Model reductions for inference: generality of pairwise, binary, and planar factor graphs.

We offer a solution to the problem of efficiently translating algorithms between different types of discrete statistical model. We investigate the expressive power of three classes of model-those with binary variables, with pairwise factors, and with planar topology-as well as their four intersections. We formalize a notion of "simple reduction" for the problem of inferring marginal probabilities and consider whether it is possible to "simply reduce" marginal inference from general discrete factor graphs to factor graphs in each of these seven subclasses. We characterize the reducibility of each class, showing in particular that the class of binary pairwise factor graphs is able to simply reduce only positive models. We also exhibit a continuous "spectral reduction" based on polynomial interpolation, which overcomes this limitation. Experiments assess the performance of standard approximate inference algorithms on the outputs of our reductions.

200 v superjunction N-type lateral insulated-gate bipolar transistor with improved latch-up characteristics

This paper evaluates the technique used to improve the latching characteristics of the 200 V n-type superjunction (SJ) lateral insulated-gate bipolar transistor (LIGBT) on a partial silicon-on-insulator. SJ IGBT devices are more prone to latch-up than standard IGBTs due to the presence of a strong pnp transistor with the p layer serving as an effective collector of holes. The initial SJ LIGBT design latches at about 23 V with a gate voltage of 5 V with a forward voltage drop (VON) of 2 V at 300 Acm2. The latch-up current density is 1100 Acm2. The latest SJ LIGBT design shows an increase in latch-up voltage close to 100 V without a significant penalty in VON. The latest design shows a latch-up current density of 1195 A cm2. The enhanced robustness against static latch-up leads to a better forward bias safe operating area. © 1963-2012 IEEE.

LiMn2-xTixO4 spinel-type compounds (x ≤ 1): Structural, electrical and magnetic properties

LiMn2-xTixO4 compounds with 0 ≤ x ≤ 1 were prepared by solid state reaction and Pechini technique. Powder X-ray diffraction showed that all samples crystallize with the spinel crystal structure (S.G. Fd3-m). The cubic unit-cell parameter increases with the Ti content. The influence of the Ti content and cationic distribution on the magnetic properties of the compounds was studied by measuring the temperature and magnetic field dependences of the magnetization: substitution by non-magnetic d0 Ti4+ ions appeared to weaken the magnetic interactions between the manganese ions. The electrical properties of LiMnTiO4 were studied by AC impedance spectroscopy and DC polarisation measurements, which revealed the electronic character of the conduction process. © 2006 Elsevier B.V. All rights reserved.

Neural mechanisms of belief inference during cooperative games.

Humans have the arguably unique ability to understand the mental representations of others. For success in both competitive and cooperative interactions, however, this ability must be extended to include representations of others' belief about our intentions, their model about our belief about their intentions, and so on. We developed a "stag hunt" game in which human subjects interacted with a computerized agent using different degrees of sophistication (recursive inferences) and applied an ecologically valid computational model of dynamic belief inference. We show that rostral medial prefrontal (paracingulate) cortex, a brain region consistently identified in psychological tasks requiring mentalizing, has a specific role in encoding the uncertainty of inference about the other's strategy. In contrast, dorsolateral prefrontal cortex encodes the depth of recursion of the strategy being used, an index of executive sophistication. These findings reveal putative computational representations within prefrontal cortex regions, supporting the maintenance of cooperation in complex social decision making.

Effect of operating conditions and fuel type on crevice hc emissions: Model results and comparison with experiments

A one-dimensional model for crevice HC post-flame oxidation is used to calculate and understand the effect of operating parameters and fuel type (propane and isooctane) on the extent of crevice hydrocarbon and the product distribution in the post flame environment. The calculations show that the main parameters controlling oxidation are: bulk burned gas temperatures, wall temperatures, turbulent diffusivity, and fuel oxidation rates. Calculated extents of oxidation agree well with experimental values, and the sensitivities to operating conditions (wall temperatures, equivalence ratio, fuel type) are reasonably well captured. Whereas the bulk gas temperatures largely determine the extent of oxidation, the hydrocarbon product distribution is not very much affected by the burned gas temperatures, but mostly by diffusion rates. Uncertainties in both turbulent diffusion rates as well as in mechanisms are an important factor limiting the predictive capabilities of the model. However, it seems well suited to sensitivity calculations about a baseline. Copyright © 1999 Society of Automotive Engineers, Inc.

M-type channels selectively control bursting in rat dopaminergic neurons

Midbrain dopaminergic neurons in the substantia nigra, pars compacta and ventral tegmental area are critically important in many physiological functions. These neurons exhibit firing patterns that include tonic slow pacemaking, irregular firing and bursting, and the amount of dopamine that is present in the synaptic cleft is much increased during bursting. The mechanisms responsible for the switch between these spiking patterns remain unclear. Using both in-vivo recordings combined with microiontophoretic or intraperitoneal drug applications and in-vitro experiments, we have found that M-type channels, which are present in midbrain dopaminergic cells, modulate the firing during bursting without affecting the background low-frequency pacemaker firing. Thus, a selective blocker of these channels, 10,10-bis(4-pyridinylmethyl)-9(10H)- anthracenone dihydrochloride, specifically potentiated burst firing. Computer modeling of the dopamine neuron confirmed the possibility of a differential influence of M-type channels on excitability during various firing patterns. Therefore, these channels may provide a novel target for the treatment of dopamine-related diseases, including Parkinson's disease and drug addiction. Moreover, our results demonstrate that the influence of M-type channels on the excitability of these slow pacemaker neurons is conditional upon their firing pattern. © 2010 Federation of European Neuroscience Societies and Blackwell Publishing Ltd.

