Expectation Propagation with Factorizing Distributions: A Gaussian Approximation and Performance Results for Simple Models

We discuss the expectation propagation (EP) algorithm for approximate Bayesian inference using a factorizing posterior approximation. For neural network models, we use a central limit theorem argument to make EP tractable when the number of parameters is large. For two types of models, we show that EP can achieve optimal generalization performance when data are drawn from a simple distribution.

Drinfeld twists and symmetric Bethe vectors of supersymmetric fermion models

We construct the Drinfeld twists ( factorizing F-matrices) of the gl(m-n)-invariant fermion model. Completely symmetric representation of the pseudo-particle creation operators of the model are obtained in the basis provided by the F-matrix ( the F-basis). We resolve the hierarchy of the nested Bethe vectors in the F-basis for the gl(m-n) supersymmetric model.

Binary games with many players

We examine a problem with n players each facing the same binary choice. One choice is superior to the other. The simple assumption of competition - that an individual's payoff falls with a rise in the number of players making the same choice, guarantees the existence of a unique symmetric equilibrium (involving mixed strategies). As n increases, there are two opposing effects. First, events in the middle of the distribution - where a player finds itself having made the same choice as many others - become more likely, but the payoffs in these events fall. In opposition, events in the tails of the distribution - where a player finds itself having made the same choice as few others - become less likely, but the payoffs in these events remain high. We provide a sufficient condition (strong competition) under which an increase in the number of players leads to a reduction in the equilibrium probability that the superior choice is made.

Luminescent Langmuir-Blodgett film of a new amphiphilic Eu(3+) beta-diketonate

This work reports on the synthesis and characterization of the ligand 3-hexadecylpentane-2,4-drone (Hhdacac) and its Eu(3+) complexes Eu(hdacac)(6) center dot 2H(2)O, Eu(hdacac)(6) center dot phen and Eu(hdacac)(6) center dot tta, where phen and tta denote 1,10-phenanthroline and thenoyltrifluoroacetone, respectively. These new compounds present long carbon chains and their expected miscibility into non-polar ambients is confirmed by the emission spectra of Eu(hdacac)6 center dot tta in hexane. Moreover, the amphiphilic properties of Eu(hdacac)6 complexes allow the obtainment of thin luminescent films by the Langmuir-Blodgett technique. In both cases (solids and films), the typical antenna effect of beta-diketonates is observed. The alluring characteristics of these compounds raise great interest in many fields of Materials Science, like photo- and electro-luminescent materials (mainly thin ""organic"" films), metal catalysts or probes in non-polar solutions, and Langmuir-Blodgett films of several compositions. For the characterization of these products, nuclear magnetic resonance spectroscopy ((1)H NMR), thermogravimetric analysis, elementary analyses (C, H), scanning electron microscopy (energy dispersive X-ray spectroscopy), absorption (UV-vis/FT-IR) and photoluminescence spectroscopies were used. (c) 2008 Elsevier B.V. All rights reserved.

Effects of immunosuppressants on hepatocyte cell mitosis during liver regeneration in growing animal models of partial hepatectomy

Objective. We sought to evaluate the effects of immunosuppressant drugs (corticosteroid, cyclosporine [CsA], and tacrolimus [Tac]) on liver regeneration in growing animals submitted to 70% hepatectomy. Materials and Methods. Newborn and weaning rats were submitted to 70% hepatectomy receiving separately methylprednisolone, CsA, or Tac. All animals were sacrificed 24 hours after the procedure. The remnant liver lobes were subjected to histomorphometric analyses with determination of hepatocyte mitotic index. Results., Administration of immunosuppressants did not change the mitotic index of the regenerating liver in newborn animals. In weaning rats, methylprednisolone reduced the mitotic index (P = .01) and Tac caused a greater increase in this rate (P = .001). CsA had no effect on mitotic index. The number of hepatocyte mitoses in newborn animal livers was greater than that in weaning animal livers (P = .001). Conclusion. In situations in which intense, fast processes of liver regeneration are crucial, the advantages of the use of Tac must be considered, such as in pediatric transplant patients.

