First-Principles Calculation of Electric Field Gradients and Hyperfine Couplings in YBa2Cu3O7

The local electronic structure of YBa2Cu3O7 has been calculated using first-principles cluster methods. Several clusters embedded in an appropriate background potential have been investigated. The electric field gradients at the copper and oxygen sites are determined and compared to previous theoretical calculations and experiments. Spin polarized calculations with different spin multiplicities have enabled a detailed study of the spin density distribution to be made and a simultaneous determination of magnetic hyperfine coupling parameters. The contributions from on-site and transferred hyperfine fields have been disentangled with the conclusion that the transferred spin densities essentially are due to nearest neighbour copper ions only with marginal influence of ions further away. This implies that the variant temperature dependencies of the planar copper and oxygen NMR spin-lattice relaxation rates are only compatible with commensurate antiferromagnetic correlations. The theoretical hyperfine parameters are compared with those derived from experimental data.Comment: 14 pages, 12 figures, accepted to appear in EPJ

The effects of training on the quantification of uncertainty

The use of intuitive heuristics has been put forward as an explanation for people’s assessment of probabilities (Kahneman & Tversky, 1972, 1973; Tversky & Kahneman, 1971, 1974). This phenomenon is seen as robust since “experts” (professional psychologists) make use of the same heuristics as “novices” (laypeople), despite having “had extensive training in statistics” (Tversky & Kahneman, 1974, p. 1130). However, replacing probability calculus with heuristics can lead to systematic errors and biases in probabilistic judgments. This study was designed to investigate the effects of statistical training on how people think about probabilistic judgments. Subjects’ knowledge base of probabilistic concepts, as defined by the number of correct answers on the Probability Knowledge Questionnaire, was assessed prior to receiving (or not) a brief training session. Immediately following training, subjects completed a Probability Test which consisted of ten Tversky and Kahneman (e.g., 1974) problems. The findings suggested that the training served to make a statistical approach to the probability test problems more salient. It was also observed that “novices”, with training, correctly solved a significantly higher proportion of test problems than did “experts” with no training. Finally, training served to increase subjects’ judgmental accuracy as measured by confidence ratings. The training session, which was designed to sensitize subjects to some basic probabilistic concepts, was successful in reducing the use of heuristics. Information on why people use heuristics and their robustness appears to point to a minimal probability knowledge base

Eperythrozoonosis In Swine

Eperythrozoonosis is an acute febrile, icteroanemic disease of shoats caused by the rickettsial organism Eperythrozoon spp. There are two species which are commonly associated with swine, E. suis, which produces a febrile disease, and E. parvum, which is innoxious

Bayesian Value-of-Information Analysis: An Application to a Policy Model of Alzheimer's Disease

A framework is presented which distinguishes the conceptually separate decisions of which treatment strategy is optimal from the question of whether more information is required to inform this choice in the future. The authors argue that the choice of treatment strategy should be based on expected utility and the only valid reason to characterise the uncertainty surrounding outcomes of interest is to establish the value of acquiring additional information. A Bayesian decision theoretic approach is demonstrated though a probabilistic analysis of a published policy model of Alzheimer’s disease. The expected value of perfect information is estimated for the decision to adopt a new pharmaceutical for the population of US Alzheimer’s disease patients. This provides an upper bound on the value of additional research. The value of information is also estimated for each of the model inputs. This analysis can focus future research by identifying those parameters where more precise estimates would be most valuable, and indicating whether an experimental design would be required. We also discuss how this type of analysis can also be used to design experimental research efficiently (identifying optimal sample size and optimal sample allocation) based on the marginal cost and marginal benefit of sample information. Value-of-information analysis can provide a measure of the expected payoff from proposed research, which can be used to set priorities in research and development. It can also inform an efficient regulatory framework for new health care technologies: an analysis of the value of information would define when a claim for a new technology should be deemed “substantiated” and when evidence should be considered “competent and reliable” when it is not cost-effective to gather anymore information.stochastic CEA; Bayesian decision theory; value of information.

Modelling the cost effectiveness of interferon beta and glatiramer acetate in the management of multiple sclerosis

OBJECTIVE: To evaluate the cost effectiveness of four disease modifying treatments (interferon betas and glatiramer acetate) for relapsing remitting and secondary progressive multiple sclerosis in the United Kingdom. DESIGN: Modelling cost effectiveness. SETTING: UK NHS. PARTICIPANTS: Patients with relapsing remitting multiple sclerosis and secondary progressive multiple sclerosis. MAIN OUTCOME MEASURES: Cost per quality adjusted life year gained. RESULTS: The base case cost per quality adjusted life year gained by using any of the four treatments ranged from £42 000 ($66 469; 61 630) to £98 000 based on efficacy information in the public domain. Uncertainty analysis suggests that the probability of any of these treatments having a cost effectiveness better than £20 000 at 20 years is below 20%. The key determinants of cost effectiveness were the time horizon, the progression of patients after stopping treatment, differential discount rates, and the price of the treatments. CONCLUSIONS: Cost effectiveness varied markedly between the interventions. Uncertainty around point estimates was substantial. This uncertainty could be reduced by conducting research on the true magnitude of the effect of these drugs, the progression of patients after stopping treatment, the costs of care, and the quality of life of the patients. Price was the key modifiable determinant of the cost effectiveness of these treatments

Report of Conference On Physical Education, February 27, 1918

A typed copy of a report on the Conference On Physical Education, dated February 27, 1918. It documents the proposals for how to implement better physical education for the nation\u27s children and lists participants at the conference.https://digitalcommons.ursinus.edu/fmhw_firstworldwar_documents/1074/thumbnail.jp

Letter From Philander Claxton to Francis Mairs Huntington-Wilson, March 15, 1918

A typed letter by Philander Claxton to Francis Mairs Huntington-Wilson, dated March 15, 1918. Within, Claxton writes to tell Wilson that he will be reaching out to Dr. Willard S. Small to get his input for Wilson\u27s pamphlet.https://digitalcommons.ursinus.edu/fmhw_firstworldwar_documents/1080/thumbnail.jp