930 resultados para selection methods


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A classical condition for fast learning rates is the margin condition, first introduced by Mammen and Tsybakov. We tackle in this paper the problem of adaptivity to this condition in the context of model selection, in a general learning framework. Actually, we consider a weaker version of this condition that allows one to take into account that learning within a small model can be much easier than within a large one. Requiring this “strong margin adaptivity” makes the model selection problem more challenging. We first prove, in a general framework, that some penalization procedures (including local Rademacher complexities) exhibit this adaptivity when the models are nested. Contrary to previous results, this holds with penalties that only depend on the data. Our second main result is that strong margin adaptivity is not always possible when the models are not nested: for every model selection procedure (even a randomized one), there is a problem for which it does not demonstrate strong margin adaptivity.

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Single particle analysis (SPA) coupled with high-resolution electron cryo-microscopy is emerging as a powerful technique for the structure determination of membrane protein complexes and soluble macromolecular assemblies. Current estimates suggest that ∼104–105 particle projections are required to attain a 3 Å resolution 3D reconstruction (symmetry dependent). Selecting this number of molecular projections differing in size, shape and symmetry is a rate-limiting step for the automation of 3D image reconstruction. Here, we present SwarmPS, a feature rich GUI based software package to manage large scale, semi-automated particle picking projects. The software provides cross-correlation and edge-detection algorithms. Algorithm-specific parameters are transparently and automatically determined through user interaction with the image, rather than by trial and error. Other features include multiple image handling (∼102), local and global particle selection options, interactive image freezing, automatic particle centering, and full manual override to correct false positives and negatives. SwarmPS is user friendly, flexible, extensible, fast, and capable of exporting boxed out projection images, or particle coordinates, compatible with downstream image processing suites.

