Quantitative LEED I-V and ab initio study of the Si(111)-3x2-Sm surface structure and the missing half order spots in the 3x1 diffraction pattern

We have used Low Energy Electron Diffraction (LEED) I-V analysis and ab initio calculations to quantitatively determine the honeycomb chain model structure for the Si(111)-3x2-Sm surface. This structure and a similar 3x1 recontruction have been observed for many Alkali-Earth and Rare-Earth metals on the Si(111) surface. Our ab initio calculations show that there are two almost degenerate sites for the Sm atom in the unit cell and the LEED I-V analysis reveals that an admixture of the two in a ratio that slightly favours the site with the lower energy is the best match to experiment. We show that the I-V curves are insensitive to the presence of the Sm atom and that this results in a very low intensity for the half order spots which might explain the appearance of a 3x1 LEED pattern produced by all of the structures with a 3x2 unit cell.Comment: 10 pages, 13 figures. Preliminary work presented at the the APS March meeting, Baltimore MD, 2006. To be published in Phys. Rev. B. April/May 200

Structurally Embedded Electrical Systems Using Ultrasonic Consolidation (UC)

Current research has demonstrated the use of Ultrasonic Consolidation (UC) to embed several USB-based sensors into aluminum, and is working toward embedding suites of sensors, heaters and other devices, connected via USB hubs, which can be monitored and controlled using an embedded USB capable processor. Additionally, the research has shown that electronics can be embedded at room temperature, but with some inter-layer delamination between the ultrasonically bonded aluminum layers. Embedding sensors and electronics at 300o F to overcome the delamination issues resulted in optimal bonding, and the sensors used thus far have functioned normally. Future investigation will explore other UC parameter combinations to ascertain the quality of embedding at lower temperatures.Mechanical Engineerin

A motif-based approach to network epidemics

Networks have become an indispensable tool in modelling infectious diseases, with the structure of epidemiologically relevant contacts known to affect both the dynamics of the infection process and the efficacy of intervention strategies. One of the key reasons for this is the presence of clustering in contact networks, which is typically analysed in terms of prevalence of triangles in the network. We present a more general approach, based on the prevalence of different four-motifs, in the context of ODE approximations to network dynamics. This is shown to outperform existing models for a range of small world networks

STM and ab initio study of holmium nanowires on a Ge(111) Surface

A nanorod structure has been observed on the Ho/Ge(111) surface using scanning tunneling microscopy (STM). The rods do not require patterning of the surface or defects such as step edges in order to grow as is the case for nanorods on Si(111). At low holmium coverage the nanorods exist as isolated nanostructures while at high coverage they form a periodic 5x1 structure. We propose a structural model for the 5x1 unit cell and show using an ab initio calculation that the STM profile of our model structure compares favorably to that obtained experimentally for both filled and empty states sampling. The calculated local density of states shows that the nanorod is metallic in character.Comment: 4 pages, 12 figures (inc. subfigures). Presented at the the APS March meeting, Baltimore MD, 200

The impact of contact tracing in clustered populations

The tracing of potentially infectious contacts has become an important part of the control strategy for many infectious diseases, from early cases of novel infections to endemic sexually transmitted infections. Here, we make use of mathematical models to consider the case of partner notification for sexually transmitted infection, however these models are sufficiently simple to allow more general conclusions to be drawn. We show that, when contact network structure is considered in addition to contact tracing, standard “mass action” models are generally inadequate. To consider the impact of mutual contacts (specifically clustering) we develop an improvement to existing pairwise network models, which we use to demonstrate that ceteris paribus, clustering improves the efficacy of contact tracing for a large region of parameter space. This result is sometimes reversed, however, for the case of highly effective contact tracing. We also develop stochastic simulations for comparison, using simple re-wiring methods that allow the generation of appropriate comparator networks. In this way we contribute to the general theory of network-based interventions against infectious disease

Retrofit 2050:Critical challenges for urban transitions

Scaling up retrofit presents a number of critical challenges for the transition to urban sustainability. Drawing together insights from the EPSRC Retrofit 2050 project this briefing sets out key success factors that need to be in place to deliver sustainable futures for UK cities

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

Dynamics of multi-stage infections on networks

This paper investigates the dynamics of infectious diseases with a nonexponentially distributed infectious period. This is achieved by considering a multistage infection model on networks. Using pairwise approximation with a standard closure, a number of important characteristics of disease dynamics are derived analytically, including the final size of an epidemic and a threshold for epidemic outbreaks, and it is shown how these quantities depend on disease characteristics, as well as the number of disease stages. Stochastic simulations of dynamics on networks are performed and compared to output of pairwise models for several realistic examples of infectious diseases to illustrate the role played by the number of stages in the disease dynamics. These results show that a higher number of disease stages results in faster epidemic outbreaks with a higher peak prevalence and a larger final size of the epidemic. The agreement between the pairwise and simulation models is excellent in the cases we consider

A review of current and future weather data for building simulation

PublishedThis is the author accepted manuscript. The final version is available from SAGE Publications via the DOI in this record.This article provides the first comprehensive assessment of methods for the creation of weather variables for use in building simulation. We undertake a critical analysis of the fundamental issues and limitations of each methodology and discusses new challenges, such as how to deal with uncertainty, the urban heat island, climate change and extreme events. Proposals for the next generation of weather files for building simulation are made based on this analysis. A seven-point list of requirements for weather files is introduced and the state-of-the-art compared to this via a mapping exercise. It is found that there are various issues with all current and suggested approaches, but the two areas most requiring attention are the production of weather files for the urban landscape and files specifically designed to test buildings against the criteria of morbidity, mortality and building services system failure. Practical application: Robust weather files are key to the design of sustainable, healthy and comfortable buildings. This article provides the first comprehensive assessment of their technical requirements to ensure buildings perform well in both current and future climates.The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This research has been performed in the project COLBE (The Creation of Localized Current and Future Weather for the Built Environment) funded by the EPSRC (EP/M021890/1, EP/M022099/1)

A pattern matching technique for measuring sediment displacement levels

This paper describes a novel technique for obtaining accurate, high (spatial) resolution measurements of sediment redeposition levels. A sequence of different random patterns are projected onto a sediment layer and captured using a high-resolution camera, producing a set of reference images. The same patterns are used to obtain a corresponding sequence of deformed images after a region of the sediment layer has been displaced and redeposited, allowing the use of a high-accuracy pattern matching algorithm to quantify the distribution of the redeposited sediment. A set of experiments using the impact of a vortex ring with a glass ballotini particle layer as the resuspension mechanism are described to test and illustrate the technique. The accuracy of the procedure is assessed using a known crater profile, manufactured to simulate the features of the craters observed in the experiments