Population inversion in optically pumped asymmetric quantum well terahertz lasers

Intersubband carrier lifetimes and population ratios are calculated for three- and four-level optically pumped terahertz laser structures. Laser operation is based on intersubband transitions between the conduction band states of asymmetric GaAs-Ga(1 – x)Al(x)As quantum wells. It is shown that the carrier lifetimes in three-level systems fulfill the necessary conditions for stimulated emission only at temperatures below 200 K. The addition of a fourth level, however, enables fast depopulation of the lower laser level by resonant longitudinal optical phonon emission and thus offers potential for room temperature laser operation. © 1997 American Institute of Physics

Supervised machine learning for audio emotion recognition

The field of Music Emotion Recognition has become and established research sub-domain of Music Information Retrieval. Less attention has been directed towards the counterpart domain of Audio Emotion Recognition, which focuses upon detection of emotional stimuli resulting from non-musical sound. By better understanding how sounds provoke emotional responses in an audience, it may be possible to enhance the work of sound designers. The work in this paper uses the International Affective Digital Sounds set. A total of 76 features are extracted from the sounds, spanning the time and frequency domains. The features are then subjected to an initial analysis to determine what level of similarity exists between pairs of features measured using Pearson’s r correlation coefficient before being used as inputs to a multiple regression model to determine their weighting and relative importance. The features are then used as the input to two machine learning approaches: regression modelling and artificial neural networks in order to determine their ability to predict the emotional dimensions of arousal and valence. It was found that a small number of strong correlations exist between the features and that a greater number of features contribute significantly to the predictive power of emotional valence, rather than arousal. Shallow neural networks perform significantly better than a range of regression models and the best performing networks were able to account for 64.4% of the variance in prediction of arousal and 65.4% in the case of valence. These findings are a major improvement over those encountered in the literature. Several extensions of this research are discussed, including work related to improving data sets as well as the modelling processes

Supervised machine learning for audio emotion recognition: Enhancing film sound design using audio features, regression models and artificial neural networks

This version of the article has been accepted for publication, after peer review (when applicable) and is subject to Springer Nature’s AM terms of use, but is not the Version of Record and does not reflect post-acceptance improvements, or any corrections. The Version of Record is available online at: https://doi.org/10.1007/s00779-020-01389-0The field of Music Emotion Recognition has become and established research sub-domain of Music Information Retrieval. Less attention has been directed towards the counterpart domain of Audio Emotion Recognition, which focuses upon detection of emotional stimuli resulting from non-musical sound. By better understanding how sounds provoke emotional responses in an audience, it may be possible to enhance the work of sound designers. The work in this paper uses the International Affective Digital Sounds set. A total of 76 features are extracted from the sounds, spanning the time and frequency domains. The features are then subjected to an initial analysis to determine what level of similarity exists between pairs of features measured using Pearson’s r correlation coefficient before being used as inputs to a multiple regression model to determine their weighting and relative importance. The features are then used as the input to two machine learning approaches: regression modelling and artificial neural networks in order to determine their ability to predict the emotional dimensions of arousal and valence. It was found that a small number of strong correlations exist between the features and that a greater number of features contribute significantly to the predictive power of emotional valence, rather than arousal. Shallow neural networks perform significantly better than a range of regression models and the best performing networks were able to account for 64.4% of the variance in prediction of arousal and 65.4% in the case of valence. These findings are a major improvement over those encountered in the literature. Several extensions of this research are discussed, including work related to improving data sets as well as the modelling processes

Quantum well infrared photodetectors hardiness to the non ideality of the energy band profile

We report results on the effect of a non-sharp and disordered potential in Quantum Well Infrared Photodetectors (QWIP). Scanning electronic transmission microscopy is used to measure the alloy profile of the structure which is shown to present a gradient of composition along the growth axis. Those measurements are used as inputs to quantify the effect on the detector performance (peak wavelength, spectral broadening and dark current). The influence of the random positioning of the doping is also studied. Finally we demonstrate that QWIP properties are quite robust with regard to the non ideality of the energy band profile