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In Uganda, vitamin A deficiency (VAD) and iron deficiency anaemia (IDA) are major public health problems with between 15-32% of children under 5 years of age showing VAD and 73% being anaemic. This is largely due to the fact that the staple food crop of the country, banana, is low in pro-vitamin A and iron, therefore leading to dietary deficiencies. Although worldwide progress has been made to control VAD and IDA through supplementation, food fortification and diet diversification, their long term sustainability and impact in developing countries such as Uganda is limited. The approach taken by researchers at Queensland University of Technology (QUT), Australia, in collaboration with the National Agricultural Research Organization (NARO), Uganda, to address this problem, is to generate consumer acceptable banana varieties with significantly increased levels of pro-vitamin A and iron in the fruit using genetic engineering techniques. Such an approach requires the use of suitable, well characterised genes and promoters for targeted transgene expression. Recently, a new banana phytoene synthase gene (APsy2a) involved in the synthesis of pro-vitamin A (pVA) carotenoids was isolated from a high â-carotene banana (F’ei cv Asupina). In addition, sequences of banana ferritin, an iron storage protein, have been isolated from Cavendish banana. The aim of the research described in this thesis was to evaluate the function of these genes to assess their suitability for the biofortification of banana fruit. In addition, a range of banana-derived promoters were characterised to determine their suitability for controlling the expression of transgenes in banana fruit. Due to the time constraints involved with generating transgenic banana fruit, rice was used as the model crop to investigate the functionality of the banana-derived APsy2a and ferritin genes. Using Agrobacterium-mediated transformation, rice callus was transformed with APsy2a +/- the bacterial-derived carotene desaturase gene (CrtI) each under the control of the constitutive maize poly-ubiquitin promoter (ZmUbi) or seed-specific rice glutelin1 (Gt1) promoter. The maize phytoene synthase (ZmPsy1) gene was included as a control. On selective media, with the exception of ZmUbi-CrtI-transgenic callus, all antibiotic resistant callus displayed a yellow-orange colour from which the presence of â-carotene was demonstrated using Raman spectroscopy. Although the regeneration of plants from yellow-orange callus was difficult, 16 transgenic plants were obtained and characterised from callus transformed with ZmUbi-APys2a alone. At least 50% of the T1 seeds developed a yellow-orange coloured callus which was found to contain levels of â-carotene ranging from 4.6-fold to 72-fold higher than that in non-transgenic rice callus. Using the seed-specific Gt1 promoter, 38 transgenic rice plants were generated from APsy2a-CrtI-transformed callus while 32 plants were regenerated from ZmPsy1-CrtI-transformed callus. However, when analysed for presence of transgene by PCR, all transgenic plants contained the APsy2a, ZmPsy1 or CrtI transgene, with none of the plants found to be co-transformed. Using Raman spectroscopy, no â-carotene was detected in-situ in representative T1 seeds. To investigate the potential of the banana-derived ferritin gene (BanFer1) to enhance iron content, rice callus was transformed with constitutively expressed BanFer1 using the soybean ferritin gene (SoyFer) as a control. A total of 12 and 11 callus lines independently transformed with BanFer1 and SoyFer, respectively, were multiplied and transgene expression was verified by RT-PCR. Pearl’s Prussian blue staining for in-situ detection of ferric iron showed a stronger blue colour in rice callus transformed with BanFer1 compared to SoyFer. Using flame atomic absorption spectrometry, the highest mean amount of iron quantified in callus transformed with BanFer1 was 30-fold while that obtained using the SoyFer was 14-fold higher than the controls. In addition, ~78% of BanFer1-transgenic callus lines and ~27% of SoyFer-transgenic callus lines had significantly higher iron content than the non-transformed controls. Since the genes used for enhancing micronutrient content need to be expressed in banana fruit, the activity of a range of banana-derived, potentially fruit-active promoters in banana was investigated. Using uidA (GUS) as a reporter gene, the function of the Expansin1 (MaExp1), Expansin1 containing the rice actin intron (MaExp1a), Expansin4 (MaExp4), Extensin (MaExt), ACS (MaACS), ACO (MaACO), Metallothionein (MaMT2a) and phytoene synthase (APsy2a) promoters were transiently analysed in intact banana fruit using two transformation methods, particle bombardment and Agrobacterium-mediated infiltration (agro-infiltration). Although a considerable amount of variation in promoter activity was observed both within and between experiments, similar trends were obtained using both transformation methods. The MaExp1 and MaExp1a directed high levels of GUS expression in banana fruit which were comparable to those observed from the ZmUbi and Banana bunchy top virus-derived BT4 promoters that were included as positive controls. Lower levels of promoter activity were obtained in both methods using the MaACO and MaExt promoters while the MaExp4, MaACS, and APsy2a promoters directed the lowest GUS activity in banana fruit. An attempt was subsequently made to use agro-infiltration to assess the expression of pVA biosynthesis genes in banana fruit by infiltrating fruit with constructs in which the ZmUbi promoter controlled the expression of APsy2a +/- CrtI, and with the maize phytoene synthase gene (ZmPsy1) included as a control. Unfortunately, the large amount of variation and inconsistency observed within and between experiments precluded any meaningful conclusions to be drawn. The final component of this research was to assess the level of promoter activity and specificity in non-target tissue. These analyses were done on leaves obtained from glasshouse-grown banana plants stably transformed with MaExp1, MaACO, APsy2a, BT4 and ZmUbi promoters driving the expression of the GUS gene in addition to leaves from a selection of the same transgenic plants which were growing in a field trial in North Queensland. The results from both histochemical and fluorometric GUS assays showed that the MaExp1 and MaACO promoters directed very low GUS activities in leaves of stably transformed banana plants compared to the constitutive ZmUbi and BT4 promoters. In summary, the results from this research provide evidence that the banana phytoene synthase gene (APsy2a) and the banana ferritin gene (BanFer1) are functional, since the constitutive over-expression of each of these transgenes led to increased levels of pVA carotenoids (for APsy2a) and iron content (for BanFer1) in transgenic rice callus. Further work is now required to determine the functionality of these genes in stably-transformed banana fruit. This research also demonstrated that the MaExp1 and MaACO promoters are fruit-active but have low activity in non-target tissue (leaves), characteristics that make them potentially useful for the biofortification of banana fruit. Ultimately, however, analysis of fruit from field-grown transgenic plants will be required to fully evaluate the suitability of pVA biosynthesis genes and the fruit-active promoters for fruit biofortification.

