Transformations between HCLP and PCSP

We present a general methodology for transforming between HCLP and PCSP in both directions. HCLP and PCSP each have advantages when modelling problems, and each have advantages when implementing models and solving them. Using the work presented in this paper, the appropriate paradigm can be used for each of these steps, with a meaning-preserving transformation in between if necessary

Developing a new business model for enabling research - the case of the ACPFG in Australia

Publisher's postprint archived as permitted by publisher.The way in which companies, research centres and educational institutions are organised and structured may provide a competitive advantage for commercialisation, in particular if companies are dependent on the deployment of complementary assets and capabilities by third parties. This paper presents the case of the Australian Centre for Plant Functional Genomics (ACPFG), a private agricultural biotechnology (agbiotech) company specialising in early stage Research and Development (R&D) to produce superior adapted cereal varieties, tolerant to abiotic stress conditions such as drought, frost, salt, or mineral toxicity, all of which have a direct and negative impact on plant growth and crop productivity. The organisational structure of the company has been influenced and shaped by Government policy, shareholders expectations and trends in the agbiotech industrial organisation. It has proved attractive to potential alliance partners for collaborative R&D and commercialisation. We present the ACPFG as a new business model to fund basic research and facilitate technology transfer.Stephanie C. Agius, David Corkindale, Antonio G. Dottore, Michael Gilber

Prediction of protein-protein interaction types using association rule based classification

This article has been made available through the Brunel Open Access Publishing Fund - Copyright @ 2009 Park et alBackground: Protein-protein interactions (PPI) can be classified according to their characteristics into, for example obligate or transient interactions. The identification and characterization of these PPI types may help in the functional annotation of new protein complexes and in the prediction of protein interaction partners by knowledge driven approaches. Results: This work addresses pattern discovery of the interaction sites for four different interaction types to characterize and uses them for the prediction of PPI types employing Association Rule Based Classification (ARBC) which includes association rule generation and posterior classification. We incorporated domain information from protein complexes in SCOP proteins and identified 354 domain-interaction sites. 14 interface properties were calculated from amino acid and secondary structure composition and then used to generate a set of association rules characterizing these domain-interaction sites employing the APRIORI algorithm. Our results regarding the classification of PPI types based on a set of discovered association rules shows that the discriminative ability of association rules can significantly impact on the prediction power of classification models. We also showed that the accuracy of the classification can be improved through the use of structural domain information and also the use of secondary structure content. Conclusion: The advantage of our approach is that we can extract biologically significant information from the interpretation of the discovered association rules in terms of understandability and interpretability of rules. A web application based on our method can be found at http://bioinfo.ssu.ac.kr/~shpark/picasso/SHP was supported by the Korea Research Foundation Grant funded by the Korean Government(KRF-2005-214-E00050). JAR has been supported by the Programme Alβan, the European Union Programme of High level Scholarships for Latin America, scholarship E04D034854CL. SK was supported by Soongsil University Research Fund

Microgravity Combustion Diagnostics Workshop

Through the Microgravity Science and Applications Division (MSAD) of the Office of Space Science and Applications (OSSA) at NASA Headquarters, a program entitled, Advanced Technology Development (ATD) was promulgated with the objective of providing advanced technologies that will enable the development of future microgravity science and applications experimental flight hardware. Among the ATD projects one, Microgravity Combustion Diagnostics (MCD), has the objective of developing advanced diagnostic techniques and technologies to provide nonperturbing measurements of combustion characteristics and parameters that will enhance the scientific integrity and quality of microgravity combustion experiments. As part of the approach to this project, a workshop was held on July 28 and 29, 1987, at the NASA Lewis Research Center. A small group of laser combustion diagnosticians met with a group of microgravity combustion experimenters to discuss the science requirements, the state-of-the-art of laser diagnostic technology, and plan the direction for near-, intermediate-, and long-term programs. This publication describes the proceedings of that workshop

Motor starting techniques for the 2 to 15 kW Brayton space power system

Motor starting techniques for 2-15 kW Brayton space power syste

Theory and Simulation of the diffusion of kinks on dislocations in bcc metals

Isolated kinks on thermally fluctuating (1/2) screw, edge and (1/2) edge dislocations in bcc iron are simulated under zero stress conditions using molecular dynamics (MD). Kinks are seen to perform stochastic motion in a potential landscape that depends on the dislocation character and geometry, and their motion provides fresh insight into the coupling of dislocations to a heat bath. The kink formation energy, migration barrier and friction parameter are deduced from the simulations. A discrete Frenkel-Kontorova-Langevin (FKL) model is able to reproduce the coarse grained data from MD at a fraction of the computational cost, without assuming an a priori temperature dependence beyond the fluctuation-dissipation theorem. Analytic results reveal that discreteness effects play an essential r\^ole in thermally activated dislocation glide, revealing the existence of a crucial intermediate length scale between molecular and dislocation dynamics. The model is used to investigate dislocation motion under the vanishingly small stress levels found in the evolution of dislocation microstructures in irradiated materials

Effect of Edge Roughness on Electronic Transport in Graphene Nanoribbon Channel Metal Oxide Semiconductor Field-Effect Transistors

Results of quantum mechanical simulations of the influence of edge disorder on transport in graphene nanoribbon metal oxide semiconductor field-effect transistors (MOSFETs) are reported. The addition of edge disorder significantly reduces ON-state currents and increases OFF-state currents, and introduces wide variability across devices. These effects decrease as ribbon widths increase and as edges become smoother. However the bandgap decreases with increasing width, thereby increasing the band-to-band tunneling mediated subthreshold leakage current even with perfect nanoribbons. These results suggest that without atomically precise edge control during fabrication, MOSFET performance gains through use of graphene will be difficult to achieve.Comment: 8 pages, 5 figure

Modelling the cAMP pathway using BioNessie, and the use of BVP techniques for solving ODEs (Poster Presentation)

Copyright @ 2007 Gu et al; licensee BioMed Central LtdBiochemists often conduct experiments in-vivo in order to explore observable behaviours and understand the dynamics of many intercellular and intracellular processes. However an intuitive understanding of their dynamics is hard to obtain because most pathways of interest involve components connected via interlocking loops. Formal methods for modelling and analysis of biochemical pathways are therefore indispensable. To this end, ODEs (ordinary differential equations) have been widely adopted as a method to model biochemical pathways because they have an unambiguous mathematical format and are amenable to rigorous quantitative analysis. BioNessie http://www.bionessie.com webcite is a workbench for the composition, simulation and analysis of biochemical networks which is being developed in by the Systems Biology team at the Bioinformatics Research Centre as a part of a large DTI funded project 'BPS: A Software Tool for the Simulation and Analysis of Biochemical Networks' http://www.brc.dcs.gla.ac.uk/projects/dti_beacon webcite. BioNessie is written in Java using NetBeans Platform libraries that makes it platform independent. The software employs specialised differential equations solvers for stiff and non-stiff systems to produce model simulation traces. BioNessie provides a user-friendly interfact that comes up with an intuitive tree-based graphical layout, an edition function to SBML-compatible models and feature of data output