From harmonisation to better, smart and fit food law

As the European Union (EU) approaches its 60th anniversary, it is worth assessing progress towards a key objective – the abolition of barriers to the marketing of food in the EU. Food has always created particular problems for the EU as national differences in diets, culture and geography make standardisation impossible. Early attempts focussed on direct measures to harmonise requirements or, later, to create an ‘internal market’. Subsequently a changed emphasis brought about the need to focus more clearly on the harmonisation of food safety. More widely, the recent recognition that too much legislation can itself create barriers has led legislators to attempt to consider more carefully the impact of their efforts. This paper reflects on the various stages in the creation of harmonised food controls and considers how case law has impacted the process. Today there are still differences and complete barrier-free trade seems some way off.

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.

Investigating preferences for dynamic electricity tariffs: the effect of environmental and system benefit disclosure

Dynamic electricity pricing can produce efficiency gains in the electricity sector and help achieve energy policy goals such as increasing electric system reliability and supporting renewable energy deployment. Retail electric companies can offer dynamic pricing to residential electricity customers via smart meter-enabled tariffs that proxy the cost to procure electricity on the wholesale market. Current investments in the smart metering necessary to implement dynamic tariffs show policy makers’ resolve for enabling responsive demand and realizing its benefits. However, despite these benefits and the potential bill savings these tariffs can offer, adoption among residential customers remains at low levels. Using a choice experiment approach, this paper seeks to determine whether disclosing the environmental and system benefits of dynamic tariffs to residential customers can increase adoption. Although sampling and design issues preclude wide generalization, we found that our environmentally conscious respondents reduced their required discount to switch to dynamic tariffs around 10% in response to higher awareness of environmental and system benefits. The perception that shifting usage is easy to do also had a significant impact, indicating the potential importance of enabling technology. Perhaps the targeted communication strategy employed by this study is one way to increase adoption and achieve policy goals.

Bio-fabrication and physiological self-release of tissue equivalents using smart peptide amphiphile templates

In this study we applied a smart biomaterial formed from a self-assembling, multi-functional synthetic peptide amphiphile (PA) to coat substrates with various surface chemistries. The combination of PA coating and alignment-inducing functionalised substrates provided a template to instruct human corneal stromal fibroblasts to adhere, become aligned and then bio-fabricate a highlyordered, multi-layered, three-dimensional tissue by depositing an aligned, native-like extracellular matrix. The newly-formed corneal tissue equivalent was subsequently able to eliminate the adhesive properties of the template and govern its own complete release via the action of endogenous proteases. Tissues recovered through this method were structurally stable, easily handled, and carrier-free. Furthermore, topographical and mechanical analysis by atomic force microscopy showed that tissue equivalents formed on the alignment-inducing PA template had highly-ordered, compact collagen deposition, with a two-fold higher elastic modulus compared to the less compact tissues produced on the non-alignment template, the PA-coated glass. We suggest that this technology represents a new paradigm in tissue engineering and regenerative medicine, whereby all processes for the biofabrication and subsequent self-release of natural, bioprosthetic human tissues depend solely on simple templatetissue feedback interactions.

The role of evaporating showers in the transfer of sting-jet momentum to the surface

The most damaging winds in a severe extratropical cyclone often occur just ahead of the evaporating ends of cloud filaments emanating from the so-called cloud head. These winds are associated with low-level jets (LLJs), sometimes occurring just above the boundary layer. The question then arises as to how the high momentum is transferred to the surface. An opportunity to address this question arose when the severe ‘St Jude's Day’ windstorm travelled across southern England on 28 October 2013. We have carried out a mesoanalysis of a network of 1 min resolution automatic weather stations and high-resolution Doppler radar scans from the sensitive S-band Chilbolton Advanced Meteorological Radar (CAMRa), along with satellite and radar network imagery and numerical weather prediction products. We show that, although the damaging winds occurred in a relatively dry region of the cyclone, there was evidence within the LLJ of abundant precipitation residues from shallow convective clouds that were evaporating in a localized region of descent. We find that pockets of high momentum were transported towards the surface by the few remaining actively precipitating convective clouds within the LLJ and also by precipitation-free convection in the boundary layer that was able to entrain evaporatively cooled air from the LLJ. The boundary-layer convection was organized in along-wind rolls separated by 500 to about 3000 m, the spacing varying according to the vertical extent of the convection. The spacing was greatest where the strongest winds penetrated to the surface. A run with a medium-resolution version of the Weather Research and Forecasting (WRF) model was able to reproduce the properties of the observed LLJ. It confirmed the LLJ to be a sting jet, which descended over the leading edge of a weaker cold-conveyor-belt jet.

Exploring smart grid possibilities: a complex systems modelling approach

Smart grid research has tended to be compartmentalised, with notable contributions from economics, electrical engineering and science and technology studies. However, there is an acknowledged and growing need for an integrated systems approach to the evaluation of smart grid initiatives. The capacity to simulate and explore smart grid possibilities on various scales is key to such an integrated approach but existing models – even if multidisciplinary – tend to have a limited focus. This paper describes an innovative and flexible framework that has been developed to facilitate the simulation of various smart grid scenarios and the interconnected social, technical and economic networks from a complex systems perspective. The architecture is described and related to realised examples of its use, both to model the electricity system as it is today and to model futures that have been envisioned in the literature. Potential future applications of the framework are explored, along with its utility as an analytic and decision support tool for smart grid stakeholders.

Automatic dimming multi-lamp fluorescent management system with active input power factor corrector stage

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Automatic system for thermal damage detection in manufacturing process with Internet monitoring

This work involved the development of a smart system dedicated to surface burning detection in the grinding process through constant monitoring of the process by acoustic emission and electrical power signals. A program in Visual Basic® for Windows® was developed, which collects the signals through an analog-digital converter and further processes them using burning detection algorithms already known. Three other parameters are proposed here and a comparative study carried out. When burning occurs, the newly developed software program sends a control signal warning the operator or interrupting the process, and delivers process information via the Internet. Parallel to this, the user can also interfere in the process via Internet, changing parameters and/or monitoring the grinding process. The findings of a comparative study of the various parameters are also discussed here. Copyright © 2006 by ABCM.

Power quality, smart meters and additional information from different power terms

This paper shows how the detailed examination of active and nonactive power components may produce new information for modern smart meters. For this purpose, a prototype of electronic power meter has been implemented and applied to the evaluation of the Conservative Power Theory (CPT). Considering five sorts of loads, under four different operating conditions, the experimental results indicate that the CPT is able to provide a good methodology for load characterization, which could possibly benefits consumers and power utilities in several different ways. The results also show that depending on the situation, the analysis of nonactive power terms may be more important than the observation of traditional power quality indices, such as total harmonic distortion, unbalance factors or the fundamental positive sequence power factor.

Smart histogram analysis applied to the skull-stripping problem in T1-weighted MRI

In this paper we address the "skull-stripping" problem in 3D MR images. We propose a new method that employs an efficient and unique histogram analysis. A fundamental component of this analysis is an algorithm for partitioning a histogram based on the position of the maximum deviation from a Gaussian fit. In our experiments we use a comprehensive image database, including both synthetic and real MRI. and compare our method with other two well-known methods, namely BSE and BET. For all datasets we achieved superior results. Our method is also highly independent of parameter tuning and very robust across considerable variations of noise ratio.