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Autonomous development of sensorimotor coordination enables a robot to adapt and change its action choices to interact with the world throughout its lifetime. The Experience Network is a structure that rapidly learns coordination between visual and haptic inputs and motor action. This paper presents methods which handle the high dimensionality of the network state-space which occurs due to the simultaneous detection of multiple sensory features. The methods provide no significant increase in the complexity of the underlying representations and also allow emergent, task-specific, semantic information to inform action selection. Experimental results show rapid learning in a real robot, beginning with no sensorimotor mappings, to a mobile robot capable of wall avoidance and target acquisition.

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The stochastic simulation algorithm was introduced by Gillespie and in a different form by Kurtz. There have been many attempts at accelerating the algorithm without deviating from the behavior of the simulated system. The crux of the explicit τ-leaping procedure is the use of Poisson random variables to approximate the number of occurrences of each type of reaction event during a carefully selected time period, τ. This method is acceptable providing the leap condition, that no propensity function changes “significantly” during any time-step, is met. Using this method there is a possibility that species numbers can, artificially, become negative. Several recent papers have demonstrated methods that avoid this situation. One such method classifies, as critical, those reactions in danger of sending species populations negative. At most, one of these critical reactions is allowed to occur in the next time-step. We argue that the criticality of a reactant species and its dependent reaction channels should be related to the probability of the species number becoming negative. This way only reactions that, if fired, produce a high probability of driving a reactant population negative are labeled critical. The number of firings of more reaction channels can be approximated using Poisson random variables thus speeding up the simulation while maintaining the accuracy. In implementing this revised method of criticality selection we make use of the probability distribution from which the random variable describing the change in species number is drawn. We give several numerical examples to demonstrate the effectiveness of our new method.

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Biologists are increasingly conscious of the critical role that noise plays in cellular functions such as genetic regulation, often in connection with fluctuations in small numbers of key regulatory molecules. This has inspired the development of models that capture this fundamentally discrete and stochastic nature of cellular biology - most notably the Gillespie stochastic simulation algorithm (SSA). The SSA simulates a temporally homogeneous, discrete-state, continuous-time Markov process, and of course the corresponding probabilities and numbers of each molecular species must all remain positive. While accurately serving this purpose, the SSA can be computationally inefficient due to very small time stepping so faster approximations such as the Poisson and Binomial τ-leap methods have been suggested. This work places these leap methods in the context of numerical methods for the solution of stochastic differential equations (SDEs) driven by Poisson noise. This allows analogues of Euler-Maruyuma, Milstein and even higher order methods to be developed through the Itô-Taylor expansions as well as similar derivative-free Runge-Kutta approaches. Numerical results demonstrate that these novel methods compare favourably with existing techniques for simulating biochemical reactions by more accurately capturing crucial properties such as the mean and variance than existing methods.

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This paper gives a modification of a class of stochastic Runge–Kutta methods proposed in a paper by Komori (2007). The slight modification can reduce the computational costs of the methods significantly.

