Autism in the air: using Point of View Video Priming and Natural Environment Teaching to help children with autism travel by plane

This paper describes a study that used video materials and visits to an airport to prepare children on the autism spectrum for travel by plane. Twenty parents and carers took part in the study with children aged from 3 to 16 years. The authors explain that the methods they used were based on Applied Behaviour Analysis (ABA) research; a video modeling technique called Point-Of-View Video-priming and during visits to an airport they used procedures known as Natural Environment Teaching. The findings suggest that using video and preparing children by taking them through what is likely to happen in the real environment when they travel by plane is effective and the authors suggest these strategies could be used to support children with autism with other experiences they need or would like to engage in such as visits to the dentist or hairdressers and access to leisure centres and other public spaces.

Point of view filming and the elicitation interview

Face-to-face interviews are a fundamental research tool in qualitative research. Whilst this form of data collection can provide many valuable insights, it can often fall short of providing a complete picture of a research subject's experiences. Point of view (PoV) interviewing is an elicitation technique used in the social sciences as a means of enriching data obtained from research interviews. Recording research subjects' first person perspectives, for example by wearing digital video glasses, can afford deeper insights into their experiences. PoV interviewing can promote making visible the unverbalizable and does not rely as much on memory as the traditional interview. The use of such relatively inexpensive technology is gaining interest in health profession educational research and pedagogy, such as dynamic simulation-based learning and research activities. In this interview, Dr Gerry Gormley (a medical education researcher) talks to Dr Jonathan Skinner (an anthropologist with an interest in PoV interviewing), exploring some of the many crossover implications with PoV interviewing for medical education research and practice.

Differential Scanning Calorimetry Study and Computer Modeling of b a Phase Transformation in Ti-6Al-4V Alloy

The relationship between heat-treatment parameters and microstructure in titanium alloys has so far been mainly studied empirically, using characterization techniques such as microscopy. Calculation and modeling of the kinetics of phase transformation have not yet been widely used for these alloys. Differential scanning calorimetry (DSC) has been widely used for the study of a variety of phase transformations. There has been much work done on the calculation and modeling of the kinetics of phase transformations for different systems based on the results from DSC study. In the present work, the kinetics of the transformation in a Ti-6Al-4V titanium alloy were studied using DSC, at continuous cooling conditions with constant cooling rates of 5 °C, 10 °C, 20 °C, 30 °C, 40 °C, and 50 °C/min. The results from calorimetry were then used to trace and model the transformation kinetics in continuous cooling conditions. Based on suitably interpreted DSC results, continuous cooling–transformation (CCT) diagrams were calculated with lines of isotransformed fraction. The kinetics of transformation were modeled using the Johnson–Mehl–Avrami (JMA) theory and by applying the "concept of additivity." The JMA kinetic parameters were derived. Good agreement between the calculated and experimental transformed fractions is demonstrated. Using the derived kinetic parameters, the transformation in a Ti-6Al-4V alloy can be described for any cooling path and condition. An interpretation of the results from the point of view of activation energy for nucleation is also presented.

Modelling the correlation between processing parameters and properties of maraging steels using artificial neural network

An artificial neural network (ANN) model is developed for the analysis and simulation of the correlation between the properties of maraging steels and composition, processing and working conditions. The input parameters of the model consist of alloy composition, processing parameters (including cold deformation degree, ageing temperature, and ageing time), and working temperature. The outputs of the ANN model include property parameters namely: ultimate tensile strength, yield strength, elongation, reduction in area, hardness, notched tensile strength, Charpy impact energy, fracture toughness, and martensitic transformation start temperature. Good performance of the ANN model is achieved. The model can be used to calculate properties of maraging steels as functions of alloy composition, processing parameters, and working condition. The combined influence of Co and Mo on the properties of maraging steels is simulated using the model. The results are in agreement with experimental data. Explanation of the calculated results from the metallurgical point of view is attempted. The model can be used as a guide for further alloy development.

