It is a striking observation that tissue of patients invaded by the deep mycoses often lacks evidence of an inflammatory response. This lack of host response is often attributed to neutropenia secondary to chemotherapy. However, systematic studies do not support this simplistic explanation. However, invasive fungal lesions are characterized by abundant fungal functional amyloid, which in turn is bound by serum amyloid P component (SAP). We postulate that SAP is important in the local immune response in invasive fungal infections. The interaction between fungal functional amyloid, SAP, and the immune response in deep mycoses is discussed.

Bacteria may live in harsh environments where they face changing and new conditions. Therefore, the ability to maintain homeostasis in cells may be vital for survival. Transition metals such as iron, zinc, and copper are essential nutrients for cell survival, but become toxic if in excess amount. In order to survive, bacteria have developed defensive mechanisms to protect themselves. Copper and silver levels need to be carefully maintained within cells to balance cellular needs with potential toxicity. This dissertation focuses on the Cus copper and silver efflux system in E. coli. The E. coli cus system is composed of two divergently transcribed operons, cusCFBA and cusRS. The cusCFBA genes encode for a tripartite metal efflux pump CusCBA and a metallochaperone CusF. The cusRS genes encode a two-component system CusS-CusR that regulates the expression of the cusCFBA genes in response to elevated levels of copper or silver in the periplasm. The histidine kinase CusS senses and binds to metals on its periplasmic sensor domain and transduces signal into the cytoplasm to further communicate with its cognate response regulator CusR through histidyl-aspartyl phosphotransfer event. CusR then outputs cellular response by activating the upregulation of the cusCFBA genes, which then turn on the CusCBA efflux pump to eliminate excess copper or silver in the periplasm. While bacterial two-component systems have been widely studied, the mechanisms of ligand-induced signal transduction by histidine kinases remain unclear. It is now known that cusS is essential for copper and silver resistance, and CusS directly binds metal ions in the periplasmic sensor domain and dimerizes upon metal binding. Thus, the goal of this research is to characterize the metal binding properties in the sensor domain, and to elucidate the signal transduction and autophosphorylation mechanisms of CusS upon metal binding. The data from this work reveal that there are two distinct metal binding sites, interface and internal binding sites, in the sensor domain of CusS, and the interface binding site is functionally more important in metal resistance in E. coli. Furthermore, metal-induced dimerization through the interface metal binding site plays an important role in CusS kinase activity. Together, these findings aid in our understanding of the molecular details in metal binding within the sensor domain of CusS. Based on these data, we propose a model for the signal transduction mechanism and histidine phosphorylation mechanism of the histidine kinase CusS.

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The gram-positive bacterium Streptococcus sanguinis is a member of human indigenous oral microbialflora and has long been recognized as a key player in the bacterial colonization of the mouth. S. sanguinis is also the most common viridians streptococcal species implicated in infective endocarditis. Although many studies have focused on two-component systems in closely related Streptococcus species such as S. mutans, S. pneumoniae and S. gordonii; the mechanism of the response regulator in S. sanguinis is still unknown. The ability of S. sanguinis to adapt and thrive in hostile environments suggests this bacterium is capable of sensing and responding to various environmental stimuli. The present study clearly demonstrates that a number of RR genes, SSA_0204, SSA_0217, SSA_1810, SSA_1794, and SSA_1842, in S. sanguinis are essential to the recognition and response to various environmental stresses. Results from this study also identified genes SSA_0260, SSA_0261, and SSA-0262, involved in acidic tolerance and suppressed by SSA_0204 response regulator.

