Detectability of bovine TB using the tuberculin skin test does not vary significantly according to pathogen genotype within Northern Ireland

Strains of many infectious diseases differ in parameters that influence epidemic spread, for example virulence, transmissibility, detectability and host specificity. Knowledge of inter-strain variation can be exploited to improve management and decrease disease incidence. Bovine tuberculosis (bTB) is increasingly prevalent among farmed cattle in the UK, exerting a heavy economic burden on the farming industry and government. We aimed to determine whether strains of Mycobacterium bovis (the causative agent of bTB) identified and classified using genetic markers (spoligotyping and multi-locus VNTR analysis) varied in response to the tuberculin skin test; this being the primary method of bTB detection used in the UK. Inter-strain variation in detectability of M. bovis could have important implications for disease control. The skin test is based on a differential delayed type hypersensitivity (DTH) response to intradermal injections of purified protein derivative (PPD) from M. bovis (PPD-B) and Mycobacterium avium (PPD-A). We searched for an association between skin test response (PPD-B skin rise minus PPD-A skin rise) and M. bovis genotype at the disclosing test in culture-confirmed cases using a field dataset consisting of 21,000 isolates belonging to 63 genotypes of M. bovis from cattle in Northern Ireland. We found no substantial variation among genotypes (estimated responses clustered tightly around the mean) controlling for animal sex, breed and test effects. We also estimated the ratio of skin test detected to undetected cases (i.e. cases only detected at abattoir). The skin test detection ratio varied among abattoirs with some detecting a greater proportion of cases than others but this variation was unrelated to the community composition of genotypes within each abattoir catchment. These two lines of evidence indicate that M. bovis genotypes in Northern Ireland have similar detectability using the skin test.

Low-cost Process monitoring for polymer extrusion

Polymer extrusion is regarded as an energy-intensive production process, and the real-time monitoring of both energy consumption and melt quality has become necessary to meet new carbon regulations and survive in the highly competitive plastics market. The use of a power meter is a simple and easy way to monitor energy, but the cost can sometimes be high. On the other hand, viscosity is regarded as one of the key indicators of melt quality in the polymer extrusion process. Unfortunately, viscosity cannot be measured directly using current sensory technology. The employment of on-line, in-line or off-line rheometers is sometimes useful, but these instruments either involve signal delay or cause flow restrictions to the extrusion process, which is obviously not suitable for real-time monitoring and control in practice. In this paper, simple and accurate real-time energy monitoring methods are developed. This is achieved by looking inside the controller, and using control variables to calculate the power consumption. For viscosity monitoring, a ‘soft-sensor’ approach based on an RBF neural network model is developed. The model is obtained through a two-stage selection and differential evolution, enabling compact and accurate solutions for viscosity monitoring. The proposed monitoring methods were tested and validated on a Killion KTS-100 extruder, and the experimental results show high accuracy compared with traditional monitoring approaches.

Energy monitoring and quality control of a single screw extruder

Polymer extrusion, in which a polymer is melted and conveyed to a mould or die, forms the basis of most polymer processing techniques. Extruders frequently run at non-optimised conditions and can account for 15–20% of overall process energy losses. In times of increasing energy efficiency such losses are a major concern for the industry. Product quality, which depends on the homogeneity and stability of the melt flow which in turn depends on melt temperature and screw speed, is also an issue of concern of processors. Gear pumps can be used to improve the stability of the production line, but the cost is usually high. Likewise it is possible to introduce energy meters but they also add to the capital cost of the machine. Advanced control incorporating soft sensing capabilities offers opportunities to this industry to improve both quality and energy efficiency. Due to strong correlations between the critical variables, such as the melt temperature and melt pressure, traditional decentralized PID (Proportional–Integral–Derivative) control is incapable of handling such processes if stricter product specifications are imposed or the material is changed from one batch to another. In this paper, new real-time energy monitoring methods have been introduced without the need to install power meters or develop data-driven models. The effects of process settings on energy efficiency and melt quality are then studied based on developed monitoring methods. Process variables include barrel heating temperature, water cooling temperature, and screw speed. Finally, a fuzzy logic controller is developed for a single screw extruder to achieve high melt quality. The resultant performance of the developed controller has shown it to be a satisfactory alternative to the expensive gear pump. Energy efficiency of the extruder can further be achieved by optimising the temperature settings. Experimental results from open-loop control and fuzzy control on a Killion 25 mm single screw extruder are presented to confirm the efficacy of the proposed approach.

Genome-wide meta-analysis identifies 11 new loci for anthropometric traits and provides insights into genetic architecture

Approaches exploiting trait distribution extremes may be used to identify loci associated with common traits, but it is unknown whether these loci are generalizable to the broader population. In a genome-wide search for loci associated with the upper versus the lower 5th percentiles of body mass index, height and waist-to-hip ratio, as well as clinical classes of obesity, including up to 263,407 individuals of European ancestry, we identified 4 new loci (IGFBP4, H6PD, RSRC1 and PPP2R2A) influencing height detected in the distribution tails and 7 new loci (HNF4G, RPTOR, GNAT2, MRPS33P4, ADCY9, HS6ST3 and ZZZ3) for clinical classes of obesity. Further, we find a large overlap in genetic structure and the distribution of variants between traits based on extremes and the general population and little etiological heterogeneity between obesity subgroups.

