An external field prior for the hidden Potts model with application to cone-beam computed tomography

In images with low contrast-to-noise ratio (CNR), the information gain from the observed pixel values can be insufficient to distinguish foreground objects. A Bayesian approach to this problem is to incorporate prior information about the objects into a statistical model. A method for representing spatial prior information as an external field in a hidden Potts model is introduced. This prior distribution over the latent pixel labels is a mixture of Gaussian fields, centred on the positions of the objects at a previous point in time. It is particularly applicable in longitudinal imaging studies, where the manual segmentation of one image can be used as a prior for automatic segmentation of subsequent images. The method is demonstrated by application to cone-beam computed tomography (CT), an imaging modality that exhibits distortions in pixel values due to X-ray scatter. The external field prior results in a substantial improvement in segmentation accuracy, reducing the mean pixel misclassification rate for an electron density phantom from 87% to 6%. The method is also applied to radiotherapy patient data, demonstrating how to derive the external field prior in a clinical context.

Quantifying uncertainty in parameter estimates for stochastic models of collective cell spreading using approximate Bayesian computation

Wound healing and tumour growth involve collective cell spreading, which is driven by individual motility and proliferation events within a population of cells. Mathematical models are often used to interpret experimental data and to estimate the parameters so that predictions can be made. Existing methods for parameter estimation typically assume that these parameters are constants and often ignore any uncertainty in the estimated values. We use approximate Bayesian computation (ABC) to estimate the cell diffusivity, D, and the cell proliferation rate, λ, from a discrete model of collective cell spreading, and we quantify the uncertainty associated with these estimates using Bayesian inference. We use a detailed experimental data set describing the collective cell spreading of 3T3 fibroblast cells. The ABC analysis is conducted for different combinations of initial cell densities and experimental times in two separate scenarios: (i) where collective cell spreading is driven by cell motility alone, and (ii) where collective cell spreading is driven by combined cell motility and cell proliferation. We find that D can be estimated precisely, with a small coefficient of variation (CV) of 2–6%. Our results indicate that D appears to depend on the experimental time, which is a feature that has been previously overlooked. Assuming that the values of D are the same in both experimental scenarios, we use the information about D from the first experimental scenario to obtain reasonably precise estimates of λ, with a CV between 4 and 12%. Our estimates of D and λ are consistent with previously reported values; however, our method is based on a straightforward measurement of the position of the leading edge whereas previous approaches have involved expensive cell counting techniques. Additional insights gained using a fully Bayesian approach justify the computational cost, especially since it allows us to accommodate information from different experiments in a principled way.

Prediction of GMA welding characteristic parameter by artificial neural network system

Nowadays, demand for automated Gas metal arc welding (GMAW) is growing and consequently need for intelligent systems is increased to ensure the accuracy of the procedure. To date, welding pool geometry has been the most used factor in quality assessment of intelligent welding systems. But, it has recently been found that Mahalanobis Distance (MD) not only can be used for this purpose but also is more efficient. In the present paper, Artificial Neural Networks (ANN) has been used for prediction of MD parameter. However, advantages and disadvantages of other methods have been discussed. The Levenberg–Marquardt algorithm was found to be the most effective algorithm for GMAW process. It is known that the number of neurons plays an important role in optimal network design. In this work, using trial and error method, it has been found that 30 is the optimal number of neurons. The model has been investigated with different number of layers in Multilayer Perceptron (MLP) architecture and has been shown that for the aim of this work the optimal result is obtained when using MLP with one layer. Robustness of the system has been evaluated by adding noise into the input data and studying the effect of the noise in prediction capability of the network. The experiments for this study were conducted in an automated GMAW setup that was integrated with data acquisition system and prepared in a laboratory for welding of steel plate with 12 mm in thickness. The accuracy of the network was evaluated by Root Mean Squared (RMS) error between the measured and the estimated values. The low error value (about 0.008) reflects the good accuracy of the model. Also the comparison of the predicted results by ANN and the test data set showed very good agreement that reveals the predictive power of the model. Therefore, the ANN model offered in here for GMA welding process can be used effectively for prediction goals.

