New insights on growth mechanisms of protein clusters at surfaces: an AFM and simulation study

Despite its relevance to a wide range of technological and fundamental areas, a quantitative understanding of protein surface clustering dynamics is often lacking. In inorganic crystal growth, surface clustering of adatoms is well described by diffusion-aggregation models. In such models, the statistical properties of the aggregate arrays often reveal the molecular scale aggregation processes. We investigate the potential of these theories to reveal hitherto hidden facets of protein clustering by carrying out concomitant observations of lysozyme adsorption onto mica surfaces, using atomic force microscopy. and Monte Carlo simulations of cluster nucleation and growth. We find that lysozyme clusters diffuse across the substrate at a rate that varies inversely with size. This result suggests which molecular scale mechanisms are responsible for the mobility of the proteins on the substrate. In addition the surface diffusion coefficient of the monomer can also be extracted from the comparison between experiments and simulations. While concentrating on a model system of lysozyme-on-mica, this 'proof of concept' study successfully demonstrates the potential of our approach to understand and influence more biomedically applicable protein-substrate couples.

Solid phases of cyclopentane: combined experimental and simulation study

The phase diagram of cyclopentane has been studied by powder neutron diffraction, providing diffraction patterns for phases I, II, and III, over a range of temperatures and pressures. The putative phase IV was not observed. The structure of the ordered phase III has been solved by single-crystal diffraction. Computational modeling reveals that there are many equienergetic ordered structures for cyclopentane within a small energy range. Molecular dynamics simulations reproduce the structures and diffraction patterns for phases I and III and also show an intermediate disordered phase, which is used to interpret phase II.

Design, testing, and simulation of fibre composite leaf springs for heavy axle loads

This paper summarizes the design, manufacturing, testing, and finite element analysis (FEA) of glass-fibre-reinforced polyester leaf springs for rail freight vehicles. FEA predictions of load-deflection curves under static loading are presented, together with comparisons with test results. Bending stress distribution at typical load conditions is plotted for the springs. The springs have been mounted on a real wagon and drop tests at tare and full load have been carried out on a purpose-built shaker rig. The transient response of the springs from tests and FEA is presented and discussed.

Innovative approach to building systems integration problems: Using systems theory, technological forecasting and scenario planning

Building services are worth about 2% GDP and are essential for the effective and efficient operations of the building. It is increasingly recognised that the value of a building is related to the way it supports the client organisation’s ongoing business operations. Building services are central to the functional performance of buildings and provide the necessary conditions for health, well-being, safety and security of the occupants. They frequently comprise several technologically distinct sub-systems and their design and construction requires the involvement of numerous disciplines and trades. Designers and contractors working on the same project are frequently employed by different companies. Materials and equipment is supplied by a diverse range of manufacturers. Facilities managers are responsible for operation of the building service in use. The coordination between these participants is crucially important to achieve optimum performance, but too often is neglected. This leaves room for serious faults. The need for effective integration is important. Modern technology offers increasing opportunities for integrated personal-control systems for lighting, ventilation and security as well as interoperability between systems. Opportunities for a new mode of systems integration are provided by the emergence of PFI/PPP procurements frameworks. This paper attempts to establish how systems integration can be achieved in the process of designing, constructing and operating building services. The essence of the paper therefore is to envisage the emergent organisational responses to the realisation of building services as an interactive systems network.

Solving optimal control problems with state constraints using nonlinear programming and simulation tools

This paper illustrates how nonlinear programming and simulation tools, which are available in packages such as MATLAB and SIMULINK, can easily be used to solve optimal control problems with state- and/or input-dependent inequality constraints. The method presented is illustrated with a model of a single-link manipulator. The method is suitable to be taught to advanced undergraduate and Master's level students in control engineering.

Urban microclimates and simulation

This chapter examines the workings of urban microclimates and looks at the associated causes and effects of the urban heat island (UHI). It also clarifies the relationship between urban form and the key climatic parameters (sun, daylight, wind, temperature). A particular section is devoted to the concepts of UHI intensity and sky view factor (SVF); these are useful indicators for researchers in this area. The challenge of how to model urban microclimates is covered, featuring the six archetypal urban forms familiar to analysts involved in using simulation software. The latter sections address the issue of urban thermal comfort, the importance of urban ventilation and finally what mitigating strategies can be implemented to curb negative UHI effects.

Regularized logistic models for probabilistic forecasting and diagnostics

Logistic models are studied as a tool to convert dynamical forecast information (deterministic and ensemble) into probability forecasts. A logistic model is obtained by setting the logarithmic odds ratio equal to a linear combination of the inputs. As with any statistical model, logistic models will suffer from overfitting if the number of inputs is comparable to the number of forecast instances. Computational approaches to avoid overfitting by regularization are discussed, and efficient techniques for model assessment and selection are presented. A logit version of the lasso (originally a linear regression technique), is discussed. In lasso models, less important inputs are identified and the corresponding coefficient is set to zero, providing an efficient and automatic model reduction procedure. For the same reason, lasso models are particularly appealing for diagnostic purposes.