Hui and Walter's latent-class model extended to estimate diagnostic test properties from surveillance data: a latent model for latent data

Diagnostic test sensitivity and specificity are probabilistic estimates with far reaching implications for disease control, management and genetic studies. In the absence of 'gold standard' tests, traditional Bayesian latent class models may be used to assess diagnostic test accuracies through the comparison of two or more tests performed on the same groups of individuals. The aim of this study was to extend such models to estimate diagnostic test parameters and true cohort-specific prevalence, using disease surveillance data. The traditional Hui-Walter latent class methodology was extended to allow for features seen in such data, including (i) unrecorded data (i.e. data for a second test available only on a subset of the sampled population) and (ii) cohort-specific sensitivities and specificities. The model was applied with and without the modelling of conditional dependence between tests. The utility of the extended model was demonstrated through application to bovine tuberculosis surveillance data from Northern and the Republic of Ireland. Simulation coupled with re-sampling techniques, demonstrated that the extended model has good predictive power to estimate the diagnostic parameters and true herd-level prevalence from surveillance data. Our methodology can aid in the interpretation of disease surveillance data, and the results can potentially refine disease control strategies.

A Conventional Internal Combustion Engine Versus a Range Extended Electric Vehicle Under the Current Regulatory Regime in the United Kingdom

Transport accounts for 22% of greenhouse gas emissions in the United Kingdom and cars are expected tomore than double by 2050. Car manufacturers are continually aiming for a substantially reduced carbonfootprint through improved fuel efficiency and better powertrain performance due to the strict EuropeanUnion emissions standards. However, road tax, not just fuel efficiency, is a key consideration of consumerswhen purchasing a car. While measures have been taken to reduce emissions through stricter standards, infuture, alternative technologies will be used. Electric vehicles, hybrid vehicles and range extended electricvehicles have been identified as some of these future technologies. In this research a virtual test bed of aconventional internal combustion engine and a range extended electric vehicle family saloon car were builtin AVL’s vehicle and powertrain system level simulation tool, CRUISE, to simulate the New EuropeanDrive Cycle and the results were then soft-linked to a techno-economic model to compare the effectivenessof current support mechanisms over the full life cycle of both cars. The key finding indicates that althoughcarbon emissions are substantially reduced, switching is still not financially the best option for either theconsumer or the government in the long run.

Averaged Extended Tree Augmented Naive Classifier

This work presents a new general purpose classifier named Averaged Extended Tree Augmented Naive Bayes (AETAN), which is based on combining the advantageous characteristics of Extended Tree Augmented Naive Bayes (ETAN) and Averaged One-Dependence Estimator (AODE) classifiers. We describe the main properties of the approach and algorithms for learning it, along with an analysis of its computational time complexity. Empirical results with numerous data sets indicate that the new approach is superior to ETAN and AODE in terms of both zero-one classification accuracy and log loss. It also compares favourably against weighted AODE and hidden Naive Bayes. The learning phase of the new approach is slower than that of its competitors, while the time complexity for the testing phase is similar. Such characteristics suggest that the new classifier is ideal in scenarios where online learning is not required.

Learning Extended Tree Augmented Naive Structures

This work proposes an extended version of the well-known tree-augmented naive Bayes (TAN) classifier where the structure learning step is performed without requiring features to be connected to the class. Based on a modification of Edmonds' algorithm, our structure learning procedure explores a superset of the structures that are considered by TAN, yet achieves global optimality of the learning score function in a very efficient way (quadratic in the number of features, the same complexity as learning TANs). We enhance our procedure with a new score function that only takes into account arcs that are relevant to predict the class, as well as an optimization over the equivalent sample size during learning. These ideas may be useful for structure learning of Bayesian networks in general. A range of experiments shows that we obtain models with better prediction accuracy than naive Bayes and TAN, and comparable to the accuracy of the state-of-the-art classifier averaged one-dependence estimator (AODE). We release our implementation of ETAN so that it can be easily installed and run within Weka.

Production of extended-spectrum β-lactamases and the potential indirect pathogenic role of Prevotella isolates from the cystic fibrosis respiratory microbiota

Extended-spectrum β-lactamase (ESBL) production and the prevalence of the β-lactamase-encoding gene blaTEM were determined in Prevotella isolates (n=50) cultured from the respiratory tract of adults and young people with cystic fibrosis (CF). Time-kill studies were used to investigate the concept of passive antibiotic resistance and to ascertain whether a β-lactamase-positive Prevotella isolate can protect a recognised CF pathogen from the action of ceftazidime in vitro. The results indicated that approximately three-quarters (38/50; 76%) of Prevotella isolates produced ESBLs. Isolates positive for ESBL production had higher minimum inhibitory concentrations (MICs) of β-lactam antibiotics compared with isolates negative for production of ESBLs (P<0.001). The blaTEM gene was detected more frequently in CF Prevotella isolates from paediatric patients compared with isolates from adults (P=0.002), with sequence analysis demonstrating that 21/22 (95%) partial blaTEM genes detected were identical to blaTEM-116. Furthermore, a β-lactamase-positive Prevotella isolate protected Pseudomonas aeruginosa from the antimicrobial effects of ceftazidime (P=0.03). Prevotella isolated from the CF respiratory microbiota produce ESBLs and may influence the pathogenesis of chronic lung infection via indirect methods, including shielding recognised pathogens from the action of ceftazidime.

