359 resultados para repeat induced point mutation
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Diesel engine fuel injector faults can lead to reduced power, increased fuel consumption and greater exhaust emission levels and if left unchecked, can eventually lead to premature engine failure. This paper provides an overview of the Diesel, or compression ignition combustion process, and of the two basic fuel injector nozzle designs used in Diesel engines, namely, the pintle-type and hole-type nozzles. Also described are some common faults associated with these two types of fuel injector nozzles and the techniques previously used to experimentally simulate these faults. This paper also presents a recent experimental campaign undertaken using two different diesel engines whereby various fuel injector nozzle faults were induced into the engines. The first series of tests was undertaken using a turbo-charged 5.9 litre; Cummins Diesel engine whist the second series of tests was undertaken using a naturally aspirated 4 cylinder, 2.216 litre, Perkins Diesel engine. Data corresponding to different injector fault conditions was captured using in-cylinder pressure, and acoustic emission transducers along with both crank-angle encoder and top-dead centre reference signals. Using averaged in-cylinder pressure signals, it was possible to qualify the severity of the faults whilst averaged acoustic emission signals were in turn, used as the basis for wavelets decomposition. Initial observations from this signal decomposition are also presented and discussed.
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Objective: To critically examine the DSM-IV-TR criteria for Substance-Induced Psychotic Disorder (SIPD). Data sources: Leading electronic databases (such as Medline, Pubmed) were searched for the years 1992 through 2007, using combinations of the following key search terms: substance abuse/dependence, alcohol, marijuana, cannabis, methamphetamine, crack, cocaine, amphetamine, ecstasy, ketamine, phencyclidine, LSD, mental health, drug-induced psychosis, substance-induced psychosis, psychosis, schizophrenia. References identified from bibliographies of pertinent articles and books in the field were also collected and reviewed. Data extraction: Only research studies or case reports series that presented data on populations diagnosed with SIPD using clinical or structured diagnostic interviews published in English were used to assess the validity of the current SIPD criteria. Data synthesis: We identified 49 articles that presented clinical data on SIPD. The majority of these publications were case reports, with only 18 articles specifically focusing on delineating the clinical characteristics or outcomes of individuals diagnosed with SIPD. While several large studies have recently been conducted to assess the stability of SIPD, there is a dearth of research rigorously examining the validity of DSM-IV diagnostic criteria across substances. Conclusions: There remains a striking paucity of information on the outcome, treatment and best practice for substance-associated psychotic episodes. Further work is clearly required before the advent of DSM-V. We propose an alternative, broader classification that better reflects the current evidence base, inferring association rather than causation.
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In humans the presence of negative affect is thought to promote food intake, but there is widespread variability. Susceptibility to negative affect-induced eating may depend on trait eating behaviours, notably ‘emotional eating’, ‘restrained eating’ and ‘disinhibited eating’, but the evidence is not consistent. In the present study, 30 non-obese, non-dieting women were given access to palatable food whilst in a state of negative or neutral affect, induced by a validated autobiographical recall technique. As predicted, food intake was higher in the presence of negative affect; however, this effect was moderated by the pattern of eating behaviour traits and enhanced wanting for the test food. Specifically, the High Restraint-High Disinhibition subtype in combination with higher scores on emotional eating and food wanting was able to predict negative-affect intake (adjusted R2 = .61). In the absence of stress, individuals who are both restrained and vulnerable to disinhibited eating are particularly susceptible to negative affect food intake via stimulation of food wanting. Identification of traits that predispose individuals to overconsume and a more detailed understanding of the specific behaviours driving such overconsumption may help to optimise strategies to prevent weight gain.
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This paper formulates a node-based smoothed conforming point interpolation method (NS-CPIM) for solid mechanics. In the proposed NS-CPIM, the higher order conforming PIM shape functions (CPIM) have been constructed to produce a continuous and piecewise quadratic displacement field over the whole problem domain, whereby the smoothed strain field was obtained through smoothing operation over each smoothing domain associated with domain nodes. The smoothed Galerkin weak form was then developed to create the discretized system equations. Numerical studies have demonstrated the following good properties: NS-CPIM (1) can pass both standard and quadratic patch test; (2) provides an upper bound of strain energy; (3) avoid the volumetric locking; (4) provides the higher accuracy than those in the node-based smoothed schemes of the original PIMs.
