Disallowed Ramachandran conformations of amino acid residues in protein structures

An analysis of the nature and distribution of disallowed Ramachandran conformations of amino acid residues observed in high resolution protein crystal structures has been carried out. A data set consisting of 110 high resolution, non-homologous, protein crystal structures from the Brookhaven Protein Data Bank was examined. The data set consisted of a total of 18,708 non-Gly residues, which were characterized on the basis of their backbone dihedral angles (phi, psi). Residues falling outside the defined "broad allowed limits" on the Ramachandran map were chosen and the reported B-factor value of the alpha-carbon atom was used to further select well defined disallowed conformations. The conformations of the selected 66 disallowed residues clustered in distinct regions of the Ramachandran map indicating that specific phi, psi angle distortions are preferred under compulsions imposed by local constraints. The distribution of various amino acid residues in the disallowed residue data set showed a predominance of small polar/charged residues, with bulky hydrophobic residues being infrequent. As a further check, for all the 66 cases non-hydrogen van der Waals short contacts in the protein structures were evaluated and compared with the ideal "Ala-dipeptide" constructed using disallowed dihedral angle (phi, psi) values. The analysis reveals that short contacts are eliminated in most cases by local distortions of bond angles. An analysis of the conformation of the identified disallowed residues in related protein structures reveals instances of conservation of unusual stereochemistry.     

Process and die profile design for tube extrusion of γ iron

This study is related to material modeling and die and process design of tube extrusion of γ iron. Strain dependent rate power law is used for material modeling whose coefficients are arrived at through genetic algorithm (GA). Die profile of the tube extrusion process is optimized to produce microstructurally sound product at maximum production speed and minimum left out material in the die. The design problem is formulated as a nonlinear programming problem which is solved using GA. Selection of the processing parameters is carried out using dynamic material modeling (DMM). Using this approach tube extrusion process of γ iron is successfully designed.     

<Emphasis Type="Italic">New-Age</Emphasis>: A Negative Bias Temperature Instability-Estimation Framework for Microarchitectural Components

Degradation of device parameters over the lifetime of a system is emerging as a significant threat to system reliability. Among the aging mechanisms, wearout resulting from Negative Bias Temperature Instability (NBTI) is of particular concern in deep submicron technology generations. While there has been significant effort at the device and circuit level to model and characterize the impact of NBTI, the analysis of NBTI’s impact at the architectural level is still at its infancy. To facilitate architectural level aging analysis, a tool capable of evaluating NBTI vulnerabilities early in the design cycle has been developed that evaluates timing degradation due to NBTI. The tool includes workload-based temperature and performance degradation analysis across a variety of technologies and operating conditions, revealing a complex interplay between factors influencing NBTI timing degradation.     

Using GOMS and NASA-TLX to Evaluate Human–Computer Interaction Process in Interactive Segmentation

HCI plays an important role in interactive medical image segmentation. The Goals, Operators, Methods, and Selection rules (GOMS) model and the National Aeronautics and Space Administration Task Load Index (NASA-TLX) questionnaire are different methods that are often used to evaluate the HCI process. In this article, we aim at improving the HCI process of interactive segmentation using both the GOMS model and the NASA-TLX questionnaire to: 1) identify the relations between these two methods and 2) propose HCI design suggestions based on the synthesis of the evaluation results using both methods. For this, we conducted an experiment where three physicians used two interactive segmentation approaches to segment different types of organs at risk for radiotherapy planning. Using the GOMS model, we identified 16 operators and 10 methods. Further analysis discovered strong relations between the use of GOMS operators and the results of the NASA-TLX questionnaire. Finally, HCI design issues were identified, and suggestions were proposed based on the evaluation results and the identified relations.     

Discovering excitatory relationships using dynamic Bayesian networks

Mining temporal network models from discrete event streams is an important problem with applications in computational neuroscience, physical plant diagnostics, and human–computer interaction modeling. In this paper, we introduce the notion of excitatory networks which are essentially temporal models where all connections are stimulative, rather than inhibitive. The emphasis on excitatory connections facilitates learning of network models by creating bridges to frequent episode mining. Specifically, we show that frequent episodes help identify nodes with high mutual information relationships and that such relationships can be summarized into a dynamic Bayesian network (DBN). This leads to an algorithm that is significantly faster than state-of-the-art methods for inferring DBNs, while simultaneously providing theoretical guarantees on network optimality. We demonstrate the advantages of our approach through an application in neuroscience, where we show how strong excitatory networks can be efficiently inferred from both mathematical models of spiking neurons and several real neuroscience datasets.     

