Integration of CSAB and ABET

The Accreditation Board for Engineering and Technology, Inc. (ABET) and the Computing Sciences Accreditation Board (CSAB) signed a Memorandum of Agreement in November 1998 to integrate CSAB\u27\u27s accreditation services with ABET, with a transition time of approximately two years. During the interim period, the operations of the Computer Science Accreditation Commission (CSAC) are contracted by CSAB to ABET. A committee with CSAC, CSAB, and ABET representation is working to set up the new commission for accrediting programs in the computing sciences. This new commission will probably be called the Computing Accreditation Commission (CAC). Other activities are underway to try to assure that this integration goes as smoothly as possible. This paper discusses from various points of view the current status of the integration and plans for the completion of the integration

Modeling of Nonseasonal Quarterly Earnings Data: Working Paper Series--05-17

We present new empirical evidence on the predictive power of statistically-based quarterly earnings expectation models for firms which exhibit nonseasonal quarterly earnings patterns. In marked contrast to extant work we find: 1) a considerably greater frequency of nonseasonal firms (36%) when compared to Lorek and Bathke (1984) (12%) and Brown and Han (2000) (17%), 2) the random walk model (RW) provides significantly more accurate pooled, one-step ahead quarterly earnings predictions across 40 quarters in the 1994-2003 holdout period than the first-order autoregressive model (AR1) popularized by Lorek and Bathke and Brown and Han, and 3) the RW model provides significantly more accurate quarterly earnings predictions for large nonseasonal firms than smaller nonseasonal firms. The latter finding documents a size-effect with respect to predictive ability for nonseasonal firms similar to that evidenced for seasonal firms. These findings are particularly salient to researchers in search of efficient statistically-based quarterly earnings expectation models since 129 of 296 (43.6%) sample firms are not covered by security analysts

Lipid Metabolism During Bacterial Growth, Sporulation, and Germination: Differential Synthesis of Individual Branched and Normal-Chain Fatty Acids During Spore Germination and Outgrowth of \u3ci\u3eBacillus thuringiensis\u3c/i\u3e

The biosynthesis of individual branched- and normal-chain fatty acids during Bacillus thuringiensis spore germination and outgrowth was studied by comparing pulsed and continuous labeling of these fatty acids with [U- 14C ]acetate. The relative specific activity of each fatty acid varies with time as the cell progresses through outgrowth. However, fatty acid synthesis does occur in two distinct phases. Upon germination, acetate is incorporated only into the iso-isomers i-C13, i-C14, and i-C16; no normal or anteiso synthesis occurs. Subsequent to T30, the full complement of branched- and normal-chain homologues is formed and there is a dramatic enhancement in the overall rate of fatty acid synthesis. Significantly, this rate increase coincides with a marked shift from the synthesis of short-chain to long-chain fatty acids. These findings illustrate a dichotomy in synthesis that may result from initial fatty acid formation by preexisting spore fatty acid biosynthetic enzymes in the absence of de novo protein synthesis. Elucidation of the timing and kinetics of individual fatty acid formation provides a biochemical profile of activities directly related to membrane differentiation and cellular development

Segmentation of fluorescence microscopy images using three dimensional active contours with inhomogeneity correction

Image segmentation is an important step in the quantitative analysis of fluorescence microscopy data. Since fluorescence microscopy volumes suffer from intensity inhomogeneity, low image contrast and limited depth resolution, poor edge details, and irregular structure shape, segmentation still remains a challenging problem. This paper describes a nuclei segmentation method for fluorescence microscopy based on the use of three dimensional (3D) active contours with inhomogeneity correction. The correction information utilizes 3D volume information while addressing intensity inhomogeneity across vertical and horizontal directions. Experimental results demonstrate that the proposed method achieves better performance than other reported methods

Physiology of Sporeforming Bacteria Associated with Insects: Radiorespirometric Survey of Carbohydrate Metabolism In the 12 Serotypes of \u3ci\u3eBacillus thuringiensis\u3c/i\u3e

Radiorespirometry was used to compare the primary pathways of glucose catabolism in 18 strains of Bacillus thuringiensis representing the 12 established serotypes. Every strain utilizes the Embden-Meyerhof-Pamas pathway almost exclusively; pentose-phosphate pathway participation is minor. The Embden- Meyerhof-Parnas pathway predominates regardless of whether the cells were grown in a minimal medium or one containing yeast extract. The results indicate that the absolute requirement for citrate and related compounds is not a result of defective citrate or glucose transport and metabolism

Tubule Segmentation of Fluorescence Microscopy Images Based on Convolutional Neural Networks With Inhomogeneity Correction

Fluorescence microscopy has become a widely used tool for studying various biological structures of in vivo tissue or cells. However, quantitative analysis of these biological structures remains a challenge due to their complexity which is exacerbated by distortions caused by lens aberrations and light scattering. Moreover, manual quantification of such image volumes is an intractable and error-prone process, making the need for automated image analysis methods crucial. This paper describes a segmentation method for tubular structures in fluorescence microscopy images using convolutional neural networks with data augmentation and inhomogeneity correction. The segmentation results of the proposed method are visually and numerically compared with other microscopy segmentation methods. Experimental results indicate that the proposed method has better performance with correctly segmenting and identifying multiple tubular structures compared to other methods