1200 V 4H-SiC Bipolar Junction Transistors with A Record β of 70

A common current gain of 70 has been achieved in 4H-SiC bipolar junction transistors (BJTs) at room temperature, which is the highest among those reported. BJTs having an active area of 4 mm × 4 mm exhibit a specific on-resistance of 6.3 mΩ cm² at 25°C, which increases to 17.4 mΩ cm² at 250°C. BV_CEO (the breakdown voltage from collector to emitter with open base) and BV_CBO (the breakdown voltage from collector to base with open emitter) of 1200 V were observed at <5 μA leakage currents at all temperatures up to 250°C. Dynamic characteristics were measured using the IXYS RF/Directed Energy IXDD415 gate driver evaluation board to drive the BJT. A collector current (I _C) rise time at turn-on of 32 ns was measured with a 1.6 A gate current provided to support the collector current of 63 A. An I _C fall time at turn-off of 16 ns was achieved.     

Exploring the Contemporary State of Information Technology Governance Transparency in Belgian Firms

This article provides an exploratory insight in the contemporary state of IT governance transparency in Belgian firms. Our findings show that Belgian firms exhibit low IT governance disclosure rates in general. We also find preliminary evidence that IT governance disclosure is positively related to IT usage intensity for listed firms, and that listed firms tend to be more concerned with disclosing on their IT governance compared to non-listed firms, given a comparable level of IT usage intensity.     

Trends in the Electronic Control of Mine Hoists

The trends in electronic control of mine hoists and winders in the last two decades are reviewed. Both the conventional methods for ac and dc winders and the modern thyristor control concepts are surveyed. Practical cases are drawn from industry to illustrate the typical methods of hoist control in use. Comparison of drives is also attempted.     

Short Communication RESIDENCE TIME DISTRIBUTION IN THE EXTRA CAPILLARY SPACE OF HOLLOW FIBER BIOREACTORS

The residence time distribution (RTD) in the extracapillary space (ECS) of hollow fiber bioreactors (HFBRs) has been studied using a high molecular weight protein, bovine serum albumin, as a tracer. The RTD measurements have been carried out at different conditions of flow in the ECS and the intracapillary space (ICS). The RTD results obtained give an indication of the flow patterns existing in the ECS. The implications of these studies on cell cultivation as well as product recovery from HFBRs have been discussed.     

A Locally Adaptive Multimode Photodetector Circuit

Photodetection circuits form the first stage of the artificial image acquisition process. The image acquisition circuits discussed in this paper pertain to circuits fabricated in a standard CMOS process. Such circuits offers advantages such as random access to a pixel, faster readout, integration of processing circuitry on the same die, low voltage and low power dissipation, and lower cost over the conventional Charge Coupled Device (CCD) process. We describe a new locally adaptive multimode photodetector circuit. The advantages of the circuit are local adaptation, wide dynamic range, excellent sensitivity, and large output voltage swing. The circuit was fabricated in the 2 CMOS process through MOSIS. Simulation and experimental results of the circuit are given.     

Interplay between intensity standardization and inhomogeneity correction in MR image processing

Image intensity standardization is a postprocessing method designed for correcting acquisition-to-acquisition signal intensity variations (nonstandardness) inherent in magnetic resonance (MR) images. Inhomogeneity correction is a process used to suppress the low frequency background nonuniformities (inhomogeneities) of the image domain that exist in MR images. Both these procedures have important implications in MR image analysis. The effects of these postprocessing operations on improvement of image quality in isolation has been well documented. However, the combined effects of these two processes on MR images and how the processes influence each other have not been studied thus far. In this paper, we evaluate the effect of inhomogeneity correction followed by standardization and vice-versa on MR images in order to determine the best sequence to follow for enhancing image quality. We conducted experiments on several clinical and phantom data sets (nearly 4000 three-dimensional MR images were analyzed) corresponding to four different MRI protocols. Different levels of artificial nonstandardness, and different models and levels of artificial background inhomogeneity were used in these experiments. Our results indicate that improved standardization can be achieved by preceding it with inhomogeneity correction. There is no statistically significant difference in image quality obtained between the results of standardization followed by correction and that of correction followed by standardization from the perspective of inhomogeneity correction. The correction operation is found to bias the effect of standardization. We demonstrate this bias both qualitatively and quantitatively by using two different methods of inhomogeneity correction. We also show that this bias in standardization is independent of the specific inhomogeneity correction method used. The effect of this bias due to correction was also seen in magnetization transfer ratio (MTR) images, which are naturally endowed with the standardness property. Standardization, on the other hand, does not seem to influence the correction operation. It is also found that longer sequences of repeated correction and standardization operations do not considerably improve image quality. These results were found to hold for the clinical and the phantom data sets, for different MRI protocols, for different levels of artificial nonstandardness, for different models and levels of artificial inhomogeneity, for different correction methods, and for images that were endowed with inherent standardness as well as for those that were standardized by using the intensity standardization method. Overall, we conclude that inhomogeneity correction followed by intensity standardization is the best sequence to follow from the perspective of both image quality and computational efficiency.     

