Spectroscopy of neutron-rich Dy168,170: Yrast band evolution close to the NpNn valence maximum

The yrast sequence of the neutron-rich dysprosium isotope Dy168 has been studied using multinucleon transfer reactions following collisions between a 460-MeV Se82 beam and an Er170 target. The reaction products were identified using the PRISMA magnetic spectrometer and the γ rays detected using the CLARA HPGe-detector array. The 2+ and 4+ members of the previously measured ground-state rotational band of Dy168 have been confirmed and the yrast band extended up to 10+. A tentative candidate for the 4+→2+ transition in Dy170 was also identified. The data on these nuclei and on the lighter even-even dysprosium isotopes are interpreted in terms of total Routhian surface calculations and the evolution of collectivity in the vicinity of the proton-neutron valence product maximum is discussed. © 2010 The American Physical Society.

A Maximum-Likelihood Interpretation for Slow Feature Analysis

The brain extracts useful features from a maelstrom of sensory information, and a fundamental goal of theoretical neuroscience is to work out how it does so. One proposed feature extraction strategy is motivated by the observation that the meaning of sensory data, such as the identity of a moving visual object, is often more persistent than the activation of any single sensory receptor. This notion is embodied in the slow feature analysis (SFA) algorithm, which uses “slowness” as an heuristic by which to extract semantic information from multi-dimensional time-series. Here, we develop a probabilistic interpretation of this algorithm showing that inference and learning in the limiting case of a suitable probabilistic model yield exactly the results of SFA. Similar equivalences have proved useful in interpreting and extending comparable algorithms such as independent component analysis. For SFA, we use the equivalent probabilistic model as a conceptual spring-board, with which to motivate several novel extensions to the algorithm.

Single-sensor maximum power point tracking algorithms

Single-sensor maximum power point tracking algorithms for photovoltaic systems are presented. The algorithms have the features, characteristics and advantages of the widely used incremental conductance (INC) algorithm. However; unlike the INC algorithm which requires two sensors (the voltage sensor and the current sensor), the single-sensor algorithms are more desirable because they require only one sensor: the voltage sensor. The algorithms operate by maximising power at the DC-DC converter output, instead of the input. © 2013 The Institution of Engineering and Technology.

Gate commutated thyristor with voltage independent maximum controllable current

In this letter, we use a novel 3-D model, earlier calibrated with experimental results on standard gate commutated thyristors (GCTs), with the aim to explain the physics behind the high-power technology (HPT) GCT, to investigate what impact this design would have on 24 mm diameter GCTs, and to clarify the mechanisms that limit safe switching at different dc-link voltages. The 3-D simulation results show that the HPT design can increase the maximum controllable current in 24 mm diameter devices beyond the realm of GCT switching, known as the hard-drive limit. It is proposed that the maximum controllable current becomes independent of the dc-link voltage for the complete range of operating voltage. © 1980-2012 IEEE.

Parameters influencing the maximum controllable current in gate commutated thyristors

The model of interconnected numerical device segments can give a prediction on the dynamic performance of large area full wafer devices such as the Gate Commutated Thyristors (GCTs) and can be used as an optimisation tool for designing GCTs. In this study the authors evaluate the relative importance of the shallow p-base thickness, its peak concentration, the depth of the p-base and the buffer peak concentration. © The Institution of Engineering and Technology 2014.