Simulation-Based Finite and Large Sample Tests in Multivariate Regressions.

In the context of multivariate linear regression (MLR) models, it is well known that commonly employed asymptotic test criteria are seriously biased towards overrejection. In this paper, we propose a general method for constructing exact tests of possibly nonlinear hypotheses on the coefficients of MLR systems. For the case of uniform linear hypotheses, we present exact distributional invariance results concerning several standard test criteria. These include Wilks' likelihood ratio (LR) criterion as well as trace and maximum root criteria. The normality assumption is not necessary for most of the results to hold. Implications for inference are two-fold. First, invariance to nuisance parameters entails that the technique of Monte Carlo tests can be applied on all these statistics to obtain exact tests of uniform linear hypotheses. Second, the invariance property of the latter statistic is exploited to derive general nuisance-parameter-free bounds on the distribution of the LR statistic for arbitrary hypotheses. Even though it may be difficult to compute these bounds analytically, they can easily be simulated, hence yielding exact bounds Monte Carlo tests. Illustrative simulation experiments show that the bounds are sufficiently tight to provide conclusive results with a high probability. Our findings illustrate the value of the bounds as a tool to be used in conjunction with more traditional simulation-based test methods (e.g., the parametric bootstrap) which may be applied when the bounds are not conclusive.

Markovian Processes, Two-Sided Autoregressions and Finite-Sample Inference for Stationary and Nonstationary Autoregressive Processes.

In this paper, we develop finite-sample inference procedures for stationary and nonstationary autoregressive (AR) models. The method is based on special properties of Markov processes and a split-sample technique. The results on Markovian processes (intercalary independence and truncation) only require the existence of conditional densities. They are proved for possibly nonstationary and/or non-Gaussian multivariate Markov processes. In the context of a linear regression model with AR(1) errors, we show how these results can be used to simplify the distributional properties of the model by conditioning a subset of the data on the remaining observations. This transformation leads to a new model which has the form of a two-sided autoregression to which standard classical linear regression inference techniques can be applied. We show how to derive tests and confidence sets for the mean and/or autoregressive parameters of the model. We also develop a test on the order of an autoregression. We show that a combination of subsample-based inferences can improve the performance of the procedure. An application to U.S. domestic investment data illustrates the method.

Simulation-Based Finite-and Large-sample Inference Methods in Multivariate Regressions and Seemingly Unrelated Regressions

In the context of multivariate regression (MLR) and seemingly unrelated regressions (SURE) models, it is well known that commonly employed asymptotic test criteria are seriously biased towards overrejection. in this paper, we propose finite-and large-sample likelihood-based test procedures for possibly non-linear hypotheses on the coefficients of MLR and SURE systems.

Enhanced MALDI MS sensitivity by weak base additives and glycerol sample coating

The concept of rationally designing MALDI matrices has been extended to the next “whole sample” level. These studies have revealed some unexpected and exploitable insights in improving MALDI sensitivity. It is shown that (i) additives which only provide additional laser energy absorption are best to be avoided; (ii) the addition of proton donors in the form of protonated weak bases can be highly beneficial; (iii) the addition of glycerol for coating crystalline samples is highly recommended. Overall, analytical sensitivity has been significantly increased compared to the current “gold” standards in MALDI MS, and new insights into the mechanisms and processes of MALDI have been gained.

Potential common radiation problems for components and diagnostics in future magnetic and inertial confinement fusion devices

This work aims at identifying commonpotentialproblems that futurefusiondevices will encounter for both magnetic and inertialconfinement approaches in order to promote joint efforts and to avoid duplication of research. Firstly, a comparison of radiation environments found in both fusion reaction chambers will be presented. Then, wall materials, optical components, cables and electronics will be discussed, pointing to possible future areas of common research. Finally, a brief discussion of experimental techniques available to simulate the radiation effect on materials is included

Retinoic acid induces proteasome-dependent degradation of retinoic acid receptor α (RARα) and oncogenic RARα fusion proteins

Analyzing the pathways by which retinoic acid (RA) induces promyelocytic leukemia/retinoic acid receptor α (PML/RARα) catabolism in acute promyelocytic leukemia (APL), we found that, in addition to caspase-mediated PML/RARα cleavage, RA triggers degradation of both PML/RARα and RARα. Similarly, in non-APL cells, RA directly targeted RARα and RARα fusions to the proteasome degradation pathway. Activation of either RARα or RXRα by specific agonists induced degradation of both proteins. Conversely, a mutation in RARα that abolishes heterodimer formation and DNA binding, blocked both RARα and RXRα degradation. Mutations in the RARα DNA-binding domain or AF-2 transcriptional activation region also impaired RARα catabolism. Hence, our results link transcriptional activation to receptor catabolism and suggest that transcriptional up-regulation of nuclear receptors by their ligands may be a feedback mechanism allowing sustained target-gene activation.

Formation and Turnover of NSF- and SNAP-containing “Fusion” Complexes Occur on Undocked, Clathrin-coated Vesicle–derived Membranes

Specificity of vesicular transport is determined by pair-wise interaction between receptors (SNAP receptors or SNAREs) associated with a transport vesicle and its target membrane. Two additional factors, N-ethylmaleimide-sensitive fusion protein (NSF) and soluble NSF attachment protein (SNAP) are ubiquitous components of vesicular transport pathways. However, the precise role they play is not known. On the basis that NSF and SNAP can be recruited to preformed SNARE complexes, it has been proposed that NSF- and SNAP-containing complexes are formed after SNARE-dependent docking of transport vesicles. This would enable ATPase-dependent complex disassembly to be coupled directly to membrane fusion. Alternatively, binding and release of NSF/SNAP may occur before vesicle docking, and perhaps be involved in the activation of SNAREs. To gain more information about the point at which so-called 20S complexes form during the transport vesicle cycle, we have examined NSF/SNAP/SNARE complex turnover on clathrin-coated vesicle–derived membranes in situ. This has been achieved under conditions in which the extent of membrane docking can be precisely monitored. We demonstrate by UV-dependent cross-linking experiments, coupled to laser light-scattering analysis of membranes, that complexes containing NSF, SNAP, and SNAREs will form and dissociate on the surface of undocked transport vesicles.

Radiation pressure confinement, the shock pinch and feasibility of fusion propulsion,

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A parent-report measure of children's anxiety: psychometric properties and comparison with child-report in a clinic and normal sample

This study examined the psychometric properties of the parent version of the Spence Children's Anxiety Scale (SCAS-P); 484 parents of anxiety disordered children and 261 parents in a normal control group participated in the study. Results of confirmatory factor analysis provided support for six intercorrelated factors, that corresponded with the child self-report as well as with the classification of anxiety disorders by DSM-IV (namely separation anxiety, generalized anxiety, social phobia, panic/agoraphobia, obsessive-compulsive disorder, and fear of physical injuries). A post-hoc model in which generalized anxiety functioned as the higher order factor for the other five factors described the data equally well. The reliability of the subscales was satisfactory to excellent. Evidence was found for both convergent and divergent validity: the measure correlated well with the parent report for internalizing symptoms, and lower with externalizing symptoms. Parent-child agreement ranged from 0.41 to 0.66 in the anxiety-disordered group, and from 0.23 to 0.60 in the control group. The measure differentiated significantly between anxiety-disordered children versus controls, and also between the different anxiety disorders except GAD. The SCAS-P is recommended as a screening instrument for normal children and as a diagnostic instrument in clinical settings. (C) 2003 Elsevier Ltd. All rights reserved.