The Effect of Acceptance Training on Psychological and Physical Health Outcomes in Elders with Chronic Conditions

This pilot trial investigated the short and long-term effects of Acceptance Training (ACT) intervention on acceptance, perceived health, functional status, anxiety, and depression in elders with chronic conditions living in retirement communities (RCs). The ACT intervention combined Rational Emotive Behavior Therapy with music, relaxation, and guided imagery during six weekly 2-hour sessions. Face-to-face interviews were conducted with 16 African-American and 46 White elders across four data collection points in six randomly selected RCs using well-established measures of perceived health, functional status, anxiety, and depression, and a measure of acceptance of chronic conditions adapted from a previous measure of acceptance of diabetes. While changes were found in perceived health, functional status, anxiety, and depression, the most significant changes occurred in the elders\u27 acceptance of chronic conditions immediately after the intervention (t = -2.62, P \u3c .02), and these changes persisted for 6 and 12 weeks (t\u27s = -2.74, -3.32, p\u27s \u3c .01), respectively. Although a 40% attrition rate reduced the sample size from 62 (N = 62) to 37 (N = 37), the significant increases in acceptance over time provide initial evidence for the fidelity of the ACT intervention

Preconditioning Markov Chain Monte Carlo Simulations Using Coarse-Scale Models

We study the preconditioning of Markov chain Monte Carlo (MCMC) methods using coarse-scale models with applications to subsurface characterization. The purpose of preconditioning is to reduce the fine-scale computational cost and increase the acceptance rate in the MCMC sampling. This goal is achieved by generating Markov chains based on two-stage computations. In the first stage, a new proposal is first tested by the coarse-scale model based on multiscale finite volume methods. The full fine-scale computation will be conducted only if the proposal passes the coarse-scale screening. For more efficient simulations, an approximation of the full fine-scale computation using precomputed multiscale basis functions can also be used. Comparing with the regular MCMC method, the preconditioned MCMC method generates a modified Markov chain by incorporating the coarse-scale information of the problem. The conditions under which the modified Markov chain will converge to the correct posterior distribution are stated in the paper. The validity of these assumptions for our application and the conditions which would guarantee a high acceptance rate are also discussed. We would like to note that coarse-scale models used in the simulations need to be inexpensive but not necessarily very accurate, as our analysis and numerical simulations demonstrate. We present numerical examples for sampling permeability fields using two-point geostatistics. The Karhunen--Loève expansion is used to represent the realizations of the permeability field conditioned to the dynamic data, such as production data, as well as some static data. Our numerical examples show that the acceptance rate can be increased by more than 10 times if MCMC simulations are preconditioned using coarse-scale models

Fermions as Global Correction: the QCD Case

It is widely believed that the fermion determinant cannot be treated in global acceptance-rejection steps of gauge link configurations that differ in a large fraction of the links. However, for exact factorizations of the determinant that separate the ultraviolet from the infrared modes of the Dirac operator it is known that the latter show less variation under changes of the gauge field compared to the former. Using a factorization based on recursive domain decomposition allows for a hierarchical algorithm that starts with pure gauge updates of the links within the domains and ends after a number of filters with a global acceptance-rejection step. Ratios of determinants have to be treated stochastically and we construct techniques to reduce the noise. We find that the global acceptance rate is high on moderate lattice sizes and demonstrate the effectiveness of the hierarchical filter.Comment: 36 pages, 9 figures; improved version to be published in Comput.Phys.Commun., new results for the topological charge presented in Figure

Rate theory for correlated processes: Double-jumps in adatom diffusion

We study the rate of activated motion over multiple barriers, in particular the correlated double-jump of an adatom diffusing on a missing-row reconstructed Platinum (110) surface. We develop a Transition Path Theory, showing that the activation energy is given by the minimum-energy trajectory which succeeds in the double-jump. We explicitly calculate this trajectory within an effective-medium molecular dynamics simulation. A cusp in the acceptance region leads to a sqrt{T} prefactor for the activated rate of double-jumps. Theory and numerical results agree

Results From The UKQCD Parallel Tempering Project

We present results from our study of the Parallel Tempering algorithm. We examine the swapping acceptance rate of a twin subensemble PT system. We use action matching technology in an attempt to maximise the swap acceptance rate. We model the autocorrelation times within Parallel Tempering ensembles in terms of autocorrelation times from Hybrid Monte Carlo. We present estimates for the autocorrelation times of the plaquette operator.Comment: LATTICE98(algorithms