125 resultados para Serial number


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Deciding the appropriate population size and number of is- lands for distributed island-model genetic algorithms is often critical to the algorithm’s success. This paper outlines a method that automatically searches for good combinations of island population sizes and the number of islands. The method is based on a race between competing parameter sets, and collaborative seeding of new parameter sets. This method is applicable to any problem, and makes distributed genetic algorithms easier to use by reducing the number of user-set parameters. The experimental results show that the proposed method robustly and reliably finds population and islands settings that are comparable to those found with traditional trial-and-error approaches.

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The use of Bayesian methodologies for solving optimal experimental design problems has increased. Many of these methods have been found to be computationally intensive for design problems that require a large number of design points. A simulation-based approach that can be used to solve optimal design problems in which one is interested in finding a large number of (near) optimal design points for a small number of design variables is presented. The approach involves the use of lower dimensional parameterisations that consist of a few design variables, which generate multiple design points. Using this approach, one simply has to search over a few design variables, rather than searching over a large number of optimal design points, thus providing substantial computational savings. The methodologies are demonstrated on four applications, including the selection of sampling times for pharmacokinetic and heat transfer studies, and involve nonlinear models. Several Bayesian design criteria are also compared and contrasted, as well as several different lower dimensional parameterisation schemes for generating the many design points.

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Preventive Maintenance (PM) is often applied to improve the reliability of production lines. A Split System Approach (SSA) based methodology is presented to assist in making optimal PM decisions for serial production lines. The methodology treats a production line as a complex series system with multiple (imperfect) PM actions over multiple intervals. The conditional and overall reliability of the entire production line over these multiple PM intervals are hierarchically calculated using SSA, and provide a foundation for cost analysis. Both risk-related cost and maintenance-related cost are factored into the methodology as either deterministic or random variables. This SSA based methodology enables Asset Management (AM) decisions to be optimised considering a variety of factors including failure probability, failure cost, maintenance cost, PM performance, and the type of PM strategy. The application of this new methodology and an evaluation of the effects of these factors on PM decisions are demonstrated using an example. The results of this work show that the performance of a PM strategy can be measured by its Total Expected Cost Index (TECI). The optimal PM interval is dependent on TECI, PM performance and types of PM strategies. These factors are interrelated. Generally, it was found that a trade-off between reliability and the number of PM actions needs to be made so that one can minimise Total Expected Cost (TEC) for asset maintenance.

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Herein the mechanical properties of graphene, including Young’s modulus, fracture stress and fracture strain have been investigated by molecular dynamics simulations. The simulation results show that the mechanical properties of graphene are sensitive to the temperature changes but insensitive to the layer numbers in the multilayer graphene. Increasing temperature exerts adverse and significant effects on the mechanical properties of graphene. However, the adverse effect produced by the increasing layer number is marginal. On the other hand, isotope substitutions in graphene play a negligible role in modifying the mechanical properties of graphene.

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A newly developed computational approach is proposed in the paper for the analysis of multiple crack problems based on the eigen crack opening displacement (COD) boundary integral equations. The eigen COD particularly refers to a crack in an infinite domain under fictitious traction acting on the crack surface. With the concept of eigen COD, the multiple cracks in great number can be solved by using the conventional displacement discontinuity boundary integral equations in an iterative fashion with a small size of system matrix to determine all the unknown CODs step by step. To deal with the interactions among cracks for multiple crack problems, all cracks in the problem are divided into two groups, namely the adjacent group and the far-field group, according to the distance to the current crack in consideration. The adjacent group contains cracks with relatively small distances but strong effects to the current crack, while the others, the cracks of far-field group are composed of those with relatively large distances. Correspondingly, the eigen COD of the current crack is computed in two parts. The first part is computed by using the fictitious tractions of adjacent cracks via the local Eshelby matrix derived from the traction boundary integral equations in discretized form, while the second part is computed by using those of far-field cracks so that the high computational efficiency can be achieved in the proposed approach. The numerical results of the proposed approach are compared not only with those using the dual boundary integral equations (D-BIE) and the BIE with numerical Green's functions (NGF) but also with those of the analytical solutions in literature. The effectiveness and the efficiency of the proposed approach is verified. Numerical examples are provided for the stress intensity factors of cracks, up to several thousands in number, in both the finite and infinite plates.

