1000 resultados para Via do mevalonato


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Power system stabilizer (PSS) is one of the most important controllers in modern power systems for damping low frequency oscillations. Many efforts have been dedicated to design the tuning methodologies and allocation techniques to obtain optimal damping behaviors of the system. Traditionally, it is tuned mostly for local damping performance, however, in order to obtain a globally optimal performance, the tuning of PSS needs to be done considering more variables. Furthermore, with the enhancement of system interconnection and the increase of system complexity, new tools are required to achieve global tuning and coordination of PSS to achieve optimal solution in a global meaning. Differential evolution (DE) is a recognized as a simple and powerful global optimum technique, which can gain fast convergence speed as well as high computational efficiency. However, as many other evolutionary algorithms (EA), the premature of population restricts optimization capacity of DE. In this paper, a modified DE is proposed and applied for optimal PSS tuning of 39-Bus New-England system. New operators are introduced to reduce the probability of getting premature. To investigate the impact of system conditions on PSS tuning, multiple operating points will be studied. Simulation result is compared with standard DE and particle swarm optimization (PSO).

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In the field of face recognition, Sparse Representation (SR) has received considerable attention during the past few years. Most of the relevant literature focuses on holistic descriptors in closed-set identification applications. The underlying assumption in SR-based methods is that each class in the gallery has sufficient samples and the query lies on the subspace spanned by the gallery of the same class. Unfortunately, such assumption is easily violated in the more challenging face verification scenario, where an algorithm is required to determine if two faces (where one or both have not been seen before) belong to the same person. In this paper, we first discuss why previous attempts with SR might not be applicable to verification problems. We then propose an alternative approach to face verification via SR. Specifically, we propose to use explicit SR encoding on local image patches rather than the entire face. The obtained sparse signals are pooled via averaging to form multiple region descriptors, which are then concatenated to form an overall face descriptor. Due to the deliberate loss spatial relations within each region (caused by averaging), the resulting descriptor is robust to misalignment & various image deformations. Within the proposed framework, we evaluate several SR encoding techniques: l1-minimisation, Sparse Autoencoder Neural Network (SANN), and an implicit probabilistic technique based on Gaussian Mixture Models. Thorough experiments on AR, FERET, exYaleB, BANCA and ChokePoint datasets show that the proposed local SR approach obtains considerably better and more robust performance than several previous state-of-the-art holistic SR methods, in both verification and closed-set identification problems. The experiments also show that l1-minimisation based encoding has a considerably higher computational than the other techniques, but leads to higher recognition rates.

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Because professions seek graduates who can 'collaborate, share skills and knowledge, and communicate' (Kruck and Reif, 2001, p 37), it is important that university graduates are not equipped solely with the content knowledge of their discipline, but also with prospective employment skills. Furthermore, when students 'interact more in positive ways with their teachers and peers, they gain more in terms of essential skills and competencies, such as critical thinking, problem~solving [and] effective communication' (NSSE, 2000, p 2)./n this way, peer assisted fellowing has the potential to enhance students' professional development, and provide the social inclusion and engagement necessary for effective learning. This session describes two peer assisted learning models embedded within first year QUT Faculty of Law units. Through a partnership between teaching staff, student mentors and mentees, the models aim to facilitate student socialisation whilst supplementing understanding of substantive law with the development of academic and work·related skills. Mentor and mentee perceptions, and program implications, are considered.

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A process for catalytic conversion and/or adsorption of gases inclusive of NOx, SOx, CO2, CO, dioxins and PAHs and combinations thereof wherein said gases may contain particulates which include contacting one or more of such gases with an alumino-silicate material having: a primarily tetrahedrally co-ordinated aluminium as established by the fact that the 27 A1 Magic Angle Spinning (MAS) provides a single peak at 55-58 ppm (FWHM ~23 ppm) relative to Al(H 2 0) 6 3 and (ii) a cation exchange capacity of at least 1 meq 100 in aqueous solution at room temperature.

