Excitation of higher spatial harmonics by a moving light pattern in sillenites

We investigate numerically the dependence of higher harmonics of the space-charge field on the detuning frequency between the pump waves, which form a running interference pattern. Bistability and hysteresis of harmonics are predicted for a contrast of the interference pattern m =(0.25-0.3). For contrasts m˜1 and small detuning frequencies we show the existence of a narrow resonance, connected with the nonlinear excitation of a slowly decreasing sequence of spatial harmonics. For experiments we use a BSO crystal in the optical configuration which avoids nonlinear optical distortions. The experimental data show good qualitative agreement with theory.

Excitation of higher harmonic gratings in AC-field biased photorefractive crystals

We analyze the nonlinear excitation of holographic gratings in a photorefractive crystal being subject to an alternating electric field and a stationary light interference pattern. The influence of the higher harmonics on the fundamental grating is illustrated for the case where a crystal of Bi12SiO20 is the recording medium. We analyze both the steady state and the transient consequences of the higher harmonic excitation.

The effects of birth order on personality traits and feelings of academic sibling rivalry

The influence of birth order on personality and sibling rivalry is controversial; little research has been conducted into academic sibling rivalry, and none into the connection with personality traits. This study considers the interaction of all three factors. Firstborns (N=22) and lastborns (N=24) completed online personality tests and an Academic Sibling Rivalry Questionnaire. Lastborns were found to experience more academic sibling rivalry: t=2.33, DF=44; p less than 0.05, whereas firstborns are more likely to be conscientious: F(1,44)=3.58; p less than 0.05, and dutiful: F(1,44)=5.39; p less than 0.05. This raises possible implications in domains including education, health and psychotherapy. Further research could be conducted to expand these findings in terms of variables and geographical location. (Contains 2 figures.)

Impact of the order of cavity elements in all-normal dispersion ring fiber lasers

Nonlinearity plays a critical role in the intra-cavity dynamics of high-pulse energy fiber lasers. Management of the intra-cavity nonlinear dynamics is the key to increase the output pulse energy in such laser systems. Here, we examine the impact of the order of the intra-cavity elements on the energy of generated pulses in the all-normal dispersion mode-locked ring fiber laser cavity. In mathematical terms, the nonlinear light dynamics in resonator makes operators corresponding to the action of laser elements (active and passive fiber, out-coupler, saturable absorber) non-commuting and the order of their appearance in a cavity important. For the simple design of all-normal dispersion ring fiber laser with varying cavity length, we found the order of the cavity elements, leading to maximum output pulse energy.

Impact of third-order dispersion on the evolution of parabolic pulses

We present a perturbation analysis that describes the effect of third-order dispersion on the similariton pulse solution of the nonlinear Schrödinger equation in a fibre gain medium. The theoretical model predicts with sufficient accuracy the pulse structural changes induced, which are observed through direct numerical simulations.

Enhancing the performance of intelligent control systems in the face of higher levels of complexity and uncertainty

Modern advances in technology have led to more complex manufacturing processes whose success centres on the ability to control these processes with a very high level of accuracy. Plant complexity inevitably leads to poor models that exhibit a high degree of parametric or functional uncertainty. The situation becomes even more complex if the plant to be controlled is characterised by a multivalued function or even if it exhibits a number of modes of behaviour during its operation. Since an intelligent controller is expected to operate and guarantee the best performance where complexity and uncertainty coexist and interact, control engineers and theorists have recently developed new control techniques under the framework of intelligent control to enhance the performance of the controller for more complex and uncertain plants. These techniques are based on incorporating model uncertainty. The newly developed control algorithms for incorporating model uncertainty are proven to give more accurate control results under uncertain conditions. In this paper, we survey some approaches that appear to be promising for enhancing the performance of intelligent control systems in the face of higher levels of complexity and uncertainty.

Effect of second order signal-noise interactions in nonlinearity compensated optical transmission systems

In this Letter, we theoretically and numerically analyze the performance of coherent optical transmission systems that deploy inline or transceiver based nonlinearity compensation techniques. For systems where signal-signal nonlinear interactions are fully compensated, we find that beyond the performance peak the signal-to-noise ratio degradation has a slope of 3 dBSNR/dBPower suggesting a quartic rather than quadratic dependence on signal power. This is directly related to the fact that signals in a given span will interact not only with linear amplified spontaneous emission noise, but also with the nonlinear four-wave mixing products generated from signal-noise interaction in previous (hitherto) uncompensated spans. The performance of optical systems employing different nonlinearity compensation schemes were numerically simulated and compared against analytical predictions, showing a good agreement within a 0.4 dB margin of error.

Neuroimaging in human amblyopia

Functional magnetic resonance imaging (fMRI), positron emission tomography (PET) and magnetoencephalography (MEG) have been the principal neuroimaging tools used to assess the site and nature of cortical deficits in human amblyopia. A review of this growing body of work is presented here with particular reference to various controversial issues, including whether or not the primary visual cortex is dysfunctional, the involvement of higher-order visual areas, neural differences between strabismic and anisometropic amblyopes, and the effects of modern-day drug treatments. We also present our own recent MEG work in which we used the analysis technique of synthetic aperture magnetometry (SAM) to examine the effects of strabismic amblyopia on cortical function. Our results provide evidence that the neuronal assembly associated with form perception in the extrastriate cortex may be dysfunctional in amblyopia, and that the nature of this dysfunction may relate to a change in the normal temporal pattern of neuronal discharges. Based on these results and existing literature, we conclude that a number of cortical areas show reduced levels of activation in amblyopia, including primary and secondary visual areas and regions within the parieto-occipital cortex and ventral temporal cortex. Copyright © 2006 Taylor & Francis Group, LLC.

