Updating predictive accident models of modern rural single carriageway A-roads

Reliable predictive accident models (PAMs) are essential to design and maintain safe road networks and yet the models most commonly used in the UK were derived using data collected 20 to 30 years ago. Given that the national personal injury accident total fell by some 30% in the last 25 years, while road traffic increased by over 60%, significant errors in scheme appraisal and evaluation based on the models currently in use seem inevitable. In this paper the temporal transferability of PAMs for modern rural single carriageway A-roads is investigated and their predictive performance is evaluated against a recent data set. Despite the age of these models, the PAMs for predicting the total accidents provide a remarkably good fit to recent data and these are more accurate than models where accidents are disaggregated by type. The performance of the models can be improved by calibrating them against recent data

Computers in Medicine

From a dissertation read before the Society on Friday, 4th November, 1966The subject of this dissertation is Computers in Medicine and even those who have had nothing to do with these machines will be unable to ignore them in the very near future. A brief account of how they work is given here, followed by the description of a few of their applications in Medicine. In fact, learning to programme the machine is very simple, and the University Computer unit runs a special course three times a year for this purpose. Many people think of the computer as something between a glorified adding machine and a sort of god that can do anything, whereas in fact the truth lies somewhere in between

The United Kingdom Ministry of Defence and the European Union's electrical and electronic equipment directives

The growth of the generation of Electrical and Electronic Equipment (EEE), and the use of hazardous substances in the production of these items, has required legislation to minimise the harm to the environment that their existing use, ultimate disposal and continued growth of the sector may pose. The European Union (EU) started to tackle this problem with the passing of two Directives in 2002, which focused on restricting the use of hazardous substances (RoHS - 2002/95/EC) and organising the recycling or disposal of discarded electronic and electrical equipment (WEEE - 2002/96/EC). These Directives have been recently recast and their scope widened; however, one exception to them remains items specifically designed for defence and military purposes. This paper looks at how and why these European Directives were passed, the impact they have had on defence in the United Kingdom (UK) up to the present moment, what impact the further extension of those directives might have on UK defence policy and how the UK Ministry of Defence (MOD) has begun to prepare for any extension, including the use of alternative products from the commercial market, and substituting less harmful materials. The paper reviews the information available to carry out future decision making and what level of decision making it can support. Where the data is insufficient, it makes recommendations on actions to take for improvement

KMOS LENsing Survey (KLENS) : morpho-kinematic analysis of star-forming galaxies at z∼2z \sim 2

We present results from the KMOS lensing survey-KLENS which is exploiting gravitational lensing to study the kinematics of 24 star forming galaxies at $1.4<z<3.5$ with a median mass of $\rm log(M_\star/M_\odot)=9.6$ and median star formation rate (SFR) of $\rm 7.5\,M_\odot\,yr^{-1}$. We find that 25% of these low-mass/low-SFR galaxies are rotation dominated, while the majority of our sample shows no velocity gradient. When combining our data with other surveys, we find that the fraction of rotation dominated galaxies increases with the stellar mass, and decreases for galaxies with a positive offset from the main sequence. We also investigate the evolution of the intrinsic velocity dispersion, $\sigma_0$, as a function of the redshift, $z$, and stellar mass, $\rm M_\star$, assuming galaxies in quasi-equilibrium (Toomre Q parameter equal to 1). From the $z-\sigma_0$ relation, we find that the redshift evolution of the velocity dispersion is mostly expected for massive galaxies ($\rm log(M_\star/M_\odot)>10$). We derive a $\rm M_\star-\sigma_0$ relation, using the Tully-Fisher relation, which highlights that a different evolution of the velocity dispersion is expected depending on the stellar mass, with lower velocity dispersions for lower masses, and an increase for higher masses, stronger at higher redshift. The observed velocity dispersions from this work and from comparison samples spanning $0<z<3.5$ appear to follow this relation, except at higher redshift ($z>2$), where we observe higher velocity dispersions for low masses ($\rm log(M_\star/M_\odot)\sim 9.6$) and lower velocity dispersions for high masses ($\rm log(M_\star/M_\odot)\sim 10.9$) than expected. This discrepancy could, for instance, suggest that galaxies at high-$z$ do not satisfy the stability criterion, or that the adopted parametrisation of the specific star formation rate and molecular properties fail at high redshift.Comment: Accepted for publication in A&A, 21 pages, 10 figure

Evaluating Global Aerosol Models and Aerosol and Water Vapor Properties Near Clouds