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In recent years, development of Unmanned Aerial Vehicles (UAV) has become a significant growing segment of the global aviation industry. These vehicles are developed with the intention of operating in regions where the presence of onboard human pilots is either too risky or unnecessary. Their popularity with both the military and civilian sectors have seen the use of UAVs in a diverse range of applications, from reconnaissance and surveillance tasks for the military, to civilian uses such as aid relief and monitoring tasks. Efficient energy utilisation on an UAV is essential to its functioning, often to achieve the operational goals of range, endurance and other specific mission requirements. Due to the limitations of the space available and the mass budget on the UAV, it is often a delicate balance between the onboard energy available (i.e. fuel) and achieving the operational goals. This thesis presents an investigation of methods for increasing the energy efficiency on UAVs. One method is via the development of a Mission Waypoint Optimisation (MWO) procedure for a small fixed-wing UAV, focusing on improving the onboard fuel economy. MWO deals with a pre-specified set of waypoints by modifying the given waypoints within certain limits to achieve its optimisation objectives of minimising/maximising specific parameters. A simulation model of a UAV was developed in the MATLAB Simulink environment, utilising the AeroSim Blockset and the in-built Aerosonde UAV block and its parameters. This simulation model was separately integrated with a multi-objective Evolutionary Algorithm (MOEA) optimiser and a Sequential Quadratic Programming (SQP) solver to perform single-objective and multi-objective optimisation procedures of a set of real-world waypoints in order to minimise the onboard fuel consumption. The results of both procedures show potential in reducing fuel consumption on a UAV in a ight mission. Additionally, a parallel Hybrid-Electric Propulsion System (HEPS) on a small fixedwing UAV incorporating an Ideal Operating Line (IOL) control strategy was developed. An IOL analysis of an Aerosonde engine was performed, and the most efficient (i.e. provides greatest torque output at the least fuel consumption) points of operation for this engine was determined. Simulation models of the components in a HEPS were designed and constructed in the MATLAB Simulink environment. It was demonstrated through simulation that an UAV with the current HEPS configuration was capable of achieving a fuel saving of 6.5%, compared to the ICE-only configuration. These components form the basis for the development of a complete simulation model of a Hybrid-Electric UAV (HEUAV).

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Strategic communication is held to be a key process by which organisations respond to environmental uncertainty. In the received view articulated in the literatures of organisational communication and public relations, strategic communication results from collaborative efforts by organisational members to create shared understanding about environmental uncertainty and, as a result of this collective understanding, formulate appropriate communication responses. In this study, I explore how such collaborative efforts towards the development of strategic communication are derived from, and bounded by, culturally shared values and assumptions. Study of the influences of an organisation‟s culture on the formulation of strategic communication is a fundamental conceptual challenge for public relations and, to date, a largely unaddressed area of research. This thesis responds to this challenge by describing a key property of organisational culture – the action of cultural selection (Durham, 1992). I integrate this property of cultural selection to extend and refine the descriptive range of Weick‟s (1969, 1979) classic sociocultural model of organizing. From this integration I propose a new model, the Cultural Selection of Strategic Communication (CSSC). Underpinning the CSSC model is the central proposition that because of the action of cultural selection during organizing processes, the inherently conservative properties of an organisation‟s culture constrain development of effective strategic communication in ways that may be unrelated to the outcomes of “environmental scanning” and other monitoring functions heralded by the public relations literature as central to organisational adaptation. Thus, by examining the development of strategic communication, I describe a central conservative influence on the social ecology of organisations. This research also responds to Butschi and Steyn‟s (2006) call for the development of theory focusing on strategic communication as well as Grunig (2006) and Sriramesh‟s (2007) call for research to further understand the role of culture in public relations practice. In keeping with the explorative and descriptive goals of this study, I employ organisational ethnography to examine the influence of cultural selection on the development of strategic communication. In this methodological approach, I use the technique of progressive contextualisation to compare data from two related but distinct cultural settings. This approach provides a range of descriptive opportunities to permit a deeper understanding of the work of cultural selection. Findings of this study propose that culture, operating as a system of shared and socially transmitted social knowledge, acts through the property of cultural selection to influence decision making, and decrease conceptual variation within a group. The findings support the view that strategic communication, as a cultural product derived from the influence of cultural selection, is an essential feature to understand the social ecology of an organisation.

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We consider time-space fractional reaction diffusion equations in two dimensions. This equation is obtained from the standard reaction diffusion equation by replacing the first order time derivative with the Caputo fractional derivative, and the second order space derivatives with the fractional Laplacian. Using the matrix transfer technique proposed by Ilic, Liu, Turner and Anh [Fract. Calc. Appl. Anal., 9:333--349, 2006] and the numerical solution strategy used by Yang, Turner, Liu, and Ilic [SIAM J. Scientific Computing, 33:1159--1180, 2011], the solution of the time-space fractional reaction diffusion equations in two dimensions can be written in terms of a matrix function vector product $f(A)b$ at each time step, where $A$ is an approximate matrix representation of the standard Laplacian. We use the finite volume method over unstructured triangular meshes to generate the matrix $A$, which is therefore non-symmetric. However, the standard Lanczos method for approximating $f(A)b$ requires that $A$ is symmetric. We propose a simple and novel transformation in which the standard Lanczos method is still applicable to find $f(A)b$, despite the loss of symmetry. Numerical results are presented to verify the accuracy and efficiency of our newly proposed numerical solution strategy.

