A robust Bayesian two-sample test for detecting intervals of differential gene expression in microarray time series.

Understanding the regulatory mechanisms that are responsible for an organism's response to environmental change is an important issue in molecular biology. A first and important step towards this goal is to detect genes whose expression levels are affected by altered external conditions. A range of methods to test for differential gene expression, both in static as well as in time-course experiments, have been proposed. While these tests answer the question whether a gene is differentially expressed, they do not explicitly address the question when a gene is differentially expressed, although this information may provide insights into the course and causal structure of regulatory programs. In this article, we propose a two-sample test for identifying intervals of differential gene expression in microarray time series. Our approach is based on Gaussian process regression, can deal with arbitrary numbers of replicates, and is robust with respect to outliers. We apply our algorithm to study the response of Arabidopsis thaliana genes to an infection by a fungal pathogen using a microarray time series dataset covering 30,336 gene probes at 24 observed time points. In classification experiments, our test compares favorably with existing methods and provides additional insights into time-dependent differential expression.

One step self-aligned multilayer patterning process for the fabrication of organic complementary circuits in combination with inkjet printing

Recent development of solution processable organic semiconductors delineates the emergence of a new generation of air-stable, high performance p- and n-type materials. This makes it indeed possible for printed organic complementary circuits (CMOS) to be used in real applications. The main technical bottleneck for organic CMOS to be adopted as the next generation organic integrated circuit is how to deposit and pattern both p- and n-type semiconductor materials with high resolutions at the same time. It represents a significant technical challenge, especially if it can be done for multiple layers without mask alignment. In this paper, we propose a one-step self-aligned fabrication process which allows the deposition and high resolution patterning of functional layers for both p- and n-channel thin film transistors (TFTs) simultaneously. All the dimensional information of the device components is featured on a single imprinting stamp, and the TFT-channel geometry, electrodes with different work functions, p- and n-type semiconductors and effective gate dimensions can all be accurately defined by one-step imprinting and the subsequent pattern transfer process. As an example, we have demonstrated an organic complementary inverter fabricated by 3D imprinting in combination with inkjet printing and the measured electrical characteristics have validated the feasibility of the novel technique. © 2012 Elsevier B.V. All rights reserved.

SuperJunction IGBTS: An evolutionary step of silicon power devices with high impact potential

15 years ago the vertical SuperJunction (SJ) concept conceived for SJ power MOSFETs was the last, major breakthrough in the field of silicon power devices. Today, the SuperJunction MOSFET technologies have reached a mature stage characterized by gradual performance improvements. SuperJunction Insulated Gate Bipolar Transistors (SJ IGBTs) could interrupt this stagnation holding promise to revitalize voltage classes from 600 up to 1200 V. Such SJ IGBTs surpass by a very significant margin their SJ MOSFET counterparts both in terms of power handling capability, on-state and turn-off losses, all at the same time. On the higher end of the voltage class, SJ IGBTs would top the performance of 1.2 kV IGBTs by a similar margin. © 2012 IEEE.

Two problems with variational expectation maximisation for time-series models

Variational methods are a key component of the approximate inference and learning toolbox. These methods fill an important middle ground, retaining distributional information about uncertainty in latent variables, unlike maximum a posteriori methods (MAP), and yet generally requiring less computational time than Monte Carlo Markov Chain methods. In particular the variational Expectation Maximisation (vEM) and variational Bayes algorithms, both involving variational optimisation of a free-energy, are widely used in time-series modelling. Here, we investigate the success of vEM in simple probabilistic time-series models. First we consider the inference step of vEM, and show that a consequence of the well-known compactness property of variational inference is a failure to propagate uncertainty in time, thus limiting the usefulness of the retained distributional information. In particular, the uncertainty may appear to be smallest precisely when the approximation is poorest. Second, we consider parameter learning and analytically reveal systematic biases in the parameters found by vEM. Surprisingly, simpler variational approximations (such a mean-field) can lead to less bias than more complicated structured approximations.

Development of a time and space resolved sampling probe diagnostic for engine exhaust hydrocarbons

In order to understand how unburned hydrocarbons emerge from SI engines and, in particular, how non-fuel hydrocarbons are formed and oxidized, a new gas sampling technique has been developed. A sampling unit, based on a combination of techniques used in the Fast Flame Ionization Detector (FFID) and wall-mounted sampling valves, was designed and built to capture a sample of exhaust gas during a specific period of the exhaust process and from a specific location within the exhaust port. The sampling unit consists of a transfer tube with one end in the exhaust port and the other connected to a three-way valve that leads, on one side, to a FFID and, on the other, to a vacuum chamber with a high-speed solenoid valve. Exhaust gas, drawn by the pressure drop into the vacuum chamber, impinges on the face of the solenoid valve and flows radially outward. Once per cycle during a specified crank angle interval, the solenoid valve opens and traps exhaust gas in a storage unit, from which gas chromatography (GC) measurements are made. The port end of the transfer tube can be moved to different locations longitudinally or radially, thus allowing spatial resolution and capturing any concentration differences between port walls and the center of the flow stream. Further, the solenoid valve's opening and closing times can be adjusted to allow sampling over a window as small as 0.6 ms during any portion of the cycle, allowing resolution of a crank angle interval as small as 15°CA. Cycle averaged total HC concentration measured by the FFID and that measured by the sampling unit are in good agreement, while the sampling unit goes one step further than the FFID by providing species concentrations. Comparison with previous measurements using wall-mounted sampling valves suggests that this sampling unit is fully capable of providing species concentration information as a function of air/fuel ratio, load, and engine speed at specific crank angles. © Copyright 1996 Society of Automotive Engineers, Inc.