Streptococci resident in the oral cavity have been linked to infective endocarditis (IE). While viridans streptococci are commonly studied and associated with IE, less research has been focused on Streptococcus pneumoniae. Two-component systems (TCSs), consisting of a histidine kinase (HK) protein and response regulator (RR) protein, are bacterial signaling systems that may mediate S. pneumoniae TIGR4 strain virulence in IE. To test this hypothesis, TCS RR mutants of TIGR4 were examined in vivo through use of rabbit models. There were 14 RR proteins identified and 13 RR mutants synthesized because SP_1227 was found to be essential. The requirement of the 13 RRs for S. pneumoniae growth in IE models was assessed by quantifying mutants after overnight inoculation in IE infected rabbits through use of real time PCR (qPCR), colony enumeration on antibiotic selection plates, and competitive index assays. Real time PCR pinpointed several candidate virulence factors. Candidate RR SP_0798 was selected to be further examined. In the in vivo model, mutant SP_0798 grew significantly less than our control mutant SP_1678, which encodes a hypothetical protein and grew at a comparable rate to wild-type TIGR4 strains. Literature and databases identified SP_0798 as the ciaR gene, which has roles in regulating many diverse cellular functions. Our data suggests that RR SP_0798 is a virulence factor of S. pneumoniae TIGR4 strain in IE. This research may place more emphasis on virulence factors and lead to novel methods to combat pneumococcal endocarditis.

Anthropogenic climate change is arguably the greatest challenge of modern times posing significant risks to natural resources and the environment. Socio-economic change, severe droughts, and environmental concerns focus attention upon sustainability of water supplies and the ability of water utilities to meet competing demands worldwide. The 2012 Climate Change Risk Assessment identified water security as one of the most significant climate threats facing the UK. It is now recognised that household water demand management could offer a low regret adaptation measure (both financially and environmentally) given large uncertainties about future climate and non-climatic pressures. This thesis uses Anglian Water Services (AWS) Golden 100 dataset to explore the climate sensitivity of historic micro-component water-use. This work contributes to a larger integrated assessment of the South-East England water system under the EPSRC Adaptation and Resilience to a Changing Climate Coordination Network (ARCC CN). The Golden 100 is a metered record of 100 households daily water consumption by basin, bath, dishwasher, external, kitchen sink, shower, WC and washing machine use. The archive also includes socio-economic information for each household, dates of the year and daily time series of observed minimum temperature, maximum temperature, sunshine hours, soil moisture deficit, concurrent, and antecedent rainfall amounts. The methodology developed within this research provides a portable approach to error trapping, formatting and mining large, complex water sector datasets, for exploring the relative sensitivities of micro-component metered water-use to weather/non-weather variables. This research recognises both the importance of the choice to use a micro-component and the volume used. As such, logistic and linear generalised regression techniques are employed to explore the relative sensitivity of these two aspects of water-use to climatic and non-climatic variables. The 2009 UK Climate Projections (UKCP09) projections and climate analogues are then used to bound a climate sensitivity analysis of the most weather-sensitive micro-components using temperature and rainfall scenarios for the 2050s and 2080s. This research provides empirical evidence that the most weather sensitive micro-components are external and shower water-use. A key contribution of this research to existing knowledge is the non-linear response of likelihood and volume of external water-use to average air temperatures. There is an abrupt increase in the likelihood of external water-use on days above ~15??C. Climate sensitivity analysis further suggests that by the 2080s, under a hotter/drier climate, average unmetered households could be 8% more likely to use external-water and expend ~9 litres more per day during the summer. For the same parameters, high water users (defined here as the 90th percentile) could consume ~13 litres more external water per day. Importantly, this research has re-affirmed the relative importance of behavioural drivers of water-use as manifested by pronounced day of week and bank holiday signatures in both the likelihood and volume of use statistics. As such, this prompts future studies and water management efforts to consider the impact of behavioural drivers as well as climate. It must be recognised that the small sample size of the Golden 100 combined with the Hawthorn effect, self-selection and sample biases in factors such as socio-economic status, billing method and occupancy rate all limit the sample representativeness of the wider population. As such, any predictions based on the data must be treated as illustrative rather than definitive. Furthermore, the results are probably specific to the demographic and socio-economic groups comprising the sample. Nonetheless, this research sheds new light into water-use within the home thereby adding value to a dataset that was not originally collected with household-level, weather-related research in mind.