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Project selection is a decision-making process that is not merely influenced by technical aspects but also by the people who involved in the process. Organisational culture is described as a set of values and norms that are shared by people within the organisation that affects the way they interact with each other and with stakeholders from outside the organisation. The aim of this paper is to emphasize the importance of organisational culture on improving the quality of decisions in the project selection process, in addition to the influence of technical aspects of a project. The discussion is based on an extensive literature review and, as such, represents the first part of a research agenda investigating the impact of organisational culture on the project selection process applicable specifically to road infrastructure contracts. Four existing models of organisational culture (Denison 1990; Cameron and Quinn 2006; Hofstede 2001; Glaser et al 1987) are discussed and reviewed in view of their use in the larger research project to investigate the impact of culture on identified critical elements of decision-making. An understating of the way organisational culture impacts on project selection will increase the likelihood in future of relevant government departments selecting projects that achieve their stated organisational goals.

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Continuous user authentication with keystroke dynamics uses characters sequences as features. Since users can type characters in any order, it is imperative to find character sequences (n-graphs) that are representative of user typing behavior. The contemporary feature selection approaches do not guarantee selecting frequently-typed features which may cause less accurate statistical user-representation. Furthermore, the selected features do not inherently reflect user typing behavior. We propose four statistical based feature selection techniques that mitigate limitations of existing approaches. The first technique selects the most frequently occurring features. The other three consider different user typing behaviors by selecting: n-graphs that are typed quickly; n-graphs that are typed with consistent time; and n-graphs that have large time variance among users. We use Gunetti’s keystroke dataset and k-means clustering algorithm for our experiments. The results show that among the proposed techniques, the most-frequent feature selection technique can effectively find user representative features. We further substantiate our results by comparing the most-frequent feature selection technique with three existing approaches (popular Italian words, common n-graphs, and least frequent ngraphs). We find that it performs better than the existing approaches after selecting a certain number of most-frequent n-graphs.

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In this paper, we seek to expand the use of direct methods in real-time applications by proposing a vision-based strategy for pose estimation of aerial vehicles. The vast majority of approaches make use of features to estimate motion. Conversely, the strategy we propose is based on a MR (Multi- Resolution) implementation of an image registration technique (Inverse Compositional Image Alignment ICIA) using direct methods. An on-board camera in a downwards-looking configuration, and the assumption of planar scenes, are the bases of the algorithm. The motion between frames (rotation and translation) is recovered by decomposing the frame-to-frame homography obtained by the ICIA algorithm applied to a patch that covers around the 80% of the image. When the visual estimation is required (e.g. GPS drop-out), this motion is integrated with the previous known estimation of the vehicles’ state, obtained from the on-board sensors (GPS/IMU), and the subsequent estimations are based only on the vision-based motion estimations. The proposed strategy is tested with real flight data in representative stages of a flight: cruise, landing, and take-off, being two of those stages considered critical: take-off and landing. The performance of the pose estimation strategy is analyzed by comparing it with the GPS/IMU estimations. Results show correlation between the visual estimation obtained with the MR-ICIA and the GPS/IMU data, that demonstrate that the visual estimation can be used to provide a good approximation of the vehicle’s state when it is required (e.g. GPS drop-outs). In terms of performance, the proposed strategy is able to maintain an estimation of the vehicle’s state for more than one minute, at real-time frame rates based, only on visual information.

