Arrival direction distribution of cosmic rays of energy 10 (18) eV

The Haverah Park air-shower experiment recorded over 8500 events with primary energy 10 to the 18th power eV between 1963 and 1983. An analysis of these events for anisotropies in celestial and galactic coordinates is reported. No very striking anisotropies are observed

The primary cosmic ray spectrum above 10 to the 19th power eV

Progress on a re-evaluation of the spectrum of cosmic rays determined with the Haverah Park shower array is described. Particular attention is paid to the reality of some giant showers

Modelling the impact of local reactive school closures on critical care provision during an influenza pandemic

Despite the fact that the 2009 H1N1 pandemic influenza strain was less severe than had been feared, both seasonal epidemics of influenza-like-illness and future influenza pandemics have the potential to place a serious burden on health services. The closure of schools has been postulated as a means of reducing transmission between children and hence reducing the number of cases at the peak of an epidemic; this is supported by the marked reduction in cases during school holidays observed across the world during the 2009 pandemic. However, a national policy of long-duration school closures could have severe economic costs. Reactive short-duration closure of schools in regions where health services are close to capacity offers a potential compromise, but it is unclear over what spatial scale and time frame closures would need to be made to be effective. Here, using detailed geographical information for England, we assess how localized school closures could alleviate the burden on hospital intensive care units (ICUs) that are reaching capacity. We show that, for a range of epidemiologically plausible assumptions, considerable local coordination of school closures is needed to achieve a substantial reduction in the number of hospitals where capacity is exceeded at the peak of the epidemic. The heterogeneity in demand per hospital ICU bed means that even widespread school closures are unlikely to have an impact on whether demand will exceed capacity for many hospitals. These results support the UK decision not to use localized school closures as a control mechanism, but have far wider international public-health implications. The spatial heterogeneities in both population density and hospital capacity that give rise to our results exist in many developed countries, while our model assumptions are sufficiently general to cover a wide range of pathogens. This leads us to believe that when a pandemic has severe implications for ICU capacity, only widespread school closures (with their associated costs and organizational challenges) are sufficient to mitigate the burden on the worst-affected hospitals

A proposed methodology for deriving tsunami fragility functions for buildings using optimum intensity measures

Tsunami fragility curves are statistical models which form a key component of tsunami risk models, as they provide a probabilistic link between a tsunami intensity measure (TIM) and building damage. Existing studies apply different TIMs (e.g. depth, velocity, force etc.) with conflicting recommendations of which to use. This paper presents a rigorous methodology using advanced statistical methods for the selection of the optimal TIM for fragility function derivation for any given dataset. This methodology is demonstrated using a unique, detailed, disaggregated damage dataset from the 2011 Great East Japan earthquake and tsunami (total 67,125 buildings), identifying the optimum TIM for describing observed damage for the case study locations. This paper first presents the proposed methodology, which is broken into three steps: (1) exploratory analysis, (2) statistical model selection and trend analysis and (3) comparison and selection of TIMs. The case study dataset is then presented, and the methodology is then applied to this dataset. In Step 1, exploratory analysis on the case study dataset suggests that fragility curves should be constructed for the sub-categories of engineered (RC and steel) and non-engineered (wood and masonry) construction materials. It is shown that the exclusion of buildings of unknown construction material (common practice in existing studies) may introduce bias in the results; hence, these buildings are estimated as engineered or non-engineered through use of multiple imputation (MI) techniques. In Step 2, a sensitivity analysis of several statistical methods for fragility curve derivation is conducted in order to select multiple statistical models with which to conduct further exploratory analysis and the TIM comparison (to draw conclusions which are non-model-specific). Methods of data aggregation and ordinary least squares parameter estimation (both used in existing studies) are rejected as they are quantitatively shown to reduce fragility curve accuracy and increase uncertainty. Partially ordered probit models and generalised additive models (GAMs) are selected for the TIM comparison of Step 3. In Step 3, fragility curves are then constructed for a number of TIMs, obtained from numerical simulation of the tsunami inundation of the 2011 GEJE. These fragility curves are compared using K-fold cross-validation (KFCV), and it is found that for the case study dataset a force-based measure that considers different flow regimes (indicated by Froude number) proves the most efficient TIM. It is recommended that the methodology proposed in this paper be applied for defining future fragility functions based on optimum TIMs. With the introduction of several concepts novel to the field of fragility assessment (MI, GAMs, KFCV for model optimisation and comparison), this study has significant implications for the future generation of empirical and analytical fragility functions

Effects of Contact Network Models on Stochastic Epidemic Simulations

The importance of modeling the spread of epidemics through a population has led to the development of mathematical models for infectious disease propagation. A number of empirical studies have collected and analyzed data on contacts between individuals using a variety of sensors. Typically one uses such data to fit a probabilistic model of network contacts over which a disease may propagate. In this paper, we investigate the effects of different contact network models with varying levels of complexity on the outcomes of simulated epidemics using a stochastic Susceptible-Infectious-Recovered (SIR) model. We evaluate these network models on six datasets of contacts between people in a variety of settings. Our results demonstrate that the choice of network model can have a significant effect on how closely the outcomes of an epidemic simulation on a simulated network match the outcomes on the actual network constructed from the sensor data. In particular, preserving degrees of nodes appears to be much more important than preserving cluster structure for accurate epidemic simulations.Comment: To appear at International Conference on Social Informatics (SocInfo) 201

School's Out: Seasonal Variation in the Movement Patterns of School Children.

