Granular superconductors:from the nonlinear σ model to the Bose-Hubbard description

We modify a nonlinear σ model (NLσM) for the description of a granular disordered system in the presence of both the Coulomb repulsion and the Cooper pairing. We show that under certain controlled approximations the action of this model is reduced to the Ambegaokar-Eckern-Schön (AES) action, which is further reduced to the Bose-Hubbard (or “dirty-boson”) model with renormalized coupling constants. We obtain an effective action which is more general than the AES one but still simpler than the full NLσM action. This action can be applied in the region of parameters where the reduction to the AES or the Bose-Hubbard model is not justified. This action may lead to a different picture of the superconductor-insulator transition in two-dimensional systems.

Web based expert elicitation of uncertainties in environmental model inputs

When constructing and using environmental models, it is typical that many of the inputs to the models will not be known perfectly. In some cases, it will be possible to make observations, or occasionally physics-based uncertainty propagation, to ascertain the uncertainty on these inputs. However, such observations are often either not available or even possible, and another approach to characterising the uncertainty on the inputs must be sought. Even when observations are available, if the analysis is being carried out within a Bayesian framework then prior distributions will have to be specified. One option for gathering or at least estimating this information is to employ expert elicitation. Expert elicitation is well studied within statistics and psychology and involves the assessment of the beliefs of a group of experts about an uncertain quantity, (for example an input / parameter within a model), typically in terms of obtaining a probability distribution. One of the challenges in expert elicitation is to minimise the biases that might enter into the judgements made by the individual experts, and then to come to a consensus decision within the group of experts. Effort is made in the elicitation exercise to prevent biases clouding the judgements through well-devised questioning schemes. It is also important that, when reaching a consensus, the experts are exposed to the knowledge of the others in the group. Within the FP7 UncertWeb project (http://www.uncertweb.org/), there is a requirement to build a Webbased tool for expert elicitation. In this paper, we discuss some of the issues of building a Web-based elicitation system - both the technological aspects and the statistical and scientific issues. In particular, we demonstrate two tools: a Web-based system for the elicitation of continuous random variables and a system designed to elicit uncertainty about categorical random variables in the setting of landcover classification uncertainty. The first of these examples is a generic tool developed to elicit uncertainty about univariate continuous random variables. It is designed to be used within an application context and extends the existing SHELF method, adding a web interface and access to metadata. The tool is developed so that it can be readily integrated with environmental models exposed as web services. The second example was developed for the TREES-3 initiative which monitors tropical landcover change through ground-truthing at confluence points. It allows experts to validate the accuracy of automated landcover classifications using site-specific imagery and local knowledge. Experts may provide uncertainty information at various levels: from a general rating of their confidence in a site validation to a numerical ranking of the possible landcover types within a segment. A key challenge in the web based setting is the design of the user interface and the method of interacting between the problem owner and the problem experts. We show the workflow of the elicitation tool, and show how we can represent the final elicited distributions and confusion matrices using UncertML, ready for integration into uncertainty enabled workflows.We also show how the metadata associated with the elicitation exercise is captured and can be referenced from the elicited result, providing crucial lineage information and thus traceability in the decision making process.

An aspect-oriented and model-driven approach for managing dynamic variability

Constructing and executing distributed systems that can adapt to their operating context in order to sustain provided services and the service qualities are complex tasks. Managing adaptation of multiple, interacting services is particularly difficult since these services tend to be distributed across the system, interdependent and sometimes tangled with other services. Furthermore, the exponential growth of the number of potential system configurations derived from the variabilities of each service need to be handled. Current practices of writing low-level reconfiguration scripts as part of the system code to handle run time adaptation are both error prone and time consuming and make adaptive systems difficult to validate and evolve. In this paper, we propose to combine model driven and aspect oriented techniques to better cope with the complexities of adaptive systems construction and execution, and to handle the problem of exponential growth of the number of possible configurations. Combining these techniques allows us to use high level domain abstractions, simplify the representation of variants and limit the problem pertaining to the combinatorial explosion of possible configurations. In our approach we also use models at runtime to generate the adaptation logic by comparing the current configuration of the system to a composed model representing the configuration we want to reach. © 2008 Springer-Verlag Berlin Heidelberg.

Interacting nonequilibrium systems with two temperatures

We investigate a simplified model of two fully connected magnetic systems maintained at different temperatures by virtue of being connected to two independent thermal baths while simultaneously being interconnected with each other. Using generating functional analysis, commonly used in statistical mechanics, we find exactly soluble expressions for their individual magnetization that define a two-dimensional nonlinear map, the equations of which have the same form as those obtained for densely connected equilibrium systems. Steady states correspond to the fixed points of this map, separating the parameter space into a rich set of nonequilibrium phases that we analyze in asymptotically high and low (nonequilibrium) temperature limits. The theoretical formalism is shown to revert to the classical nonequilibrium steady state problem for two interacting systems with a nonzero heat transfer between them that catalyzes a phase transition between ambient nonequilibrium states. © 2013 American Physical Society.