Incipient turn-to-turn winding fault diagnosis of power transformers by the on-load exciting current Extended Park`s Vector Approach

This paper presents the application of the on-load exciting current Extended Park's Vector Approach for diagnosing incipient turn-to-turn winding faults in operating power transformers. Experimental and simulated test results demonstrate the effectiveness of the proposed technique, which is based on the spectral analysis of the AC component of the on-load exciting current Park's Vector modulus.

Tensile behaviour of a structural adhesive at high temperatures by the extended finite element method

Component joining is typically performed by welding, fastening, or adhesive-bonding. For bonded aerospace applications, adhesives must withstand high-temperatures (200°C or above, depending on the application), which implies their mechanical characterization under identical conditions. The extended finite element method (XFEM) is an enhancement of the finite element method (FEM) that can be used for the strength prediction of bonded structures. This work proposes and validates damage laws for a thin layer of an epoxy adhesive at room temperature (RT), 100, 150, and 200°C using the XFEM. The fracture toughness (G Ic ) and maximum load ( ); in pure tensile loading were defined by testing double-cantilever beam (DCB) and bulk tensile specimens, respectively, which permitted building the damage laws for each temperature. The bulk test results revealed that decreased gradually with the temperature. On the other hand, the value of G Ic of the adhesive, extracted from the DCB data, was shown to be relatively insensitive to temperature up to the glass transition temperature (T g ), while above T g (at 200°C) a great reduction took place. The output of the DCB numerical simulations for the various temperatures showed a good agreement with the experimental results, which validated the obtained data for strength prediction of bonded joints in tension. By the obtained results, the XFEM proved to be an alternative for the accurate strength prediction of bonded structures.

Strength prediction of single- and double-lap joints by standard and extended finite element modelling

The structural integrity of multi-component structures is usually determined by the strength and durability of their unions. Adhesive bonding is often chosen over welding, riveting and bolting, due to the reduction of stress concentrations, reduced weight penalty and easy manufacturing, amongst other issues. In the past decades, the Finite Element Method (FEM) has been used for the simulation and strength prediction of bonded structures, by strength of materials or fracture mechanics-based criteria. Cohesive-zone models (CZMs) have already proved to be an effective tool in modelling damage growth, surpassing a few limitations of the aforementioned techniques. Despite this fact, they still suffer from the restriction of damage growth only at predefined growth paths. The eXtended Finite Element Method (XFEM) is a recent improvement of the FEM, developed to allow the growth of discontinuities within bulk solids along an arbitrary path, by enriching degrees of freedom with special displacement functions, thus overcoming the main restriction of CZMs. These two techniques were tested to simulate adhesively bonded single- and double-lap joints. The comparative evaluation of the two methods showed their capabilities and/or limitations for this specific purpose.

Board-level prototype validation: a built-in controller and extended BST architecture

Prototype validation is a major concern in modern electronic product design and development. Simulation, structural test, functional and timing debug are all forming parts of the validation process, although very often addressed as dissociated tasks. In this paper we describe an integrated approach to board-level prototype validation, based on a set of mandatory/optional BST instructions and a built-in controller for debug and test, that addresses the late mentioned tasks as inherent parts of a whole process

Verbal emotional memory in a case with left amygdala damage.

The amygdala nuclei appear to be critically implicated in emotional memory. However, in most studies, encoding and consolidation processes cannot be analyzed separately. We thus studied the verbal emotional memory in a young woman with a ganglioglioma of the left amygdala and analyzed its impact (1) on each step of the memory process (encoding, retrieval, and recognition) (2) on short- and long-term consolidation (1-hour and 1-week delay) and (3) on processing of valence (positive and negative items compared to neutral words). Results showed emotional encoding impairments and, after encoding was controlled for, emotional long-term consolidation. Finally, although the negative words were not acknowledged as emotionally arousing by the patient, these words were specifically poorly encoded, recalled, and consolidated. Our data suggest that separate cerebral networks support the processing of emotional versus neutral stimuli.

Returning from the Wild: Exploring Participant's Experiences of Re-entry from Extended Wilderness Trips

The experience of a strong sense of community developed while participating in extended wilderness expeditions is one of the most significant and meaningful experiences associated with taking part in this form of outdoor recreation. The experience of returning to a home community from an extended wilderness expedition is explored through the impacts associated with psychological sense of community (McMillian & Chavis, 1986; McMillian, 1996). A phenomenological approach was used to investigate the re-entry experiences of six individuals through the use of semi-structured interviews. Twelve main themes and seventeen subthemes emerged within the findings and illustrate a lack of preparation for the difficulties associated with re-entry, negative impacts associated with the experience of sense of community, and problems transferring aspects of a wilderness community into participant’s post-expedition lives.