R-Matrix Theory for Nanoscale Phonon Thermal Transport across Devices and Interfaces

We have adapted R-matrix theory to calculate phonon scattering across systems of molecular to mesoscopic scale. The key novelty of this work is that the only required information about the scattering region is its normal modes, which are evaluated only once for a system. Thus, R-matrix theory is a computationally efficient and simple approach to calculate phonon scattering in larger systems. To validate and to demonstrate the applicability of the theory, we apply it to two systems: a one-dimensional chain of atoms and a graphene nanoribbon. In both cases, we discuss the effect of mass impurities on thermal transport.     

Starter strain related effects on the biochemical and sensory properties of Cheddar cheese

A detailed investigation was undertaken to determine the effects of four single starter strains, Lactococcus lactis subsp. lactis 303, Lc. lactis subsp. cremoris HP, Lc. lactis subsp. cremoris AM2, and Lactobacillus helveticus DPC4571 on the proteolytic, lipolytic and sensory characteristics of Cheddar cheese. Cheeses produced using the highly autolytic starters 4571 and AM2 positively impacted on flavour development, whereas cheeses produced from the poorly autolytic starters 303 and HP developed off-flavours. Starter selection impacted significantly on the proteolytic and sensory characteristics of the resulting Cheddar cheeses. It appeared that the autolytic and/or lipolytic properties of starter strains also influenced lipolysis, however lipolysis appeared to be limited due to a possible lack of availability or access to suitable milk fat substrates over ripening. The impact of lipolysis on the sensory characteristics of Cheddar cheese was unclear, possibly due to minimal differences in the extent of lipolysis between the cheeses at the end of ripening. As anticipated seasonal milk supply influenced both proteolysis and lipolysis in Cheddar cheese. The contribution of non-starter lactic acid bacteria towards proteolysis and lipolysis over the first 8 months of Cheddar cheese ripening was negligible.     

2D-LC analysis of BRP 3 erythropoietin N-glycosylation using anion exchange fractionation and hydrophilic interaction UPLC reveals long poly-N-acetyl lactosamine extensions

Post-translational modifications, in particular glycosylation, represent critical structural attributes that govern both the pharmacodynamic and pharmacokinetic properties of therapeutic glycoproteins. To guarantee safety and efficacy of recombinant therapeutics, characterization of glycosylation present is a regulatory requirement. In the current paper, we applied a multidimensional strategy comprising a shallow anion exchange gradient in the first dimension, followed by analysis using the recently introduced 1.7 μm HILIC phase in the second dimension for the comprehensive separation of complex N-glycans present on the European Biological Reference Preparation (BRP) 3 erythropoietin standard. Tetra-antennary glycans with multiple sialic acids and poly-N-acetyl lactosamine extensions were the most abundant oligosaccharides present on the molecule. Site-specific glycan analysis was performed to examine microheterogeneity. Tetra-antennary glycans with up to four sialic acids and up to five poly-N-acetyl lactosamine extensions were observed at asparagine 24 and 83, while biantennary glycans were the major structures at asparagine 38. The combined AEC x UPLC HILIC allows for the rapid and comprehensive analysis of complex N-glycosylation present on therapeutic glycoproteins, such as BRP3 erythropoietin.     

Detecting,categorizing and forecasting large ramps in wind farm power output using meteorological observations and WPPT

The Wind Power Prediction Tool (WPPT) has been installed in Australia for the first time, to forecast the power output from the 65MW Roaring 40s Renewable Energy P/L Woolnorth Bluff Point wind farm. This article analyses the general performance of WPPT as well as its performance during large ramps (swings) in power output. In addition to this, detected large ramps are studied in detail and categorized. WPPT combines wind speed and direction forecasts from the Australian Bureau of Meteorology regional numerical weather prediction model, MesoLAPS, with real‐time wind power observations to make hourly forecasts of the wind farm power output. The general performances of MesoLAPS and WPPT are evaluated over 1 year using the root mean square error (RMSE). The errors are significantly lower than for basic benchmark forecasts but higher than for many other WPPT installations, where the site conditions are not as complicated as Woolnorth Bluff Point. Large ramps are considered critical events for a wind power forecast for energy trading as well as managing power system security. A methodology is developed to detect large ramp events in the wind farm power data. Forty‐one large ramp events are detected over 1 year and these are categorized according to their predictability by MesoLAPS, the mechanical behaviour of the wind turbine, the power change observed on the grid and the source weather event. During these events, MesoLAPS and WPPT are found to give an RMSE only roughly equivalent to just predicting the mean (climatology forecast). Copyright © 2007 John Wiley & Sons, Ltd.     

The efficiency of visually guided movement in real and virtual space

Virtual Reality - There is an increasing interest in the use of low-cost virtual reality (VR) for training and simulation. As effective training for many tasks requires efficient...