Gas generation in interconnected power systems with high wind power penetration

Increasing installed capacities of wind power in an effort to achieve sustainable power systems for future generations pose problems for system operators. Volatility in generation volumes due to the adoption of stochastic wind power is increasing. Storage has been shown to act as a buffer for these stochastic energy sources, facilitating the integration of renewable energy into a historically inflexible power system. This paper examines peak and off peak benefits realised by installing a short term discharge storage unit in a system with a high penetration of wind power in 2020. A fully representative unit commitment and economic dispatch model is used to analyse two scenarios, one ‘with storage’ and one ‘without storage’. Key findings of this preliminary study show that wind curtailment can be reduced in the storage scenario, with a larger reduction in peak time ramping of gas generators is realised.

Combining Bio- and Chemo-catalysis for the Conversion of Bio-Renewable Alcohols

The use of biomass as a source of fuel is on the sharp increase. In parallel with this expansion, new chemical processes and technologies are required to improve efficiency, sustainability, and profitability.
Biocatalytic and chemocatalytic methods can be combined to affect the conversion of bio-alcohols, and convert them to valuable chemical targets in an atom efficient and environmentally benign manor. Fermentation offers a useful first step in biomass conversion, as whole cell biocatalysts can provide sustained activity when fed with crude biomass. Coupling this with homogeneous and/or heterogeneous catalysis enables the preparation of a diverse product range. The transition between biocatalytic and chemocatalytic steps can be assisted by utilising ionic liquids.
Ionic liquids have potential roles in biorefineries that generate alcohols; as an extractant, reaction medium, and catalytic reagent. Underpinning the potential of ionic liquids in this area is: 1. the ability of ionic liquids to solubilize polyols and alcohols; 2. the facility to functionalise ionic liquids and tune properties; 3. the low volatility of ionic liquids.
The FP7 project GRAIL will be highlighted; this project focusses on the utilisation of glycerol formed as a by-product in biodiesel synthesis.

Characteristics of Corticospinal Projections to the Intrinsic Hand Muscles in Skilled Harpists.

The process of learning to play a musical instrument necessarily alters the functional organisation of the cortical motor areas that are involved in generating the required movements. In the case of the harp, the demands placed on the motor system are quite specific. During performance, all digits with the sole exception of the little finger are used to pluck the strings. With a view to elucidating the impact of having acquired this highly specialized musical skill on the characteristics of corticospinal projections to the intrinsic hand muscles, focal transcranial magnetic stimulation (TMS) was used to elicit motor evoked potentials (MEPs) in three muscles (of the left hand): abductor pollicis brevis (APB); first dorsal interosseous (FDI); and abductor digiti minimi (ADM) in seven harpists. Seven non-musicians served as controls. With respect to the FDI muscle–which moves the index finger, the harpists exhibited reliably larger MEP amplitudes than those in the control group. In contrast, MEPs evoked in the ADM muscle–which activates the little finger, were smaller in the harpists than in the non-musicians. The locations on the scalp over which magnetic stimulation elicited discriminable responses in ADM also differed between the harpists and the non-musicians. This specific pattern of variation in the excitability of corticospinal projections to these intrinsic hand muscles exhibited by harpists is in accordance with the idiosyncratic functional demands that are imposed in playing this instrument.

Identifying the relative importance of stock characteristics

There is no consensus in the literature as to which stock characteristic best explains returns. In this study, we employ a novel econometric approach better suited than the traditional characteristic sorting method to answer this question for the UK market. We evaluate the relative explanatory power of market, size, momentum, volatility, liquidity and book-to-market factors in a semiparametric characteristic-based factor model which does not require constructing characteristic portfolios. We find that momentum is the most important factor and liquidity is the least important based on their relative contribution to the fit of the model and the proportion of sample months for which factor returns are significant. Overall, this study provides strong evidence to support that the momentum characteristic can best explain stock returns in the UK market. The econometric approach employed in this study is a novel way to assess relevant investment risk in international financial markets outside U.S. Moreover, multinational institutions and investors can use this approach to identify regional factors in order to diversify their portfolios.

Perceptual learning of acoustic noise generates memory-evoked potentials

Experience continuously imprints on the brain at all stages of life. The traces it leaves behind can produce perceptual learning [1], which drives adaptive behavior to previously encountered stimuli. Recently, it has been shown that even random noise, a type of sound devoid of acoustic structure, can trigger fast and robust perceptual learning after repeated exposure [2]. Here, by combining psychophysics, electroencephalography (EEG), and modeling, we show that the perceptual learning of noise is associated with evoked potentials, without any salient physical discontinuity or obvious acoustic landmark in the sound. Rather, the potentials appeared whenever a memory trace was observed behaviorally. Such memory-evoked potentials were characterized by early latencies and auditory topographies, consistent with a sensory origin. Furthermore, they were generated even on conditions of diverted attention. The EEG waveforms could be modeled as standard evoked responses to auditory events (N1-P2) [3], triggered by idiosyncratic perceptual features acquired through learning. Thus, we argue that the learning of noise is accompanied by the rapid formation of sharp neural selectivity to arbitrary and complex acoustic patterns, within sensory regions. Such a mechanism bridges the gap between the short-term and longer-term plasticity observed in the learning of noise [2, 4-6]. It could also be key to the processing of natural sounds within auditory cortices [7], suggesting that the neural code for sound source identification will be shaped by experience as well as by acoustics.