Random walks in local dynamics of network losses

We suggest a model for data losses in a single node (memory buffer) of a packet-switched network (like the Internet) which reduces to one-dimensional discrete random walks with unusual boundary conditions. By construction, the model has critical behavior with a sharp transition from exponentially small to finite losses with increasing data arrival rate. We show that for a finite-capacity buffer at the critical point the loss rate exhibits strong fluctuations and non-Markovian power-law correlations in time, in spite of the Markovian character of the data arrival process.

The influence of pH and fluid dynamics on the antibacterial efficacy of 45S5 Bioglass

In recent years, there has been considerable interest in the potential antibacterial properties that bioactive glasses may possess. However, there have been several conflicting reports on the antibacterial efficacy of 45S5 Bioglass®. Various mechanisms regarding its mode of action have been proposed, such as changes in the environmental pH, increased osmotic pressure, and ‘needle like’ sharp glass debris which could potentially damage prokaryotic cell walls and thus inactivate bacteria. In this current study, a systematic investigation was undertaken on the antibacterial efficacy of 45S5 Bioglass® on Escherichia coli NCTC 10538 and Staphylococcus aureus ATCO 6538 under a range of clinically relevant scenarios including varying Bioglass® concentration, direct and indirect contact between Bioglass® and microorganisms, static and shaking incubation conditions, elevated and neutralised pH environments. The results demonstrated that under elevated pH conditions, Bioglass® particles has no antibacterial effect on S. aureus whilst, a concentration dependent antibacterial effect against E. coli was observed. However, the antibacterial activity ceased when the pH of the media was neutralised. The results of this current study therefore suggest that the mechanism of antibacterial activity of Bioglass® is associated with changes in the environmental pH; an environment that is less likely to occur in vivo due to buffering of the system.

The role of pinning and instability in a class of non-equilibrium growth models

We study the dynamics of a growing crystalline facet where the growth mechanism is controlled by the geometry of the local curvature. A continuum model, in (2+1) dimensions, is developed in analogy with the Kardar-Parisi-Zhang (KPZ) model is considered for the purpose. Following standard coarse graining procedures, it is shown that in the large time, long distance limit, the continuum model predicts a curvature independent KPZ phase, thereby suppressing all explicit effects of curvature and local pinning in the system, in the "perturbative" limit. A direct numerical integration of this growth equation, in 1+1 dimensions, supports this observation below a critical parametric range, above which generic instabilities, in the form of isolated pillared structures lead to deviations from standard scaling behaviour. Possibilities of controlling this instability by introducing statistically "irrelevant" (in the sense of renormalisation groups) higher ordered nonlinearities have also been discussed.

A taxonomy of heterogeneity and dynamics in particle swarm optimisation

We propose a taxonomy for heterogeneity and dynamics of swarms in PSO, which separates the consideration of homogeneity and heterogeneity from the presence of adaptive and non-adaptive dynamics, both at the particle and swarm level. It thus supports research into the separate and combined contributions of each of these characteristics. An analysis of the literature shows that most recent work has focussed on only parts of the taxonomy. Our results agree with prior work that both heterogeneity and dynamics are useful. However while heterogeneity does typically improve PSO, this is often dominated by the improvement due to dynamics. Adaptive strategies used to generate heterogeneity may end up sacrificing the dynamics which provide the greatest performance increase. We evaluate exemplar strategies for each area of the taxonomy and conclude with recommendations.

Travelling-wave model of semiconductor optical amplifier based non-linear loop mirror

A travelling-wave model of a semiconductor optical amplifier based non-linear loop mirror is developed to investigate the importance of travelling-wave effects and gain/phase dynamics in predicting device behaviour. A constant effective carrier recovery lifetime approximation is found to be reasonably accurate (±10%) within a wide range of control pulse energies. Based on this approximation, a heuristic model is developed for maximum computational efficiency. The models are applied to a particular configuration involving feedback.

