Visual Analysis of Biomolecular Surfaces

Surface models of biomolecules have become crucially important for the study and understanding of interaction between biomolecules and their environment. We argue for the need for a detailed understanding of biomolecular surfaces by describing several applications in computational and structural biology. We review methods used to model, represent, characterize, and visualize biomolecular surfaces focusing on the role that geometry and topology play in identifying features on the surface. These methods enable the development of efficient computational and visualization tools for studying the function of biomolecules.

Computing complete test graphs for hierarchical systems

Conformance testing focuses on checking whether an implementation. under test (IUT) behaves according to its specification. Typically, testers are interested it? performing targeted tests that exercise certain features of the IUT This intention is formalized as a test purpose. The tester needs a "strategy" to reach the goal specified by the test purpose. Also, for a particular test case, the strategy should tell the tester whether the IUT has passed, failed. or deviated front the test purpose. In [8] Jeron and Morel show how to compute, for a given finite state machine specification and a test purpose automaton, a complete test graph (CTG) which represents all test strategies. In this paper; we consider the case when the specification is a hierarchical state machine and show how to compute a hierarchical CTG which preserves the hierarchical structure of the specification. We also propose an algorithm for an online test oracle which avoids a space overhead associated with the CTG.

A simple n-state model for water

A simple n-state configurational excitation model which takes into account the presence of weakly connected pentamer units in liquid water is proposed. The model has features of both the “continuum” and “mixture” models. Calculations based on this model satisfactorily account for the important, diagnostic thermodynamic properties of water such as the density maximum, fraction of monomers and so on.

Electrochemical phase formation involving multicomponents: hemispherical overlap models for varied nucleation and growth conditions

The phenomenological theory of hemispherical growth in the context of phase formation with more than one component is presented. The model discusses in a unified manner both instantaneous and progressive nucleation (at the substrate) as well as arbitrary growth rates (e.g. constant and diffusion controlled growth rates). A generalized version of Avrami ansatz (a mean field description) is used to tackle the ''overlap'' aspects arising from the growing multicentres of the many components involved, observing that the nucleation is confined to the substrate plane only. The time evolution of the total extent of macrogrowth as well as those of the individual components are discussed explicitly for the case of two phases. The asymptotic expressions for macrogrowth are derived. Such analysis depicts a saturation limit (i.e. the maximum extent of growth possible) for the slower growing component and its dependence on the kinetic parameters which, in the electrochemical context, can be controlled through potential. The significance of this model in the context of multicomponent alloy deposition and possible future directions for further development are pointed out.

Context based service discovery for ubiquitous applications

Service discovery is vital in ubiquitous applications, where a large number of devices and software components collaborate unobtrusively and provide numerous services without user intervention. Existing service discovery schemes use a service matching process in order to offer services of interest to the users. Potentially, the context information of the users and surrounding environment can be used to improve the quality of service matching. To make use of context information in service matching, a service discovery technique needs to address certain challenges. Firstly, it is required that the context information shall have unambiguous representation. Secondly, the devices in the environment shall be able to disseminate high level and low level context information seamlessly in the different networks. And thirdly, dynamic nature of the context information be taken into account. We propose a C-IOB(Context-Information, Observation and Belief) based service discovery model which deals with the above challenges by processing the context information and by formulating the beliefs based on the observations. With these formulated beliefs the required services will be provided to the users. The method has been tested with a typical ubiquitous museum guide application over different cases. The simulation results are time efficient and quite encouraging.

Executable Analysis using Abstract Interpretation with Circular Linear Progressions

We propose a new abstract domain for static analysis of executable code. Concrete states are abstracted using circular linear progressions (CLPs). CLPs model computations using a finite word length as is seen in any real life processor. The finite abstraction allows handling overflow scenarios in a natural and straight-forward manner. Abstract transfer functions have been defined for a wide range of operations which makes this domain easily applicable for analyzing code for a wide range of ISAs. CLPs combine the scalability of interval domains with the discreteness of linear congruence domains. We also present a novel, lightweight method to track linear equality relations between static objects that is used by the analysis to improve precision. The analysis is efficient, the total space and time overhead being quadratic in the number of static objects being tracked.

