33 resultados para BPE-RPC conjugate

em Queensland University of Technology - ePrints Archive


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Background Recurrent protracted bacterial bronchitis (PBB), chronic suppurative lung disease (CSLD) and bronchiectasis are characterised by a chronic wet cough and are important causes of childhood respiratory morbidity globally. Haemophilus influenzae and Streptococcus pneumoniae are the most commonly associated pathogens. As respiratory exacerbations impair quality of life and may be associated with disease progression, we will determine if the novel 10-valent pneumococcal-Haemophilus influenzae protein D conjugate vaccine (PHiD-CV) reduces exacerbations in these children. Methods A multi-centre, parallel group, double-blind, randomised controlled trial in tertiary paediatric centres from three Australian cities is planned. Two hundred six children aged 18 months to 14 years with recurrent PBB, CSLD or bronchiectasis will be randomised to receive either two doses of PHiD-CV or control meningococcal (ACYW(135)) conjugate vaccine 2 months apart and followed for 12 months after the second vaccine dose. Randomisation will be stratified by site, age (<6 years and >= 6 years) and aetiology (recurrent PBB or CSLD/bronchiectasis). Clinical histories, respiratory status (including spirometry in children aged >= 6 years), nasopharyngeal and saliva swabs, and serum will be collected at baseline and at 2, 3, 8 and 14 months post-enrolment. Local and systemic reactions will be recorded on daily diaries for 7 and 30 days, respectively, following each vaccine dose and serious adverse events monitored throughout the trial. Fortnightly, parental contact will help record respiratory exacerbations. The primary outcome is the incidence of respiratory exacerbations in the 12 months following the second vaccine dose. Secondary outcomes include: nasopharyngeal carriage of H. influenzae and S. pneumoniae vaccine and vaccine-related serotypes; systemic and mucosal immune responses to H. influenzae proteins and S. pneumoniae vaccine and vaccine-related serotypes; impact upon lung function in children aged >= 6 years; and vaccine safety. Discussion As H. influenzae is the most common bacterial pathogen associated with these chronic respiratory diseases in children, a novel pneumococcal conjugate vaccine that also impacts upon H. influenzae and helps prevent respiratory exacerbations would assist clinical management with potential short- and long-term health benefits. Our study will be the first to assess vaccine efficacy targeting H. influenzae in children with recurrent PBB, CSLD and bronchiectasis.

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Objective To evaluate the effectiveness of the 7-valent pneumococcal conjugate vaccine (PCV7) in preventing pneumonia, diagnosed radiologically according to World Health Organization (WHO) criteria, among indigenous infants in the Northern Territory of Australia. Methods We conducted a historical cohort study of consecutive indigenous birth cohorts between 1 April 1998 and 28 February 2005. Children were followed up to 18 months of age. The PCV7 programme commenced on 1 June 2001. All chest X-rays taken within 3 days of any hospitalization were assessed. The primary endpoint was a first episode of WHO-defined pneumonia requiring hospitalization. Cox proportional hazards models were used to compare disease incidence. Findings There were 526 pneumonia events among 10 600 children - an incidence of 3.3 per 1000 child-months; 183 episodes (34.8%) occurred before 5 months of age and 247 (47.0%) by 7 months. Of the children studied, 27% had received 3 doses of vaccine by 7 months of age. Hazard ratios for endpoint pneumonia were 1.01 for 1 versus 0 doses; 1.03 for 2 versus 0 doses; and 0.84 for 3 versus 0 doses. Conclusion There was limited evidence that PCV7 reduced the incidence of radiologically confirmed pneumonia among Northern Territory indigenous infants, although there was a non-significant trend towards an effect after receipt of the third dose. These findings might be explained by lack of timely vaccination and/or occurrence of disease at an early age. Additionally, the relative contribution of vaccine-type pneumococcus to severe pneumonia in a setting where multiple other pathogens are prevalent may differ with respect to other settings where vaccine efficacy has been clearly established.