The 'Evaluating Global Aerosol Models and Aerosol and Water Vapor Properties Near Clouds' project focused extensively on the analysis and utilization of water vapor and aerosol profiles derived from the ARM Raman lidar at the Southern Great Plains ARM site. A wide range of different tasks were performed during this project, all of which improved quality of the data products derived from the lidar or advanced the understanding of atmospheric processes over the site. These activities included: upgrading the Raman lidar to improve its sensitivity; participating in field experiments to validate the lidar aerosol and water vapor retrievals; using the lidar aerosol profiles to evaluate the accuracy of the vertical distribution of aerosols in global aerosol model simulations; examining the correlation between relative humidity and aerosol extinction, and how these change, due to horizontal distance away from cumulus clouds; inferring boundary layer turbulence structure in convective boundary layers from the high-time-resolution lidar water vapor measurements; retrieving cumulus entrainment rates in boundary layer cumulus clouds; and participating in a field experiment that provided data to help validate both the entrainment rate retrievals and the turbulent profiles derived from lidar observations

Training Deep Gaussian Processes using Stochastic Expectation Propagation and Probabilistic Backpropagation

Deep Gaussian processes (DGPs) are multi-layer hierarchical generalisations of Gaussian processes (GPs) and are formally equivalent to neural networks with multiple, infinitely wide hidden layers. DGPs are probabilistic and non-parametric and as such are arguably more flexible, have a greater capacity to generalise, and provide better calibrated uncertainty estimates than alternative deep models. The focus of this paper is scalable approximate Bayesian learning of these networks. The paper develops a novel and efficient extension of probabilistic backpropagation, a state-of-the-art method for training Bayesian neural networks, that can be used to train DGPs. The new method leverages a recently proposed method for scaling Expectation Propagation, called stochastic Expectation Propagation. The method is able to automatically discover useful input warping, expansion or compression, and it is therefore is a flexible form of Bayesian kernel design. We demonstrate the success of the new method for supervised learning on several real-world datasets, showing that it typically outperforms GP regression and is never much worse

WASP-120b, WASP-122b and WASP-123b: Three newly discovered planets from the WASP-South survey

We present the discovery by the WASP-South survey of three planets transiting moderately bright stars (V ~ 11). WASP-120b is a massive (5.0MJup) planet in a 3.6-day orbit that we find likely to be eccentric (e = 0.059+0.025-0.018) around an F5 star. WASP-122b is a hot-Jupiter (1.37MJup, 1.79RJup) in a 1.7-day orbit about a G4 star. Our predicted transit depth variation cause by the atmosphere of WASP-122b suggests it is well suited to characterisation. WASP-123b is a hot-Jupiter (0.92MJup, 1.33RJup) in a 3.0-day orbit around an old (~ 7 Gyr) G5 star.Comment: 15 pages, 10 figures, 5 table

Comparison of Observed and Simulated Grow-Finish Swine Performance Under Summer Conditions

As a part of a National Pork Producers Council educational program, our research and extension team at the University of Kentucky was linked with an independent commercial swine producer to test the NCPIG model against observed commercial on-farm data. This experience provided improved information for model development as well as increased producer insight into the data input needs and potential benefits of modeling. Detailed production information comparisons between the NCPIG model and producer data are presented for summer time conditions to assess the validity of the NCPIG model for simulation of grow-finish swine performance. Results demonstrated that the NCPIG model accurately simulated performance

Absolute parameters for AI Phoenicis using WASP photometry

Context. AI Phe is a double-lined, detached eclipsing binary, in which a K-type sub-giant star totally eclipses its main-sequence companion every 24.6 days. This configuration makes AI Phe ideal for testing stellar evolutionary models. Difficulties in obtaining a complete lightcurve mean the precision of existing radii measurements could be improved. Aims. Our aim is to improve the precision of the radius measurements for the stars in AI Phe using high-precision photometry from the Wide Angle Search for Planets (WASP), and use these improved radius measurements together with estimates of the masses, temperatures and composition of the stars to place constraints on the mixing length, helium abundance and age of the system. Methods. A best-fit EBOP model is used to obtain lightcurve parameters, with their standard errors calculated using a prayer-bead algorithm. These were combined with previously published spectroscopic orbit results, to obtain masses and radii. A Bayesian method is used to estimate the age of the system for model grids with different mixing lengths and helium abundances. Results. The radii are found to be R1 = 1.835 ± 0.014 RO, R2 = 2.912 ± 0.014 RO and the masses M1 = 1.1973 ± 0.0037 Mo, M2 = 1.2473 ± 0.0039 MO. From the best-fit stellar models we infer a mixing length of 1.78, a helium abundance of YAI = 0.26+0.02−0.01 and an age of 4.39 ± 0.32 Gyr. Times of primary minimum show the period of AI Phe is not constant. Currently, there are insufficient data to determine the cause of this variation. Conclusions. Improved precision in the masses and radii have improved the age estimate, and allowed the mixing length and helium abundance to be constrained. The eccentricity is now the largest source of uncertainty in calculating the masses. Further work is needed to characterise the orbit of AI Phe. Obtaining more binaries with parameters measured to a similar level of precision would allow us to test for relationships between helium abundance and mixing length