Structural analysis of plate-type fuel assemblies and development of a non-destructive method to assess their integrity

This work is concerned with the structural behaviour and the integrity of parallel plate-type nuclear fuel assemblies. A plate-type assembly consists of several thin plates mounted in a box-like structure and is subjected to a coolant flow that can result in a considerable drag force. A finite element model of an assembly is presented to study the sensitivity of the natural frequencies to the stiffness of the plates' junctions. It is shown that the shift in the natural frequencies of the torsional modes can be used to check the global integrity of the fuel assembly while the local natural frequencies of the inner plates can be used to estimate the maximum drag force they can resist. Finally a non-destructive method is developed to assess the resistance of the inner plates to bear an applied load. Extensive computational and experimental results are presented to prove the applicability of the method presented. © 2013 Elsevier B.V. All rights reserved.

The Supervised IBP: Neighbourhood Preserving Infinite Latent Feature Models

We propose a probabilistic model to infer supervised latent variables in the Hamming space from observed data. Our model allows simultaneous inference of the number of binary latent variables, and their values. The latent variables preserve neighbourhood structure of the data in a sense that objects in the same semantic concept have similar latent values, and objects in different concepts have dissimilar latent values. We formulate the supervised infinite latent variable problem based on an intuitive principle of pulling objects together if they are of the same type, and pushing them apart if they are not. We then combine this principle with a flexible Indian Buffet Process prior on the latent variables. We show that the inferred supervised latent variables can be directly used to perform a nearest neighbour search for the purpose of retrieval. We introduce a new application of dynamically extending hash codes, and show how to effectively couple the structure of the hash codes with continuously growing structure of the neighbourhood preserving infinite latent feature space.

Rebuilding the limit order book: Sequential Bayesian inference on hidden states

The limit order book of an exchange represents an information store of market participants' future aims and for many traders the information held in this store is of interest. However, information loss occurs between orders being entered into the exchange and limit order book data being sent out. We present an online algorithm which carries out Bayesian inference to replace information lost at the level of the exchange server and apply our proof of concept algorithm to real historical data from some of the world's most liquid futures contracts as traded on CME GLOBEX, EUREX and NYSE Liffe exchanges. © 2013 © 2013 Taylor & Francis.

Bayesian parameter identification for vibro-acoustic models with nonparametric uncertainty

Vibration and acoustic analysis at higher frequencies faces two challenges: computing the response without using an excessive number of degrees of freedom, and quantifying its uncertainty due to small spatial variations in geometry, material properties and boundary conditions. Efficient models make use of the observation that when the response of a decoupled vibro-acoustic subsystem is sufficiently sensitive to uncertainty in such spatial variations, the local statistics of its natural frequencies and mode shapes saturate to universal probability distributions. This holds irrespective of the causes that underly these spatial variations and thus leads to a nonparametric description of uncertainty. This work deals with the identification of uncertain parameters in such models by using experimental data. One of the difficulties is that both experimental errors and modeling errors, due to the nonparametric uncertainty that is inherent to the model type, are present. This is tackled by employing a Bayesian inference strategy. The prior probability distribution of the uncertain parameters is constructed using the maximum entropy principle. The likelihood function that is subsequently computed takes the experimental information, the experimental errors and the modeling errors into account. The posterior probability distribution, which is computed with the Markov Chain Monte Carlo method, provides a full uncertainty quantification of the identified parameters, and indicates how well their uncertainty is reduced, with respect to the prior information, by the experimental data. © 2013 Taylor & Francis Group, London.

Identification of an additional two-cysteine containing type I interferon in rainbow trout Oncorhynchus mykiss provides evidence of a major gene duplication event within this gene family in teleosts

Multiple type I interferons (IFNs) have recently been identified in salmonids, containing two or four conserved cysteines. In this work, a novel two-cysteine containing (2C) IFN gene was identified in rainbow trout. This novel trout IFN gene (termed IFN5) formed a phylogenetic group that is distinct from the other three salmonid IFN groups sequenced to date and had a close evolutionary relationship with IFNs from advanced fish species. Our data demonstrate that two subgroups are apparent within each of the 2C and 4C type I IFNs, an evolutionary outcome possibly due to two rounds of genome duplication events that have occurred within teleosts. We have examined gene expression of the trout 2C type I IFN in cultured cells following stimulation with lipopolysaccharide, phytohaemagglutinin, polyI:C or recombinant IFN, or after transfection with polyI:C. The kinetics of gene expression was also studied after viral infection. Analysis of the regulatory elements in the IFN promoter region predicted several binding sites for key transcription factors that potentially play an important role in mediating IFN5 gene expression.