School children are core groups in the transmission of many common infectious diseases, and are likely to play a key role in the spatial dispersal of disease across multiple scales. However, there is currently little detailed information about the spatial movements of this epidemiologically important age group. To address this knowledge gap, we collaborated with eight secondary schools to conduct a survey of movement patterns of school pupils in primary and secondary schools in the United Kingdom. We found evidence of a significant change in behaviour between term time and holidays, with term time weekdays characterised by predominately local movements, and holidays seeing much broader variation in travel patterns. Studies that use mathematical models to examine epidemic transmission and control often use adult commuting data as a proxy for population movements. We show that while these data share some features with the movement patterns reported by school children, there are some crucial differences between the movements of children and adult commuters during both term-time and holidays.AJK was supported by the Medical Research Council (fellowship MR/K021524/1, http://www.mrc.ac.uk/) and the RAPIDD program of the Science & Technology Directorate, Department of Homeland Security, and the Fogarty International Center, National Institutes of Health (http://www.fic.nih.gov/about/staff/pages​/epidemiology-population.aspx#rapidd). AJKC was supported by the Alborada Trust (http://www.alboradatrust.com/). KTDE was supported by the NIHR (CDF-2011-04- 019, http://www.nihr.ac.uk/). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.This is the final version. It was first published by PLOS at http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0128070#

Chemical biology in the embryo: In situ imaging of sulfur biochemistry in normal and proteoglycan-deficient cartilage matrix

© 2016 American Chemical Society. Proteoglycans (PGs) are heavily glycosylated proteins that play major structural and biological roles in many tissues. Proteoglycans are abundant in cartilage extracellular matrix; their loss is a main feature of the joint disease osteoarthritis. Proteoglycan function is regulated by sulfation-sulfate ester formation with specific sugar residues. Visualization of sulfation within cartilage matrix would yield vital insights into its biological roles. We present synchrotron-based X-ray fluorescence imaging of developing zebrafish cartilage, providing the first in situ maps of sulfate ester distribution. Levels of both sulfur and sulfate esters decrease as cartilage develops through late phase differentiation (maturation or hypertrophy), suggesting a functional link between cartilage matrix sulfur content and chondrocyte differentiation. Genetic experiments confirm that sulfate ester levels were due to cartilage proteoglycans and support the hypothesis that sulfate ester levels regulate chondrocyte differentiation. Surprisingly, in the PG synthesis mutant, the total level of sulfur was not significantly reduced, suggesting sulfur is distributed in an alternative chemical form during lowered cartilage proteoglycan production. Fourier transform infrared imaging indicated increased levels of protein in the mutant fish, suggesting that this alternative sulfur form might be ascribed to an increased level of protein synthesis in the mutant fish, as part of a compensatory mechanism

A revised morphing algorithm for creating future weather for building performance evaluation

This is the final version. Available from SAGE Publications via the DOI in this record. Climate change is one of the greatest challenges the building industry faces. Engineers and architects require representative future weather data if they would like to see how their buildings and designs will fare under a changing climate. The most common method used to create future weather involves manipulating observations commonly known as morphing, but the most used algorithms can create implausible weather conditions due to their unbounded nature. Here, bounded morphing algorithms will be described and their effectiveness proved mathematically. The improved bounded method applies two additional conditions on the morphed distribution to the maximum and minimum values, in addition to the mean values. The benefits over the standard approach will also be illustrated considering the changes in the distribution of temperature and solar irradiation due to climate change. The improved algorithms outperform the standard morphing procedures in terms of preserving the underlying climate signal while not creating unrealistic or implausible weather conditions. This method should give engineers confidence that the generated future weather series are more robust and representative of potential future weather. Practical application: The use of future weather to inform building design is now commonplace within the industry. Reliable weather files are crucial to support and deliver strategies for decarbonisation and adaptation to climate change in the built environment and the wider industry. This article provides support for the use of revised morphing algorithms which result in improved future weather time series which can be used in building simulation. For example, when applied to the temperature, it can be used to produce more accurate representations of future temperature profiles due to climate change, and for building performance assessment, such as energy consumption and overheating. It plays an important role in producing reliable and realistic weather data for future-proof building design.CIBSE, Innovate U

Web-based participatory surveillance of infectious diseases: the Influenzanet participatory surveillance experience.

To overcome the limitations of the state-of-the-art influenza surveillance systems in Europe, we established in 2008 a European-wide consortium aimed at introducing an innovative information and communication technology approach for a web-based surveillance system across different European countries, called Influenzanet. The system, based on earlier efforts in The Netherlands and Portugal, works with the participation of the population in each country to collect real-time information on the distribution of influenza-like illness cases through web surveys administered to volunteers reporting their symptoms (or lack of symptoms) every week during the influenza season. Such a large European-wide web-based monitoring infrastructure is intended to rapidly identify public health emergencies, contribute to understanding global trends, inform data-driven forecast models to assess the impact on the population, optimize the allocation of resources, and help in devising mitigation and containment measures. In this article, we describe the scientific and technological issues faced during the development and deployment of a flexible and readily deployable web tool capable of coping with the requirements of different countries for data collection, during either a public health emergency or an ordinary influenza season. Even though the system is based on previous successful experience, the implementation in each new country represented a separate scientific challenge. Only after more than 5 years of development are the existing platforms based on a plug-and-play tool that can be promptly deployed in any country wishing to be part of the Influenzanet network, now composed of The Netherlands, Belgium, Portugal, Italy, the UK, France, Sweden, Spain, Ireland, and Denmark