Driven to distraction: Determining the effects of roadside advertising on driver attention

There is growing concern that roadside advertising presents a real risk to driving safety, with conservative estimates putting external distractors responsible for up to 10% of all accidents. In this report, we present a simulator study quantifying the effects of billboards on driver attention, mental workload and performance in Urban, Motorway and Rural environments. The results demonstrate that roadside advertising has a clear detrimental effect on lateral control, increases mental workload and eye fixations, and on some roads can draw attention away from more relevant road signage. Detailed analysis of the data suggests that the effects of billboards may in fact be more consequential in scenarios which are monotonous or of lower workload. Nevertheless, the overriding conclusion is that prudence should be exercised when authorising or placing roadside advertising. The findings are discussed with respect to governmental policy and guidelines.Final report of a study funded by The Rees Jeffreys Road Fun

Promoting green issues and sustainability in UK higher education libraries

Climate change affects us all. Individually and collectively, we must reduce our carbon footprint to protect the future of the planet. But how can higher education libraries contribute? In April of 2007, a request was made to SCONUL libraries – via LIS-SCONUL – for information on library green initiatives that they were taking forward. The responses highlighted that there is growing interest in the issue and that sustainability issues are beginning to be taken very seriously. This is partially driven by the greater awareness of the need to reduce carbon emissions throughout society. Specifically within higher education, it is also a result of encouragement by funding bodies, such as the Higher Education Funding Council for England (HEFCE) (see http://www.hefce. ac.uk/lgm/sustain/), through pressure from groups such as People and Planet and their ‘green league’ of higher education institutions (http:// peopleandplanet.org/gogreen/greenleague2007), and through rewards for excellence such as the Times Higher Education and Higher Education Academy Awards for an outstanding contribution by a higher education institution to sustainable development. Library staff are often active in wider institutional sustainability initiatives and can act as ‘champions’ for environmental issues and initiatives. Most of the libraries that responded to the request for information have aligned their green initiatives/ policies with those of their host organisation. Some libraries have participated in a wider institutional initiative to apply for the environmental management standard, ISO 14001. However, there are many specific ways that libraries can become more environmentally friendly and can make a difference

Probabilistic prediction of Alzheimer’s disease from multimodal image data with Gaussian processes

Alzheimer’s disease, the most common form of dementia, is an extremely serious health problem, and one that will become even more so in the coming decades as the global population ages. This has led to a massive effort to develop both new treatments for the condition and new methods of diagnosis; in fact the two are intimately linked as future treatments will depend on earlier diagnosis, which in turn requires the development of biomarkers that can be used to identify and track the disease. This is made possible by studies such as the Alzheimer’s disease neuroimaging initiative which provides previously unimaginable quantities of imaging and other data freely to researchers. It is the task of early diagnosis that this thesis focuses on. We do so by borrowing modern machine learning techniques, and applying them to image data. In particular, we use Gaussian processes (GPs), a previously neglected tool, and show they can be used in place of the more widely used support vector machine (SVM). As combinations of complementary biomarkers have been shown to be more useful than the biomarkers are individually, we go on to show GPs can also be applied to integrate different types of image and non-image data, and thanks to their properties this improves results further than it does with SVMs. In the final two chapters, we also look at different ways to formulate both the prediction of conversion to Alzheimer’s disease as a machine learning problem and the way image data can be used to generate features for input as a machine learning algorithm. Both of these show how unconventional approaches may improve results. The result is an advance in the state-of-the-art for a very clinically important problem, which may prove useful in practice and show a direction of future research to further increase the usefulness of such method

Characterization of the Temporomandibular Joint of Southern Sea Otters (Enhydra lutris nereis).

The structure-function relationship of the temporomandibular joint (TMJ) of southern sea otter has largely not been described. This study aims to describe the histological, biochemical, and biomechanical features of the TMJ disk in the southern sea otter. The TMJ disks from fresh cadaver heads of southern sea otter adult males (n = 8) and females (n = 8) acquired from strandings were examined. Following macroscopical evaluation, the TMJs were investigated for their histological, mechanical, and biochemical properties. We found that the sea otter TMJ disks are, in general, similar to other carnivores. Macroscopically, the TMJ disk was highly congruent, and the mandibular head was encased tightly by the mandibular fossa with a thin disk separating the joint into two compartments. Histologically, the articular surfaces were lined with dense fibrous connective tissue that gradually transitioned into one to two cell thick layer of hyaline-like cartilage. The disk fibers were aligned primarily in the rostrocaudal direction and had occasional lacuna with chondrocyte-like cells. The disk was composed primarily of collagen type 1. Biochemical analysis indicates sulfated glycosaminoglycan content lower than other mammals, but significantly higher in male sea otters than female sea otters. Finally, mechanical analysis demonstrated a disk that was not only stronger and stiffer in the rostrocaudal direction than the mediolateral direction but also significantly stronger and stiffer in females than males. We conclude that the congruent design of the TMJ, thin disk, biochemical content, and mechanical properties all reflect a structure-function relationship within the TMJ disk that is likely designed for the sea otter's hard diet and continuous food intake

Necrotizing meningoencephalitis in atypical dog breeds: a case series and literature review.