Analysis of dynamic process models for structural insight and model reduction .1. Structural identification measures

An important consideration in the development of mathematical models for dynamic simulation, is the identification of the appropriate mathematical structure. By building models with an efficient structure which is devoid of redundancy, it is possible to create simple, accurate and functional models. This leads not only to efficient simulation, but to a deeper understanding of the important dynamic relationships within the process. In this paper, a method is proposed for systematic model development for startup and shutdown simulation which is based on the identification of the essential process structure. The key tool in this analysis is the method of nonlinear perturbations for structural identification and model reduction. Starting from a detailed mathematical process description both singular and regular structural perturbations are detected. These techniques are then used to give insight into the system structure and where appropriate to eliminate superfluous model equations or reduce them to other forms. This process retains the ability to interpret the reduced order model in terms of the physico-chemical phenomena. Using this model reduction technique it is possible to attribute observable dynamics to particular unit operations within the process. This relationship then highlights the unit operations which must be accurately modelled in order to develop a robust plant model. The technique generates detailed insight into the dynamic structure of the models providing a basis for system re-design and dynamic analysis. The technique is illustrated on the modelling for an evaporator startup. Copyright (C) 1996 Elsevier Science Ltd

Analysis of dynamic models for structural insight and model reduction .2. A multi-stage compressor shutdown case-study

In this second paper, the three structural measures which have been developed are used in the modelling of a three stage centrifugal synthesis gas compressor. The goal of this case study is to determine the essential mathematical structure which must be incorporated into the compressor model to accurately model the shutdown of this system. A simple, accurate and functional model of the system is created via three structural measures. It was found that the model can be correctly reduced into its basic modes and that the order of the differential system can be reduced from 51(st) to 20(th). Of the 31 differential equational 21 reduce to algebraic relations, 8 become constants and 2 can be deleted thereby increasing the algebraic set from 70 to 91 equations. An interpretation is also obtained as to which physical phenomena are dominating the dynamics of the compressor add whether the compressor will enter surge during the shutdown. Comparisons of the reduced model performance against the full model are given, showing the accuracy and applicability of the approach. Copyright (C) 1996 Elsevier Science Ltd

Discrete and continuous models for dry masonry columns

The dynamic response of dry masonry columns can be approximated with finite-difference equations. Continuum models follow by replacing the difference quotients of the discrete model by corresponding differential expressions. The mathematically simplest of these models is a one-dimensional Cosserat theory. Within the presented homogenization context, the Cosserat theory is obtained by making ad hoc assumptions regarding the relative importance of certain terms in the differential expansions. The quality of approximation of the various theories is tested by comparison of the dispersion relations for bending waves with the dispersion relation of the discrete theory. All theories coincide with differences of less than 1% for wave-length-block-height (L/h) ratios bigger than 2 pi. The theory based on systematic differential approximation remains accurate up to L/h = 3 and then diverges rapidly. The Cosserat model becomes increasingly inaccurate for L/h < 2 pi. However, in contrast to the systematic approximation, the wave speed remains finite. In conclusion, considering its relative simplicity, the Cosserat model appears to be the natural starting point for the development of continuum models for blocky structures.

Properties of rapidly solidified binary copper alloys

A number of binary Cu-X alloys (X = Fe, Cr, Si and Al) with alloying elements up to approximate to 12 at % for Fe and Cr, and = 20 at% for Al and Si were cast into thin ribbons (30-50 mu m thickness) by chill block melt spinning. The structural state of the as-cast ribbons was determined by X-ray diffraction (XRD) and microstructures of the quenched alloys were compared with the ingot equivalent, It was possible to achieve solid solution and fine dispersion of secondary phase beyond XRD detection up to approximate to 8 at% solute for Fe and Cr, which is beyond the expected concentration limits from equilibrium phase diagrams. The effects of alloying on resistivity and microhardness are also presented.

