Plasmonic Sensing Using Nanodome Arrays Fabricated by Soft Nanoimprint Lithography

Arrays of gold-coated nanodomes were fabricated on glass substrates using a soft
nanoimprint lithography technique. Optical transmission measurements revealed complex
plasmonic resonances that proved highly sensitive to the array dimensions, the thickness of
the gold layer, and the refractive index of the surrounding medium. As one promising
application for these structures, the refractive index sensing capabilities of the nanodome
arrays were assessed.

Review of constitutive models for describing the time dependent behaviour of soft clays

Different classes of constitutive models have been proposed to capture the time-dependent behaviour of soft soil (creep, stress relaxation, rate dependency). This paper critically reviews many of the models developed based on understanding of the time dependent stress-strain-stress rate-strain rate behaviour of soils and viscoplasticity in terms of their strengths and weaknesses. Some discussion is also made on the numerical implementation aspects of these models. Typical findings from numerical analyses of geotechnical structures constructed on soft soils are also discussed. The general elastic viscoplastic (EVP) models can roughly be divided into two categories: models based on the concept of overstress and models based on non-stationary flow surface theory. Although general in structure, both categories have their own strengths and shortcomings. This review indicates that EVP analysis is yet to be vastly used by the geotechnical engineers, apparently due to the mathematical complication involved in the formulation of the constitutive models, unconvincing benefit in terms of the accuracy of performance prediction, requirement of additional soil parameter(s), difficulties in determining them, and the necessity of excessive computing resources and time. © 2013 Taylor & Francis.

Review of visco-plastic soil models for predicting the performance of embankments on soft soils

A number of constitutive models that account for creep or secondary compression and rate dependent behaviour of soil have been reviewed in terms of their strengths and weaknesses. Some results of numerical analysis of some embankments have been discussed and an effort has been made to find out their strengths and limitations.

An Analysis of Soft Law Applicable to Humanitarian Assistance: Relative Normativity in Action?

There is limited binding international law specifically covering the provision of humanitarian assistance in response to natural and human-made disasters. Yet a variety of authoritative soft law texts have been developed in the past 20 years, including the UN Guiding Principles on Internal Displacement, the Red Cross Red Crescent Code of Conduct and the Sphere Project’s Humanitarian Charter and Minimum Standards in Disaster Response. While such ‘non-binding normative standards’ do not carry the weight of international law, they play an essential role in the provision of humanitarian assistance albeit subject to their limited enforceability vis-à-vis intended beneficiaries and to their voluntary application by humanitarian actors. Notwithstanding a lack of legal compulsion, certain non-binding normative standards may directly influence the actions of States and non-State actors, and so obtain a strongly persuasive character. Analysis of texts that influence the practice of humanitarian assistance advances our understanding of humanitarian principles and performance standards for disaster response. As the International Law Commission debates draft articles on the Protection of Persons in the Event of Disasters, such non-binding normative standards are crucial to the development of an internationally accepted legal framework to protect victims of disasters.

Electron impact excitation of Mg VIII: Collision strengths, transition probabilities and theoretical EUV and soft X-ray line intensities for Mg VIII

Context: Mg VIII emission lines are observed in a range of astronomical objects such as the Sun, other cool stars and in the coronal line region of Seyfert galaxies. Under coronal conditions Mg VIII emits strongly in the extreme ultraviolet (EUV) and soft X-ray spectral regions which makes it an ideal ion for plasma diagnostics.

Aims. Two theoretical atomic models, consisting of 125 fine structure levels, are developed for the Mg VIII ion. The 125 levels arise from the 2s(2)2p, 2s(2)p2, 2p(3), 2s(2)3s, 2s(2)3p, 2s(2)3d, 2s2p3s, 2s2p3p, 2s2p3d, 2p(2)3s, 2p(2)3p and 2p(2)3d configurations. Electron impact excitation collision strengths and radiative transition probabilities are calculated for both Mg VIII models, compared with existing data, and the best model selected to generate a set of theoretical emission line intensities. The EUV lines, covering 312-790 angstrom, are compared with existing solar spectra (SERTS-89 and SUMER), while the soft X-ray transitions (69-97 angstrom) are examined for potential density diagnostic line ratios and also compared with the limited available solar and stellar observational data.

Methods. The R-matrix codes Breit-Pauli RMATRXI and RMATRXII are utilised, along with the PSTGF code, to calculate the collision strengths for two Mg VIII models. Collision strengths are averaged over a Maxwellian distribution to produce the corresponding effective collision strengths for use in astrophysical applications. Transition probabilities are also calculated using the CIV3 atomic structure code. The best data are then incorporated into the modelling code CLOUDY and line intensities generated for a range of electron temperatures and densities appropriate to solar and stellar coronal plasmas.

Results. The present effective collision strengths are compared with two previous calculations. Good levels of agreement are found with the most recent, but there are large differences with the other for forbidden transitions. The resulting line intensities compare favourably with the observed values from the SERTS-89 and SUMER spectra. Theoretical soft X-ray emission lines are presented and several density diagnostic line ratios examined, which are in reasonable agreement with the limited observational data available.

