An investigation of Mode I and Mode II fracture toughness enhancement using aligned carbon nanotubes forests at the crack interface

A novel approach for introducing aligned multi-walled carbon nanotubes (MWCNTs) in a carbon-fibre composite pre-impregnated (prepreg) laminate, to improve the through-thickness fracture toughness, is presented. Carbon nanotube (CNT) 'forests' were grown on a silicon substrate with a thermal oxide layer, using a chemical vapour deposition (CVD) process. The forests were then transferred to a pre-cured laminate interface, using a combination of pressure and heat, while maintaining through-thickness CNT alignment. Standard Mode I and four-point bend end-notched flexure Mode II tests were undertaken on a set of specimens and compared with pristine specimens. Mode I fracture toughness for T700/M21 laminates was improved by an average of 31% while for T700/SE84LV specimens, an improvement of 61% was observed. Only T700/M21 specimens were tested in Mode II which yielded an average fracture toughness improvement of 161%. Scanning Electron Microscopy (SEM) showed good wetting of the CNT forest as well as evidence of penetration of the forest into the adjacent plies. © 2013 Elsevier Ltd.

Evaluation of the performance of a multi-band antenna for On-Board applications

The performance of a multi-band antenna consisting of a microstrip patch with two U-slots is designed and tested for use in aircraft cabin wireless access points. The objective of this paper is to evaluate this antenna that covers most of the current wireless bands from 1.7GHz to 5.85GHz.A specially designed wideband probe antenna is used for characterization
of field radiated from this antenna. This measurement setup gives room for future development like human presence in the cabin, the fading effects, and the path loss between transmitter and receiver.

The use of ensemble empirical mode decomposition with canonical correlation analysis as a novel artifact removal technique

Biosignal measurement and processing is increasingly being deployed in ambulatory situations particularly in connected health applications. Such an environment dramatically increases the likelihood of artifacts which can occlude features of interest and reduce the quality of information available in the signal. If multichannel recordings are available for a given signal source, then there are currently a considerable range of methods which can suppress or in some cases remove the distorting effect of such artifacts. There are, however, considerably fewer techniques available if only a single-channel measurement is available and yet single-channel measurements are important where minimal instrumentation complexity is required. This paper describes a novel artifact removal technique for use in such a context. The technique known as ensemble empirical mode decomposition with canonical correlation analysis (EEMD-CCA) is capable of operating on single-channel measurements. The EEMD technique is first used to decompose the single-channel signal into a multidimensional signal. The CCA technique is then employed to isolate the artifact components from the underlying signal using second-order statistics. The new technique is tested against the currently available wavelet denoising and EEMD-ICA techniques using both electroencephalography and functional near-infrared spectroscopy data and is shown to produce significantly improved results. © 1964-2012 IEEE.

Coordinated Design of Phase Measurement Unit and Power System Stabilisers in Large Scale Power System

This paper presents a case-study of a PMU application with PSS support in a real large scale Chinese power system to suppress inter-area oscillations. The paper uses PMU measured feedback signals from a PSS input signal for dynamic torque analysis (DTA). In the paper, a mathematical model of multi-machine power system is described, followed by formation of the residue and DTA indices. Simulations of the model are used with a large-scale power system model to demonstrate the role of PSS and the equivalence of DTA residue indices.

Measurement-based Method for Wind Farm Power System Oscillation Monitoring

The global increase in the penetration of renewable energy is pushing electrical power systems into uncharted territory, especially in terms of transient and dynamic stability. In particular, the greater penetration of wind generation in European power networks is, at times, displacing a significant capacity of conventional synchronous generation with fixed-speed induction generation and now more commonly, doubly-fed induction generators. The impact of such changes in the generation mix requires careful monitoring to assess the impact on transient and dynamic stability. This paper presents a measurement based method for the early detection of power system oscillations, with attention to mode damping, in order to raise alarms and develop strategies to actively improve power system dynamic stability and security. A method is developed based on wavelet transform and support vector data description (SVDD) to detect oscillation modes in wind farm output power, which may excite dynamic instabilities in the wider system. The wavelet transform is used as a filter to identify oscillations in different frequency bands, while SVDD is used to extract dominant features from different scales and generate an assessment boundary according to the extracted features. Poorly damped oscillations of a large magnitude or that are resonant can be alarmed to the system operator, to reduce the risk of system instability. Method evaluation is exemplified used real data from a chosen wind farm.