BackgroundCanine necrotizing meningoencephalitis (NME) is a fatal, noninfectious inflammatory disease of unknown etiology. NME has been reported only in a small number of dog breeds, which has led to the presumption that it is a breed-restricted disorder.Hypothesis/objectivesOur objective was to describe histopathologically confirmed NME in dog breeds in which the condition has not been reported previously and to provide preliminary evidence that NME affects a wider spectrum of dog breeds than previously reported.AnimalsFour dogs with NME.MethodsArchives from 3 institutions and from 1 author's (BS) collection were reviewed to identify histopathologically confirmed cases of NME in breeds in which the disease has not been reported previously. Age, sex, breed, survival from onset of clinical signs, and histopathologic findings were evaluated.ResultsNecrotizing meningoencephalitis was identified in 4 small dog breeds (Papillon, Shih Tzu, Coton de Tulear, and Brussels Griffon). Median age at clinical evaluation was 2.5 years. Histopathologic abnormalities included 2 or more of the following: lymphoplasmacytic or histiocytic meningoencephalitis or encephalitis, moderate-to-severe cerebrocortical necrosis, variable involvement of other anatomic locations within the brain (cerebellum, brainstem), and absence of detectable infectious agents.Conclusions and clinical importanceUntil now, NME has only been described in 5 small dog breeds. We document an additional 4 small breeds previously not shown to develop NME. Our cases further illustrate that NME is not a breed-restricted disorder and should be considered in the differential diagnosis for dogs with signalment and clinical signs consistent with inflammatory brain disease

Determination of the strange nucleon form factors

The strange contribution to the electric and magnetic form factors of the nucleon is determined at a range of discrete values of $Q^2$ up to $1.4$ GeV$^2$. This is done by combining recent lattice QCD results for the electromagnetic form factors of the octet baryons with experimental determinations of those quantities. The most precise result is a small negative value for the strange magnetic moment: $G_M^s(Q^2=0) = -0.07\pm0.03\,\mu_N$. At larger values of $Q^2$ both the electric and magnetic form factors are consistent with zero to within $2$-sigma

Charge Symmetry Violation in the Electromagnetic Form Factors of the Proton

Experimental tests of QCD through its predictions for the strange-quark content of the proton have been drastically restricted by our lack of knowledge of the violation of charge symmetry (CSV). We find unexpectedly tiny CSV in the proton's electromagnetic form factors by performing the first extraction of these quantities based on an analysis of lattice QCD data. The resulting values are an order of magnitude smaller than current bounds on proton strangeness from parity violating electron-proton scattering experiments. This result paves the way for a new generation of experimental measurements of the proton's strange form factors to challenge the predictions of QCD

A simulation system for biomarker evolution in neurodegenerative disease

We present a framework for simulating cross-sectional or longitudinal biomarker data sets from neurodegenerative disease cohorts that reflect the temporal evolution of the disease and population diversity. The simulation system provides a mechanism for evaluating the performance of data-driven models of disease progression, which bring together biomarker measurements from large cross-sectional (or short term longitudinal) cohorts to recover the average population-wide dynamics. We demonstrate the use of the simulation framework in two different ways. First, to evaluate the performance of the Event Based Model (EBM) for recovering biomarker abnormality orderings from cross-sectional datasets. Second, to evaluate the performance of a differential equation model (DEM) for recovering biomarker abnormality trajectories from short-term longitudinal datasets. Results highlight several important considerations when applying data-driven models to sporadic disease datasets as well as key areas for future work. The system reveals several important insights into the behaviour of each model. For example, the EBM is robust to noise on the underlying biomarker trajectory parameters, under-sampling of the underlying disease time course and outliers who follow alternative event sequences. However, the EBM is sensitive to accurate estimation of the distribution of normal and abnormal biomarker measurements. In contrast, we find that the DEM is sensitive to noise on the biomarker trajectory parameters, resulting in an over estimation of the time taken for biomarker trajectories to go from normal to abnormal. This over estimate is approximately twice as long as the actual transition time of the trajectory for the expected noise level in neurodegenerative disease datasets. This simulation framework is equally applicable to a range of other models and longitudinal analysis techniques