Influence of the structural characteristic of pyrolysis products on thermal stability of styrene-butadiene rubber composites reinforced by different particle sized kaolinites

A series of rubber composites were prepared by blending styrene-butadiene rubber (SBR) latex and the different particle sized kaolinites. The thermal stabilities of the rubber composites were characterized using thermogravimetry, digital photography, scanning electron microscopy, X-ray diffraction, Fourier transform infrared spectroscopy, and Raman spectroscopy. Kaolinite SBR composites showed much greater thermal stability when compared with that of the pure SBR. With the increase of kaolinite particle size, the pyrolysis products became much looser; the char layer and crystalline carbon content gradually decreased in the pyrolysis residues. The pyrolysis residues of the SBR composites filled with the different particle sized kaolinites showed some remarkable changes in structural characteristics. The increase of kaolinite particle size was not beneficial to form the compact and stable crystalline carbon in the pyrolysis process, and resulted in a negative influence in improving the thermal stability of kaolinite/SBR composites.

Towards strongly consistent online HMM parameter estimation using one-step Kerridge inaccuracy

In this paper, we propose a novel online hidden Markov model (HMM) parameter estimator based on the new information-theoretic concept of one-step Kerridge inaccuracy (OKI). Under several regulatory conditions, we establish a convergence result (and some limited strong consistency results) for our proposed online OKI-based parameter estimator. In simulation studies, we illustrate the global convergence behaviour of our proposed estimator and provide a counter-example illustrating the local convergence of other popular HMM parameter estimators.

Hertzian Tales: Electronic Products, Aesthetic Experience, and Critical Design

Anthony Dunne’s Hertzian Tales is an exploration of the aesthetic and conceptual aspects of industrial design and its potential to bring about social change for the users of electronic objects. It is a provoking and – to first-time readers – positively alarming social commentary on the interrelationship between electronic product design and culture, and the powerful but largely under-explored potential of electronic innovation to trigger social awareness. Hertzian Tales proposes an innovative approach to critical design and therefore serves as a reflection on and a critique of the commercial design practices at large. In this second edition, Dunne reiterates the original rationale for his project: a concern that the majority of industrial designers have unwittingly joined a treadmill culture of post-industrial mass-production – turning out electronic goods that have long simply met the brief of an optimally functioning and eagerly consumable technology.

GPU accelerated algorithms for computing matrix function vector products with applications to exponential integrators and fractional diffusion

The efficient computation of matrix function vector products has become an important area of research in recent times, driven in particular by two important applications: the numerical solution of fractional partial differential equations and the integration of large systems of ordinary differential equations. In this work we consider a problem that combines these two applications, in the form of a numerical solution algorithm for fractional reaction diffusion equations that after spatial discretisation, is advanced in time using the exponential Euler method. We focus on the efficient implementation of the algorithm on Graphics Processing Units (GPU), as we wish to make use of the increased computational power available with this hardware. We compute the matrix function vector products using the contour integration method in [N. Hale, N. Higham, and L. Trefethen. Computing Aα, log(A), and related matrix functions by contour integrals. SIAM J. Numer. Anal., 46(5):2505–2523, 2008]. Multiple levels of preconditioning are applied to reduce the GPU memory footprint and to further accelerate convergence. We also derive an error bound for the convergence of the contour integral method that allows us to pre-determine the appropriate number of quadrature points. Results are presented that demonstrate the effectiveness of the method for large two-dimensional problems, showing a speedup of more than an order of magnitude compared to a CPU-only implementation.

A comprehensive mechanistic kinetic model for dilute acid hydrolysis of switchgrass cellulose to glucose, 5-HMF and levulinic acid

