT clinics in China. In total, 418 service providers participated in the survey. Linear mixed effects regression models were performed to identify factors associated with provider-client interaction. It was observed that negative attitude toward drug users was associated with lower level of provider-client interaction and less time spent with each client. Other factors associated with lower level of interaction included being female, being younger, being a nurse, and fewer years in medical field. Higher provider-client interaction was associated with provider reported job satisfaction. The findings of this study call for a need to address provider negative attitudes that can impact provider-client interaction and the effectiveness of MMT. Future intervention efforts targeting MMT providers should be tailored by gender, provider type, and medical experiences

    The Important Functions of GSH-Dependent Enzyme Glutaredoxin 2 (Grx2)

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    Reactive oxygen species (ROS) are generated at a very high rate throughout our lives as part of normal aerobic life. Glutathione (GSH), normally an antioxidant molecule that scavenges free radicals, oxidizes to form glutathione mixed disulfide (GSSG). As the GSSG/GSH ratio increases, GSSG naturally adds to other proteins, causing protein glutathionylation. Protein glutathionylation, defined as the reversible formation of a mixed disulfide (PSSG) between protein thiols (P-SH) and glutathione (GSH), appears to be the most important mode of thiol oxidation. In my chapter, we will discuss the important roles of GSH and GSH-dependent enzymes in health and disease, with the emphasis on glutaredoxin and thioredoxin systems. Their structures, catalytic reaction mechanisms, major physiological functions, and associations with diseases will be summarized in my chapter. We will also mention how GSH-dependent enzymes play a role in each major organ systems including the nervous, cardiovascular, immune, and visual system
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