Sequential decision making with partially ordered preferences

This paper presents new insights and novel algorithms for strategy selection in sequential decision making with partially ordered preferences; that is, where some strategies may be incomparable with respect to expected utility. We assume that incomparability amongst strategies is caused by indeterminacy/imprecision in probability values. We investigate six criteria for consequentialist strategy selection: Gamma-Maximin, Gamma-Maximax, Gamma-Maximix, Interval Dominance, Maximality and E-admissibility. We focus on the popular decision tree and influence diagram representations. Algorithms resort to linear/multilinear programming; we describe implementation and experiments. (C) 2010 Elsevier B.V. All rights reserved.

Nop53p interacts with 5.8S rRNA co-transcriptionally, and regulates processing of pre-rRNA by the exosome

In eukaryotes, pre-rRNA processing depends on a large number of nonribosomal trans-acting factors that form intriguingly organized complexes. One of the early stages of pre-rRNA processing includes formation of the two intermediate complexes pre-40S and pre-60S, which then form the mature ribosome subunits. Each of these complexes contains specific pre-rRNAs, ribosomal proteins and processing factors. The yeast nucleolar protein Nop53p has previously been identified in the pre-60S complex and shown to affect pre-rRNA processing by directly binding to 5.8S rRNA, and to interact with Nop17p and Nip7p, which are also involved in this process. Here we show that Nop53p binds 5.8S rRNA co-transcriptionally through its N-terminal region, and that this protein portion can also partially complement growth of the conditional mutant strain Delta nop53/GAL:NOP53. Nop53p interacts with Rrp6p and activates the exosome in vitro. These results indicate that Nop53p may recruit the exosome to 7S pre-rRNA for processing. Consistent with this observation and similar to the observed in exosome mutants, depletion of Nop53p leads to accumulation of polyadenylated pre-rRNAs.

Structure and thermal reactivity of Zn(II) salts of isocinchomeronic acid (2,5-pyridinedicarboxylic acid)

The synthesis, an improved refined crystal and molecular structure re-determination, and the thermal decomposition behavior of two Zn(II) derivatives of isocinchomeronic acid (2,5-pyridinedicarboxylic acid or H(2)2,5-pydc) are presented. [Zn(2,5-pydc)(H(2)O)(3)Zn(2,5-pydc)(H(2)O)(2)](2) (1) crystallizes in the triclinic P-1 space group with a = 7.106(2), b = 11.450(2), c = 11.869(1) angstrom, alpha = 107.29(1), beta = 104.08(1), gamma = 90.32(2)degrees, and Z = 2. [Zn(2,5-pydc)(H(2)O)(2)] center dot H(2)O (2) is orthorhombic (P2(1)2(1)2(1) space group), with a = 7.342(1), b = 9.430(1), c = 13.834(2) angstrom, and Z = 4. The structures were refined to agreement R(1)-factors of 0.0315 (1) and 0.0336 (2). Complex (1) is arranged as molecular Zn(4)(2,5-pydc)(4)(H(2)O)(10) tetramers, the cages of which define channels that remain unblocked by anions. Compound (2) is polymeric with Zn(2,5-pydc)(H(2)O)(2) and Zn(2,5-pydc)(H(2)O)(3) units linked through bridging ligands. Both compounds were synthesized under mild conditions in aqueous media, without need to resort to hydrothermal media. Changing the pH from 4.51 to 5.75 suffices to direct the chemical processes toward the orthorhombic compound rather than to the triclinic one.

Hypothesis testing in an errors-in-variables model with heteroscedastic measurement errors

In many epidemiological studies it is common to resort to regression models relating incidence of a disease and its risk factors. The main goal of this paper is to consider inference on such models with error-prone observations and variances of the measurement errors changing across observations. We suppose that the observations follow a bivariate normal distribution and the measurement errors are normally distributed. Aggregate data allow the estimation of the error variances. Maximum likelihood estimates are computed numerically via the EM algorithm. Consistent estimation of the asymptotic variance of the maximum likelihood estimators is also discussed. Test statistics are proposed for testing hypotheses of interest. Further, we implement a simple graphical device that enables an assessment of the model`s goodness of fit. Results of simulations concerning the properties of the test statistics are reported. The approach is illustrated with data from the WHO MONICA Project on cardiovascular disease. Copyright (C) 2008 John Wiley & Sons, Ltd.