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It has not yet been established whether the spatial variation of particle number concentration (PNC) within a microscale environment can have an effect on exposure estimation results. In general, the degree of spatial variation within microscale environments remains unclear, since previous studies have only focused on spatial variation within macroscale environments. The aims of this study were to determine the spatial variation of PNC within microscale school environments, in order to assess the importance of the number of monitoring sites on exposure estimation. Furthermore, this paper aims to identify which parameters have the largest influence on spatial variation, as well as the relationship between those parameters and spatial variation. Air quality measurements were conducted for two consecutive weeks at each of the 25 schools across Brisbane, Australia. PNC was measured at three sites within the grounds of each school, along with the measurement of meteorological and several other air quality parameters. Traffic density was recorded for the busiest road adjacent to the school. Spatial variation at each school was quantified using coefficient of variation (CV). The portion of CV associated with instrument uncertainty was found to be 0.3 and therefore, CV was corrected so that only non-instrument uncertainty was analysed in the data. The median corrected CV (CVc) ranged from 0 to 0.35 across the schools, with 12 schools found to exhibit spatial variation. The study determined the number of required monitoring sites at schools with spatial variability and tested the deviation in exposure estimation arising from using only a single site. Nine schools required two measurement sites and three schools required three sites. Overall, the deviation in exposure estimation from using only one monitoring site was as much as one order of magnitude. The study also tested the association of spatial variation with wind speed/direction and traffic density, using partial correlation coefficients to identify sources of variation and non-parametric function estimation to quantify the level of variability. Traffic density and road to school wind direction were found to have a positive effect on CVc, and therefore, also on spatial variation. Wind speed was found to have a decreasing effect on spatial variation when it exceeded a threshold of 1.5 (m/s), while it had no effect below this threshold. Traffic density had a positive effect on spatial variation and its effect increased until it reached a density of 70 vehicles per five minutes, at which point its effect plateaued and did not increase further as a result of increasing traffic density.

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This mathematics education research provides significant insights for the teaching of decimals to children. It is well known that decimals is one of the most difficult topics to learn and teach. Annette’s research is unique in that it focuses not only on the cognitive, but also on the affective and conative aspects of learning and teaching of decimals. The study is innovative as it includes the students as co-constructors and co-researchers. The findings open new ways of thinking for educators about how students cognitively process decimal knowledge, as well as how students might develop a sense of self as a learner, teacher and researcher in mathematics.

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Serial killers are among the most popular and enduring character types in contemporary culture. In this exegesis I investigate one of the reasons for this popularity by examining the representational relationships between serial killers and serial consumers. I initially establish that all monsters, whether they are vampires, werewolves or serial killers, emerge from cultural anxieties and signify the anxiety which gave them birth. I go on to identify that the cultural anxiety at play with serial killers is consumerism and in doing so, I identify two key parallels between the serial killer and the consumer, namely a sense of lack and a desire for transformation. I then examine the ways in which the serial killer is representative of the consumer in three exemplar texts, The Silence of the Lambs by Thomas Harris, American Psycho by Bret Easton Ellis and Darkly Dreaming Dexter by Jeff Lindsay. I go on to self-reflexively examine the creation of my novel Carnivore, the accompanying draft of which has been influenced by both the exemplar texts and the findings of the exegesis.

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Multiple sclerosis (MS) is a common chronic inflammatory disease of the central nervous system. Susceptibility to the disease is affected by both environmental and genetic factors. Genetic factors include haplotypes in the histocompatibility complex (MHC) and over 50 non-MHC loci reported by genome-wide association studies. Amongst these, we previously reported polymorphisms in chromosome 12q13-14 with a protective effect in individuals of European descent. This locus spans 288 kb and contains 17 genes, including several candidate genes which have potentially significant pathogenic and therapeutic implications. In this study, we aimed to fine-map this locus. We have implemented a two-phase study: a variant discovery phase where we have used next-generation sequencing and two target-enrichment strategies [long-range polymerase chain reaction (PCR) and Nimblegen's solution phase hybridization capture] in pools of 25 samples; and a genotyping phase where we genotyped 712 variants in 3577 healthy controls and 3269 MS patients. This study confirmed the association (rs2069502, P = 9.9 × 10−11, OR = 0.787) and narrowed down the locus of association to an 86.5 kb region. Although the study was unable to pinpoint the key-associated variant, we have identified a 42 (genotyped and imputed) single-nucleotide polymorphism haplotype block likely to harbour the causal variant. No evidence of association at previously reported low-frequency variants in CYP27B1 was observed. As part of the study we compared variant discovery performance using two target-enrichment strategies. We concluded that our pools enriched with Nimblegen's solution phase hybridization capture had better sensitivity to detect true variants than the pools enriched with long-range PCR, whilst specificity was better in the long-range PCR-enriched pools compared with solution phase hybridization capture enriched pools; this result has important implications for the design of future fine-mapping studies.