A model of coupled thermal, mechanical, and electrostatic field effects in III-N thin film heterostructures

A one-dimensional coupled multi-physics based model has been developed to accurately compute the effects of electrostatic, mechanical, and thermal field interactions on the electronic energy band structure in group III-nitrides thin film heterostructures. Earlier models reported in published literature assumes electro-mechanical field with uniform temperature thus neglecting self-heating. Also, the effects of diffused interface on the energy band structure were not studied. We include these effects in a self-consistent manner wherein the transport equation is introduced along with the electro-mechanical models, and the lattice structural variation as observed in experiments are introduced at the interface. Due to these effects, the electrostatic potential distribution in the heterostructure is altered. The electron and hole ground state energies decrease by 5% and 9%, respectively, at a relative temperature of 700 K, when compared with the results obtained from the previously reported electro-mechanical model assuming constant and uniform temperature distribution. A diffused interface decreases the ground state energy of electrons and holes by about 11% and 9%, respectively, at a relative temperature of 700 K when compared with the predictions based on uniform temperature based electro-mechanical model. (C) 2013 AIP Publishing LLC.

Interdependent cache analyses for better precision and safety

One of the challenges for accurately estimating Worst Case Execu-tion Time(WCET) of executables is to accurately predict their cache behaviour. Various techniques have been developed to predict the cache contents at different program points to estimate the execution time of memory-accessing instructions. One of the most widely used techniques is Abstract Interpretation based Must Analysis, which de-termines the cache blocks guaranteed to be present in the cache, and hence provides safe estimation of cache hits and misses. However,Must Analysis is highly imprecise, and platforms using Must Analysis have been known to produce blown-up WCET estimates. In our work, we propose to use May Analysis to assist the Must Analysis cache up-date and make it more precise. We prove the safety of our approach as well as provide examples where our Improved Must Analysis provides better precision. Further, we also detect a serious flaw in the original Persistence Analysis, and use Must and May Analysis to assist the Persistence Analysis cache update, to make it safe and more precise than the known solutions to the problem.

Role of melt convection on optimization of PCM-based heat sink under cyclic heat load

In this article, we study the thermal performance of phase-change material (PCM)-based heat sinks under cyclic heat load and subjected to melt convection. Plate fin type heat sinks made of aluminum and filled with PCM are considered in this study. The heat sink is heated from the bottom. For a prescribed value of heat flux, design of such a heat sink can be optimized with respect to its geometry, with the objective of minimizing the temperature rise during heating and ensuring complete solidification of PCM at the end of the cooling period for a given cycle. For given length and base plate thickness of a heat sink, a genetic algorithm (GA)-based optimization is carried out with respect to geometrical variables such as fin thickness, fin height, and the number of fins. The thermal performance of the heat sink for a given set of parameters is evaluated using an enthalpy-based heat transfer model, which provides the necessary data for the optimization algorithm. The effect of melt convection is studied by taking two cases, one without melt convection (conduction regime) and the other with convection. The results show that melt convection alters the results of geometrical optimization.

Adaptive Flight-Control Design Using Neural-Network-Aided Optimal Nonlinear Dynamic Inversion