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Herein are reported the synthesis of a conjugate of chitosan with L-leucine, the preparation of nanoparticles from both chitosan and the conjugate for use in pulmonary drug delivery, and the in vitro evaluation of toxicity and inflammatory effects of both the polymers and their nanoparticles on the bronchial epithelial cell line, BEAS-2B. The nanoparticles, successfully prepared both from chitosan and the conjugate, had a diameter in the range of 10−30 nm. The polymers and their nanoparticles were tested for their effects on cell viability by MTT assay, on trans-epithelial permeability by using sodium fluorescein as a fluid phase marker, and on IL-8 secretion by ELISA. The conjugate nanoparticles had a low overall toxicity (IC50 = 2 mg/mL following 48 h exposure; no induction of IL-8 release at 0.5 mg/mL concentration), suggesting that they may be safe for pulmonary drug delivery applications.

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The selection criteria for contractor pre-qualification are characterized by the co-existence of both quantitative and qualitative data. The qualitative data is non-linear, uncertain and imprecise. An ideal decision support system for contractor pre-qualification should have the ability of handling both quantitative and qualitative data, and of mapping the complicated nonlinear relationship of the selection criteria, such that rational and consistent decisions can be made. In this research paper, an artificial neural network model was developed to assist public clients identifying suitable contractors for tendering. The pre-qualification criteria (variables) were identified for the model. One hundred and twelve real pre-qualification cases were collected from civil engineering projects in Hong Kong, and eighty-eight hypothetical pre-qualification cases were also generated according to the “If-then” rules used by professionals in the pre-qualification process. The results of the analysis totally comply with current practice (public developers in Hong Kong). Each pre-qualification case consisted of input ratings for candidate contractors’ attributes and their corresponding pre-qualification decisions. The training of the neural network model was accomplished by using the developed program, in which a conjugate gradient descent algorithm was incorporated for improving the learning performance of the network. Cross-validation was applied to estimate the generalization errors based on the “re-sampling” of training pairs. The case studies show that the artificial neural network model is suitable for mapping the complicated nonlinear relationship between contractors’ attributes and their corresponding pre-qualification (disqualification) decisions. The artificial neural network model can be concluded as an ideal alternative for performing the contractor pre-qualification task.

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We describe the design and implementation of a public-key platform, secFleck, based on a commodity Trusted Platform Module (TPM) chip that extends the capability of a standard node. Unlike previous software public-key implementations this approach provides E- Commerce grade security; is computationally fast, energy efficient; and has low financial cost — all essential attributes for secure large-scale sen- sor networks. We describe the secFleck message security services such as confidentiality, authenticity and integrity, and present performance re- sults including computation time, energy consumption and cost. This is followed by examples, built on secFleck, of symmetric key management, secure RPC and secure software update.

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This article presents the design and implementation of a trusted sensor node that provides Internet-grade security at low system cost. We describe trustedFleck, which uses a commodity Trusted Platform Module (TPM) chip to extend the capabilities of a standard wireless sensor node to provide security services such as message integrity, confidentiality, authenticity, and system integrity based on RSA public-key and XTEA-based symmetric-key cryptography. In addition trustedFleck provides secure storage of private keys and provides platform configuration registers (PCRs) to store system configurations and detect code tampering. We analyze system performance using metrics that are important for WSN applications such as computation time, memory size, energy consumption and cost. Our results show that trustedFleck significantly outperforms previous approaches (e.g., TinyECC) in terms of these metrics while providing stronger security levels. Finally, we describe a number of examples, built on trustedFleck, of symmetric key management, secure RPC, secure software update, and remote attestation.

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A hybrid genetic algorithm/scaled conjugate gradient regularisation method is designed to alleviate ANN `over-fitting'. In application to day-ahead load forecasting, the proposed algorithm performs better than early-stopping and Bayesian regularisation, showing promising initial results.