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Graphene has promised many novel applications in nanoscale electronics and sustainable energy due to its novel electronic properties. Computational exploration of electronic functionality and how it varies with architecture and doping presently runs ahead of experimental synthesis yet provides insights into types of structures that may prove profitable for targeted experimental synthesis and characterization. We present here a summary of our understanding on the important aspects of dimension, band gap, defect, and interfacial engineering of graphene based on state-of-the-art ab initio approaches. Some most recent experimental achievements relevant for future theoretical exploration are also covered.

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The interaction of bare graphene nanoribbons (GNRs) was investigated by ab initio density functional theory calculations with both the local density approximation (LDA) and the generalized gradient approximation (GGA). Remarkably, two bare 8-GNRs with zigzag-shaped edges are predicted to form an (8, 8) armchair single-wall carbon nanotube (SWCNT) without any obvious activation barrier. The formation of a (10, 0) zigzag SWCNT from two bare 10-GNRs with armchair-shaped edges has activation barriers of 0.23 and 0.61 eV for using the LDA and the revised PBE exchange correlation functional, respectively, Our results suggest a possible route to control the growth of specific types SWCNT via the interaction of GNRs.

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Approximate Bayesian computation has become an essential tool for the analysis of complex stochastic models when the likelihood function is numerically unavailable. However, the well-established statistical method of empirical likelihood provides another route to such settings that bypasses simulations from the model and the choices of the approximate Bayesian computation parameters (summary statistics, distance, tolerance), while being convergent in the number of observations. Furthermore, bypassing model simulations may lead to significant time savings in complex models, for instance those found in population genetics. The Bayesian computation with empirical likelihood algorithm we develop in this paper also provides an evaluation of its own performance through an associated effective sample size. The method is illustrated using several examples, including estimation of standard distributions, time series, and population genetics models.

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Periodontitis results from the destructive inflammatory reaction of the host elicited by a bacterial biofilm adhering to the tooth surface and if left untreated, may lead to the loss of the teeth and the surrounding tissues, including the alveolar bone. Cementum is a specialized calcified tissue covering the tooth root and an essential part of the periodontium which enables the attachment of the periodontal ligament to the root and the surrounding alveolar bone. Periodontal ligament cells (PDLCs) represent a promising cell source for periodontal tissue engineering. Since cementogenesis is the critical event for the regeneration of periodontal tissues, this study examined whether inorganic stimuli derived from bioactive bredigite (Ca7MgSi4O16) bioceramics could stimulate the proliferation and cementogenic differentiation of PDLCs, and further investigated the involvement of the Wnt/β-catenin signalling pathway during this process via analysing gene/protein expression of PDLCs which interacted with bredigite extracts. Our results showed that the ionic products from bredigite powder extracts led to significantly enhanced proliferation and cementogenic differentiation, including mineralization–nodule formation, ALP activity and a series of bone/cementum-related gene/protein expression (ALP, OPN, OCN, BSP, CAP and CEMP1) of PDLCs in a concentration dependent manner. Furthermore, the addition of cardamonin, a Wnt/β-catenin signalling inhibitor, reduced the pro-cementogenesis effect of the bredigite extracts, indicating the involvement of the Wnt/β-catenin signalling pathway in the cementogenesis of PDLCs induced by bredigite extracts. The present study suggests that an entirely inorganic stimulus with a specific composition of bredigite bioceramics possesses the capacity to trigger the activation of the Wnt/β-catenin signalling pathway, leading to stimulated differentiation of PDLCs toward a cementogenic lineage. The results indicate the therapeutic potential of bredigite ceramics in periodontal tissue engineering application.