Towards novel compact laser sources for non-invasive diagnostics and treatment

An important field of application of lasers is biomedical optics. Here, they offer great utility for diagnosis, therapy and surgery. For the development of novel methods of laser-based biomedical diagnostics careful study of light propagation in biological tissues is necessary to enhance our understanding of the optical measurements undertaken, increase research and development capacity and the diagnostic reliability of optical technologies. Ultimately, fulfilling these requirements will increase uptake in clinical applications of laser based diagnostics and therapeutics. To address these challenges informative biomarkers relevant to the biological and physiological function or disease state of the organism must be selected. These indicators are the results of the analysis of tissues and cells, such as blood. For non-invasive diagnostics peripheral blood, cells and tissue can potentially provide comprehensive information on the condition of the human organism. A detailed study of the light scattering and absorption characteristics can quickly detect physiological and morphological changes in the cells due to thermal, chemical, antibiotic treatments, etc [1-5]. The selection of a laser source to study the structure of biological particles also benefits from the fact that gross pathological changes are not induced and diagnostics make effective use of the monochromatic directional coherence properties of laser radiation.

Fibre optic sensors for high speed hypervelocity impact studies and low velocity drop tests

The initial aim of this project was to develop a non-contact fibre optic based displacement sensor to operate in the harsh environment of a 'Light Gas Gun' (LGG), which can 'fire' small particles at velocities ranging from 1-8.4 km/s. The LGG is used extensively for research in aerospace to analyze the effects of high speed impacts on materials. Ideally the measurement should be made close to the centre of the impact to minimise corruption of the data from edge effects and survive the impact. A further requirement is that it should operate at a stand-off distance of ~ 8cm. For these reasons we chose to develop a pseudo con-focal intensity sensor, which demonstrated resolution comparable with conventional PVDF sensors combined with high survivability and low cost. A second sensor was developed based on 'Fibre Bragg Gratings' (FBG) which although requiring contact with the target the low weight and very small contact area had minimal effect on the dynamics of the target. The FBG was mounted either on the surface of the target or tangentially between a fixed location. The output signals from the FBG were interrogated in time by a new method. Measurements were made on composite and aluminium plates in the LGG and on low speed drop tests. The particle momentum for the drop tests was chosen to be similar to that of the particles used in the LGG.

Multiscale molecular dynamics/hydrodynamics implementation of two dimensional “Mercedes Benz” water model

A multiscale Molecular Dynamics/Hydrodynamics implementation of the 2D Mercedes Benz (MB or BN2D) [1] water model is developed and investigated. The concept and the governing equations of multiscale coupling together with the results of the two-way coupling implementation are reported. The sensitivity of the multiscale model for obtaining macroscopic and microscopic parameters of the system, such as macroscopic density and velocity fluctuations, radial distribution and velocity autocorrelation functions of MB particles, is evaluated. Critical issues for extending the current model to large systems are discussed.

Comprehensive secondary pyrolysis in fluidized-bed fast pyrolysis of biomass, a fluid dynamics based modelling effort

Homogenous secondary pyrolysis is category of reactions following the primary pyrolysis and presumed important for fast pyrolysis. For the comprehensive chemistry and fluid dynamics, a probability density functional (PDF) approach is used; with a kinetic scheme comprising 134 species and 4169 reactions being implemented. With aid of acceleration techniques, most importantly Dimension Reduction, Chemistry Agglomeration and In-situ Tabulation (ISAT), a solution within reasonable time was obtained. More work is required; however, a solution for levoglucosan (C6H10O5) being fed through the inlet with fluidizing gas at 500 °C, has been obtained. 88.6% of the levoglucosan remained non-decomposed, and 19 different decomposition product species were found above 0.01% by weight. A homogenous secondary pyrolysis scheme proposed can thus be implemented in a CFD environment and acceleration techniques can speed-up the calculation for application in engineering settings.