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Metallic materials exposed to oxygen-enriched atmospheres – as commonly used in the medical, aerospace, aviation and numerous chemical processing industries – represent a significant fire hazard which must be addressed during design, maintenance and operation. Hence, accurate knowledge of metallic materials flammability is required. Reduced gravity (i.e. space-based) operations present additional unique concerns, where the absence of gravity must also be taken into account. The flammability of metallic materials has historically been quantified using three standardised test methods developed by NASA, ASTM and ISO. These tests typically involve the forceful (promoted) ignition of a test sample (typically a 3.2 mm diameter cylindrical rod) in pressurised oxygen. A test sample is defined as flammable when it undergoes burning that is independent of the ignition process utilised. In the standardised tests, this is indicated by the propagation of burning further than a defined amount, or „burn criterion.. The burn criterion in use at the onset of this project was arbitrarily selected, and did not accurately reflect the length a sample must burn in order to be burning independent of the ignition event and, in some cases, required complete consumption of the test sample for a metallic material to be considered flammable. It has been demonstrated that a) a metallic material.s propensity to support burning is altered by any increase in test sample temperature greater than ~250-300 oC and b) promoted ignition causes an increase in temperature of the test sample in the region closest to the igniter, a region referred to as the Heat Affected Zone (HAZ). If a test sample continues to burn past the HAZ (where the HAZ is defined as the region of the test sample above the igniter that undergoes an increase in temperature of greater than or equal to 250 oC by the end of the ignition event), it is burning independent of the igniter, and should be considered flammable. The extent of the HAZ, therefore, can be used to justify the selection of the burn criterion. A two dimensional mathematical model was developed in order to predict the extent of the HAZ created in a standard test sample by a typical igniter. The model was validated against previous theoretical and experimental work performed in collaboration with NASA, and then used to predict the extent of the HAZ for different metallic materials in several configurations. The extent of HAZ predicted varied significantly, ranging from ~2-27 mm depending on the test sample thermal properties and test conditions (i.e. pressure). The magnitude of the HAZ was found to increase with increasing thermal diffusivity, and decreasing pressure (due to slower ignition times). Based upon the findings of this work, a new burn criterion requiring 30 mm of the test sample to be consumed (from the top of the ignition promoter) was recommended and validated. This new burn criterion was subsequently included in the latest revision of the ASTM G124 and NASA 6001B international test standards that are used to evaluate metallic material flammability in oxygen. These revisions also have the added benefit of enabling the conduct of reduced gravity metallic material flammability testing in strict accordance with the ASTM G124 standard, allowing measurement and comparison of the relative flammability (i.e. Lowest Burn Pressure (LBP), Highest No-Burn Pressure (HNBP) and average Regression Rate of the Melting Interface(RRMI)) of metallic materials in normal and reduced gravity, as well as determination of the applicability of normal gravity test results to reduced gravity use environments. This is important, as currently most space-based applications will typically use normal gravity information in order to qualify systems and/or components for reduced gravity use. This is shown here to be non-conservative for metallic materials which are more flammable in reduced gravity. The flammability of two metallic materials, Inconel® 718 and 316 stainless steel (both commonly used to manufacture components for oxygen service in both terrestrial and space-based systems) was evaluated in normal and reduced gravity using the new ASTM G124-10 test standard. This allowed direct comparison of the flammability of the two metallic materials in normal gravity and reduced gravity respectively. The results of this work clearly show, for the first time, that metallic materials are more flammable in reduced gravity than in normal gravity when testing is conducted as described in the ASTM G124-10 test standard. This was shown to be the case in terms of both higher regression rates (i.e. faster consumption of the test sample – fuel), and burning at lower pressures in reduced gravity. Specifically, it was found that the LBP for 3.2 mm diameter Inconel® 718 and 316 stainless steel test samples decreased by 50% from 3.45 MPa (500 psia) in normal gravity to 1.72 MPa (250 psia) in reduced gravity for the Inconel® 718, and 25% from 3.45 MPa (500 psia) in normal gravity to 2.76 MPa (400 psia) in reduced gravity for the 316 stainless steel. The average RRMI increased by factors of 2.2 (27.2 mm/s in 2.24 MPa (325 psia) oxygen in reduced gravity compared to 12.8 mm/s in 4.48 MPa (650 psia) oxygen in normal gravity) for the Inconel® 718 and 1.6 (15.0 mm/s in 2.76 MPa (400 psia) oxygen in reduced gravity compared to 9.5 mm/s in 5.17 MPa (750 psia) oxygen in normal gravity) for the 316 stainless steel. Reasons for the increased flammability of metallic materials in reduced gravity compared to normal gravity are discussed, based upon the observations made during reduced gravity testing and previous work. Finally, the implications (for fire safety and engineering applications) of these results are presented and discussed, in particular, examining methods for mitigating the risk of a fire in reduced gravity.

