Computational Verification of Two Universal Relations for Simple Ionic Liquids. Kinetic Properties of a Model 2:1 Molten Salt

Two semianalytical relations [Nature, 1996, 381, 137 and Phys. Rev. Lett. 2001, 87, 245901] predicting dynamical coefficients of simple liquids on the basis of structural properties have been tested by extensive molecular dynamics simulations for an idealized 2:1 model molten salt. In agreement with previous simulation studies, our results support the validity of the relation expressing the self-diffusion coefficient as a Function of the radial distribution functions for all thermodynamic conditions such that the system is in the ionic (ie., fully dissociated) liquid state. Deviations are apparent for high-density samples in the amorphous state and in the low-density, low-temperature range, when ions condense into AB(2) molecules. A similar relation predicting the ionic conductivity is only partially validated by our data. The simulation results, covering 210 distinct thermodynamic states, represent an extended database to tune and validate semianalytical theories of dynamical properties and provide a baseline for the interpretation of properties of more complex systems such as the room-temperature ionic liquids.

Structural similarity of directed universal hierarchical graphs: A low computational complexity approach

In the present paper we mainly introduce an efficient approach to measure the structural similarity of so called directed universal hierarchical graphs. We want to underline that directed universal hierarchical graphs can be obtained from generalized trees which are already introduced. In order to classify these graphs, we state our novel graph similarity method. As a main result we notice that our novel algorithm has low computational complexity. (c) 2007 Elsevier Inc. All rights reserved.

A Capabilities-Aware Framework for Using Computational Accelerators in Data-Intensive Computing

Multicore computational accelerators such as GPUs are now commodity components for highperformance computing at scale. While such accelerators have been studied in some detail as stand-alone computational engines, their integration in large-scale distributed systems raises new challenges and trade-offs. In this paper, we present an exploration of resource management alternatives for building asymmetric accelerator-based distributed systems. We present these alternatives in the context of a capabilities-aware framework for data-intensive computing, which uses an enhanced implementation of the MapReduce programming model for accelerator-based clusters, compared to the state of the art. The framework can transparently utilize heterogeneous accelerators for deriving high performance with low programming effort. Our work is the first to compare heterogeneous types of accelerators, GPUs and a Cell processors, in the same environment and the first to explore the trade-offs between compute-efficient and control-efficient accelerators on data-intensive systems. Our investigation shows that our framework scales well with the number of different compute nodes. Furthermore, it runs simultaneously on two different types of accelerators, successfully adapts to the resource capabilities, and performs 26.9% better on average than a static execution approach.

A COMPUTATIONAL INVESTIGATION OF THE NEON-LIKE GERMANIUM COLLISIONALLY PUMPED LASER

The complex problem of a collisionally pumped Ne-like geranium laser is examined through several detailed models. The central model is EHYBRID; a 1 1/2D fluid code which self consistently treats the plasma expansion with the atomic physics of the Ne-like ion for 124 excited levels through a collisional radiative treatment. The output of EHYBRID is used as data for ray-tracing and saturation codes which generate experimental observables. A detailed description of the models is given.

A computational model of cellular response to modulated radiation fields

Purpose:
To develop a model to describe the response of cell populations to spatially modulated radiation exposures of relevance to advanced radiotherapies.

Materials and Methods:
A Monte Carlo model of cellular radiation response was developed. This model incorporated damage from both direct radiation and intercellular communication including bystander signaling. The predictions of this model were compared to previously measured survival curves for a normal human fibroblast line (AGO1522) and prostate tumor cells (DU145) exposed to spatially modulated fields.

Results:
The model was found to be able to accurately reproduce cell survival both in populations which were directly exposed to radiation and those which were outside the primary treatment field. The model predicts that the bystander effect makes a significant contribution to cell killing even in uniformly irradiated cells. The bystander effect contribution varies strongly with dose, falling from a high of 80% at low doses to 25% and 50% at 4 Gy for AGO1522 and DU145 cells, respectively. This was verified using the inducible nitric oxide synthase inhibitor aminoguanidine to inhibit the bystander effect in cells exposed to different doses, which showed significantly larger reductions in cell killing at lower doses.

Conclusions:
The model presented in this work accurately reproduces cell survival following modulated radiation exposures, both in and out of the primary treatment field, by incorporating a bystander component. In addition, the model suggests that the bystander effect is responsible for a significant portion of cell killing in uniformly irradiated cells, 50% and 70% at doses of 2 Gy in AGO1522 and DU145 cells, respectively. This description is a significant departure from accepted radiobiological models and may have a significant impact on optimization of treatment planning approaches if proven to be applicable in vivo.

Molecular Dynamics of HIV1-Integrase in Complex with 93del - A Structural Perspective on the Mechanism of Inhibition

HIV1 integrase is an important target for the antiviral therapy. Guanine-rich quadruplex, such as 93del, have been shown to be potent inhibitors of this enzyme and thus representing a new class of antiviral agents. Although X-ray and NMR structures of HIV1 integrase and 93del have been reported, there is no structural information of the complex and the mechanism of inhibition still remains unexplored. A number of computational methods including automated protein-DNA docking and molecular dynamics simulation in explicit solvent were used to model the binding of 93del to HIV1 integrase. Analysis of the dynamic behaviour of the complex using principal components analysis and elastic network modelling techniques allow us to understand how the binding of 93del aptamer and its interactions with key residues affect the intrinsic motions of the catalytic loops by stabilising them in catalytically inactive conformations. Such insights into the structural mechanism of inhibition can aid in improving the design of anti-HIV aptamers.