Peptide length significantly influences in vitro affinity for MHC class II molecules

Class II Major Histocompatibility Complex (MHC) molecules have an open-ended binding groove which can accommodate peptides of varying lengths. Several studies have demonstrated that peptide flanking residues (PFRs) which lie outside the core binding groove can influence peptide binding and T cell recognition. By using data from the AntiJen database we were able to characterise systematically the influence of PFRs on peptide affinity for MHC class II molecules

Modelling Extreme Traffic Loading on Bridges Using Kernal Density Estimators

Innovations on Bridges and Soil-Bridge Interaction (IBSBI 2011), Athens, Greece, October 13-15, 2011Kernel density estimators are a non-parametric method of estimating the probability density function of sample data. In this paper, the method is applied to find characteristic maximum daily truck weights on highway bridges. The results are then compared with the conventional approach.Deposited by bulk impor

The use of micro-simulation for congested traffic load modelling of medium- and long-span bridges

This paper presents a new approach to the modelling of congested traffic loading events on long span bridges. Conventional traffic load models are based on weigh-in-motion data of non-congested traffic, or something similar to a Poisson Arrival process. In neither case do they account for the mixing between lanes that takes place as traffic becomes congested. It is shown here that cars move out from between trucks as traffic slows down which results in a higher frequency of long platoons of trucks in the slow lane of the bridge. These longer platoons increase some characteristic load effects under the slow lane by a modest but significant amount. Micro-simulation, the process of modelling individual vehicles that is widely used in traffic modelling, is presented here as a means of predicting imposed traffic loading on long-span bridges more accurately. The traffic flow on a congested bridge is modelled using a random mixing process for trucks and cars in each lane, where each vehicle is modelled individually with driver behaviour parameters assigned randomly in a Monte Carlo process. Over a number of simulated kilometres, the vehicles move between lanes in simulated lane-changing manoeuvres. The algorithm was calibrated against video recordings of traffic on a bridge in the Netherlands. Extreme value statistics of measured strains on the bridge are then compared to the corresponding simulation statistics to validate the model. The micro-simulation algorithm shows that the histograms of truck platoon length are moderately affected by lane changing. This in turn is shown to influence some characteristic load effects of the bridge deck.Higher Education AuthorityCan't locate article. 12M embargo from date of publication. On publication, add citation to set text in Rights field - AV 2/08/2011 Citation added - OR 10/1/201

Application of statistical process control to qualitative molecular diagnostic assays.

Modern pathology laboratories and in particular high throughput laboratories such as clinical chemistry have developed a reliable system for statistical process control. Such a system is absent from the majority of molecular laboratories and where present is confined to quantitative assays. As the inability to apply statistical process control to assay is an obvious disadvantage this study aimed to solve this problem by using a frequency estimate coupled with a confidence interval calculation to detect deviations from an expected mutation frequency. The results of this study demonstrate the strengths and weaknesses of this approach and highlight minimum sample number requirements. Notably, assays with low mutation frequencies and detection of small deviations from an expected value require greater samples with a resultant protracted time to detection. Modelled laboratory data was also used to highlight how this approach might be applied in a routine molecular laboratory. This article is the first to describe the application of statistical process control to qualitative laboratory data

A quantitative risk assessment of E.coli 0157:H7 in Irish minced beef

End of Project ReportA national quantitative risk assessment was undertaken for minced beef in the Republic of Ireland. The objective was to estimate the probability of E. coli O157:H7 infection from consumption of Irish beef and to investigate the parts of the beef chain contributing most to the risk posed by this pathogen.The quantitative risk assessment was broken into 3 main modules: 1) production of boxed beef trimmings; 2) processing of trimmings and burger formation and 3) retail/domestic consumption phase. Key points in each module (beef hide, beef trimmings and beef products at retail) were validated using data derived from microbiology sampling at beef abattoirs, supermarkets and butchers’ shops in Ireland

Traffic Load Effect Forecasting for Bridges

IABSE Conference on Structural Engineering: Providing Solutions to Global Challenges, Geneva, Switzerland, 23-25 September 2015Traffic flows, as well as truck weights, increase with time. This must be taken into account in order to accurately assess traffic loading on bridges. The Eurocode Load Model 1 is used for the design of new bridges but a scaled down version of the model can be used for the assessment of existing bridges. This scaling is usually done by applying α–factors to the load model. The effect of traffic growth on these α–factors is assessed in this paper. Weigh-in-motion data from the Netherlands is used as the basis for traffic models which simulate year-on-year growth of both traffic flow and truck weights. A time-varying generalised extreme value distribution is then used to calculate the characteristic load effects and determine the α–factors. The effect of different traffic growth rates on these α–factors is then examined. It is found that an increase in truck weights has the most influence on the α–factors but that increased flow also has a significant effect.National road administrations of Denmark, Germany, Ireland, Netherlands, UK and Sloveni

