Modulational instability in asymmetric coupled wave functions

The evolution of the amplitude of two nonlinearly interacting waves is considered, via a set of coupled nonlinear Schrödinger-type equations. The dynamical profile is determined by the wave dispersion laws (i.e. the group velocities and the group velocity dispersion terms) and the nonlinearity and coupling coefficients, on which no assumption is made. A generalized dispersion relation is obtained, relating the frequency and wave-number of a small perturbation around a coupled monochromatic (Stokes') wave solution. Explicitly stability criteria are obtained. The analysis reveals a number of possibilities. Two (individually) stable systems may be destabilized due to coupling. Unstable systems may, when coupled, present an enhanced instability growth rate, for an extended wave number range of values. Distinct unstable wavenumber windows may arise simultaneously.

Statistical-mechanical description of classical test-particle dynamics in the presence of an external force field: modelling noise and damping from first principles

Aiming to establish a rigorous link between macroscopic random motion (described e.g. by Langevin-type theories) and microscopic dynamics, we have undertaken a kinetic-theoretical study of the dynamics of a classical test-particle weakly coupled to a large heat-bath in thermal equilibrium. Both subsystems are subject to an external force field. From the (time-non-local) generalized master equation a Fokker-Planck-type equation follows as a "quasi-Markovian" approximation. The kinetic operator thus defined is shown to be ill-defined; in specific, it does not preserve the positivity of the test-particle distribution function f(x, v; t). Adopting an alternative approach, previously introduced for quantum open systems, is proposed to lead to a correct kinetic operator, which yields all the expected properties. A set of explicit expressions for the diffusion and drift coefficients are obtained, allowing for modelling macroscopic diffusion and dynamical friction phenomena, in terms of an external field and intrinsic physical parameters.

Development and Validation of a Compact Thermal Model for an Aircraft Compartment

The development of accurate structural/thermal numerical models of complex systems, such as aircraft fuselage barrels, is often limited and determined by the smallest scales that need to be modelled. The development of reduced order models of the smallest scales and consequently their integration with higher level models can be a way to minimise the bottle neck present, while still having efficient, robust and accurate numerical models. In this paper a methodology on how to develop compact thermal fluid models (CTFMs) for compartments where mixed convection regimes are present is demonstrated. Detailed numerical simulations (CFD) have been developed for an aircraft crown compartment and validated against experimental data obtained from a 1:1 scale compartment rig. The crown compartment is defined as the confined area between the upper fuselage and the passenger cabin in a single aisle commercial aircraft. CFD results were utilised to extract average quantities (temperature and heat fluxes) and characteristic parameters (heat transfer coefficients) to generate CTFMs. The CTFMs have then been compared with the results obtained from the detailed models showing average errors for temperature predictions lower than 5%. This error can be deemed acceptable when compared to the nominal experimental error associated with the thermocouple measurements.

The CTFMs methodology developed allows to generate accurate reduced order models where accuracy is restricted to the region of Boundary Conditions applied. This limitation arises from the sensitivity of the internal flow structures to the applied boundary condition set. CTFMs thus generated can be then integrated in complex numerical modelling of whole fuselage sections.

Further steps in the development of an exhaustive methodology would be the implementation of a logic ruled based approach to extract directly from the CFD simulations numbers and positions of the nodes for the CTFM.

Ultrafast Electron Dynamics in Phenylalanine Initiated by Attosecond Pulses

In the last decade attosecond technology has opened up the investigation of ultrafast electronic processes in atoms, simple molecules and solids. Here we report the application of isolated attosecond pulses to prompt ionization of the amino acid phenylalanine, and the subsequent detection of ultrafast dynamics on a sub-4.5-fs temporal scale, which is shorter than the vibrational response of the molecule. The ability to initiate and observe such electronic dynamics in polyatomic molecules represents a crucial step forward in attosecond science, which is progressively moving towards the investigation of more and more complex systems.

A new self-learning TLBO algorithm for RBF neural modelling of batteries in electric vehicles

One of the main purposes of building a battery model is for monitoring and control during battery charging/discharging as well as for estimating key factors of batteries such as the state of charge for electric vehicles. However, the model based on the electrochemical reactions within the batteries is highly complex and difficult to compute using conventional approaches. Radial basis function (RBF) neural networks have been widely used to model complex systems for estimation and control purpose, while the optimization of both the linear and non-linear parameters in the RBF model remains a key issue. A recently proposed meta-heuristic algorithm named Teaching-Learning-Based Optimization (TLBO) is free of presetting algorithm parameters and performs well in non-linear optimization. In this paper, a novel self-learning TLBO based RBF model is proposed for modelling electric vehicle batteries using RBF neural networks. The modelling approach has been applied to two battery testing data sets and compared with some other RBF based battery models, the training and validation results confirm the efficacy of the proposed method.