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This thesis developed semi-parametric regression models for estimating the spatio-temporal distribution of outdoor airborne ultrafine particle number concentration (PNC). The models developed incorporate multivariate penalised splines and random walks and autoregressive errors in order to estimate non-linear functions of space, time and other covariates. The models were applied to data from the "Ultrafine Particles from Traffic Emissions and Child" project in Brisbane, Australia, and to longitudinal measurements of air quality in Helsinki, Finland. The spline and random walk aspects of the models reveal how the daily trend in PNC changes over the year in Helsinki and the similarities and differences in the daily and weekly trends across multiple primary schools in Brisbane. Midday peaks in PNC in Brisbane locations are attributed to new particle formation events at the Port of Brisbane and Brisbane Airport.

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Individual variability in the acquisition, consolidation and extinction of conditioned fear potentially contributes to the development of fear pathology including posttraumatic stress disorder (PTSD). Pavlovian fear conditioning is a key tool for the study of fundamental aspects of fear learning. Here, we used a selected mouse line of High and Low Pavlovian conditioned fear created from an advanced intercrossed line (AIL) in order to begin to identify the cellular basis of phenotypic divergence in Pavlovian fear conditioning. We investigated whether phosphorylated MAPK (p44/42 ERK/MAPK), a protein kinase required in the amygdala for the acquisition and consolidation of Pavlovian fear memory, is differentially expressed following Pavlovian fear learning in the High and Low fear lines. We found that following Pavlovian auditory fear conditioning, High and Low line mice differ in the number of pMAPK-expressing neurons in the dorsal sub nucleus of the lateral amygdala (LAd). In contrast, this difference was not detected in the ventral medial (LAvm) or ventral lateral (LAvl) amygdala sub nuclei or in control animals. We propose that this apparent increase in plasticity at a known locus of fear memory acquisition and consolidation relates to intrinsic differences between the two fear phenotypes. These data provide important insights into the micronetwork mechanisms encoding phenotypic differences in fear. Understanding the circuit level cellular and molecular mechanisms that underlie individual variability in fear learning is critical for the development of effective treatment of fear-related illnesses such as PTSD.

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A newspaper numbers game based on simple arithmetic relationships is discussed. Its potential to give students of elementary algebra practice in semi-ad hoc reasoning and to build general arithmetic reasoning skills is explored.

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Number theory has in recent decades assumed a great practical importance, due primarily to its application to cryptography. This chapter discusses how elementary concepts of number theory may be illuminated and made accessible to upper secondary school students via appropriate spreadsheet models. In such environments, students can observe patterns, gain structural insight, form and test conjectures, and solve problems. The chapter begins by reviewing literature on the use of spreadsheets in general and the use of spreadsheets in number theory in particular. Two sample applications are then discussed. The first, factoring factorials, is presented and instructions are given to construct a model in Excel 2007. The second application, the RSA cryptosystem, is included because of its importance to Science, Technology, Engineering, and Mathematics (STEM) students. Number theoretic concepts relevant to RSA are discussed, and an outline of RSA. is given, with example. The chapter ends with instructions on how to construct a simple spreadsheet illustrating RSA.

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The routine cultivation of human corneal endothelial cells, with the view to treating patients with endothelial dysfunction, remains a challenging task. While progress in this field has been buoyed by the proposed existence of progenitor cells for the corneal endothelium at the corneal limbus, strategies for exploiting this concept remain unclear. In the course of evaluating methods for growing corneal endothelial cells, we have noted a case where remarkable growth was achieved using a serial explant culture technique. Over the course of 7 months, a single explant of corneal endothelium, acquired from cadaveric human tissue, was sequentially seeded into 7 culture plates and on each occasion produced a confluent cell monolayer. Sample cultures were confirmed as endothelial in origin by positive staining for glypican-4. On each occasion, small cells, closest to the tissue explant, developed into a highly compact layer with an almost homogenous structure. This layer was resistant to removal with trypsin and produced continuous cell outgrowth during multiple culture periods. The small cells gave rise to larger cells with phase-bright cell boundaries and prominent immunostaining for both nestin and telomerase. Nestin and telomerase were also strongly expressed in small cells immediately adjacent to the wound site, following transfer of the explant to another culture plate. These findings are consistent with the theory that progenitor cells for the corneal endothelium reside within the limbus and provide new insights into expected expression patterns for nestin and telomerase within the differentiation pathway.