The physical and mechanical properties of oxide films

Imperial Users onl

Early Decision Indicators for Foot-and-Mouth Disease Outbreaks in Non-Endemic Countries

Disease managers face many challenges when deciding on the most effective control strategy to manage an outbreak of foot and mouth disease (FMD). Decisions have to be made under conditions of uncertainty and where the situation is continually evolving. In addition, resources for control are often limited. A modelling study was carried out to identify characteristics measurable during the early phase of a FMD outbreak that might be useful as predictors of the total number of infected places, outbreak duration and the total area under control. The study involved two modelling platforms in two countries (Australia and New Zealand) and encompassed a large number of incursion scenarios. Linear regression, classification and regression tree and boosted regression tree analyses were used to quantify the predictive value of a set of parameters on three outcome variables of interest: the total number of infected places, outbreak duration and the total area under control. The number of infected premises, number of pending culls, area under control, estimated dissemination ratio, and cattle density around the index herd at days 7, 14 and 21 following first detection were associated with each of the outcome variables. Regression models for the size of the area under control had the highest predictive value (R2 = 0.51-0.9) followed by the number of infected premises (R2 = 0.3-0.75) and outbreak duration (R2 = 0.28-0.57). Predictability improved at later time points in the outbreak. Predictive regression models using various cut-points at day 14 to define small and large outbreaks had positive predictive values of 0.85‒0.98 and negative predictive values of 0.52‒0.91, with 79‒97% of outbreaks correctly classified. On the strict assumption that each of the simulation models used in this study provide a realistic indication of the spread of FMD in animal populations our conclusion is that relatively simple metrics available early in a control program can be used to indicate the likely magnitude of an FMD outbreak under Australian and New Zealand conditions

Characterization of Zirconium Oxides Part I: Raman Mapping and Spectral Feature Analysis

Raman mapping of sectioned zirconium cladding oxides was performed to analyze different spectral features before and after breakaway, as well as between zirconium and its alloys Zr-2.65Nb, Zry-3, and Zry-4. Oxide phase composition, or percent tetragonality, was defined to compare tetragonal to monoclinic zirconia. Percent tetragonality was spatially mapped to support distinction of zirconia phase distribution. A tetragonal-rich layer was seen at the metal/oxide interface, while post-breakaway samples exhibited increased amount of tetragonal phase in the bulk of their oxides. Spatial mapping of spectral peak location and half-width at half-maximum was accomplished to distinguish differences in stability mechanisms of tetragonal-rich zirconia phase. Shifts in monoclinic peak positions provided mapping of relative stress state, supporting the differences in stabilization of tetragonal phase near the metal/oxide interface and tetragonal phase in the bulk of the oxide. Tetragonal phase near the metal/oxide interface is stabilized through support of oxygen sub-stoichiometry and compressive stress. Tetragonal phase observed in the bulk of the oxide is stabilized through oxygen sub-stoichiometry, void of compressive stress. A linear trend between percent tetragonality and stress state was determined. This resulted in a connection between mechanism of tetragonal to monoclinic phase transformation and a cladding\u27s ability to resist oxidation and breakaway. Poor performing samples displayed greater stress gradients, driven by lattice mismatch at the metal/oxide interface, as well as between tetragonal and monoclinic phase boundaries. Tetragonal phase at the metal/oxide interface for superior performing samples have reduced epitaxial growth of tetragonal grains, lowering compressive stress gradients and provided more resistant inner-oxide layers. With increased utility of Raman spectroscopy for characterizing zirconium cladding materials, different degradation mechanisms can be further understood

Moving interdisciplinary science forward: integrating participatory modelling with mathematical modelling of zoonotic disease in Africa

This review outlines the benefits of using multiple approaches to improve model design and facilitate multidisciplinary research into infectious diseases, as well as showing and proposing practical examples of effective integration. It looks particularly at the benefits of using participatory research in conjunction with traditional modelling methods to potentially improve disease research, control and management. Integrated approaches can lead to more realistic mathematical models which in turn can assist with making policy decisions that reduce disease and benefit local people. The emergence, risk, spread and control of diseases are affected by many complex bio-physical, environmental and socio-economic factors. These include climate and environmental change, land-use variation, changes in population and people’s behaviour. The evidence base for this scoping review comes from the work of a consortium, with the aim of integrating modelling approaches traditionally used in epidemiological, ecological and development research. A total of five examples of the impacts of participatory research on the choice of model structure are presented. Example 1 focused on using participatory research as a tool to structure a model. Example 2 looks at identifying the most relevant parameters of the system. Example 3 concentrates on identifying the most relevant regime of the system (e.g., temporal stability or otherwise), Example 4 examines the feedbacks from mathematical models to guide participatory research and Example 5 goes beyond the so-far described two-way interplay between participatory and mathematical approaches to look at the integration of multiple methods and frameworks. This scoping review describes examples of best practice in the use of participatory methods, illustrating their potential to overcome disciplinary hurdles and promote multidisciplinary collaboration, with the aim of making models and their predictions more useful for decision-making and policy formulation