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Controlled drug delivery is a key topic in modern pharmacotherapy, where controlled drug delivery devices are required to prolong the period of release, maintain a constant release rate, or release the drug with a predetermined release profile. In the pharmaceutical industry, the development process of a controlled drug delivery device may be facilitated enormously by the mathematical modelling of drug release mechanisms, directly decreasing the number of necessary experiments. Such mathematical modelling is difficult because several mechanisms are involved during the drug release process. The main drug release mechanisms of a controlled release device are based on the device’s physiochemical properties, and include diffusion, swelling and erosion. In this thesis, four controlled drug delivery models are investigated. These four models selectively involve the solvent penetration into the polymeric device, the swelling of the polymer, the polymer erosion and the drug diffusion out of the device but all share two common key features. The first is that the solvent penetration into the polymer causes the transition of the polymer from a glassy state into a rubbery state. The interface between the two states of the polymer is modelled as a moving boundary and the speed of this interface is governed by a kinetic law. The second feature is that drug diffusion only happens in the rubbery region of the polymer, with a nonlinear diffusion coefficient which is dependent on the concentration of solvent. These models are analysed by using both formal asymptotics and numerical computation, where front-fixing methods and the method of lines with finite difference approximations are used to solve these models numerically. This numerical scheme is conservative, accurate and easily implemented to the moving boundary problems and is thoroughly explained in Section 3.2. From the small time asymptotic analysis in Sections 5.3.1, 6.3.1 and 7.2.1, these models exhibit the non-Fickian behaviour referred to as Case II diffusion, and an initial constant rate of drug release which is appealing to the pharmaceutical industry because this indicates zeroorder release. The numerical results of the models qualitatively confirms the experimental behaviour identified in the literature. The knowledge obtained from investigating these models can help to develop more complex multi-layered drug delivery devices in order to achieve sophisticated drug release profiles. A multi-layer matrix tablet, which consists of a number of polymer layers designed to provide sustainable and constant drug release or bimodal drug release, is also discussed in this research. The moving boundary problem describing the solvent penetration into the polymer also arises in melting and freezing problems which have been modelled as the classical onephase Stefan problem. The classical one-phase Stefan problem has unrealistic singularities existed in the problem at the complete melting time. Hence we investigate the effect of including the kinetic undercooling to the melting problem and this problem is called the one-phase Stefan problem with kinetic undercooling. Interestingly we discover the unrealistic singularities existed in the classical one-phase Stefan problem at the complete melting time are regularised and also find out the small time behaviour of the one-phase Stefan problem with kinetic undercooling is different to the classical one-phase Stefan problem from the small time asymptotic analysis in Section 3.3. In the case of melting very small particles, it is known that surface tension effects are important. The effect of including the surface tension to the melting problem for nanoparticles (no kinetic undercooling) has been investigated in the past, however the one-phase Stefan problem with surface tension exhibits finite-time blow-up. Therefore we investigate the effect of including both the surface tension and kinetic undercooling to the melting problem for nanoparticles and find out the the solution continues to exist until complete melting. The investigation of including kinetic undercooling and surface tension to the melting problems reveals more insight into the regularisations of unphysical singularities in the classical one-phase Stefan problem. This investigation gives a better understanding of melting a particle, and contributes to the current body of knowledge related to melting and freezing due to heat conduction.

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In this letter the core-core-valence Auger transitions of an atomic impurity, both in bulk or adsorbed on a jellium-like surface, are computed within a DFT framework. The Auger rates calculated by the Fermi golden rule are compared with those determined by an approximate and simpler expression. This is based on the local density of states (LDOS) with a core hole present, in a region around the impurity nucleus. Different atoms, Na and Mg, solids, Al and Ag, and several impurity locations are considered. We obtain an excellent agreement between KL1V and KL23V rates worked out with the two approaches. The radius of the sphere in which we calculate the LDOS is the relevant parameter of the simpler approach. Its value only depends on the atomic species regardless of the location of the impurity and the type of substrate. (C) 2003 Elsevier B.V. All rights reserved.

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The paper utilises the Juhn Murphy and Pierce (1991) decomposition to shed light on the pattern of slow male-female wage convergance in Australia over the 1980s. The analysis allows one to distinguish between the role of wage structure and genderspecific effects. The central question addressed is whether rising wage inequality counteracted the forces of increased female investment in labour market skills, i.e. education and experience. The conclusion is that in contrast to the US and the UK, Australian women do not appear to have been swimming against a tide of adverse wage structure changes.