Evolutionary multi objective optimization for rule mining: a review

Evolutionary multi objective optimization (EMOO) systems are evolutionary systems which are used for optimizing various measures of the evolving system. Rule mining has gained attention in the knowledge discovery literature. The problem of discovering rules with specific properties is treated as a multi objective optimization problem. The objectives to be optimized being the metrics like accuracy, comprehensibility, surprisingness, novelty to name a few. There are a variety of EMOO algorithms in the literature. The performance of these EMOO algorithms is influenced by various characteristics including evolutionary technique used, chromosome representation, parameters like population size, number of generations, crossover rate, mutation rate, stopping criteria, Reproduction operators used, objectives taken for optimization, the fitness function used, optimization strategy, the type of data, number of class attributes and the area of application. This study reviews EMOO systems taking the above criteria into consideration. There are other hybridization strategies like use of intelligent agents, fuzzification, meta data and meta heuristics, parallelization, interactiveness with the user, visualization, etc., which further enhance the performance and usability of the system. Genetic Algorithms (GAs) and Genetic Programming (GPs) are two widely used evolutionary strategies for rule knowledge discovery in Data mining. Thus the proposed study aims at studying the various characteristics of the EMOO systems taking into consideration the two evolutionary strategies of Genetic Algorithm and Genetic programming.     

Robust object tracking with background-weighted local kernels

Object tracking is critical to visual surveillance, activity analysis and event/gesture recognition. The major issues to be addressed in visual tracking are illumination changes, occlusion, appearance and scale variations. In this paper, we propose a weighted fragment based approach that tackles partial occlusion. The weights are derived from the difference between the fragment and background colors. Further, a fast and yet stable model updation method is described. We also demonstrate how edge information can be merged into the mean shift framework without having to use a joint histogram. This is used for tracking objects of varying sizes. Ideas presented here are computationally simple enough to be executed in real-time and can be directly extended to a multiple object tracking system.     

Homology modeling of the DNA-binding domain of human Smad5: a molecular model for inhibitor design

Members of the Smad protein family function as signal transducers of the transforming growth factor (TGF-beta) superfamily proteins. The human Smad5 protein, a signal transducer downstream of TGF-beta/BMP receptors, is composed of N-terminal DNA binding domain (MH1) and C-terminal protein-protein interaction domain (MH2) connected together by a linker motif. We used homology-modeling techniques to generate a reliable molecular model of the Smad5 MH1 domain based on the crystal structure of Smad3 MH1 domain. Our study presents the structural features of a BMP-regulated, R-Smad subfamily member (consisting of Smad1, Smad5 and Smad8) for the first time. This model provides a structural basis for explaining both functional similarities and differences between Smad3 and Smad5. Also, the structural model of this molecular target would be useful for structure-based inhibitor design because of its high accuracy. The results of our study provide important insights into understanding the structure-function relationship of the members of the Smad protein family and can serve to guide future genetic and biochemical experiments in this area.     

The Oseen model for internal separated flows

Summary The flow field studied in this paper is the viscous laminar, separated flow downstream of a sudden expansion in a two-dimensional duct. The flow is modelled by the Oseen equations and a solution is sought for the downstream flow given the conditions at the sudden expansion. First, the exact solution to a high-Reynolds-number limit equation suggested by Kumar and Yajnik [6] is obtained. Next, the solution to the full equations is sought in terms of an eigenfunction-expansion procedure which leads to a non-standard eigenvalue problem. A detailed study is made of the latter and a number of expansion procedures are considered for the boundary-value problem. Specific calculations of the separated flow are presented for Reynolds numbers R=10 ⁿ , n=0–5. It is found that as R the solution of the full equation does indeed agree with the solution of the high-Reynolds-number limit equation. In particular it is found that the length of the recirculating region x _r scales with R as R.     

Phase transition in L-alaninium oxalate by photoacoustics

Phase transition in L-alaninium oxalate is studied by using TG, DTA and photoacoustic spectroscopy. A sharp transition at 378 K by photoacoustics is observed whereas at the same temperature the endothermic energy change observed by TG and DTA is not very sharp. This is discussed in detail with reference to the other known data for the organic crystals.