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Eating behaviour traits, namely Disinhibition and Restraint, have the potential to exert an effect on food intake and energy balance. The effectiveness of exercise as a method of weight management could be influenced by these traits. Fifty eight overweight and obese participants completed 12-weeks of supervised exercise. Each participant was prescribed supervised exercise based on an expenditure of 500 kcal/session, 5 d/week for 12-weeks. Following 12-weeks of exercise there was a significant reduction in mean body weight (-3.26 ± 3.63 kg), fat mass (FM: -3.26 ± 2.64 kg), BMI (-1.16 ± 1.17 kg/m2)and waist circumference (WC: -5.0 ± 3.23 cm). Regression analyses revealed a higher baseline Disinhibition score was associated with a greater reduction in BMI and WC, while Internal Disinhibition was associated with a larger decrease in weight, %FM and WC. Neither baseline Restraint or Hunger were associated with any of the anthropometric markers at baseline or after 12-weeks. Furthermore, after 12-weeks of exercise, a decrease in Disinhibition and increase in Restraint were associated with a greater reduction in WC, whereas only Restraint was associated with a decrease in weight. Post-hoc analysis of the sub-factors revealed a decrease in External Disinhibition and increase in Flexible Restraint were associated with weight loss. However, an increase in Rigid Restraint was associated with a reduction in %FM and WC. These findings suggest that exercise-induced weight loss is more marked in individuals with a high level of Disinhibition. These data demonstrate the important roles that Disinhibition and Restraint play in the relationship between exercise and energy balance.
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The following paper proposes a novel application of Skid-to-Turn maneuvers for fixed wing Unmanned Aerial Vehicles (UAVs) inspecting locally linear infrastructure. Fixed wing UAVs, following the design of manned aircraft, traditionally employ Bank-to-Turn maneuvers to change heading and thus direction of travel. Commonly overlooked is the effect these maneuvers have on downward facing body fixed sensors, which as a result of bank, point away from the feature during turns. By adopting Skid-to-Turn maneuvers, the aircraft is able change heading whilst maintaining wings level flight, thus allowing body fixed sensors to maintain a downward facing orientation. Eliminating roll also helps to improve data quality, as sensors are no longer subjected to the swinging motion induced as they pivot about an axis perpendicular to their line of sight. Traditional tracking controllers that apply an indirect approach of capturing ground based data by flying directly overhead can also see the feature off center due to steady state pitch and roll required to stay on course. An Image Based Visual Servo controller is developed to address this issue, allowing features to be directly tracked within the image plane. Performance of the proposed controller is tested against that of a Bank-to-Turn tracking controller driven by GPS derived cross track error in a simulation environment developed to simulate the field of view of a body fixed camera.
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PURPOSE/OBJECTIVES: To determine the prevalence of malnutrition and chemotherapy-induced nausea and vomiting (CINV) limiting dietary intake in a chemotherapy unit. DESIGN Cross sectional descriptive audit. SETTING: Chemotherapy ambulatory care unit in an Australian teaching hospital. SAMPLE 121 patients receiving chemotherapy for malignancies, ≥18yrs and able to provide verbal consent. METHODS: An Accredited Practicing Dietitian collected all data. Chi-square tests were used to determine the relationship of malnutrition with variables and demographic data. MAIN RESEARCH VARIABLES: Nutritional status, weight change, BMI, prior dietetic input, CINV and CINV that limited dietary intake. FINDINGS Thirty one (26%) participants were malnourished, 12 (10%) had intake-limiting CINV, 22 (20%) reported significant weight loss and 20 (18%) required improved nutrition symptom management. High nutrition risk diagnoses, CINV, BMI and weight loss were significantly associated with malnutrition. Thirteen (35%) participants with malnutrition, significant weight loss, intake-limiting CINV and/or critically requiring improved symptom management reported no dietetic input; the majority of whom were overweight or obese. CONCLUSIONS: This audit determined over one quarter of patients receiving chemotherapy in this ambulatory setting were malnourished and the majority of patients reporting intake-limiting CINV were malnourished. IMPLICATIONS FOR NURSING Patients with malnutrition and/or intake-limiting CINV and in need of improved nutrition symptom management may be overlooked, especially patients who are overweight or obese - an increasing proportion of the Australian population. Evidence-based practice guidelines recommend implementing validated nutrition screening tools, such as the Malnutrition Screening Tool, in patients undergoing chemotherapy to identify those at risk of malnutrition requiring dietitian referral.