Multi-Dimensional Deprivation in Ireland Among 9-Year-Olds in Ireland:An Analysis of the Growing Up in Ireland Survey’

In this paper we make use of the 9-year old wave of the Growing Up in Ireland study to analyse multidimensional deprivation in Ireland. The Alkire and Foster adjusted head count ratio approach (AHCR; 2007, 2011a, 2011b) applied here constitutes a significant improvement on union and intersection approaches and allows for the decomposition of multidimensional poverty in terms of dimensions and sub-groups. The approach involves a censoring of data such that deprivations count only for those above the specified multidimensional threshold leading to a stronger set of interrelationships between deprivation dimensions. Our analysis shows that the composition of the adjusted head ratio is influenced by a range of socio-economic factors. For less-favoured socio-economic groups dimensions relating to material deprivation are disproportionately represented while for the more advantaged groups, those relating to behavioral and emotional issues and social interaction play a greater role. Notwithstanding such variation in composition, our analysis showed that the AHCR varied systematically across categories of household type, and the social class, education and age group of the primary care giver. Furthermore, these variables combined in a cumulative manner. The most systematic variation was in relation to the head count of those above the multidimensional threshold rather than intensity, conditional on being above that cut-off point. Without seeking to arbitrate on the relative value of composite indices versus disaggregated profiles, our analysis demonstrates that there is much to be gained from adopting an approach with clearly understood axiomatic properties. Doing so allows one to evaluate the consequences of the measurement strategy employed for the understanding of levels of multidimensional deprivation, the nature of such deprivation profiles and socio-economic risk patterns. Ultimately it permits an informed assessment of the strengths and weaknesses of the particular choices made.

Multidimensional poverty measurement in Europe:An application of the adjusted headcount approach

As awareness of the limitations of relying solely on income to measure poverty has become more widespread, attention has been increasingly focused on multi-dimensional approaches, to the point where the EU has adopted a multidimensional poverty and social exclusion target for 2020. The rationale advanced is that the computation of a multidimensional poverty index is an effective way of communicating in a political environment, and a necessary tool in order to monitor 27 different national situations. By contrast with the rather ad hoc way in which the EU 2020 poverty target has been framed and rationalised, the adjusted head count ratio applied here has a number of desirable axiomatic properties. It constitutes a significant improvement on union and intersection approaches and allows for the decomposition of multidimensional poverty in terms of dimensions of deprivation and socio-economic attributes. Since understanding poverty as multidimensional does not necessarily require constructing a multidimensional poverty index, on the basis of our analysis we provide a more general consideration of the value of developing a multidimensional index of poverty for the European Union.

Nonlocality of two- and three-mode continuous variable systems

We address the nonlocality of fully inseparable three-mode Gaussian states generated either by bilinear three-mode Hamiltonians or by a sequence of bilinear two-mode Hamiltonians. Two different tests revealing nonlocality are considered, in which the dichotomic Bell operator is represented by the displaced parity and by the pseudospin operator respectively. Three-mode states are also considered as a conditional source of two-mode non-Gaussian states, whose nonlocality properties are analysed. We found that the non-Gaussian character of the conditional states allows violation of Bell's inequalities (by parity and pseudospin tests) stronger than with a conventional twin-beam state. However, the non-Gaussian character is not sufficient to reveal nonlocality through a dichotomized quadrature measurement strategy.

Inter-Area Power Oscillation Frequency Mode with Wind Turbine Generator in Irish Power System using PMU Data

Two case studies are presented in this paper to demonstrate the impact of different power system operation conditions on the power oscillation frequency modes in the Irish power system. A simplified 2 area equivalent of the Irish power system has been used in this paper, where area 1 represents the Republic of Ireland power system and area 2 represents the Northern Ireland power system.

