A low glycaemic load breakfast can attenuate cognitive impairments observed in middle aged obese females with impaired glucose tolerance.

Increased central adiposity and abnormalities in glucose tolerance preceding type 2 diabetes can have demonstrable negative effects on cognitive function, even in ostensibly healthy, middle-aged females. The potential for GL manipulations to modulate glycaemic response and cognitive function in type 2 diabetes and obesity merits further investigation..

Type 2 diabetes and impaired glucose tolerance are associated with word memory source monitoring recollection deficits but not simple recognition familiarity deficits following water, low glycaemic load, and high glycaemic load breakfasts.

Isolated source monitoring recollection deficits indicate that abnormalities in glucose metabolism are not detrimental for global episodic memory processes. This enhances our understanding of how metabolic disorders are associated with memory impairments.

Acute glycaemic load breakfast manipulations do not attenuate cognitive impairments in adults with type 2 diabetes

Abnormalities in glucose tolerance such as type 2 diabetes can have demonstrable negative effects on a range of cognitive functions. However, there was no evidence that low GL breakfasts administered acutely could confer benefits for cognitive function (ClincalTrials.gov identifier, NCT01047813).

A refined parametric model for short term load forecasting

Abstract We present a refined parametric model for forecasting electricity demand which performed particularly well in the recent Global Energy Forecasting Competition (GEFCom 2012). We begin by motivating and presenting a simple parametric model, treating the electricity demand as a function of the temperature and day of the data. We then set out a series of refinements of the model, explaining the rationale for each, and using the competition scores to demonstrate that each successive refinement step increases the accuracy of the model’s predictions. These refinements include combining models from multiple weather stations, removing outliers from the historical data, and special treatments of public holidays.

Long term individual load forecast under different electrical vehicles uptake scenarios

More and more households are purchasing electric vehicles (EVs), and this will continue as we move towards a low carbon future. There are various projections as to the rate of EV uptake, but all predict an increase over the next ten years. Charging these EVs will produce one of the biggest loads on the low voltage network. To manage the network, we must not only take into account the number of EVs taken up, but where on the network they are charging, and at what time. To simulate the impact on the network from high, medium and low EV uptake (as outlined by the UK government), we present an agent-based model. We initialise the model to assign an EV to a household based on either random distribution or social influences - that is, a neighbour of an EV owner is more likely to also purchase an EV. Additionally, we examine the effect of peak behaviour on the network when charging is at day-time, night-time, or a mix of both. The model is implemented on a neighbourhood in south-east England using smart meter data (half hourly electricity readings) and real life charging patterns from an EV trial. Our results indicate that social influence can increase the peak demand on a local level (street or feeder), meaning that medium EV uptake can create higher peak demand than currently expected.

Effect of temperature and strain rate on the compressive behaviour of supramolecular polyurethane

Supramolecular polyurethanes (SPUs) possess thermoresponsive and thermoreversible properties, and those characteristics are highly desirable in both bulk commodity and value-added applications such as adhesives, shape-memory materials, healable coatings and lightweight, impact-resistant structures (e.g. protection for mobile electronics). A better understanding of the mechanical properties, especially the rate and temperature sensitivity, of these materials are required to assess their suitability for different applications. In this paper, a newly developed SPU with tuneable thermal properties was studied, and the response of this SPU to compressive loading over strain rates from 10−3 to 104 s−1 was presented. Furthermore, the effect of temperature on the mechanical response was also demonstrated. The sample was tested using an Instron mechanical testing machine for quasi-static loading, a home-made hydraulic system for moderate rates and a traditional split Hopkinson pressure bars (SHPBs) for high strain rates. Results showed that the compression stress-strain behaviour was affected significantly by the thermoresponsive nature of SPU, but that, as expected for polymeric materials, the general trends of the temperature and the rate dependence mirror each other. However, this behaviour is more complicated than observed for many other polymeric materials, as a result of the richer range of transitions that influence the behaviour over the range of temperatures and strain rates tested.