A proteo-liposome system for the analysis of the intracellular interactome of membrane proteins using amyloid precursor protein as a model

Transmembrane proteins play crucial roles in many important physiological processes. The intracellular domain of membrane proteins is key for their function by interacting with a wide variety of cytosolic proteins. It is therefore important to examine this interaction. A recently developed method to study these interactions, based on the use of liposomes as a model membrane, involves the covalent coupling of the cytoplasmic domains of membrane proteins to the liposome membrane. This allows for the analysis of interaction partners requiring both protein and membrane lipid binding. This thesis further establishes the liposome recruitment system and utilises it to examine the intracellular interactome of the amyloid precursor protein (APP), most well-known for its proteolytic cleavage that results in the production and accumulation of amyloid beta fragments, the main constituent of amyloid plaques in Alzheimer’s disease pathology. Despite this, the physiological function of APP remains largely unclear. Through the use of the proteo-liposome recruitment system two novel interactions of APP’s intracellular domain (AICD) are examined with a view to gaining a greater insight into APP’s physiological function. One of these novel interactions is between AICD and the mTOR complex, a serine/threonine protein kinase that integrates signals from nutrients and growth factors. The kinase domain of mTOR directly binds to AICD and the N-terminal amino acids of AICD are crucial for this interaction. The second novel interaction is between AICD and the endosomal PIKfyve complex, a lipid kinase involved in the production of phosphatidylinositol-3,5-bisphosphate (PI(3,5)P2) from phosphatidylinositol-3-phosphate, which has a role in controlling ensdosome dynamics. The scaffold protein Vac14 of the PIKfyve complex binds directly to AICD and the C-terminus of AICD is important for its interaction with the PIKfyve complex. Using a recently developed intracellular PI(3,5)P2 probe it is shown that APP controls the formation of PI(3,5)P2 positive vesicular structures and that the PIKfyve complex is involved in the trafficking and degradation of APP. Both of these novel APP interactors have important implications of both APP function and Alzheimer’s disease. The proteo-liposome recruitment method is further validated through its use to examine the recruitment and assembly of the AP-2/clathrin coat from purified components to two membrane proteins containing different sorting motifs. Taken together this thesis highlights the proteo-liposome recruitment system as a valuable tool for the study of membrane proteins intracellular interactome. It allows for the mimicking of the protein in its native configuration therefore identifying weaker interactions that are not detected by more conventional methods and also detecting interactions that are mediated by membrane phospholipids.

Development of a technological innovation capability assessment model:a case study of manufacturing SMEs in Sialkot, Pakistan

Small and Medium Enterprises (SMEs) play an important part in the economy of any country. Initially, a flat management hierarchy, quick response to market changes and cost competitiveness were seen as the competitive characteristics of an SME. Recently, in developed economies, technological capabilities (TCs) management- managing existing and developing or assimilating new technological capabilities for continuous process and product innovations, has become important for both large organisations and SMEs to achieve sustained competitiveness. Therefore, various technological innovation capability (TIC) models have been developed at firm level to assess firms‘ innovation capability level. These models output help policy makers and firm managers to devise policies for deepening a firm‘s technical knowledge generation, acquisition and exploitation capabilities for sustained technological competitive edge. However, in developing countries TCs management is more of TCs upgrading: acquisitions of TCs from abroad, and then assimilating, innovating and exploiting them. Most of the TIC models for developing countries delineate the level of TIC required as firms move from the acquisition to innovative level. However, these models do not provide tools for assessing the existing level of TIC of a firm and various factors affecting TIC, to help practical interventions for TCs upgrading of firms for improved or new processes and products. Recently, the Government of Pakistan (GOP) has realised the importance of TCs upgrading in SMEs-especially export-oriented, for their sustained competitiveness. The GOP has launched various initiatives with local and foreign assistance to identify ways and means of upgrading local SMEs capabilities. This research targets this gap and developed a TICs assessment model for identifying the existing level of TIC of manufacturing SMEs existing in clusters in Sialkot, Pakistan. SME executives in three different export-oriented clusters at Sialkot were interviewed to analyse technological capabilities development initiatives (CDIs) taken by them to develop and upgrade their firms‘ TCs. Data analysed at CDI, firm, cluster and cross-cluster level first helped classify interviewed firms as leader, follower and reactor, with leader firms claiming to introduce mostly new CDIs to their cluster. Second, the data analysis displayed that mostly interviewed leader firms exhibited ‗learning by interacting‘ and ‗learning by training‘ capabilities for expertise acquisition from customers and international consultants. However, these leader firms did not show much evidence of learning by using, reverse engineering and R&D capabilities, which according to the extant literature are necessary for upgrading existing TIC level and thus TCs of firm for better value-added processes and products. The research results are supported by extant literature on Sialkot clusters. Thus, in sum, a TIC assessment model was developed in this research which qualitatively identified interviewed firms‘ TIC levels, the factors affecting them, and is validated by existing literature on interviewed Sialkot clusters. Further, the research gives policy level recommendations for TIC and thus TCs upgrading at firm and cluster level for targeting better value-added markets.

Kelvin-wave cascade in the vortex filament model

The small-scale energy-transfer mechanism in zero-temperature superfluid turbulence of helium-4 is still a widely debated topic. Currently, the main hypothesis is that weakly nonlinear interacting Kelvin waves (KWs) transfer energy to sufficiently small scales such that energy is dissipated as heat via phonon excitations. Theoretically, there are at least two proposed theories for Kelvin-wave interactions. We perform the most comprehensive numerical simulation of weakly nonlinear interacting KWs to date and show, using a specially designed numerical algorithm incorporating the full Biot-Savart equation, that our results are consistent with the nonlocal six-wave KW interactions as proposed by L'vov and Nazarenko.

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.