The potential power oscillation frequency modes on the interconnector during different operation conditions have been analysed in this paper. The main objective of this paper is to analyse the influence of different operation conditions involving wind turbine generator (WTG) penetration on power oscillation frequency modes using phasor measurement unit (PMU) data.

Fast Fourier transform (FFT) analysis was performed to identify the frequency oscillation mode while correlation coefficient analysis was used to determine the source of the frequency oscillation. The results show that WTG, particularly fixed speed induction generation (FSIG), gives significant contribution to inter-area power oscillation frequency modes during high WTG operation.

Multi-Level Wordline Driver for Low Power SRAMs in Nano-Scale CMOS Technology

In this paper, a multi-level wordline driver scheme is presented to improve SRAM read and write stability while lowering power consumption during hold operation. The proposed circuit applies a shaped wordline voltage pulse during read mode and a boosted wordline pulse during write mode. During read, the applied shaped pulse is tuned at nominal voltage for short period of time, whereas for the remaining access time, the wordline voltage is reduced to a lower level. This pulse results in improved read noise margin without any degradation in access time which is explained by examining the dynamic and nonlinear behavior of the SRAM cell. Furthermore, during hold mode, the wordline voltage starts from a negative value and reaches zero voltage, resulting in a lower leakage current compared to conventional SRAM. Our simulations using TSMC 65nm process show that the proposed wordline driver results in 2X improvement in static read noise margin while the write margin is improved by 3X. In addition, the total leakage of the proposed SRAM is reduced by 10% while the total power is improved by 12% in the worst case scenario of a single SRAM cell. The total area penalty is 10% for a 128Kb standard SRAM array.

Multi-level wordline driver for robust SRAM design in nano-scale CMOS technology

In this paper, a multi-level wordline driver scheme is presented to improve 6T-SRAM read and write stability. The proposed wordline driver generates a shaped pulse during the read mode and a boosted wordline during the write mode. During read, the shaped pulse is tuned at nominal voltage for a short period of time, whereas for the remaining access time, the wordline voltage is reduced to save the power consumption of the cell. This shaped wordline pulse results in improved read noise margin without any degradation in access time for small wordline load. The improvement is explained by examining the dynamic and nonlinear behavior of the SRAM cell. Furthermore, during the hold mode, for a short time (depending on the size of boosting capacitance), wordline voltage becomes negative and charges up to zero after a specific time that results in a lower leakage current compared to conventional SRAM. The proposed technique results in at least 2× improvement in read noise margin while it improves write margin by 3× for lower supply voltages than 0.7 V. The leakage power for the proposed SRAM is reduced by 2% while the total power is improved by 3% in the worst case scenario for an SRAM array. The main advantage of the proposed wordline driver is the improvement of dynamic noise margin with less than 2.5% penalty in area. TSMC 65 nm technology models are used for simulations.

Virtual metrology enabled early stage prediction for enhanced control of multi-stage fabrication processes

Semiconductor fabrication involves several sequential processing steps with the result that critical production variables are often affected by a superposition of affects over multiple steps. In this paper a Virtual Metrology (VM) system for early stage measurement of such variables is presented; the VM system seeks to express the contribution to the output variability that is due to a defined observable part of the production line. The outputs of the processed system may be used for process monitoring and control purposes. A second contribution of this work is the introduction of Elastic Nets, a regularization and variable selection technique for the modelling of highly-correlated datasets, as a technique for the development of VM models. Elastic Nets and the proposed VM system are illustrated using real data from a multi-stage etch process used in the fabrication of disk drive read/write heads. © 2013 IEEE.

Adherence to treatment in children and adolescents with cystic fibrosis: a cross-sectional, multi-method study investigating the influence of beliefs about treatment and parental depressive symptoms

BACKGROUND: Adherence to treatment is often reported to be low in children with cystic fibrosis. Adherence in cystic fibrosis is an important research area and more research is needed to better understand family barriers to adherence in order for clinicians to provide appropriate intervention. The aim of this study was to evaluate adherence to enzyme supplements, vitamins and chest physiotherapy in children with cystic fibrosis and to determine if any modifiable risk factors are associated with adherence.