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Microbial pollution in water periodically affects human health in Australia, particularly in times of drought and flood. There is an increasing need for the control of waterborn microbial pathogens. Methods, allowing the determination of the origin of faecal contamination in water, are generally referred to as Microbial Source Tracking (MST). Various approaches have been evaluated as indicatorsof microbial pathogens in water samples, including detection of different microorganisms and various host-specific markers. However, until today there have been no universal MST methods that could reliably determine the source (human or animal) of faecal contamination. Therefore, the use of multiple approaches is frequently advised. MST is currently recognised as a research tool, rather than something to be included in routine practices. The main focus of this research was to develop novel and universally applicable methods to meet the demands for MST methods in routine testing of water samples. Escherichia coli was chosen initially as the object organism for our studies as, historically and globally, it is the standard indicator of microbial contamination in water. In this thesis, three approaches are described: single nucleotide polymorphism (SNP) genotyping, clustered regularly interspaced short palindromic repeats (CRISPR) screening using high resolution melt analysis (HRMA) methods and phage detection development based on CRISPR types. The advantage of the combination SNP genotyping and CRISPR genes has been discussed in this study. For the first time, a highly discriminatory single nucleotide polymorphism interrogation of E. coli population was applied to identify the host-specific cluster. Six human and one animal-specific SNP profile were revealed. SNP genotyping was successfully applied in the field investigations of the Coomera watershed, South-East Queensland, Australia. Four human profiles [11], [29], [32] and [45] and animal specific SNP profile [7] were detected in water. Two human-specific profiles [29] and [11] were found to be prevalent in the samples over a time period of years. The rainfall (24 and 72 hours), tide height and time, general land use (rural, suburban), seasons, distance from the river mouth and salinity show a lack of relashionship with the diversity of SNP profiles present in the Coomera watershed (p values > 0.05). Nevertheless, SNP genotyping method is able to identify and distinquish between human- and non-human specific E. coli isolates in water sources within one day. In some samples, only mixed profiles were detected. To further investigate host-specificity in these mixed profiles CRISPR screening protocol was developed, to be used on the set of E. coli, previously analysed for SNP profiles. CRISPR loci, which are the pattern of previous DNA coliphages attacks, were considered to be a promising tool for detecting host-specific markers in E. coli. Spacers in CRISPR loci could also reveal the dynamics of virulence in E. coli as well in other pathogens in water. Despite the fact that host-specificity was not observed in the set of E. coli analysed, CRISPR alleles were shown to be useful in detection of the geographical site of sources. HRMA allows determination of ‘different’ and ‘same’ CRISPR alleles and can be introduced in water monitoring as a cost-effective and rapid method. Overall, we show that the identified human specific SNP profiles [11], [29], [32] and [45] can be useful as marker genotypes globally for identification of human faecal contamination in water. Developed in the current study, the SNP typing approach can be used in water monitoring laboratories as an inexpensive, high-throughput and easy adapted protocol. The unique approach based on E. coli spacers for the search for unknown phage was developed to examine the host-specifity in phage sequences. Preliminary experiments on the recombinant plasmids showed the possibility of using this method for recovering phage sequences. Future studies will determine the host-specificity of DNA phage genotyping as soon as first reliable sequences can be acquired. No doubt, only implication of multiple approaches in MST will allow identification of the character of microbial contamination with higher confidence and readability.