GPCR-styrene maleic acid lipid particles (GPCR-SMALPs):their nature and potential

G-protein-coupled receptors (GPCRs) form the largest class of membrane proteins and are an important target for therapeutic drugs. These receptors are highly dynamic proteins sampling a range of conformational states in order to fulfil their complex signalling roles. In order to fully understand GPCR signalling mechanisms it is necessary to extract the receptor protein out of the plasma membrane. Historically this has universally required detergents which inadvertently strip away the annulus of lipid in close association with the receptor and disrupt lateral pressure exerted by the bilayer. Detergent-solubilized GPCRs are very unstable which presents a serious hurdle to characterization by biophysical methods. A range of strategies have been developed to ameliorate the detrimental effect of removing the receptor from the membrane including amphipols and reconstitution into nanodics stabilized by membrane scaffolding proteins (MSPs) but they all require exposure to detergent. Poly(styrene-co-maleic acid) (SMA) incorporates into membranes and spontaneously forms nanoscale poly(styrene-co-maleic acid) lipid particles (SMALPs), effectively acting like a 'molecular pastry cutter' to 'solubilize' GPCRs in the complete absence of detergent at any stage and with preservation of the native annular lipid throughout the process. GPCR-SMALPs have similar pharmacological properties to membrane-bound receptor, exhibit enhanced stability compared with detergent-solubilized receptors and being non-proteinaceous in nature, are fully compatible with downstream biophysical analysis of the encapsulated GPCR.

Dynamics of spatial heterogeneity in a landfill with interacting phase densities:a stochastic analysis

A landfill represents a complex and dynamically evolving structure that can be stochastically perturbed by exogenous factors. Both thermodynamic (equilibrium) and time varying (non-steady state) properties of a landfill are affected by spatially heterogenous and nonlinear subprocesses that combine with constraining initial and boundary conditions arising from the associated surroundings. While multiple approaches have been made to model landfill statistics by incorporating spatially dependent parameters on the one hand (data based approach) and continuum dynamical mass-balance equations on the other (equation based modelling), practically no attempt has been made to amalgamate these two approaches while also incorporating inherent stochastically induced fluctuations affecting the process overall. In this article, we will implement a minimalist scheme of modelling the time evolution of a realistic three dimensional landfill through a reaction-diffusion based approach, focusing on the coupled interactions of four key variables - solid mass density, hydrolysed mass density, acetogenic mass density and methanogenic mass density, that themselves are stochastically affected by fluctuations, coupled with diffusive relaxation of the individual densities, in ambient surroundings. Our results indicate that close to the linearly stable limit, the large time steady state properties, arising out of a series of complex coupled interactions between the stochastically driven variables, are scarcely affected by the biochemical growth-decay statistics. Our results clearly show that an equilibrium landfill structure is primarily determined by the solid and hydrolysed mass densities only rendering the other variables as statistically "irrelevant" in this (large time) asymptotic limit. The other major implication of incorporation of stochasticity in the landfill evolution dynamics is in the hugely reduced production times of the plants that are now approximately 20-30 years instead of the previous deterministic model predictions of 50 years and above. The predictions from this stochastic model are in conformity with available experimental observations.

Lattice approach to the dynamics of the DPSK-encoded soliton trains

We study the dynamical properties of the RZ-DPSK encoded sequences, focusing on the instabilities in the soliton train leading to the distortions of the information transmitted. The problem is reformulated within the framework of complex Toda chain model which allows one to carry out the simplified description of the optical soliton dynamics. We elucidate how the bit composition of the pattern affects the initial (linear) stage of the train dynamics and explain the general mechanisms of the appearance of unstable collective soliton modes. Then we discuss the nonlinear regime using asymptotic properties of the pulse stream at large propagation distances and analyze the dynamical behavior of the train classifying different scenarios for the pattern instabilities. Both approaches are based on the machinery of Hermitian and non-Hermitian lattice analysis. © 2010 IEEE.