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The power system of the future will have a hierarchical structure created by layers of system control from via regional high-voltage transmission through to medium and low-voltage distribution. Each level will have generation sources such as large-scale offshore wind, wave, solar thermal, nuclear directly connected to this Supergrid and high levels of embedded generation, connected to the medium-voltage distribution system. It is expected that the fuel portfolio will be dominated by offshore wind in Northern Europe and PV in Southern Europe. The strategies required to manage the coordination of supply-side variability with demand-side variability will include large scale interconnection, demand side management, load aggregation and storage in the concept of the Supergrid combined with the Smart Grid. The design challenge associated with this will not only include control topology, data acquisition, analysis and communications technologies, but also the selection of fuel portfolio at a macro level. This paper quantifies the amount of demand side management, storage and so-called ‘back-up generation’ needed to support an 80% renewable energy portfolio in Europe by 2050.

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In this paper, the processing and characterization of Polyamide 6 (PA6) nanocomposites containing graphite nanoplatelets (GNPs) is reported. PA6 nanocomposites were prepared by melt-mixing using an industrial, co-rotating, intermeshing, twin-screw extruder. A bespoke screw configuration was used that was designed in-house to enhance nanoparticle dispersion into a polymer matrix. The effects of nano-filler type (xGnPTM M-5 and xGnPTM C-500), nano-filler content, and extruder screw speed on the bulk properties of the PA6 nanocomposites were investigated. The crystalline structures of PA6 nanocomposites are related to thermal treatment, stress history and the presence of moisture and nanofillers. DSC, Raman and XRD studies show an increase in crystallinity with increasing GNP content and a phase transformation between α-form to γ-form crystals as a result of the heterophase nucleation effect. The effect of uniaxial stretching on PA6 nanocomposites was investigated by drawing specimens heated at temperatures below the melting temperature. DSC and Raman studies on the drawn samples show an increase in yield stress as the GNP content increases due to the strain induced crystallization and γ—β transition during stretching. The rheological response of the nanocomposites resemble that of a ‘pseudo-solid’, rather than a molten liquid, and analysis of the rheological data indicates that a percolation threshold was reached at GNP contents of between 10–15wt%. An increase in tensile modulus of as much as 412% was observed for PA6/C-500 xGnPTM composites, at a filler content of 20wt%. The enhancement of Young’s modulus and yield stress can be attributed to the reinforcing effect of GNPs and their uniform dispersion in the PA6 matrix. The electrical conductivity of the composite also increased with increasing GNP content, with an addition of 15wt% GNP resulting in a 6 order-of-magnitude increase in conductivity. The effects of uniaxial-drawing and the inclusion of multiple nano-filler varieties on the electrical and mechanical properties are currently under investigation.

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In this paper, we presented a facile way of preparing PVA/Au, PVA/Ag and PVA/AuAg nanocomposites through in situ synthesis of metal nanoparticles in PVA hydrogel network using a room temperature atmospheric pressure microplasma. This is the first time microplasma technology is used for the fabrication of hydrogel based nanocomposites. The materials synthesized have been characterized for their microstructure and antibacterial properties. The nanoparticles synthesized within the PVA hydrogel network are found to be better dispersed than those synthesized in water, and their size and shape are more uniform. The new approach has opened a new avenue towards multi-scale synthesis of green and multi-functional nanocomposites, which may find wide range of potential applications in biomedical field.

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Cloud data centres are critical business infrastructures and the fastest growing service providers. Detecting anomalies in Cloud data centre operation is vital. Given the vast complexity of the data centre system software stack, applications and workloads, anomaly detection is a challenging endeavour. Current tools for detecting anomalies often use machine learning techniques, application instance behaviours or system metrics distribu- tion, which are complex to implement in Cloud computing environments as they require training, access to application-level data and complex processing. This paper presents LADT, a lightweight anomaly detection tool for Cloud data centres that uses rigorous correlation of system metrics, implemented by an efficient corre- lation algorithm without need for training or complex infrastructure set up. LADT is based on the hypothesis that, in an anomaly-free system, metrics from data centre host nodes and virtual machines (VMs) are strongly correlated. An anomaly is detected whenever correlation drops below a threshold value. We demonstrate and evaluate LADT using a Cloud environment, where it shows that the hosting node I/O operations per second (IOPS) are strongly correlated with the aggregated virtual machine IOPS, but this correlation vanishes when an application stresses the disk, indicating a node-level anomaly.

