Palmitic Acid and Health: Introduction

Interest in the dietary role and metabolic effect of saturated fatty acids has been recently renewed on the basis of epidemiologic observations and economical approach to health and well-being. Saturated fats may favorably increase blood HDL-Cholesterol levels without significant changes of the total cholesterol/HDL-Cholesterol ratio. Also, the negative effect of saturated fat on cardiovascular diseases risk has recently been challenged. Palmitic acid, among all, may have special structural and functional roles in utero and in infancy, and indeed is it is being delivered in a unique form in human milk. Future research should include objective cost-benefit analyses when disentangling the role of saturated fats in dietary recommendations.     

Bounded Degree Interval Sandwich Problems

The problems of Interval Sandwich (IS) and Intervalizing Colored Graphs (ICG) have received a lot of attention recently, due to their applicability to DNA physical mapping problems with ambiguous data. Most of the results obtained so far on the problems were hardness results. Here we study the problems under assumptions of sparseness, which hold in the biological context. We prove that both problems are polynomial when either (1) the input graph degree and the solution graph clique size are bounded, or (2) the solution graph degree is bounded. In particular, this implies that ICG is polynomial on bounded degree graphs for every fixed number of colors, in contrast with the recent result of Bodlaender and de Fluiter. Received October 2, 1997; revised April 1, 1998.     

Medical image categorization and retrieval for PACS using the GMM-KL framework.

This paper presents an image representation and matching framework for image categorization in medical image archives. Categorization enables one to determine automatically, based on the image content, the examined body region and imaging modality. It is a basic step in content-based image retrieval (CBIR) systems, the goal of which is to augment text-based search with visual information analysis. CBIR systems are currently being integrated with picture archiving and communication systems for increasing the overall search capabilities and tools available to radiologists. The proposed methodology is comprised of a continuous and probabilistic image representation scheme using Gaussian mixture modeling (GMM) along with information-theoretic image matching via the Kullback-Leibler (KL) measure. The GMM-KL framework is used for matching and categorizing X-ray images by body regions. A multidimensional feature space is used to represent the image input, including intensity, texture, and spatial information. Unsupervised clustering via the GMM is used to extract coherent regions in feature space that are then used in the matching process. A dominant characteristic of the radiological images is their poor contrast and large intensity variations. This presents a challenge to matching among the images, and is handled via an illumination-invariant representation. The GMM-KL framework is evaluated for image categorization and image retrieval on a dataset of 1500 radiological images. A classification rate of 97.5% was achieved. The classification results compare favorably with reported global and local representation schemes. Precision versus recall curves indicate a strong retrieval result as compared with other state-of-the-art retrieval techniques. Finally, category models are learned and results are presented for comparing images to learned category models.     

Mechanical and optical properties of the chalcogenide glass system As2Se3-xTex

Chalcogenide glasses of As2Se3-xTex(0 leq x leq 3) were fabricated with special care to avoid traces of oxygen, using very pure raw materials. From part of these materials, special plates were made, and from the rest fibers were pulled. From transmittance measurements, the existence of absorption bands was shown, corresponding to the presence of small crystallites of As2O3. The attenuation in the infrared of these plates increased from 14 dB/m for As2Se3to 29 dB/m for As2Se0.5Te2.5. Conversely, a decrease of microhardness VHwas observed. The attenuation of CO2laser light (lambda = 10.6 mum) transmitted through the pulled fibers was measured as a function of the Te(x) content. and an increase of the attenuation was observed from 18.1 dB/m for As2Se3to 66.7 dB/m for As5Se1.5Te1.5. The surface of each fiber was examined in the scanning electron microscope and an increase of the defects (e.g., crystallites) when the Te content was increased, was observed. These defects (crystallites) are the main factors for finding an increase in the absorption in IR.     

Zero-knowledge proofs of identity

In this paper we extend the notion of interactive proofs of assertions to interactive proofs of knowledge. This leads to the definition of unrestricted input zero-knowledge proofs of knowledge in which the prover demonstrates possession of knowledge without revealing any computational information whatsoever (not even the one bit revealed in zero-knowledge proofs of assertions). We show the relevance of these notions to identification schemes, in which parties prove their identity by demonstrating their knowledge rather than by proving the validity of assertions. We describe a novel scheme which is provably secure if factoring is difficult and whose practical implementations are about two orders of magnitude faster than RSA-based identification schemes. The advantages of thinking in terms of proofs of knowledge rather than proofs of assertions are demonstrated in two efficient variants of the scheme: unrestricted input zero-knowledge proofs of knowledge are used in the construction of a scheme which needs no directory; a version of the scheme based on parallel interactive proofs (which are not known to be zero knowledge) is proved secure by observing that the identification protocols are proofs of knowledge.     

A validation study of the Keyboard Personal Computer Style instrument (K-PeCS) for use with children

This study examines a potential instrument for measurement of typing postures of children. This paper describes inter-rater, test-retest reliability and concurrent validity of the Keyboard Personal Computer Style instrument (K-PeCS), an observational measurement of postures and movements during keyboarding, for use with children. Two trained raters independently rated videos of 24 children (aged 7-10 years). Six children returned one week later for identifying test-retest reliability. Concurrent validity was assessed by comparing ratings obtained using the K-PECS to scores from a 3D motion analysis system. Inter-rater reliability was moderate to high for 12 out of 16 items (Kappa: 0.46 to 1.00; correlation coefficients: 0.77-0.95) and test-retest reliability varied across items (Kappa: 0.25 to 0.67; correlation coefficients: r = 0.20 to r = 0.95). Concurrent validity compared favourably across arm pathlength, wrist extension and ulnar deviation. In light of the limitations of other tools the K-PeCS offers a fairly affordable, reliable and valid instrument to address the gap for measurement of typing styles of children, despite the shortcomings of some items. However further research is required to refine the instrument for use in evaluating typing among children.     

Smart Scribbles for Sketch Segmentation

We present ‘Smart Scribbles’—a new scribble‐based interface for user‐guided segmentation of digital sketchy drawings. In contrast to previous approaches based on simple selection strategies, Smart Scribbles exploits richer geometric and temporal information, resulting in a more intuitive segmentation interface. We introduce a novel energy minimization formulation in which both geometric and temporal information from digital input devices is used to define stroke‐to‐stroke and scribble‐to‐stroke relationships. Although the minimization of this energy is, in general, an NP‐hard problem, we use a simple heuristic that leads to a good approximation and permits an interactive system able to produce accurate labellings even for cluttered sketchy drawings. We demonstrate the power of our technique in several practical scenarios such as sketch editing, as‐rigid‐as‐possible deformation and registration, and on‐the‐fly labelling based on pre‐classified guidelines.     

Combining color and depth for enhanced image segmentation and retargeting

As depth cameras become more popular, pixel depth information becomes easier to obtain. This information can clearly enhance many image processing applications. However, combining depth and color information is not straightforward as these two signals can have different noise characteristics, differences in resolution, and their boundaries do not generally agree. We present a technique that combines depth and color image information from real devices in synergy. In particular, we focus on combining them to improve image segmentation. We use color information to fill and clean depth and use depth to enhance color image segmentation. We demonstrate the utility of the combined segmentation for extracting layers and present a novel image retargeting algorithm for layered images.