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Gradient-based approaches to direct policy search in reinforcement learning have received much recent attention as a means to solve problems of partial observability and to avoid some of the problems associated with policy degradation in value-function methods. In this paper we introduce GPOMDP, a simulation-based algorithm for generating a biased estimate of the gradient of the average reward in Partially Observable Markov Decision Processes (POMDPs) controlled by parameterized stochastic policies. A similar algorithm was proposed by Kimura, Yamamura, and Kobayashi (1995). The algorithm's chief advantages are that it requires storage of only twice the number of policy parameters, uses one free parameter β ∈ [0,1) (which has a natural interpretation in terms of bias-variance trade-off), and requires no knowledge of the underlying state. We prove convergence of GPOMDP, and show how the correct choice of the parameter β is related to the mixing time of the controlled POMDP. We briefly describe extensions of GPOMDP to controlled Markov chains, continuous state, observation and control spaces, multiple-agents, higher-order derivatives, and a version for training stochastic policies with internal states. In a companion paper (Baxter, Bartlett, & Weaver, 2001) we show how the gradient estimates generated by GPOMDP can be used in both a traditional stochastic gradient algorithm and a conjugate-gradient procedure to find local optima of the average reward. ©2001 AI Access Foundation and Morgan Kaufmann Publishers. All rights reserved.

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The New Hebrides Island Arc, an intra-oceanic island chain in the southwest Pacific, is formed by subduction of the Indo-Australian Plate beneath the Pacific Plate. The southern end of the New Hebrides Island Arc is an ideal location to study the magmatic and tectonic interaction of an emerging island arc as this part of the island chain is less than 3 million years old. A tectonically complex island arc, it exhibits a change in relative subduction rate from ~12cm/yr to 6 cm/yr before transitioning to a left-lateral strike slip zone at its southern end. Two submarine volcanic fields, Gemini-Oscostar and Volsmar, occur at this transition from normal arc subduction to sinistral strike slip movement. Multi-beam bathymetry and dredge samples collected during the 2004 CoTroVE cruise onboard the RV Southern Surveyor help define the relationship between magmatism and tectonics, and the source for these two submarine volcanic fields. Gemini-Oscostar volcanic field (GOVF), dominated by northwest-oriented normal faults, has mature polygenetic stratovolcanoes with evidence for explosive subaqueous eruptions and homogeneous monogenetic scoria cones. Volsmar volcanic field (VVF), located 30 km south of GOVF, exhibits a conjugate set of northwest and eastwest-oriented normal faults, with two polygenetic stratovolcanoes and numerous monogenetic scoria cones. A deep water caldera provides evidence for explosive eruptions at 1500m below sea level in the VVF. Both volcanic fields are dominated by low-K island arc tholeiites and basaltic andesites with calcalkalic andesite and dacite being found only in the GOVF. Geochemical signatures of both volcanic fields continue the along-arc trend of decreasing K2O with both volcanic fields being similar to the New Hebrides central chain lavas. Lavas from both fields display a slight depletion in high field strength elements and heavy rare earth elements, and slight enrichments in large-ion lithophile elements and light rare earth elements with respect to N-MORB mantle. Sr and Nd isotope data correlate with heavy rare earth and high field strength element data to show that both fields are derived from depleted mantle. Pb isotopes define Pacific MORB mantle sources and are consistent with isotopic variation along the New Hebrides Island Arc. Pb isotopes show no evidence for sediment contamination; the subduction component enrichment is therefore a slab-derived enrichment. There is a subtle spatial variation in source chemistry which sees a northerly trend of decreasing enrichment of slab-derived fluids.

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Here we present a sequential Monte Carlo (SMC) algorithm that can be used for any one-at-a-time Bayesian sequential design problem in the presence of model uncertainty where discrete data are encountered. Our focus is on adaptive design for model discrimination but the methodology is applicable if one has a different design objective such as parameter estimation or prediction. An SMC algorithm is run in parallel for each model and the algorithm relies on a convenient estimator of the evidence of each model which is essentially a function of importance sampling weights. Other methods for this task such as quadrature, often used in design, suffer from the curse of dimensionality. Approximating posterior model probabilities in this way allows us to use model discrimination utility functions derived from information theory that were previously difficult to compute except for conjugate models. A major benefit of the algorithm is that it requires very little problem specific tuning. We demonstrate the methodology on three applications, including discriminating between models for decline in motor neuron numbers in patients suffering from neurological diseases such as Motor Neuron disease.