Strategies for genetic model specification in the screening of genome-wide meta-analysis signals for further replication

Background Meta-analysis is increasingly being employed as a screening procedure in large-scale association studies to select promising variants for follow-up studies. However, standard methods for meta-analysis require the assumption of an underlying genetic model, which is typically unknown a priori. This drawback can introduce model misspecifications, causing power to be suboptimal, or the evaluation of multiple genetic models, which augments the number of false-positive associations, ultimately leading to waste of resources with fruitless replication studies. We used simulated meta-analyses of large genetic association studies to investigate naive strategies of genetic model specification to optimize screenings of genome-wide meta-analysis signals for further replication. Methods Different methods, meta-analytical models and strategies were compared in terms of power and type-I error. Simulations were carried out for a binary trait in a wide range of true genetic models, genome-wide thresholds, minor allele frequencies (MAFs), odds ratios and between-study heterogeneity (tau(2)). Results Among the investigated strategies, a simple Bonferroni-corrected approach that fits both multiplicative and recessive models was found to be optimal in most examined scenarios, reducing the likelihood of false discoveries and enhancing power in scenarios with small MAFs either in the presence or in absence of heterogeneity. Nonetheless, this strategy is sensitive to tau(2) whenever the susceptibility allele is common (MAF epsilon 30%), resulting in an increased number of false-positive associations compared with an analysis that considers only the multiplicative model. Conclusion Invoking a simple Bonferroni adjustment and testing for both multiplicative and recessive models is fast and an optimal strategy in large meta-analysis-based screenings. However, care must be taken when examined variants are common, where specification of a multiplicative model alone may be preferable.

Applying linear time-varying constraints to econometric models: With an application to demand systems

When linear equality constraints are invariant through time they can be incorporated into estimation by restricted least squares. If, however, the constraints are time-varying, this standard methodology cannot be applied. In this paper we show how to incorporate linear time-varying constraints into the estimation of econometric models. The method involves the augmentation of the observation equation of a state-space model prior to estimation by the Kalman filter. Numerical optimisation routines are used for the estimation. A simple example drawn from demand analysis is used to illustrate the method and its application.

Models of alcohol use by young adults: An examination of various attitude-behavior theories

Objective: The aim of this study was to test the effectiveness of various attitude-behavior theories in explaining alcohol use among young adults. The theory of reasoned action (TRA), the theory of planned behavior and an extension of the TRA that incorporates past behavior were compared by the method of maximum-likelihood estimation, as implemented in LISREL for Windows 8.12. Method: Respondents consisted of 122 university students (82 female) who were questioned about their attitudes, subjective norms, perceived behavioral control, past behavior and intentions relating to drinking behavior. Students received course credit for their participation in the research. Results: Overall, the results suggest that the extension of the theory of reasoned action which incorporates past behavior provides the best fit to the data. For these young adults, their intentions to drink alcohol were predicted by their past behavior as well as their perceptions of what important others think they should do (subjective norm). Conclusions: The main conclusions drawn from the research concern the importance of focusing on normative influences and past behavior in explaining young adult alcohol use. Issues regarding the relative merit of various alternative models and the need for greater clarity in the measure of attitudes are also discussed.

Experimental models of sepsis and their clinical relevance

Sepsis remains a major cause of morbidity and mortality mainly because of sepsis-induced multiple organ dysfunction. In contrast to preclinical studies, most clinical trials of promising new treatment strategies for sepsis have failed to demonstrate efficacy. Although many reasons could account for this discrepancy, the misinterpretation of preclinical data obtained from experimental studies and especially the use of animal models that do not adequately mimic human sepsis may have been contributing factors. In this review, the potentials and limitations of various animal models of sepsis are discussed to clarify to which extent these findings are relevant to human sepsis. Such models include intravascular infusion of endotoxin or live bacteria, bacterial peritonitis, cecal ligation and perforation, soft tissue infection, pneumonia or meningitis models using different animal species including rats, mice, rabbits, dogs, pigs, sheep, and nonhuman primates. Despite several limitations, animal models remain essential in the development of all new therapies for sepsis and septic shock because they provide fundamental information about the pharmacokinetics, toxicity, and mechanism of drug action that cannot be replaced by other methods. New therapeutic agents should be studied in infection models, even after the initiation of the septic process. Furthermore, debility conditions need to be reproduced to avoid the exclusive use of healthy animals, which often do not represent the human septic patient.