Excited States of Ladder-type Poly-p-phenylene Oligomers

Ground state properties and excited states of ladder-type paraphenylene oligomers are calculated applying semiempirical methods for up to eleven phenylene rings. The results are in qualitative agreement with experimental data. A new scheme to interpret the excited states is developed which reveals the excitonic nature of the excited states. The electron-hole pair of the S1-state has a mean distance of approximately 4 Angstroem.Comment: 24 pages, 21 figure

Communitarian perspectives on social enterprise

Concepts of social enterprise have been debated repeatedly, and continue to cause confusion. In this paper, a meta-theoretical framework is developed through discussion of individualist and communitarian philosophy. Philosophers from both traditions build social theories that emphasise either consensus (a unitarist outlook) or diversity (a pluralist outlook). The various discourses in corporate governance reflect these assumptions and create four distinct approaches that impact on the relationship between capital and labour. In rejecting the traditional discourse of private enterprise, social enterprises have adopted other approaches to tackle social exclusion, each derived from different underlying beliefs about the purpose of enterprise and the nature of governance. The theoretical framework offers a way to understand the diversity found within the sector, including the newly constituted Community Interest Company (CIC).</p

Failures in transport infrastructure embankments

To ensure that road and rail transport networks remain operational, both highway and railway embankments require continual maintenance and renewal to mitigate against ongoing deterioration and repair any sections damaged by realised failures. This paper provides a review of recent developments in the understanding of highway and railway embankment degradation and failure. Failures due to pore water pressure increase, seasonal shrink-swell deformation and progressive failure are considered. The material composition and construction of highway and railway embankments differ, which influences the dominant type and timing of embankment failure. There is evidence for highway embankment failures induced by pore water pressure increase, but not seasonal deformation and progressive failure. Some railway embankments are susceptible to pore water pressure increase, seasonal shrink-swell deformation and progressive failure due to the age and nature of the dumped clay fill used in their construction. The approaches used to measure and explore embankment failure mechanisms are compared and discussed. Field observations have been used to understand pore water pressure increase and seasonal shrink-swell deformation in embankments, while the investigation of progressive embankment failure has mainly utilised physical and numerical modelling approaches. Further field and laboratory investigation is required before the rigorous analysis of embankment failure can be routinely undertaken. However, progress is being made to empirically identify and evaluate the various risk factors affecting transport infrastructure embankment failure

Intercomparison and evaluation of global aerosol microphysical properties among AeroCom models of a range of complexity

Many of the next generation of global climate models will include aerosol schemes which explicitly simulate the microphysical processes that determine the particle size distribution. These models enable aerosol optical properties and cloud condensation nuclei (CCN) concentrations to be determined by fundamental aerosol processes, which should lead to a more physically based simulation of aerosol direct and indirect radiative forcings. This study examines the global variation in particle size distribution simulated by 12 global aerosol microphysics models to quantify model diversity and to identify any common biases against observations. Evaluation against size distribution measurements from a new European network of aerosol supersites shows that the mean model agrees quite well with the observations at many sites on the annual mean, but there are some seasonal biases common to many sites. In particular, at many of these European sites, the accumulation mode number concentration is biased low during winter and Aitken mode concentrations tend to be overestimated in winter and underestimated in summer. At high northern latitudes, the models strongly underpredict Aitken and accumulation particle concentrations compared to the measurements, consistent with previous studies that have highlighted the poor performance of global aerosol models in the Arctic. In the marine boundary layer, the models capture the observed meridional variation in the size distribution, which is dominated by the Aitken mode at high latitudes, with an increasing concentration of accumulation particles with decreasing latitude. Considering vertical profiles, the models reproduce the observed peak in total particle concentrations in the upper troposphere due to new particle formation, although modelled peak concentrations tend to be biased high over Europe. Overall, the multi-model-mean data set simulates the global variation of the particle size distribution with a good degree of skill, suggesting that most of the individual global aerosol microphysics models are performing well, although the large model diversity indicates that some models are in poor agreement with the observations. Further work is required to better constrain size-resolved primary and secondary particle number sources, and an improved understanding of nucleation and growth (e.g. the role of nitrate and secondary organics) will improve the fidelity of simulated particle size distributions