Efficient parallel algorithms for solvent accessible surface areaof proteins

We present faster sequential and parallel algorithms for computing the solvent accessible surface area (ASA) of protein molecules. The ASA is computed by finding the exposed surface areas of the spheres obtained by increasing the van der Waals radii of the atoms with the van der Waals radius of the solvent. Using domain specific knowledge, we show that the number of sphere intersections is only O(n), where n is the number of atoms in the protein molecule. For computing sphere intersections, we present hash-based algorithms that run in O(n) expected sequential time and O(n/p) expected parallel time and sort-based algorithms that run in worst-case O(n log n) sequential time and O(n log n/p) parallel time. These are significant improvements over previously known algorithms which take O(n²) time sequentially and O(n²/p) time in parallel. We present a Monte Carlo algorithm for computing the solvent accessible surface area. The basic idea is to generate points uniformly at random on the surface of spheres obtained by increasing the van der Waals radii of the atoms with the van der Waals radius of the solvent molecule and to test the points for accessibility. We also provide error bounds as a function of the sample size. Experimental verification of the algorithms is carried out using an IBM SP-2     

Meso-scale Computational Investigation of Shock-Wave Attenuation by Trailing Release Wave in Different Grades of Polyurea

Over the past several years, considerable research efforts have been made toward investigating polyurea, a segmented thermoplastic elastomer, and particularly its shock-mitigation capacity, i.e., an ability to attenuate and disperse shock-waves. These research efforts have clearly established that the shock-mitigation capacity of polyurea is closely related to its chemistry, processing route, and the resulting microstructure. Polyurea typically possesses a nano-segregated microstructure consisting of (high glass transition temperature, T _g) hydrogen-bonded discrete hard domains and a (low T _g) contiguous soft matrix. While the effect of polyurea microstructure on its shock-mitigation capacity is well-established, it is not presently clear what microstructure-dependent phenomena and processes control its shock-mitigation capacity. To help identify these phenomena and processes, meso-scale simulations of the formation of nano-segregated microstructure and its interaction with a leading shock-wave and a trailing release-wave is analyzed in the present work. The results obtained revealed that shock-induced hard-domain densification makes an important contribution to the superior shock-mitigation capacity of polyurea, and that the extent of densification is a sensitive function of the polyurea soft-segment molecular weight. In particular, the ability of release-waves to capture and neutralize shock-waves has been found to depend strongly on the extent of shock-induced hard-domain densification and, thus, on the polyurea soft-segment molecular weight.     

The Enriched Feature Enhancement Technique for Satellite Image Based on Transforms Using PCNN

The features of the satellite images can be improved by fusing or combining two images with complementary property. By fusing these two images the spatial property of the resultant image is improved. Satellite images are one of the agents that give the features of the earth’s surface. Processing these satellite images will provide more geographical information hidden in the images. This research paper have an detailed insight study of two types of the satellite images one is Panchromatic (PAN) and other Multispectral (MS). The PAN image with high spatial resolution and MS image with spectral resolution are fused to get better resultant output. For fusion process Nonsubsampled Contour let Transform is used to decompose the images into low and high frequency values. Pulse Coupled Neural Network is used to motivate the low frequency pixel and Morphological filter is applied to the edge detected image for finding the features in the images. This is an real time transformations which will give better results in SAR image processing, video processing, stereo based reconstruction of depth and width of the features present in the image.

     

Objective evaluation of speech dysfluencies using wavelet packet transform with sample entropy

Dysfluency and stuttering are a break or interruption of normal speech such as repetition, prolongation, interjection of syllables, sounds, words or phrases and involuntary silent pauses or blocks in communication. Stuttering assessment through manual classification of speech dysfluencies is subjective, inconsistent, time consuming and prone to error. This paper proposes an objective evaluation of speech dysfluencies based on the wavelet packet transform with sample entropy features. Dysfluent speech signals are decomposed into six levels by using wavelet packet transform. Sample entropy (SampEn) features are extracted at every level of decomposition and they are used as features to characterize the speech dysfluencies (stuttered events). Three different classifiers such as k-nearest neighbor (kNN), linear discriminant analysis (LDA) based classifier and support vector machine (SVM) are used to investigate the performance of the sample entropy features for the classification of speech dysfluencies. 10-fold cross validation method is used for testing the reliability of the classifier results. The effect of different wavelet families on the classification performance is also performed. Experimental results demonstrate that the proposed features and classification algorithms give very promising classification accuracy of 96.67% with the standard deviation of 0.37 and also that the proposed method can be used to help speech language pathologist in classifying speech dysfluencies.     

Reduced state correlations of the enskog modulus for gases and liquids

The Enskog modulus, bρ x, has been subjected to a generalized treatment to develop reduced state correlations for nonpolar and polar substances that exhibit hydrogen bonding. These correlations present relationships between 1 + bρx and ρ_R, the reduced density. For nonpolar substances, the PVT data of argon, nitrogen, methane, ethane, and carbon dioxide were used for the development of these relationships, which were found to depend on z_c, the critical compressibility factor. PVT data for ammonia, methyl alcohol, and water yielded a different correlation, which is applicable to polar substances which exhibit hydrogen bonding. These relationships were found to depend on the parameter, β = (T_b-T_m)/M, which quantitatively describes the extent of hydrogen bonding for polar compounds.     

A Concurrent Product-Development Approach for Friction-Stir Welded Vehicle-Underbody Structures

High-strength aluminum and titanium alloys with superior blast/ballistic resistance against armor piercing (AP) threats and with high vehicle light-weighing potential are being increasingly used as military-vehicle armor. Due to the complex structure of these vehicles, they are commonly constructed through joining (mainly welding) of the individual components. Unfortunately, these alloys are not very amenable to conventional fusion-based welding technologies [e.g., gas metal arc welding (GMAW)] and to obtain high-quality welds, solid-state joining technologies such as friction-stir welding (FSW) have to be employed. However, since FSW is a relatively new and fairly complex joining technology, its introduction into advanced military-vehicle-underbody structures is not straight forward and entails a comprehensive multi-prong approach which addresses concurrently and interactively all the aspects associated with the components/vehicle-underbody design, fabrication, and testing. One such approach is developed and applied in this study. The approach consists of a number of well-defined steps taking place concurrently and relies on two-way interactions between various steps. The approach is critically assessed using a strengths, weaknesses, opportunities, and threats (SWOT) analysis.     

Neonatal benign sacrococcygeal teratoma with N-type rectobulbar fistula

A unique case of benign sacrococcygeal teratoma associated with an N-type rectobulbar fistula is reported.