Switchgrass was treated by 1% (w/w) H₂SO₄in batch tube reactors at temperatures ranging from 140–220°C for up to 60 minutes. In this study, release patterns of glucose, 5-hydroxymethylfurfural (5-HMF), and levulinic acid from switchgrass cellulose were investigated through a mechanistic kinetic model. The predictions were consistent with the measured products of interest when new parameters reflecting the effects of reaction limitations, such as cellulose crystallinity, acid soluble lignin–glucose complex (ASL–glucose) and humins that cannot be quantitatively analyzed, were included. The new mechanistic kinetic model incorporating these parameters simulated the experimental data with R² above 0.97. Results showed that glucose yield was most sensitive to variations in the parameter regarding the cellulose crystallinity at low temperatures (140–180°C), while the impact of crystallinity on the glucose yield became imperceptible at elevated temperatures (200–220 °C). Parameters related to the undesired products (e.g. ASL–glucose and humins) were the most sensitive factors compared with rate constants and other additional parameters in impacting the levulinic acid yield at elevated temperatures (200–220°C), while their impacts were negligible at 140–180°C. These new findings provide a more rational explanation for the kinetic changes in dilute acid pretreatment performance and suggest that the influences of cellulose crystallinity and undesired products including ASL–glucose and humins play key roles in determining the generation of glucose, 5-HMF and levulinic acid from biomass-derived cellulose.

The sweet aroma of success: Modification of products for new markets in the case of TORQ by Di Bella Coffee

In 2002, Phillip Di Bella’s childhood passion for coffee and keen entrepreneurial spirit led him to establish a small coffee roasting warehouse in in the inner suburbs of Brisbane (Di Bella, 2012). With a keen sense of direction and passion for his coffee products and providing unparalleled customer service, Di Bella Coffee quickly grew to become a key player in the coffee roasting scene. This passion for the ultimate coffee experience is evident in the firm’s logo ‘Di Bella Coffee Inspires Passion’. Phillip Di Bella stated that ‘the common denominator of this company is about inspiration and passion. We are not a coffee company, we are a people company. You know, are we inspiring you from the moment you walk in the door to the moment you leave. If you are not feeling inspired then we haven’t done our job properly as a company’. Fundamentally, providing the ultimate coffee experience, as detailed in the following case is one in which focuses on the coffee consumption experience, not the coffee itself. Over that last 10 years Di Bella Coffee has constantly strived for the ultimate coffee, while expanding business operations into the booming Asian coffee market, establishing headquarters in Shanghai in 2010. In 2011, Di Bella Coffee commenced their second international venture with the launch of operations in India (Di Bella Coffee, 2012); followed shortly by the creation of a new category of coffee, set to revolutionise to coffee industry. The fusion of two traditional forms of coffee; espresso coffee and instant coffee, to create a third category- espresso instant, led to the development of TORQ by Di Bella.

The High Court of Australia and the Marlboro Man: The Battle Over the Plain Packaging of Tobacco Products

In 2012, the High Court of Australia handed down a landmark decision on the plain packaging of tobacco products. This chapter considers the historic ruling in the case of JT International SA v Commonwealth; British American Tobacco Australasia Ltd v Commonwealth. This chapter explores several themes in the decision. First, it highlights the historical work by the High Court of Australia on the role of health regulation, the use of health warnings, and tobacco control. Second, the chapter considers the High Court of Australia's view that intellectual property law promotes the public interest.Third, it explores the High Court of Australia’s analysis of the constitutional law on acquisition of property on just terms. Finally, this chapter contends that the High Court of Australia's ruling on plain packaging of tobacco products will spark an 'Olive Revolution' — and will encourage superior courts and policy-makers to follow suit.

The nutritional profile of baby and toddler food products sold in Australian supermarkets

Background/Aims To examine the nutritional profile of baby and toddler foods sold in Australia. Methods Nutrient information for baby and toddler foods available at Australian supermarkets was collected between August and December 2013. Levels of declared energy, total fat, saturated fat, total sugar, sodium and estimated added sugar were examined, as well as the presence of additional micronutrients on the label. The Health Star Rating (HSR) system was used to determine nutritional quality. The range of products on offer was also examined by product type and by the age category for which the product was marketed. Results Of the 309 products included, 29 % were fortified. On a per 100 g basis, these 309 products provided a mean (±SD) of 476 ± 486 kJ, 1.6 ± 2.4 g total fat, 10.7 ± 12.2 g total sugar, 2.7 ± 7.4 g added sugar, and 33.5 ± 66.5 mg sodium. Fruit-based products or products with fruit listed as an ingredient (58 %) were the predominant product type. On the nutrition label, 42 % displayed at least one additional micronutrient while 37 % did not display saturated fat. The most common HSR was four stars (45 %) and 6? months was the most commonly identified targeted age group (36 %). Conclusions The majority of baby and toddler foods sold in Australian supermarkets are ready-made fruit-based products aimed at children under 12 months of age. Baby and toddler foods are overlooked in public policy discussions pertaining to population nutrient intake but their relatively high sugar content deriving from fruits requires close attention to ensure these foods do not replace other more nutrient dense foods, given children have an innate preference for sweet tastes.

