Using context and preferences to implement self-adapting pervasive computing applications

Applications that exploit contextual information in order to adapt their behaviour to dynamically changing operating environments and user requirements are increasingly being explored as part of the vision of pervasive or ubiquitous computing. Despite recent advances in infrastructure to support these applications through the acquisition, interpretation and dissemination of context data from sensors, they remain prohibitively difficult to develop and have made little penetration beyond the laboratory. This situation persists largely due to a lack of appropriately high-level abstractions for describing, reasoning about and exploiting context information as a basis for adaptation. In this paper, we present our efforts to address this challenge, focusing on our novel approach involving the use of preference information as a basis for making flexible adaptation decisions. We also discuss our experiences in applying our conceptual and software frameworks for context and preference modelling to a case study involving the development of an adaptive communication application.

Generic Technique to Generate Large Branched DNA Complexes

The inherent self-recognition properties of DNA have led to its use as a scaffold for various nanotechnology self-assembly applications, with macromolecular complexes, metallic and semiconducting nanoparticles, proteins, inter alia, being assembled onto a designed DNA scaffold. Such structures may typically comprise a number of DNA molecules organized into macromolecules. Many studies have used synthetic methods to produce the constituent DNA molecules, but this typically constrains the molecules to be no longer than around 100 base pairs (30 nm). However, applications that require larger self-assembling DNA complexes, several tens of nanometers or more, need to be generated by other techniques. Here, we present a generic technique to generate large linear, branched, and/or circular DNA macromolecular complexes. The effectiveness of this technique is demonstrated here by the use of Lambda Bacteriophage DNA as a template to generate single- and double-branched DNA structures approximately 120 nm in size.

Broadsheet - Dendritic cells and their emerging clinical applications

Dendritic cells (DC) are now recognised as a unique leukocyte type, consisting of two or more subsets. The origins and functional inter-relationships of these cells are the subject of intense basic scientific investigation. They play important roles in initiating and directing immune responses, defending the host from pathogens and maintaining self tolerance. Fundamental studies are defining new molecules and mechanisms associated with DC function. The first methods for counting these rare blood cell populations are already providing interesting new clinical data. Indeed, abnormal DC function may contribute to deficiencies in the immune response against malignancies. Phase I trial data suggests that DC-based cancer vaccination protocols may contribute an important new biological approach to cancer therapy. Manipulation of DC to facilitate allogeneic transplantation and even to manage autoimmune disease are likely developments.

Work-related self-efficacy among community residents with psychiatric disabilities

A new measure of work-related self-efficacy for people with psychiatric disabilities is reported. The 37-item scale measures self-efficacy in four relevant activity domains: 1) vocational service access and career planning, 2) job acquisition, 3) work-related social skills, and 4) general work skills. The scale was developed in a 12-month longitudinal survey of urban residents diagnosed with schizophrenia or schizoaffective disorder (n = 104). Results indicate validity of both a four-factor structure differentiating four core skill domains, and a single factor representing total work-related self-efficacy. The favorable psychometric properties support further research and trial applications in supported employment and psychiatric vocational rehabilitation.

The parameterless self-organizing map algorithm

The parameterless self-organizing map (PLSOM) is a new neural network algorithm based on the self-organizing map (SOM). It eliminates the need for a learning rate and annealing schemes for learning rate and neighborhood size. We discuss the relative performance of the PLSOM and the SOM and demonstrate some tasks in which the SOM fails but the PLSOM performs satisfactory. Finally we discuss some example applications of the PLSOM and present a proof of ordering under certain limited conditions.

Test–retest repeatability of self-reported environmental exposures in Parkinson’s disease cases and healthy controls

There is substantial disagreement among published epidemiological studies regarding environmental risk factors for Parkinson’s disease (PD). Differences in the quality of measurement of environmental exposures may contribute to this variation. The current study examined the test–retest repeatability of self-report data on risk factors for PD obtained from a series of 32 PD cases recruited from neurology clinics and 29 healthy sex-, age-and residential suburb-matched controls. Exposure data were collected in face-to-face interviews using a structured questionnaire derived from previous epidemiological studies. High repeatability was demonstrated for ‘lifestyle’ exposures, such as smoking and coffee/tea consumption (kappas 0.70–1.00). Environmental exposures that involved some action by the person, such as pesticide application and use of solvents and metals, also showed high repeatability (kappas>0.78). Lower repeatability was seen for rural residency and bore water consumption (kappa 0.39–0.74). In general, we found that case and control participants provided similar rates of incongruent and missing responses for categorical and continuous occupational, domestic, lifestyle and medical exposures.

It's all very well, in theory: Theoretical perspectives and their applications in contemporary pedagogical research

Current debates about educational theory are concerned with the relationship between knowledge and power and thereby issues such as who possesses a truth and how have they arrived at it, what questions are important to ask, and how should they best be answered. As such, these debates revolve around questions of preferred, appropriate, and useful theoretical perspectives. This paper overviews the key theoretical perspectives that are currently used in physical education pedagogy research and considers how these inform the questions we ask and shapes the conduct of research. It also addresses what is contested with respect to these perspectives. The paper concludes with some cautions about allegiances to and use of theories in line with concerns for the applicability of educational research to pressing social issues.