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Background & aims: - Excess adiposity (overweight) is one of numerous risk factors for cardiometabolic disease. Most risk reduction strategies for overweight rely on weight loss through dietary energy restriction. However, since the evidence base for long-term successful weight loss interventions is scant, it is important to identify strategies for risk reduction independent of weight loss. The aim of this study was to compare the effects of isoenergetic substitution of dietary saturated fat (SFA) with monounsaturated fat (MUFA) via macadamia nuts on coronary risk compared to usual diet in overweight adults. Methods: - A randomised controlled trial design, maintaining usual energy intake, but manipulating dietary lipid profile in a group of 64 (54 female, 10 male) overweight (BMI > 25), otherwise healthy, subjects. For the intervention group, energy intakes of usual (baseline) diets were calculated from multiple 3 day diet diaries, and SFA was replaced with MUFA (target: 50%E from fat as MUFA) by altering dietary SFA sources and adding macadamia nuts to the diet. Both control and intervention groups received advice on national guidelines for physical activity and adhered to the same protocol for diet diary record keeping and trial consultations. Anthropometric and clinical measures were taken at baseline and at 10 weeks. Results: A significant increase in brachial artery flow-mediated dilation (p < 0.05) was seen in the monounsaturated diet group at week 10 compared to baseline. This corresponded to significant decreases in waist circumference, total cholesterol (p < 0.05), plasma leptin and ICAM-1 (p < 0.01). Conclusions: - In patient subgroups where adherence to dietary energy-reduction is poor, isoenergetic interventions may improve endothelial function and other coronary risk factors without changes in body weight. This trial was registered with the Australia New Zealand Clinical Trial Registry (ACTRN12607000106437).

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Generating nano-sized materials of a controlled size and chemical composition is essential for the manufacturing of materials with enhanced properties on an industrial scale, as well as for research purposes, such as toxicological studies. Among the generation methods for airborne nanoparticles (also known as aerosolisation methods), liquid-phase techniques have been widely applied due to the simplicity of their use and their high particle production rate. The use of a collison nebulizer is one such technique, in which the atomisation takes place as a result of the liquid being sucked into the air stream and injected toward the inner walls of the nebulizer reservoir via nozzles, before the solution is dispersed. Despite the above-mentioned benefits, this method also falls victim to various sources of impurities (Knight and Petrucci 2003; W. LaFranchi, Knight et al. 2003). Since these impurities can affect the characterization of the generated nanoparticles, it is crucial to understand and minimize their effect.

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Immune reactions play important roles in determining the in vivo fate of bone substitute materials, either in new bone formation or inflammatory fibrous tissue encapsulation. The paradigm for the development of bone substitute materials has been shifted from inert to immunomodulatory materials, emphasizing the importance of immune cells in the material evaluation. Macrophages, the major effector cells in the immune reaction to implants, are indispensable for osteogenesis and their heterogeneity and plasticity render macrophages a primer target for immune system modulation. However, there are very few reports about the effects of macrophages on biomaterial-regulated osteogenesis. In this study, we used b-tricalcium phosphate (b-TCP) as a model biomaterial to investigate the role of macrophages on the material stimulated osteogenesis. The macrophage phenotype switched to M2 extreme in response to b-TCP extracts, which was related to the activation of calcium-sensing receptor (CaSR) pathway. Bone morphogenetic protein 2 (BMP2) was also significantly upregulated by the b-TCP stimulation, indicating that macrophage may participate in the b-TCP stimulated osteogenesis. Interestingly, when macrophageconditioned b-TCP extracts were applied to bone marrow mesenchymal stem cells (BMSCs), the osteogenic differentiation of BMSCs was significantly enhanced, indicating the important role of macrophages in biomaterial-induced osteogenesis. These findings provided valuable insights into the mechanism of material-stimulated osteogenesis, and a strategy to optimize the evaluation system for the in vitro osteogenesis capacity of bone substitute materials.