An advanced real-time predictive maintenance framework for large scale machine systems

This thesis introduces and develops a novel real-time predictive maintenance system to estimate the machine system parameters using the motion current signature. Recently, motion current signature analysis has been addressed as an alternative to the use of sensors for monitoring internal faults of a motor. A maintenance system based upon the analysis of motion current signature avoids the need for the implementation and maintenance of expensive motion sensing technology. By developing nonlinear dynamical analysis for motion current signature, the research described in this thesis implements a novel real-time predictive maintenance system for current and future manufacturing machine systems. A crucial concept underpinning this project is that the motion current signature contains infor­mation relating to the machine system parameters and that this information can be extracted using nonlinear mapping techniques, such as neural networks. Towards this end, a proof of con­cept procedure is performed, which substantiates this concept. A simulation model, TuneLearn, is developed to simulate the large amount of training data required by the neural network ap­proach. Statistical validation and verification of the model is performed to ascertain confidence in the simulated motion current signature. Validation experiment concludes that, although, the simulation model generates a good macro-dynamical mapping of the motion current signature, it fails to accurately map the micro-dynamical structure due to the lack of knowledge regarding performance of higher order and nonlinear factors, such as backlash and compliance. Failure of the simulation model to determine the micro-dynamical structure suggests the pres­ence of nonlinearity in the motion current signature. This motivated us to perform surrogate data testing for nonlinearity in the motion current signature. Results confirm the presence of nonlinearity in the motion current signature, thereby, motivating the use of nonlinear tech­niques for further analysis. Outcomes of the experiment show that nonlinear noise reduction combined with the linear reverse algorithm offers precise machine system parameter estimation using the motion current signature for the implementation of the real-time predictive maintenance system. Finally, a linear reverse algorithm, BJEST, is developed and applied to the motion current signature to estimate the machine system parameters.

Effective electromagnetic noise cancellation with beamformers and synthetic gradiometry in shielded and partly shielded environments

The major challenge of MEG, the inverse problem, is to estimate the very weak primary neuronal currents from the measurements of extracranial magnetic fields. The non-uniqueness of this inverse solution is compounded by the fact that MEG signals contain large environmental and physiological noise that further complicates the problem. In this paper, we evaluate the effectiveness of magnetic noise cancellation by synthetic gradiometers and the beamformer analysis method of synthetic aperture magnetometry (SAM) for source localisation in the presence of large stimulus-generated noise. We demonstrate that activation of primary somatosensory cortex can be accurately identified using SAM despite the presence of significant stimulus-related magnetic interference. This interference was generated by a contact heat evoked potential stimulator (CHEPS), recently developed for thermal pain research, but which to date has not been used in a MEG environment. We also show that in a reduced shielding environment the use of higher order synthetic gradiometry is sufficient to obtain signal-to-noise ratios (SNRs) that allow for accurate localisation of cortical sensory function.

Joining the dots:using structured e-portfolio assignments to enhance reflection

Although there has been an increased interest in the use of electronic portfolios in higher education over the last five years, relatively little is known about the potential of such tools to support the development of higher order abilities for students, such as reflection, in a structured way that is suitable for assessment. This paper reports the findings from a small-scale research which sets out to compare the outcomes of reflective assignments in two cohorts of participants in a Postgraduate Certificate in Professional Practice in Higher Education in the UK. Participants in the programme were asked to submit reflective accounts using an e-portfolio system as part of their formal assessment. One cohort completed the assessment using some generic guidelines of how to reflect and construct an e-portfolio page without a given template or structure, whereas another cohort was given a specific template with clear assessment criteria to gauge the assembly of their reflections. The authors, who are also tutors in the programme, analysed the submitted reflections following open coding procedures. The analysis found a tendency for the reflection in the first cohort to be merely descriptive without progressing to speculating objectively about answers to relevant analytical questions about the process involved in the ability under scrutiny. In contrast the assignments of cohort two were found to be more insightful in terms of assimilating random bits of materials, thoughts and self-questions into complete reflective accounts. These findings bring some evidence to support and indeed promote a more structured approach to reflective practice, which can be further enhanced through a carefully created e-portfolio template and associated assessment criteria.

Hierarchy of governance institutions and the pecking order of privatisation

This article discusses property rights, corporate governance frameworks and privatisation outcomes in the Central–Eastern Europe and Central Asia (CEECA) region. We argue that while CEECA still suffers from deficient ‘higher order’ institutions, this is not attracting sufficient attention from international institutions like EBRD and the World Bank, which focus on ‘lower order’ indicators. We discuss factors that may alleviate the negative impact of the weakness in institutional environment and argue for the pecking order of privatisation, where equivalent privatisation is given a priority but speed is not compromised.