Quantum noise in optical fibers. I. Stochastic equations

We analyze the quantum dynamics of radiation propagating in a single-mode optical fiber with dispersion, nonlinearity, and Raman coupling to thermal phonons. We start from a fundamental Hamiltonian that includes the principal known nonlinear effects and quantum-noise sources, including linear gain and loss. Both Markovian and frequency-dependent, non-Markovian reservoirs are treated. This treatment allows quantum Langevin equations, which have a classical form except for additional quantum-noise terms, to be calculated. In practical calculations, it is more useful to transform to Wigner or 1P quasi-probability operator representations. These transformations result in stochastic equations that can be analyzed by use of perturbation theory or exact numerical techniques. The results have applications to fiber-optics communications, networking, and sensor technology.

Mesoporous dye-doped titanium dioxide for micro-optoelectronic applications

Optically transparent, mesostructured titanium dioxide thin films were fabricated using an amphiphilic poly(alkylene oxide) block copolymer template in combination with retarded hydrolysis of a titanium isopropoxide precursor. Prior to calcination, the films displayed a stable hexagonal mesophase and high refractive indices (1.5 to 1.6) relative to mesostructured silica (1.43). After calcination, the hexagonal mesophase was retained with surface areas >300 m2 g-1. The dye Rhodamine 6G (commonly used as a laser dye) was incorporated into the copolymer micelle during the templating process. In this way, novel dye-doped mesostructured titanium dioxide films were synthesised. The copolymer not only directs the film structure, but also provides a solubilizing environment suitable for sustaining a high monomer-to-aggregate ratio at elevated dye concentrations. The dye-doped films displayed optical thresholdlike behaviour characteristic of amplified spontaneous emission. Soft lithography was successfully applied to micropattern the dye-doped films. These results pave the way for the fabrication and demonstration of novel microlaser structures and other active optical structures. This new, high-refractive index, mesostructured, dye-doped material could also find applications in areas such as optical coatings, displays and integrated photonic devices.

A first-principles density-functional calculation of the electronic and vibrational structure of the key melanin monomers

We report first-principles density-functional calculations for hydroquinone (HQ), indolequinone (IQ), and semiquinone (SQ). These molecules are believed to be the basic building blocks of the eumelanins, a class of biomacromolecules with important biological functions (including photoprotection) and with the potential for certain bioengineering applications. We have used the difference of self-consistent fields method to study the energy gap between the highest occupied molecular orbital and the lowest unoccupied molecular orbital, HL. We show that HL is similar in IQ and SQ, but approximately twice as large in HQ. This may have important implications for our understanding of the observed broadband optical absorption of the eumelanins. The possibility of using this difference in HL to molecularly engineer the electronic properties of eumelanins is discussed. We calculate the infrared and Raman spectra of the three redox forms from first principles. Each of the molecules have significantly different infrared and Raman signatures, and so these spectra could be used in situ to nondestructively identify the monomeric content of macromolecules. It is hoped that this may be a helpful analytical tool in determining the structure of eumelanin macromolecules and hence in helping to determine the structure-property-function relationships that control the behavior of the eumelanins.

Effect of multiple transverse modes in self-mixing sensors based on vertical-cavity surface-emitting lasers

We investigate the effect of coexisting transverse modes on the operation of self-mixing sensors based on vertical-cavity surface-emitting lasers (VCSELs). The effect of multiple transverse modes on the measurement of displacement and distance were examined by simulation and in laboratory experiment. The simulation model shows that the periodic change in the shape and magnitude of the self-mixing signal with modulation current can be properly explained by the different frequency-modulation coefficients of the respective transverse modes in VCSELs. The simulation results are in excellent agreement with measurements performed on single-mode and multimode VCSELs and on self-mixing sensors based on these VCSELs.

Emotional Intelligence, emotional Self-Awareness, and Team Effectiveness

An issue at the forefront of recent emotional intelligence debates revolves around whether emotional intelligence can be linked to work performance. Although many authors continue to develop new and improved measures of emotional intelligence (e.g. Mayer, Caruso, & Salovey, 2001) to give us a better understanding of emotional intelligence, the links to performance in work settings, especially in the context of group effectiveness, have received much less attention. In this chapter, we present the results of a study in which we examined the role of emotional self-awareness and emotional intelligence as a predictor of group effectiveness. The study also addresses the utility of self- and peer assessment in measureing emotional self-awareness and emotional intelligence.

Algebraic Bethe ansatz method for the exact calculation of energy spectra and form factors: applications to models of Bose-Einstein condensates and metallic nanograins

In this review we demonstrate how the algebraic Bethe ansatz is used for the calculation of the-energy spectra and form factors (operator matrix elements in the basis of Hamiltonian eigenstates) in exactly solvable quantum systems. As examples we apply the theory to several models of current interest in the study of Bose-Einstein condensates, which have been successfully created using ultracold dilute atomic gases. The first model we introduce describes Josephson tunnelling between two coupled Bose-Einstein condensates. It can be used not only for the study of tunnelling between condensates of atomic gases, but for solid state Josephson junctions and coupled Cooper pair boxes. The theory is also applicable to models of atomic-molecular Bose-Einstein condensates, with two examples given and analysed. Additionally, these same two models are relevant to studies in quantum optics; Finally, we discuss the model of Bardeen, Cooper and Schrieffer in this framework, which is appropriate for systems of ultracold fermionic atomic gases, as well as being applicable for the description of superconducting correlations in metallic grains with nanoscale dimensions.; In applying all the above models to. physical situations, the need for an exact analysis of small-scale systems is established due to large quantum fluctuations which render mean-field approaches inaccurate.