Eye-safe UV stand-off Raman spectroscopy for the ranged detection of explosives in the field

Increasing worldwide terrorist attacks involving explosives presents a growing need for a rapid and ranged explosive detection method that can safely be deployed in the field. Stand-off Raman spectroscopy shows great promise; however, the radiant exposures of lasers required for adequate signal generation are often much greater than what is safe for the eye or the skin, restricting use of the technique to un-populated areas. Here, by determining the safe exposure levels for lasers typically used in Raman spectroscopy, optimal parameter values are identified, which produce the largest possible detection range using power densities that do not exceed the eye-safe limit. It is shown that safe ultraviolet pulse energies can be more than three orders of magnitude greater than equivalent safe visible pulse energies. Coupling this to the 16-fold increase in Raman signal obtained in the ultraviolet at 266 nm over that at 532 nm results in a 131 times larger detection range for the eye-safe 266-nm system over an equivalent eye-safe 532-nm laser system. For the Raman system described here, this translates to a maximum range of 42 m for detecting Teflon with a 266-nm laser emitting a 100-mm diameter beam of 23.5-mJ nanosecond pulses.

The case for the plain packaging of tobacco products

AIMS: The Framework Convention on Tobacco Control (FCTC) requires nations that have ratified the convention to ban all tobacco advertising and promotion. In the face of these restrictions, tobacco packaging has become the key promotional vehicle for the tobacco industry to interest smokers and potential smokers in tobacco products. This paper reviews available research into the probable impact of mandatory plain packaging and internal tobacco industry statements about the importance of packs as promotional vehicles. It critiques legal objections raised by the industry about plain packaging violating laws and international trade agreements. METHODS: Searches for available evidence were conducted within the internal tobacco industry documents through the online document archives; tobacco industry trade publications; research literature through the Medline and Business Source Premier databases; and grey literature including government documents, research reports and non-governmental organization papers via the Google internet search engine. RESULTS: Plain packaging of all tobacco products would remove a key remaining means for the industry to promote its products to billions of the world's smokers and future smokers. Governments have required large surface areas of tobacco packs to be used exclusively for health warnings without legal impediment or need to compensate tobacco companies. CONCLUSIONS: Requiring plain packaging is consistent with the intention to ban all tobacco promotions. There is no impediment in the FCTC to interpreting tobacco advertising and promotion to include tobacco packs.

Innovation in Road Building: Removing Obstacles for Diffusion of Novel Building Products

How can obstacles to innovation be overcome in road construction? Using a focus group methodology, and based on two prior rounds of empirical work, the analysis in this chapter generates a set of four key solutions to two main construction innovation obstacles: (1) restrictive tender assessment and (2) disagreement over who carries the risk of new product failure. The four key solutions uncovered were: 1) pre-project product certification; 2) past innovation performance assessment; 3) earlier involvement of product suppliers and road asset operators; and 4) performance-based specifications. Additional research is suggested in order to illicit deeper insights into possible solutions to construction innovation obstacles, and should emphasise furthering the theoretical interpretation of empirical phenomena.

Developments of the total entropy utility function for the dual purpose of model discrimination and parameter estimation in Bayesian design

The total entropy utility function is considered for the dual purpose of Bayesian design for model discrimination and parameter estimation. A sequential design setting is proposed where it is shown how to efficiently estimate the total entropy utility for a wide variety of data types. Utility estimation relies on forming particle approximations to a number of intractable integrals which is afforded by the use of the sequential Monte Carlo algorithm for Bayesian inference. A number of motivating examples are considered for demonstrating the performance of total entropy in comparison to utilities for model discrimination and parameter estimation. The results suggest that the total entropy utility selects designs which are efficient under both experimental goals with little compromise in achieving either goal. As such, the total entropy utility is advocated as a general utility for Bayesian design in the presence of model uncertainty.