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Purpose:Physical activity is recommended for optimal prevention of cardiovascular disease(CVD) and participation in sport is associated with improved well-being. However, people with long-standing illness/disability are less likely to participate in sport than others. Evidence of factors associated with their participation is limited and the best approach to encourage participation is unknown. This study aimed to identify sport participation levels and their correlates, among adults with long standing illness/disability in Northern Ireland, where CVD prevalence is high. Method:Using routinely collected data in annual surveys of population samples from 2007 to 2011, descriptive statistics were derived. Chi-squared tests were used to compare characteristics of those with a long-term illness/disability and those without long-term health problems. Uni-variate binary regression analysis for the whole sample and those with a long-standing illness/disability, using sport participation as the dependent variable, was performed and variables with a p-value of 0.1 or less were taken into a multi-variate analysis. Results:The sample included 13,683 adults; 3550(26%) reported having long-term illness/disability. Fewer of those with, than without, long-term illness/disability reported sport participation in the previous year (868/3550(24.5%) v 5615/10133(55.6%)). Multi-variate analysis showed that, for those with long-standing illness/disability, being single and less socio-economically deprived correlated positively with sport participation. For both those with long-standing illness/disability and the full sample, sport participation correlated positively with being male, aged <56 years, access to a household car/van, sports club membership, health ‘fairly good’ or ‘good’ in the previous year, doing paid/unpaid work, and living in an urban location. For the full sample but not those with long-standing illness/disability, sport participation correlated positively with being a non-smoker, higher educational status and personal internet access. Of note, personal internet access was less for those with, than without, long-term illness/disability (41% v 70%). Conclusions:Efforts to promote physical activity in sport for those with long-standing illness/disability should target older people, married females, those who live rurally, and those who are socio-economically deprived and report their health as ‘not good’. Implementation of initiatives should not rely on the internet, to which these people may not have ready access, to help support their sport participation and physical activity in optimal CVD prevention.

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This introduction contextualises the hypothesis of the two-year research project on which this book is based, and explains how the single chapters relate to this hypothesis. The reader will see that we are opening a new debate with new questions, which still await definite answers.

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Introduction Tensions between the economic and the social dimensions of European integration are being perceived as increasing, and so is the potential for conflict between national and European levels of policy-making. Both are well illustrated by a highly controversial line of Court of Justice of the European Union (ECJ) cases on industrial relations: Viking and Laval have become symbols for the continuing dominance of the economic over the social dimension of European integration and for an increasing tendency of the EU to diminish national autonomy. As one consequence, demands to protect Member States’ social policy choices from EU law pressures arise. For such demands to be tenable, isolation of national and EU policy-making and of economic and social dimensions of European integration would have to be possible. This is arguably not the case. Economic and social dimensions of integration will thus have to be reconciled across EU and national levels, if the EU and its Member States are to maintain the ability of enhancing social justice against the pulls of economic globalisation.

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Physically Unclonable Functions (PUFs), exploit inherent manufacturing variations and present a promising solution for hardware security. They can be used for key storage, authentication and ID generations. Low power cryptographic design is also very important for security applications. However, research to date on digital PUF designs, such as Arbiter PUFs and RO PUFs, is not very efficient. These PUF designs are difficult to implement on Field Programmable Gate Arrays (FPGAs) or consume many FPGA hardware resources. In previous work, a new and efficient PUF identification generator was presented for FPGA. The PUF identification generator is designed to fit in a single slice per response bit by using a 1-bit PUF identification generator cell formed as a hard-macro. In this work, we propose an ultra-compact PUF identification generator design. It is implemented on ten low-cost Xilinx Spartan-6 FPGA LX9 microboards. The resource utilization is only 2.23%, which, to the best of the authors' knowledge, is the most compact and robust FPGA-based PUF identification generator design reported to date. This PUF identification generator delivers a stable range of uniqueness of around 50% and good reliability between 85% and 100%.