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In this article, an enriched radial point interpolation method (e-RPIM) is developed for computational mechanics. The conventional radial basis function (RBF) interpolation is novelly augmented by the suitable basis functions to reflect the natural properties of deformation. The performance of the enriched meshless RBF shape functions is first investigated using the surface fitting. The surface fitting results have proven that, compared with the conventional RBF, the enriched RBF interpolation has a much better accuracy to fit a complex surface than the conventional RBF interpolation. It has proven that the enriched RBF shape function will not only possess all advantages of the conventional RBF interpolation, but also can accurately reflect the deformation properties of problems. The system of equations for two-dimensional solids is then derived based on the enriched RBF shape function and both of the meshless strong-form and weak-form. A numerical example of a bar is presented to study the effectiveness and efficiency of e-RPIM. As an important application, the newly developed e-RPIM, which is augmented by selected trigonometric basis functions, is applied to crack problems. It has been demonstrated that the present e-RPIM is very accurate and stable for fracture mechanics problems.
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The research objectives of this thesis were to contribute to Bayesian statistical methodology by contributing to risk assessment statistical methodology, and to spatial and spatio-temporal methodology, by modelling error structures using complex hierarchical models. Specifically, I hoped to consider two applied areas, and use these applications as a springboard for developing new statistical methods as well as undertaking analyses which might give answers to particular applied questions. Thus, this thesis considers a series of models, firstly in the context of risk assessments for recycled water, and secondly in the context of water usage by crops. The research objective was to model error structures using hierarchical models in two problems, namely risk assessment analyses for wastewater, and secondly, in a four dimensional dataset, assessing differences between cropping systems over time and over three spatial dimensions. The aim was to use the simplicity and insight afforded by Bayesian networks to develop appropriate models for risk scenarios, and again to use Bayesian hierarchical models to explore the necessarily complex modelling of four dimensional agricultural data. The specific objectives of the research were to develop a method for the calculation of credible intervals for the point estimates of Bayesian networks; to develop a model structure to incorporate all the experimental uncertainty associated with various constants thereby allowing the calculation of more credible credible intervals for a risk assessment; to model a single day’s data from the agricultural dataset which satisfactorily captured the complexities of the data; to build a model for several days’ data, in order to consider how the full data might be modelled; and finally to build a model for the full four dimensional dataset and to consider the timevarying nature of the contrast of interest, having satisfactorily accounted for possible spatial and temporal autocorrelations. This work forms five papers, two of which have been published, with two submitted, and the final paper still in draft. The first two objectives were met by recasting the risk assessments as directed, acyclic graphs (DAGs). In the first case, we elicited uncertainty for the conditional probabilities needed by the Bayesian net, incorporated these into a corresponding DAG, and used Markov chain Monte Carlo (MCMC) to find credible intervals, for all the scenarios and outcomes of interest. In the second case, we incorporated the experimental data underlying the risk assessment constants into the DAG, and also treated some of that data as needing to be modelled as an ‘errors-invariables’ problem [Fuller, 1987]. This illustrated a simple method for the incorporation of experimental error into risk assessments. In considering one day of the three-dimensional agricultural data, it became clear that geostatistical models or conditional autoregressive (CAR) models over the three dimensions were not the best way to approach the data. Instead CAR models are used with neighbours only in the same depth layer. This gave flexibility to the model, allowing both the spatially structured and non-structured variances to differ at all depths. We call this model the CAR layered model. Given the experimental design, the fixed part of the model could have been modelled as a set of means by treatment and by depth, but doing so allows little insight into how the treatment effects vary with depth. Hence, a number of essentially non-parametric approaches were taken to see the effects of depth on treatment, with the model of choice incorporating an errors-in-variables approach for depth in addition to a non-parametric smooth. The statistical contribution here was the introduction of the CAR layered model, the applied contribution the analysis of moisture over depth and estimation of the contrast of interest together with its credible intervals. These models were fitted using WinBUGS [Lunn et al., 2000]. The work in the fifth paper deals with the fact that with large datasets, the use of WinBUGS becomes more problematic because of its highly correlated term by term updating. In this work, we introduce a Gibbs sampler with block updating for the CAR layered model. The Gibbs sampler was implemented by Chris Strickland using pyMCMC [Strickland, 2010]. This framework is then used to consider five days data, and we show that moisture in the soil for all the various treatments reaches levels particular to each treatment at a depth of 200 cm and thereafter stays constant, albeit with increasing variances with depth. In an analysis across three spatial dimensions and across time, there are many interactions of time and the spatial dimensions to be considered. Hence, we chose to use a daily model and to repeat the analysis at all time points, effectively creating an interaction model of time by the daily model. Such an approach allows great flexibility. However, this approach does not allow insight into the way in which the parameter of interest varies over time. Hence, a two-stage approach was also used, with estimates from the first-stage being analysed as a set of time series. We see this spatio-temporal interaction model as being a useful approach to data measured across three spatial dimensions and time, since it does not assume additivity of the random spatial or temporal effects.