Young children's food brand knowledge. Early development and associations with television viewing and parent's diet

Brand knowledge is a prerequisite of children's requests and choices for branded foods. We explored the development of young children's brand knowledge of foods highly advertised on television - both healthy and less healthy. Participants were 172 children aged 3-5 years in diverse socio-economic settings, from two jurisdictions on the island of Ireland with different regulatory environments. Results indicated that food brand knowledge (i) did not differ across jurisdictions; (ii) increased significantly between 3 and 4 years; and (iii) children had significantly greater knowledge of unhealthy food brands, compared with similarly advertised healthy brands. In addition, (iv) children's healthy food brand knowledge was not related to their television viewing, their mother's education, or parent or child eating. However, (v) unhealthy brand knowledge was significantly related to all these factors, although only parent eating and children's age were independent predictors. Findings indicate that effects of food marketing for unhealthy foods take place through routes other than television advertising alone, and are present before pre-schoolers develop the concept of healthy eating. Implications are that marketing restrictions of unhealthy foods should extend beyond television advertising; and that family-focused obesity prevention programmes should begin before children are 3 years of age.

Dataflow toolset for soft-core processors on FPGA for image processing applications

With security and surveillance, there is an increasing need to be able to process image data efficiently and effectively either at source or in a large data networks. Whilst Field Programmable Gate Arrays have been seen as a key technology for enabling this, they typically use high level and/or hardware description language synthesis approaches; this provides a major disadvantage in terms of the time needed to design or program them and to verify correct operation; it considerably reduces the programmability capability of any technique based on this technology. The work here proposes a different approach of using optimised soft-core processors which can be programmed in software. In particular, the paper proposes a design tool chain for programming such processors that uses the CAL Actor Language as a starting point for describing an image processing algorithm and targets its implementation to these custom designed, soft-core processors on FPGA. The main purpose is to exploit the task and data parallelism in order to achieve the same parallelism as a previous HDL implementation but avoiding the design time, verification and debugging steps associated with such approaches.

A Soft Sensor for Viscosity Control of Polymer Extrusion

Viscosity represents a key indicator of product quality in polymer extrusion but has traditionally been difficult to measure in-process in real-time. An innovative, yet simple, solution to this problem is proposed by a Prediction-Feedback observer mechanism. A `Prediction' model based on the operating conditions generates an open-loop estimate of the melt viscosity; this estimate is used as an input to a second, `Feedback' model to predict the pressure of the system. The pressure value is compared to the actual measured melt pressure and the error used to correct the viscosity estimate. The Prediction model captures the relationship between the operating conditions and the resulting melt viscosity and as such describes the specific material behavior. The Feedback model on the other hand describes the fundamental physical relationship between viscosity and extruder pressure and is a function of the machine geometry. The resulting system yields viscosity estimates within 1% error, shows excellent disturbance rejection properties and can be directly applied to model-based control. This is of major significance to achieving higher quality and reducing waste and set-up times in the polymer extrusion industry.

Selection of burst-like transients and stochastic variables using multi-brand image differencing in the Pan-STARRS1 Medium Deep Survey

We present a novel method for the light-curve characterization of Pan-STARRS1 Medium Deep Survey (PS1 MDS) extragalactic sources into stochastic variables (SVs) and burst-like (BL) transients, using multi-band image-differencing time-series data. We select detections in difference images associated with galaxy hosts using a star/galaxy catalog extracted from the deep PS1 MDS stacked images, and adopt a maximum a posteriori formulation to model their difference-flux time-series in four Pan-STARRS1 photometric bands gP1, rP1, iP1, and zP1. We use three deterministic light-curve models to fit BL transients; a Gaussian, a Gamma distribution, and an analytic supernova (SN) model, and one stochastic light-curve model, the Ornstein-Uhlenbeck process, in order to fit variability that is characteristic of active galactic nuclei (AGNs). We assess the quality of fit of the models band-wise and source-wise, using their estimated leave-out-one cross-validation likelihoods and corrected Akaike information criteria. We then apply a K-means clustering algorithm on these statistics, to determine the source classification in each band. The final source classification is derived as a combination of the individual filter classifications, resulting in two measures of classification quality, from the averages across the photometric filters of (1) the classifications determined from the closest K-means cluster centers, and (2) the square distances from the clustering centers in the K-means clustering spaces. For a verification set of AGNs and SNe, we show that SV and BL occupy distinct regions in the plane constituted by these measures. We use our clustering method to characterize 4361 extragalactic image difference detected sources, in the first 2.5 yr of the PS1 MDS, into 1529 BL, and 2262 SV, with a purity of 95.00% for AGNs, and 90.97% for SN based on our verification sets. We combine our light-curve classifications with their nuclear or off-nuclear host galaxy offsets, to define a robust photometric sample of 1233 AGNs and 812 SNe. With these two samples, we characterize their variability and host galaxy properties, and identify simple photometric priors that would enable their real-time identification in future wide-field synoptic surveys.