Vector quantization using information theoretic concepts

The process of representing a large data set with a smaller number of vectors in the best possible way, also known as vector quantization, has been intensively studied in the recent years. Very efficient algorithms like the Kohonen self-organizing map (SOM) and the Linde Buzo Gray (LBG) algorithm have been devised. In this paper a physical approach to the problem is taken, and it is shown that by considering the processing elements as points moving in a potential field an algorithm equally efficient as the before mentioned can be derived. Unlike SOM and LBG this algorithm has a clear physical interpretation and relies on minimization of a well defined cost function. It is also shown how the potential field approach can be linked to information theory by use of the Parzen density estimator. In the light of information theory it becomes clear that minimizing the free energy of the system is in fact equivalent to minimizing a divergence measure between the distribution of the data and the distribution of the processing elements, hence, the algorithm can be seen as a density matching method.     

Number Theory.

Comments on the article by Gardner Murphy (see record 1967-11078-001), which considered the psychological sources of Pythagorean number theory. The current author offers some supplementary information, noting that there are some additional meanings attached to some numbers in the culture of India. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Porous Silicon Oxycarbide Glasses

High-surface-area silicon oxycarbide gels and glasses were synthesized from mixtures of methyldimethoxysilane (MDMS) and tetraethoxysilane (TEOS) through acidic hydrolysis and condensation. A surface area of ∼275 m²/g and an average pore size of ∼30 Å was obtained for a 50% MDMS-50% TEOS glass at 800°C under a flowing argon atmosphere. The average pore size was increased by aging the precursor gels in ammonium hydroxide. The increased average pore size and the higher strength of the mesoporous gel network enhanced the surface-area stability of the glasses; in this case, surface areas >200 m²/g were retained at 1200°C under an argon atmosphere. ²⁹Si MAS NMR spectra revealed that an oxycarbide structure was established in the mesoporous glasses obtained after pyrolysis of the aged gels. The role of carbon was demonstrated by comparing the surface-area stability of the oxycarbide glasses with that of pure silica and that of oxycarbide glasses where all the carbon groups were removed through low-temperature plasma-oxidation treatments. In the absence of carbon, the thermal stability of the surface area decreased dramatically.     

Statistical shape model for manifold regularization: Gleason grading of prostate histology

Gleason patterns of prostate cancer histopathology, characterized primarily by morphological and architectural attributes of histological structures (glands and nuclei), have been found to be highly correlated with disease aggressiveness and patient outcome. Gleason patterns 4 and 5 are highly correlated with more aggressive disease and poorer patient outcome, while Gleason patterns 1–3 tend to reflect more favorable patient outcome. Because Gleason grading is done manually by a pathologist visually examining glass (or digital) slides subtle morphologic and architectural differences of histological attributes, in addition to other factors, may result in grading errors and hence cause high inter-observer variability. Recently some researchers have proposed computerized decision support systems to automatically grade Gleason patterns by using features pertaining to nuclear architecture, gland morphology, as well as tissue texture. Automated characterization of gland morphology has been shown to distinguish between intermediate Gleason patterns 3 and 4 with high accuracy. Manifold learning (ML) schemes attempt to generate a low dimensional manifold representation of a higher dimensional feature space while simultaneously preserving nonlinear relationships between object instances. Classification can then be performed in the low dimensional space with high accuracy. However ML is sensitive to the samples contained in the dataset; changes in the dataset may alter the manifold structure. In this paper we present a manifold regularization technique to constrain the low dimensional manifold to a specific range of possible manifold shapes, the range being determined via a statistical shape model of manifolds (SSMM). In this work we demonstrate applications of the SSMM in (1) identifying samples on the manifold which contain noise, defined as those samples which deviate from the SSMM, and (2) accurate out-of-sample extrapolation (OSE) of newly acquired samples onto a manifold constrained by the SSMM. We demonstrate these applications of the SSMM in the context of distinguish between Gleason patterns 3 and 4 using glandular morphologic features in a prostate histopathology dataset of 58 patient studies. Identifying and eliminating noisy samples from the manifold via the SSMM results in a statistically significant improvement in area under the receiver operator characteristic curve (AUC), 0.832 ± 0.048 with removal of noisy samples compared to a AUC of 0.779 ± 0.075 without removal of samples. The use of the SSMM for OSE of newly acquired glands also shows statistically significant improvement in AUC, 0.834 ± 0.051 with the SSMM compared to 0.779 ± 0.054 without the SSMM. Similar results were observed for the synthetic Swiss Roll and Helix datasets.