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Urban traffic and climate change are two phenomena that have the potential to degrade urban water quality by influencing the build-up and wash-off of pollutants, respectively. However, limited knowledge has made it difficult to establish any link between pollutant buildup and wash-off under such dynamic conditions. In order to safeguard urban water quality, adaptive water quality mitigation measures are required. In this research, pollutant build-up and wash-off have been investigated from a dynamic point of view which incorporated the impacts of changed urban traffic as well as changes in the rainfall characteristics induced by climate change. The study has developed a dynamic object classification system and thereby, conceptualised the study of pollutant build-up and wash-off under future changes in urban traffic and rainfall characteristics. This study has also characterised the buildup and wash-off processes of traffic generated heavy metals, volatile, semi-volatile and non-volatile hydrocarbons under dynamic conditions which enables the development of adaptive mitigation measures for water quality. Additionally, predictive frameworks for the build-up and wash-off of some pollutants have also been developed.
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This paper presents a comprehensive study to find the most efficient bitrate requirement to deliver mobile video that optimizes bandwidth, while at the same time maintains good user viewing experience. In the study, forty participants were asked to choose the lowest quality video that would still provide for a comfortable and long-term viewing experience, knowing that higher video quality is more expensive and bandwidth intensive. This paper proposes the lowest pleasing bitrates and corresponding encoding parameters for five different content types: cartoon, movie, music, news and sports. It also explores how the lowest pleasing quality is influenced by content type, image resolution, bitrate, and user gender, prior viewing experience, and preference. In addition, it analyzes the trajectory of users’ progression while selecting the lowest pleasing quality. The findings reveal that the lowest bitrate requirement for a pleasing viewing experience is much higher than that of the lowest acceptable quality. Users’ criteria for the lowest pleasing video quality are related to the video’s content features, as well as its usage purpose and the user’s personal preferences. These findings can provide video providers guidance on what quality they should offer to please mobile users.
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Hydrocalumite (CaAl-LDH-Cl) were synthesized through a rehydration method involving a freshly prepared tricalcium aluminate (C3A) with CaCl2 solution. To understand the intercalation behaviour of sodium dodecylsulfate (SDS) with CaAl-LDH-Cl, X-ray diffraction (XRD), Fourier transform infrared (FTIR), scanning electron microscopy (SEM), transmission electron microscope (TEM), X-ray photoelectron spectroscopy (XPS), inductively coupled plasma-atomic emission spectrometer (ICP) and elemental analysis have been undertaken. The sorption isotherms with SDS reveal that the maximum sorption amount of SDS by CaAl-LDH-Cl could reach 3.67 mmol•g-1. The results revealed that CaAl-LDH-Cl holds a self-dissolution property, about 20-30% of which is dissolved. And the dissolved Ca2+, Al3+ ions are combined with SDS to form CaAl-SDS or Ca-SDS precipitation. It has been highlighted that the composition of resulting products is strongly dependent upon the SDS concentration. With increasing SDS concentrations, the main resulting product changes from CaAl-SDS to Ca-SDS, and the value of interlayer spacing increased to 3.27 nm.
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A major challenge for Streptococcus pyogenes vaccine development is the identification of epitopes that confer protection from infection by multiple S. pyogenes M-types. Here we have identified and characterised the distribution of common variant sequences from individual repeat units of the C-repeat region (CRR) of M-proteins representing 77 different M-types. Three polyvalent fusion vaccine candidates (SV1, SV2 and SV3) incorporating the most common variants were subsequently expressed and purified, and demonstrated to be alpha-helical by Circular Dichroism (CD), a secondary conformational characteristic of the CRR in the M-protein. Antibodies raised against each of these constructs recognise M-proteins that vary in their CRR, and bind to the surface of multiple S. pyogenes isolates. Antibodies raised against SV1, containing five variant sequences, also kill heterologous S. pyogenes isolates in in vitro bactericidal assays. Further structural characterisation of this construct demonstrated the conformation of SV1 was stable at different pHs, and thermal unfolding of SV1 a reversible process. Our findings demonstrate that linkage of multiple variant sequences into a single recombinant construct overcomes the need to embed the variant sequences in foreign helix promoting flanking sequences for conformational stability, and demonstrates the viability of the polyvalent candidates as global S. pyogenes vaccine candidates.