A neural-network-aided nonlinear dynamic inversion-based hybrid technique of model reference adaptive control flight-control system design is presented in this paper. Here, the gains of the nonlinear dynamic inversion-based flight-control system are dynamically selected in such a manner that the resulting controller mimics a single network, adaptive control, optimal nonlinear controller for state regulation. Traditional model reference adaptive control methods use a linearized reference model, and the presented control design method employs a nonlinear reference model to compute the nonlinear dynamic inversion gains. This innovation of designing the gain elements after synthesizing the single network adaptive controller maintains the advantages that an optimal controller offers, yet it retains a simple closed-form control expression in state feedback form, which can easily be modified for tracking problems without demanding any a priori knowledge of the reference signals. The strength of the technique is demonstrated by considering the longitudinal motion of a nonlinear aircraft system. An extended single network adaptive control/nonlinear dynamic inversion adaptive control design architecture is also presented, which adapts online to three failure conditions, namely, a thrust failure, an elevator failure, and an inaccuracy in the estimation of C-M alpha. Simulation results demonstrate that the presented adaptive flight controller generates a near-optimal response when compared to a traditional nonlinear dynamic inversion controller.

Path Sensitive Cache Analysis Using Cache Miss Paths

Cache analysis plays a very important role in obtaining precise Worst Case Execution Time (WCET) estimates of programs for real-time systems. While Abstract Interpretation based approaches are almost universally used for cache analysis, they fail to take advantage of its unique requirement: it is not necessary to find the guaranteed cache behavior that holds across all executions of a program. We only need the cache behavior along one particular program path, which is the path with the maximum execution time. In this work, we introduce the concept of cache miss paths, which allows us to use the worst-case path information to improve the precision of AI-based cache analysis. We use Abstract Interpretation to determine the cache miss paths, and then integrate them in the IPET formulation. An added advantage is that this further allows us to use infeasible path information for cache analysis. Experimentally, our approach gives more precise WCETs as compared to AI-based cache analysis, and we also provide techniques to trade-off analysis time with precision to provide scalability.

Reservoir Operation with Fuzzy State Variables for Irrigation of Multiple Crops

This paper presents the development and application of a stochastic dynamic programming model with fuzzy state variables for irrigation of multiple crops. A fuzzy stochastic dynamic programming (FSDP) model is developed in which the reservoir storage and soil moisture of the crops are considered as fuzzy numbers, and the reservoir inflow is considered as a stochastic variable. The model is formulated with an objective of minimizing crop yield deficits, resulting in optimal water allocations to the crops by maintaining storage continuity and soil moisture balance. The standard fuzzy arithmetic method is used to solve all arithmetic equations with fuzzy numbers, and the fuzzy ranking method is used to compare two or more fuzzy numbers. The reservoir operation model is integrated with a daily-based water allocation model, which results in daily temporal variations of allocated water, soil moisture, and crop deficits. A case study of an existing Bhadra reservoir in Karnataka, India, is chosen for the model application. The FSDP is a more realistic model because it considers the uncertainty in discretization of state variables. The results obtained using the FSDP model are found to be more acceptable for the case study than those of the classical stochastic dynamic model and the standard operating model, in terms of 10-day releases from the reservoir and evapotranspiration deficit. (C) 2015 American Society of Civil Engineers.

Continuum in the X-Z-Y Weak Bonds: Z= Main Group Elements

The Continuum in the variation of the X-Z bond length change from blue-shifting to red-shifting through zero-shifting in the X-Z---Y complex is inevitable. This has been analyzed by ab-initio molecular orbital calculations using Z= Hydrogen, Halogens, Chalcogens, and Pnicogens as prototypical examples. Our analysis revealed that, the competition between negative hyperconjugation within the donor (X-Z) molecule and Charge Transfer (CT) from the acceptor (Y) molecule is the primary reason for the X-Z bond length change. Here, we report that, the proper tuning of X-and Y-group for a particular Z-can change the blue-shifting nature of X-Z bond to zero-shifting and further to red-shifting. This observation led to the proposal of a continuum in the variation of the X-Z bond length during the formation of X-Z---Y complex. The varying number of orbitals and electrons available around the Z-atom differentiates various classes of weak interactions and leads to interactions dramatically different from the H-Bond. Our explanations based on the model of anti-bonding orbitals can be transferred from one class of weak interactions to another. We further take the idea of continuum to the nature of chemical bonding in general. (C) 2015 Wiley Periodicals, Inc.