Determination of Vertical Alignment of Track using Accelerometer Readings

IMechE Stephenson Conference for Railways: Research for Railways, 21 - 23 April, 2015Railway track vertical alignment is an important indicator of serviceability condition. Through comparisons with past history, track alignment also informs maintenance planning. The vertical alignment of a railway track excites a dynamic response in a train which can potentially be used to determine that alignment. A method is proposed in this paper for the detection of the alignment through an analysis of vehicle accelerations resulting from the train/track dynamic interaction. The Cross Entropy optimisation technique is applied to determine the railway track profile heights that best fit the measured accelerations at and above a railway carriage bogie. Such an approach, using relatively low-cost accelerometers fixed to trains in regular service, would provide inexpensive daily 'drive-by' track monitoring to complement and compare data collected by the Track Recording Vehicle (TRV). The use of a TRV is the current preferred method used to determine railway track profiles using laser based methods. Numerical validation of the concept is achieved by using a 2-dimensional quarter-car dynamic model for the railway carriage and bogie to infer the track profiles in the longitudinal direction. The interaction model is implemented in MATLAB. The track is modelled as an infinitely stiff beam featuring various grades of rail irregularity which excite the vehicle inducing a dynamic response. Ten vertical elevations are found at a time which give a least squares fit of theoretical to measured accelerations. In each time step, half of these elevations are retained and a new optimisation is used to determine the next ten elevations along the length of the track. The optimised displacements are collated to determine the overall rail track profile over a finite length of railway track. This paper reports the results of the numerical simulations and the plans that are underway to further develop the model and test the concept in field trials.European Commission - Seventh Framework Programme (FP7

A Bayesian approach for estimating characteristic bridge traffic load effects

Civil Engineering Research in Ireland, Belfast, UK, 28 -29 August, 2014This paper investigates the use of Bayesian updating to improve estimates of characteristic bridge traffic loading. Over recent years the use Weigh-In-Motion technologies has increased hugely. Large Weigh-In-Motion databases are now available for multiple sites on many road networks. The objective of this work is to use data gathered throughout a road network to improve site-specific estimates of bridge loading at a specific Weigh-In-Motion site on the network. Bayesian updating is a mathematical framework for combining prior knowledge with new sample data. The approach is applied here to bridge loading using a database of 81.6 million truck records, gathered at 19 sites in the US. The database represents the prior knowledge of loading throughout the road network and a new site on the network is simulated. The Bayesian approach is compared with a non-Bayesian approach, which uses only the site-specific data, and the results compared. It is found that the Bayesian approach significantly improves the accuracy of estimates of 75-year loading and, in particular, considerably reduces the standard deviation of the error. With the proposed approach less site-specific WIM data is required to obtain an accurate estimate of loading. This is particularly useful where there is concern over an existing bridge and accurate estimates of loading are required as a matter of urgency.National Roads Authority, Irelan

The Effect of Traffic Growth on Characteristic Bridge Load Effects

The 6th European Transport Research Conference. Moving Forward: Innovative Solutions for Tomorrow's Mobility, Warsaw, Poland, 18-21 April 2016Freight traffic in the European Union is increasing with time. This paper describes a method for considering this growth when assessing traffic loading on bridges and examines the effect of this growth on characteristic load effects. The Eurocode Load Model 1 is used for the design of new bridges. As this model can be overly conservative for the assessment of existing bridges, a scaled down version can be used by applying a–factors to the load model. This is usually done by modelling the traffic loading on the bridge using site-specific weigh-in-motion data and calculating the a–factors in accordance with the results. In this paper, weigh-in-motion data from a site in the Netherlands is used to demonstrate the proposed approach. 40-year simulations of traffic loading are performed on various bridges. The simulations consider year-on-year growth in both the volume and weight of trucks. Time-varying generalized extreme value distributions are then fitted to the simulated data and used to calculate the characteristic load effects. The results are then compared with the load effects generated by Load Model 1 in order to calculate the associated factors. It is found that an increase in truck weights has the most significant influence on the factors but that increased flow also has a significant effect.National road administrations of Denmark, Germany, Ireland, Netherlands, UK and Sloveni

Considering Traffic Growth in Characteristic Bridge Load Effect Calculations

8th International Conference on Bridge Maintenance, Safety & Management, IABMAS2016, Foz do Iguacu, Brazil, 26-30 June 2016Traffic volumes and weights increase with time. This is an important consideration in order toaccurately calculate characteristic load effects for the design and assessment of bridges. A modeling approach is presented which can allow for future growth of truck weights and volumes when assessing truck loading on bridges. Weigh-in-motion data from a site in the Netherlands is used as an example to demonstrate traffic growth at that site. In assessing the effect of growth on characteristic load effects, different growth rates for both truck volumes and truck weights are considered. It is found that growth of truck weights has considerablymore influence although growth in truck volumes also has a significant effect.National road administrations of Denmark, Germany, Ireland, Netherlands, UK and Sloveni