Automated Methods for Aircraft Design Integrated with Manufacturing

Aircraft design is a complex, long and iterative process that requires the use of various specialties and optimization tools. However these tools and specialities do not include manufacturing, which is often considered later in the product development process leading to higher cost and time delays. This work focuses on the development of an automated design tool that accounts for manufacture during the design process focusing on early geometry definition which in turn informs assembly planning. To accomplish this task the design process needs to be open to any variation in structural configuration while maintaining the design intent. Redefining design intent as a map which links a set of requirements to a set of functions using a numerical approach enables the design process itself to be considered as a mathematical function. This definition enables the design process to utilise captured design knowledge and translate it into a set of mathematical equations that design the structure. This process is articulated in this paper using the structural design and definition for an aircraft fuselage section as an exemplar.

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.

Streptococcus bovis bacteraemia: an evaluation of the long-term effect on cardiac outcomes

Introduction: Streptococcus bovis can lead to bacteraemia, septicaemia, and ultimately endocarditis. The objective of this study was to evaluate the long-term implications of S. bovis endocarditis on cardiac morbidity and mortality. 

Methods: A retrospective cohort study was performed between January 2000 and March 2009 to assess all patients diagnosed with S. bovis bacteraemia from the Belfast Health and Social Care Trust. The primary end-point for cardiac investigations was the presence of endocarditis. Secondary end-points included referral for cardiac surgery and overall mortality. 

Results: Sixty-one positive S. bovis blood cultures from 43 patients were included. Following echocardiography, seven patients were diagnosed with infective endocarditis (16.3 % of total patients); four patients (9.3 %) had native valve involvement while three (7.0 %) had prosthetic valve infection. Five of these seven patients had more than one positive S. bovis culture (71.4 %). Three had significant valve dysfunction that warranted surgical repair/replacement, one of whom was unfit for surgery. There was a 100 % recurrence rate amongst the valve replacement patients (n = 2) and six patients with endocarditis had colorectal pathology. Patients with endocarditis had similar long-term survival as those with non-endocarditic bacteraemia (57.1 % alive vs. 50 % of non-endocarditis patients, p = 0.73). 

Conclusion: Streptococcus bovis endocarditis patients tended to have pre-existing valvular heart disease and those with prosthetic heart valves had higher surgical intervention and relapse rates. These patients experienced a higher rate of co-existing colorectal pathology but currently have reasonable long-term outcomes. This may suggest that they represent a patient population that merits consideration for an early surgical strategy to maximise long-term results, however, further evaluation is warranted. © 2013 The Japanese Association for Thoracic Surgery.

Influence of Boundary Conditions on the Low Velocity Impact Damage Carbon Fibre Reinforced Plastic Plates (ICTWS2014-0501)

No abstract available

Multiphysics Simulation of Thermal Plasma Produced by Lightning Strike on Aircraft Structures

A novel numerical technique is proposed to model thermal plasma of microseconds/milliseconds time-scale effect. Modelling thermal plasma due to lightning strike will allow the estimation of electric current density, plasma pressure, and heat flux at the surface of the aircraft structure. These input data can then be used for better estimation of the mechanical/thermal induced damage on the aircraft structures for better protection systems design. Thermal plasma generated during laser cutting, electric (laser) welding and other plasma processing techniques have been the focus of many researchers. Thermal plasma is a gaseous state that consists from a mixture of electrons, ions, and natural particles. Thermal plasma can be assumed to be in local thermodynamic equilibrium, which means the electrons and the heavy species have equal temperature. Different numerical techniques have been developed using a coupled Navier Stokes – Heat transfer – Electromagnetic equations based on the assumption that the thermal plasma is a single laminar gas flow. These previous efforts focused on generating thermal plasma of time-scale in the range of seconds. Lighting strike on aircraft structures generates thermal plasma of time-scale of milliseconds/microseconds, which makes the previous physics used not applicable. The difficulty comes from the Navier-Stokes equations as the fluid is simulated under shock load, this introducing significant changes in the density and temperature of the fluid.

Investigation of Aircraft Panel Deformations during Riveting Process

In collaboration with Airbus-UK, the dimensional growth of small panels while being riveted with stiffeners is investigated. The stiffeners have been fastened to the panels with rivets and it has been observed that during this operation the panels expand in the longitudinal and transverse directions. It has been observed that the growth is variable and the challenge is to control the riveting process to minimize this variability. In this investigation, the assembly of the small panels and longitudinal stiffeners has been simulated using low and high fidelity nonlinear finite element models. The models have been validated against a limited set of experimental measurements; it was found that more accurate predictions of the riveting process are achieved using high fidelity explicit finite element models. Furthermore, through a series of numerical simulations and probabilistic analyses, the manufacturing process control parameters that influence panel growth have been identified. Alternative fastening approaches were examined and it was found that dimensional growth can be controlled by changing the design of the dies used for forming the rivets.