CLUSTER LEED - A VERY FAST METHOD FOR SURFACE-STRUCTURE DETERMINATION

A very fast method, cluster low-energy electron diffraction (LEED) is proposed for LEED I-V spectral analysis, in which three appproximations are introduced: the small-atom approximation, omission of the structure factors, and truncation of higher order ( > 2) scattering events. The method has been tested using a total of four sets of I-V spectra calculated by fully dynamic LEED for (i) the simple overlayer system, O on Ni{100}, and (ii) the reconstructed system, Cu on W{100}, and also one set of experimental data from W{100}-c(2 X 2)-Cu. In each case the correct structural parameters are recovered. It is suggested that for complex systems cluster LEED provides an efficient fast route to trial structures, which could be refined by automated tenser LEED.

Constructing random matrices to represent real ecosystems

Models of complex systems with n components typically have order n² parameters because each component can potentially interact with every other. When it is impractical to measure these parameters, one may choose random parameter values and study the emergent statistical properties at the system level. Many influential results in theoretical ecology have been derived from two key assumptions: that species interact with random partners at random intensities and that intraspecific competition is comparable between species. Under these assumptions, community dynamics can be described by a community matrix that is often amenable to mathematical analysis. We combine empirical data with mathematical theory to show that both of these assumptions lead to results that must be interpreted with caution. We examine 21 empirically derived community matrices constructed using three established, independent methods. The empirically derived systems are more stable by orders of magnitude than results from random matrices. This consistent disparity is not explained by existing results on predator-prey interactions. We investigate the key properties of empirical community matrices that distinguish them from random matrices. We show that network topology is less important than the relationship between a species’ trophic position within the food web and its interaction strengths. We identify key features of empirical networks that must be preserved if random matrix models are to capture the features of real ecosystems.

Preparing to prescribe: How do clerkship students learn in the midst of complexity?

Prescribing tasks, which involve pharmacological knowledge, clinical decision-making and practical skill, take place within unpredictable social environments and involve interactions within and between endlessly changing health care teams. Despite this, curriculum designers commonly assume them to be simple to learn and perform. This research used mixed methods to explore how undergraduate medical students learn to prescribe in the 'real world'. It was informed by cognitive psychology, sociocultural theory, and systems thinking. We found that learning to prescribe occurs as a dynamic series of socially negotiated interactions within and between individuals, communities and environments. As well as a thematic analysis, we developed a framework of three conceptual spaces in which learning opportunities for prescribing occur. This illustrates a complex systems view of prescribing education and defines three major system components: the "social space", where the environmental conditions influence or bring about a learning experience; the "process space", describing what happens during the learning experience; and the intra-personal "cognitive space", where the learner may develop aspects of prescribing expertise. This conceptualisation broadens the scope of inquiry of prescribing education research by highlighting the complex interplay between individual and social dimensions of learning. This perspective is also likely to be relevant to students' learning of other clinical competencies.

Possibility of designing catalysts beyond the traditional volcano curve: A theoretical framework for multi-phase surfaces

The current theory of catalyst activity in heterogeneous catalysis is mainly obtained from the study of catalysts with mono-phases, while most catalysts in real systems consist of multi-phases, the understanding of which is far short of chemists' expectation. Density functional theory (DFT) and micro-kinetics simulations are used to investigate the activities of six mono-phase and nine bi-phase catalysts, using CO hydrogenation that is arguably the most typical reaction in heterogeneous catalysis. Excellent activities that are beyond the activity peak of traditional mono-phase volcano curves are found on some bi-phase surfaces. By analyzing these results, a new framework to understand the unexpected activities of bi-phase surfaces is proposed. Based on the framework, several principles for the design of multi-phase catalysts are suggested. The theoretical framework extends the traditional catalysis theory to understand more complex systems.