Development of a monoclonal antibody binding okadaic acid and dinophysistoxins-1, -2 in proportion to their toxicity equivalence factors

Okadaic acid (OA) and structurally related toxins dinophysistoxin-1 (DTX-1), and DTX-2, are lipophilic marine biotoxins. The current reference method for the analysis of these toxins is the mouse bioassay (MBA). This method is under increasing criticism both from an ethical point of view and because of its limited sensitivity and specificity. Alternative replacement methods must be rapid, robust, cost effective, specific and sensitive. Although published immuno-based detection techniques have good sensitivities, they are restricted in their use because of their inability to: (i) detect all of the OA toxins that contribute to contamination; and (ii) factor in the relative toxicities of each contaminant. Monoclonal antibodies (MAbs) were produced to OA and an automated biosensor screening assay developed and compared with ELISA techniques. The screening assay was designed to increase the probability of identifying a MAb capable of detecting all OA toxins. The result was the generation of a unique MAb which not only cross-reacted with both DTX-1 and DTX-2 but had a cross-reactivity profile in buffer that reflected exactly the intrinsic toxic potency of the OA group of toxins. Preliminary matrix studies reflected these results. This antibody is an excellent candidate for the development of a range of functional immunochemical-based detection assays for this group of toxins.

Partial shoeprint retrieval using multiple point-of-interest detectors and SIFT descriptors

Shoeprint evidence collected from crime scenes can play an important role in forensic investigations. Usually, the analysis of shoeprints is carried out manually and is based on human expertise and knowledge. As well as being error prone, such a manual process can also be time consuming; thus affecting the usability and suitability of shoeprint evidence in a court of law. Thus, an automatic system for classification and retrieval of shoeprints has the potential to be a valuable tool. This paper presents a solution for the automatic retrieval of shoeprints which is considerably more robust than existing solutions in the presence of geometric distortions such as scale, rotation and scale distortions. It addresses the issue of classifying partial shoeprints in the presence of rotation, scale and noise distortions and relies on the use of two local point-of-interest detectors whose matching scores are combined. In this work, multiscale Harris and Hessian detectors are used to select corners and blob-like structures in a scale-space representation for scale invariance, while Scale Invariant Feature Transform (SIFT) descriptor is employed to achieve rotation invariance. The proposed technique is based on combining the matching scores of the two detectors at the score level. Our evaluation has shown that it outperforms both detectors in most of our extended experiments when retrieving partial shoeprints with geometric distortions, and is clearly better than similar work published in the literature. We also demonstrate improved performance in the face of wear and tear. As matter of fact, whilst the proposed work outperforms similar algorithms in the literature, it is shown that achieving good retrieval performance is not constrained by acquiring a full print from a scene of crime as a partial print can still be used to attain comparable retrieval results to those of using the full print. This gives crime investigators more flexibility is choosing the parts of a print to search for in a database of footwear.

A new analytical approach for the detection of palm oil in vegetable oil blends

The new Food Information Regulation (1169/2011), dictates that in a refined vegetable oil blend, the type of oil must be clearly identified in the package in contract with current practice where is labelled under the generic and often misleading term “vegetable oil”. With increase consumer awareness in food authenticity, as shown in the recent food scandal with horsemeat in beef products, the identification of the origin of species in food products becomes increasingly relevant. Palm oil is used extensively in food manufacturing and as global demand increases, producing countries suffer from the aftermath of intensive agriculture. Even if only a small portion of global production, sustainable palm oil comes in great demand from consumers and industry. It is therefore of interest to detect the presence of palm oil in food products as consumers have the right to know if it is present in the product or not, mainly from an ethical point of view. Apart from palm oil and its derivatives, rapeseed oil and sunflower oil are also included. With DNA-based methods, the gold standard for the detection of food authenticity and species recognition deemed not suitable in this analytical problem, the focus is inevitably drawn to the chromatographic and spectroscopic methods. Both chromatographic (such as GC-FID and LC-MS) and spectroscopic methods (FT-IR, Raman, NIR) are relevant. Previous attempts have not shown promising results due to oils’ natural variation in composition and complex chemical signals but the suggested two-step analytical procedure is a promising approach with very good initial results.

Existence of multibreathers in one-dimensional Debye crystals

The existence of highly localized multisite oscillatory structures (discrete multibreathers) in a nonlinear Klein-Gordon chain which is characterized by an inverse dispersion law is proven and their linear stability is investigated. The results are applied in the description of vertical (transverse, off-plane) dust grain motion in dusty plasma crystals, by taking into account the lattice discreteness and the sheath electric and/or magnetic field nonlinearity. Explicit values from experimental plasma discharge experiments are considered. The possibility for the occurrence of multibreathers associated with vertical charged dust grain motion in strongly coupled dusty plasmas (dust crystals) is thus established. From a fundamental point of view, this study aims at providing a rigorous investigation of the existence of intrinsic localized modes in Debye crystals and/or dusty plasma crystals and, in fact, suggesting those lattices as model systems for the study of fundamental crystal properties.