Managed Extensibility Framework allows development of component-based .NET applications. However relations between components can be quite complex. Therefore the MEF Editor was implemented in context of author's bachelor thesis, which can visualise the relations according to source code analysis and provide their editing. Although possibilities of the analysis are determined by available user's extensions, in some cases the editor cannot be used. This master thesis provides a solution in form of a new version of the MEF Editor which increases the number of cases it can be used in. As part of this thesis, we implemented the editor with extensions allowing analysis of application projects written in C# language and compiled assemblies. It helps to detect composition errors in these applications and allows visual editing of source code where component architecture of these applications is implemented. Powered by TCPDF (www.tcpdf.org)

In this paper a resilient sensor network is built in order to lessen the effects of a small portion of corrupted sensors when an aggregated result such as the average needs to be obtained. By examining the variance in sensor readings, a change in the pattern can be spotted and minimized in order to maintain a stable aggregated reading. Offset in sensors readings are also analyzed and compensated to help reduce a bias change in average. These two analytical techniques are later combined in Kalman filter to produce a smooth and resilient average given by the readings of individual sensors. In addition, principal components analysis is used to detect variations in the sensor network. Experiments are held using real sensors called MICAz, which are use to gather light measurements in a small area and display the light average generated in that area.

Nowadays, more and more embedded systems are equipped with e.g., various sensors that produce large amount of data. One of the challenges of traditional (CPU-based) embedded systems is to process this considerable amount of data such that it produces the appropriate performance level demanded by embedded applications. A solution comes from the usage of a specialized processing unit such as Graphics Processing Unit (GPU). A GPU can process large amount of data thanks to its parallel processing architecture, delivering an im- proved performance outcome compared to CPU. A characteristic of the GPU is that it cannot work alone; the CPU must trigger all its activities. Today, taking advantage of the latest technology breakthrough, we can benefit of the GPU technology in the context of embedded systems by using heterogeneous CPU-GPU embedded systems. Component-based development has demonstrated to be a promising methology in handling software complexity. Through component models, which describe the component specification and their interaction, the methodology has been successfully used in embedded system domain. The existing component models, designed to handle CPU-based embedded systems, face challenges in developing embedded systems with GPU capabilities. For example, current so- lutions realize the communication between components with GPU capabilities via the RAM system. This introduces an undesired overhead that negatively affects the system performance. This Licentiate presents methods and techniques that address the component- based development of embedded systems with GPU capabilities. More concretely, we provide means for component models to explicitly address the GPU-aware component-based development by using specific artifacts. For example, the overhead introduced by the traditional way of communicating via RAM is reduced by inserting automatically generated adapters that facilitate a direct component communication over the GPU memory. Another contribution of the thesis is a component allocation method over the system hardware. The proposed solution offers alternative options in opti- mizing the total system performance and balancing various system properties (e.g., memory usage, GPU load). For the validation part of our proposed solutions, we use an underwater robot demonstrator equipped with GPU hardware. / Ralf 3

Student Number : 9804484F MSc dissertation - School of Statistics and Acturial Science - Faculty of Science / This dissertation conducts a comprehensive and up to date review of measures of component and module importance within monotone systems, where it is assumed that components work independent of each other. The dissertation traces the development of these important measures from the initial definition of Birnbaum importance right through to the definition of Meng's criticality importance. Furthermore, the dissertation draws a distinction between time independent measures and time dependent measures (such as the Barlow-Proschan measures). The dissertation demonstrates how such measures may be implemented in analysing the importance of components within the monotone systems by evaluating these measures for a well known bridge structure example. This evaluation also reveals how each defined measure can be compared to each other. In conclusion, the dissertation describes how these measures can be extended to non-monotone systems or systems with dependent components.