METHODS: A sample of 100 children (≤18 years) with cystic fibrosis (44 male; median [range] 10.1 [0.2-18.6] years) and their parents were recruited to the study from the Northern Ireland Paediatric Cystic Fibrosis Centre. Adherence to enzyme supplements, vitamins and chest physiotherapy was assessed using a multi-method approach including; Medication Adherence Report Scale, pharmacy prescription refill data and general practitioner prescription issue data. Beliefs about treatments were assessed using refined versions of the Beliefs about Medicines Questionnaire-specific. Parental depressive symptoms were assessed using the Center for Epidemiologic Studies Depression Scale.

RESULTS: Using the multi-method approach 72% of children were classified as low-adherers to enzyme supplements, 59% low-adherers to vitamins and 49% low-adherers to chest physiotherapy. Variations in adherence were observed between measurement methods, treatments and respondents. Parental necessity beliefs and child age were significant independent predictors of child adherence to enzyme supplements and chest physiotherapy, but parental depressive symptoms were not found to be predictive of adherence.

CONCLUSIONS: Child age and parental beliefs about treatments should be taken into account by clinicians when addressing adherence at routine clinic appointments. Low adherence is more likely to occur in older children, whereas, better adherence to cystic fibrosis therapies is more likely in children whose parents strongly believe the treatments are necessary. The necessity of treatments should be reinforced regularly to both parents and children.

Characterization and structure–property relationship of melt-mixed high density polyethylene/multi-walled carbon nanotube composites under extensional deformation

Melt-mixed high density polyethylene (HDPE)/multi-walled carbon nanotube (MWCNT) nanocomposites with 1–10 wt% MWCNTs were prepared by twin screw extrusion and compression moulded into sheet form. The compression moulded nanocomposites exhibit a 112% increase in modulus at a MWCNT loading of 4 wt%, and a low electrical percolation threshold of 1.9 wt%. Subsequently, uniaxial, sequential (seq-) biaxial and simultaneous (sim-) biaxial stretching of the virgin HDPE and nanocomposite sheets was conducted at different strain rates and stretching temperatures to investigate the processability of HDPE with the addition of nanotubes and the influence of deformation on the structure and final properties of nanocomposites. The results show that the processability of HDPE is improved under all the uniaxial and biaxial deformation conditions due to a strengthened strain hardening behaviour with the addition of MWCNTs. Extensional deformation is observed to disentangle nanotube agglomerates and the disentanglement degree is shown to depend on the stretching mode, strain rate and stretching temperatures applied. The disentanglement effectiveness is: uniaxial stretching < sim-biaxial stretching < seq-biaxial stretching, under the same deformation parameters. In sim-biaxial stretching, reducing the strain rate and stretching temperature can lead to more nanotube agglomerate breakup. Enhanced nanotube agglomerate disentanglement exhibits a positive effect on the mechanical properties and a negative effect on the electrical properties of the deformed nanocomposites. The ultimate stress of the composite containing 4 wt% MWCNTs increased by ∼492% after seq-biaxial stretching, while the resistivity increased by ∼1012 Ω cm.

Limitations of a measurement-assisted optomechanical route to quantum macroscopicity of superposition states

Optomechanics is currently believed to provide a promising route towards the achievement of genuine quantum effects at the large, massive-system scale. By using a recently proposed figure of merit that is well suited to address continuous-variable systems, in this paper we analyze the requirements needed for the state of a mechanical mode (embodied by an end-cavity cantilever or a membrane placed within an optical cavity) to be qualified as macroscopic. We show that, according to the phase space-based criterion that we have chosen for our quantitative analysis, the state achieved through strong single-photon radiation-pressure coupling to a quantized field of light and conditioned by measurements operated on the latter might be interpreted as macroscopically quantum. In general, though, genuine macroscopic quantum superpositions appear to be possible only under quite demanding experimental conditions