Rocking behaviour of multi-block columns subjected to pulse-type ground motion accelerations

Ancient columns, made with a variety of materials such as marble, granite, stone or masonry are an important part of the
European cultural heritage. In particular columns of ancient temples in Greece and Sicily which support only the architrave are
characterized by small axial load values. This feature together with the slenderness typical of these structural members clearly
highlights as the evaluation of the rocking behaviour is a key aspect of their safety assessment and maintenance. It has to be noted
that the rocking response of rectangular cross-sectional columns modelled as monolithic rigid elements, has been widely investigated
since the first theoretical study carried out by Housner (1963). However, the assumption of monolithic member, although being
widely used and accepted for practical engineering applications, is not valid for more complex systems such as multi-block columns
made of stacked stone blocks, with or without mortar beds. In these cases, in fact, a correct analysis of the system should consider
rocking and sliding phenomena between the individual blocks of the structure. Due to the high non-linearity of the problem, the
evaluation of the dynamic behaviour of multi-block columns has been mostly studied in the literature using a numerical approach
such as the Discrete Element Method (DEM). This paper presents an introductory study about a proposed analytical-numerical
approach for analysing the rocking behaviour of multi-block columns subjected to a sine-pulse type ground motion. Based on the
approach proposed by Spanos (2001) for a system made of two rigid blocks, the Eulero-Lagrange method to obtain the motion
equations of the system is discussed and numerical applications are performed with case studies reported in the literature and with a
real acceleration record. The rocking response of single block and multi-block columns is compared and considerations are made
about the overturning conditions and on the effect of forcing function’s frequency.
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Functionality, Accuracy, and Feasibility: Talking with Modelers

Models are an important part of many policy development processes, but meeting policy objectives relies on policy analysts engaging effectively with the modeling process and modelers understanding the policy issues. Furthermore, there are many different modeling methods, each with characteristics that potentially make it more or less suitable for analyzing a particular policy issue.
This paper presents a novel framework to assist policy analysts to engage with modelers so as to make the best use of models. The framework has three dimensions: Functionality, Accuracy and Feasibility. Functionality concerns ways in which modeling can be used to support broader policy objectives, such as promoting negotiation or comparing options. Accuracy concerns how to best represent the fundamental features of the system being modeled, and relies on selecting an appropriate technique. Feasibility concerns practical issues such as access to data and modeling skills.

Catalytic enantioselective electrocyclic cascades

A catalytic enantioselective electrocyclic cascade leads to the construction of topologically complex systems comprising multiple rings with up to three stereocentres. This phase-transfer catalysed process offers a new strategy for the rapid and enantioselective generation of complex products bearing all-carbon quaternary stereogenic centres. © 2012 The Royal Society of Chemistry.

The contribution of qualitative research in designing a complex intervention for secondary prevention of coronary heart disease in two different healthcare systems

Background: Developing complex interventions for testing in randomised controlled trials is of increasing importance in healthcare planning. There is a need for careful design of interventions for secondary prevention of coronary heart disease (CHD). It has been suggested that integrating qualitative research in the development of a complex intervention may contribute to optimising its design but there is limited evidence of this in practice. This study aims to examine the contribution of qualitative research in developing a complex intervention to improve the provision and uptake of secondary prevention of CHD within primary care in two different healthcare systems.

Methods: In four general practices, one rural and one urban, in Northern Ireland and the Republic of Ireland, patients with CHD were purposively selected. Four focus groups with patients (N = 23) and four with staff (N = 29) informed the development of the intervention by exploring how it could be tailored and integrated with current secondary prevention activities for CHD in the two healthcare settings. Following an exploratory trial the acceptability and feasibility of the intervention were discussed in four focus groups (17 patients) and 10 interviews (staff). The data were analysed using thematic analysis.

Results: Integrating qualitative research into the development of the intervention provided depth of information about the varying impact, between the two healthcare systems, of different funding and administrative arrangements, on their provision of secondary prevention and identified similar barriers of time constraints, training needs and poor patient motivation. The findings also highlighted the importance to patients of stress management, the need for which had been underestimated by the researchers. The qualitative evaluation provided depth of detail not found in evaluation questionnaires. It highlighted how the intervention needed to be more practical by minimising administration, integrating role plays into behaviour change training, providing more practical information about stress management and removing self-monitoring of lifestyle change.

Conclusion: Qualitative research is integral to developing the design detail of a complex intervention and tailoring its components to address individuals' needs in different healthcare systems. The findings highlight how qualitative research may be a valuable component of the preparation for complex interventions and their evaluation.

Quadratic Forms on Complex Random Matrices and Multiple-Antenna Systems

This research published in the foremost international journal in information theory and shows interplay between complex random matrix and multiantenna information theory. Dr T. Ratnarajah is leader in this area of research and his work has been contributed in the development of graduate curricula (course reader) in Massachusetts Institute of Technology (MIT), USA, By Professor Alan Edelman. The course name is "The Mathematics and Applications of Random Matrices", see http://web.mit.edu/18.338/www/projects.html