Stress corrosion cracking: Characteristics, Mechanisms and Experimental study

Stress corrosion cracking (SCC) is a phenomenon in which the cracking of a metal alloy usually results from the combined action of a corrodent and tensile stress. Stresses that cause cracking can be residual or may be applied during service. A degree of mechanistic understanding of SCC will enable most metallic engineering materials to operate safely though stress corrosion cracking failures still continue to occur unexpectedly in industry. In this paper, the characteristics, mechanisms and methods of SCC prevention are reviewed. The results of experimental studies on alpha brass are also reported of which the failure mode conformed with the film-rupture and anodic dissolution mechanism

Monitoring mesenchymal stem cell cultures using image processing and pattern recognition techniques

Stem cells have attracted tremendous interest in recent times due to their promise in providing innovative new treatments for a great range of currently debilitating diseases. This is due to their potential ability to regenerate and repair damaged tissue, and hence restore lost body function, in a manner beyond the body's usual healing process. Bone marrow-derived mesenchymal stem cells or bone marrow stromal cells are one type of adult stem cells that are of particular interest. Since they are derived from a living human adult donor, they do not have the ethical issues associated with the use of human embryonic stem cells. They are also able to be taken from a patient or other donors with relative ease and then grown readily in the laboratory for clinical application. Despite the attractive properties of bone marrow stromal cells, there is presently no quick and easy way to determine the quality of a sample of such cells. Presently, a sample must be grown for weeks and subject to various time-consuming assays, under the direction of an expert cell biologist, to determine whether it will be useful. Hence there is a great need for innovative new ways to assess the quality of cell cultures for research and potential clinical application. The research presented in this thesis investigates the use of computerised image processing and pattern recognition techniques to provide a quicker and simpler method for the quality assessment of bone marrow stromal cell cultures. In particular, aim of this work is to find out whether it is possible, through the use of image processing and pattern recognition techniques, to predict the growth potential of a culture of human bone marrow stromal cells at early stages, before it is readily apparent to a human observer. With the above aim in mind, a computerised system was developed to classify the quality of bone marrow stromal cell cultures based on phase contrast microscopy images. Our system was trained and tested on mixed images of both healthy and unhealthy bone marrow stromal cell samples taken from three different patients. This system, when presented with 44 previously unseen bone marrow stromal cell culture images, outperformed human experts in the ability to correctly classify healthy and unhealthy cultures. The system correctly classified the health status of an image 88% of the time compared to an average of 72% of the time for human experts. Extensive training and testing of the system on a set of 139 normal sized images and 567 smaller image tiles showed an average performance of 86% and 85% correct classifications, respectively. The contributions of this thesis include demonstrating the applicability and potential of computerised image processing and pattern recognition techniques to the task of quality assessment of bone marrow stromal cell cultures. As part of this system, an image normalisation method has been suggested and a new segmentation algorithm has been developed for locating cell regions of irregularly shaped cells in phase contrast images. Importantly, we have validated the efficacy of both the normalisation and segmentation method, by demonstrating that both methods quantitatively improve the classification performance of subsequent pattern recognition algorithms, in discriminating between cell cultures of differing health status. We have shown that the quality of a cell culture of bone marrow stromal cells may be assessed without the need to either segment individual cells or to use time-lapse imaging. Finally, we have proposed a set of features, that when extracted from the cell regions of segmented input images, can be used to train current state of the art pattern recognition systems to predict the quality of bone marrow stromal cell cultures earlier and more consistently than human experts

Modelling the spread of transboundary animal disease in and between domestic and wild swine populations

The challenge of planning for transboundary animal disease outbreaks can be compounded by the complex epidemiological interplay between livestock, wild animals, and the environment. Wild boar populations can form direct and indirect spread pathways for contagious livestock diseases such as FMD, ASF and CSF, both within and between countries. In this poster we describe the enhancement of the EuFMDiS decision support tool to assist disease managers explore the sometimes unpredictable interface between domestic pigs and wild boar. A key modelling outcome was the fusion of an existing agent-based model of livestock disease transmission with a new geographic automata model of wildlife disease transmission