174 resultados para SIZE-RAMSEY 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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In the past few years, remarkable progress has been made in unveiling novel and unique optical properties of strongly coupled plasmonic nanostructures. However, application of such plasmonic nanostructures in biomedicine remains challenging due to the lack of facile and robust assembly methods for producing stable nanostructures. Previous attempts to achieve plasmonic nano-assemblies using molecular ligands were limited due to the lack of flexibility that could be exercised in forming them. Here, we report the utilization of tailor-made hyperbranched polymers (HBP) as linkers to assemble gold nanoparticles (NPs) into nano-assemblies. The ease and flexibility in tuning the particle size and number of branch ends of a HBP makes it an ideal candidate as a linker, as opposed to DNA, small organic molecules and linear or dendrimeric polymers. We report a strong correlation of polymer (HBP) concentration with the size of the hybrid nano-assemblies and “hot-spot” density. We have shown that such solutions of stable HBP-gold nano-assemblies can be barcoded with various Raman tags to provide improved surface-enhanced Raman scattering (SERS) compared with non-aggregated NP systems. These Raman barcoded hybrid nano-assemblies, with further optimization of NP shape, size and “hot-spot” density, may find application as diagnostic tools in nanomedicine.

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Flexible tubular structures fabricated from solution electrospun fibers are finding increasing use in tissue engineering applications. However it is difficult to control the deposition of fibers due to the chaotic nature of the solution electrospinning jet. By using non-conductive polymer melts instead of polymer solutions the path and collection of the fiber becomes predictable. In this work we demonstrate the melt electrospinning of polycaprolactone in a direct writing mode onto a rotating cylinder. This allows the design and fabrication of tubes using 20 μm diameter fibers with controllable micropatterns and mechanical properties. A key design parameter is the fiber winding angle, where it allows control over scaffold pore morphology (e.g. size, shape, number and porosity). Furthermore, the establishment of a finite element model as a predictive design tool is validated against mechanical testing results of melt electrospun tubes to show that a lesser winding angle provides improved mechanical response to uniaxial tension and compression. In addition, we show that melt electrospun tubes support the growth of three different cell types in vitro and are therefore promising scaffolds for tissue engineering applications.

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A novel multiple regression method (RM) is developed to predict identity-by-descent probabilities at a locus L (IBDL), among individuals without pedigree, given information on surrounding markers and population history. These IBDL probabilities are a function of the increase in linkage disequilibrium (LD) generated by drift in a homogeneous population over generations. Three parameters are sufficient to describe population history: effective population size (Ne), number of generations since foundation (T), and marker allele frequencies among founders (p). IBD L are used in a simulation study to map a quantitative trait locus (QTL) via variance component estimation. RM is compared to a coalescent method (CM) in terms of power and robustness of QTL detection. Differences between RM and CM are small but significant. For example, RM is more powerful than CM in dioecious populations, but not in monoecious populations. Moreover, RM is more robust than CM when marker phases are unknown or when there is complete LD among founders or Ne is wrong, and less robust when p is wrong. CM utilises all marker haplotype information, whereas RM utilises information contained in each individual marker and all possible marker pairs but not in higher order interactions. RM consists of a family of models encompassing four different population structures, and two ways of using marker information, which contrasts with the single model that must cater for all possible evolutionary scenarios in CM.

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Graphene–polymer nanocomposites have promising properties as new structural and functional materials. The remarkable mechanical property enhancement in these nanocomposites is generally attributed to exceptional mechanical property of graphene and possible load transfer between graphene and polymer matrix. However, the underlying strengthening and toughening mechanisms have not been well understood. In this work, the interfacial behavior of graphene-polyethylene (PE) was investigated using molecular dynamics (MD) method. The interfacial shear force (ISF) and interfacial shear stress (ISS) between graphene and PE matrix were evaluated, taking into account graphene size, the number of graphene layers and the structural defects in graphene. MD results show that the ISS at graphene-PE interface mainly distributes at each end of the graphene nanofiller within the range of 1 nm, and much larger than that at carbon nanotube (CNT)-PE interface. Moreover, it was found that the ISS at graphene-PE interface is sensitive to the layer number.

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Analysis of the particulate size and number concentration emissions from a fleet of inner city medium duty CNG buses was conducted using the newly available Diffusion Size Classifier in comparison with more traditional SMPS's and CPC's. Studies were conducted at both steady state and transient driving modes on a vehicle dynamometer utilising a CVS dilution system. Comparative analysis of the results showed that the DiSC provided equivalent information during steady state conditions and was able to provide additional information during transient conditions, namely, the modal diameter of the particle size distribution.

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The authors combine nanostenciling and pulsed laser deposition to patterngermanium(Ge)nanostructures into desired architectures. They have analyzed the evolution of the Ge morphology with coverage. Following the formation of a wetting layer within each area defined by the stencil’s apertures, Gegrowth becomes three dimensional and the size and number of Ge nanocrystals evolve with coverage. Micro-Raman spectroscopy shows that the deposits are crystalline and epitaxial. This approach is promising for the parallel patterning of semiconductor nanostructures for optoelectronic applications.

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Long-term measurements of particle number size distribution (PNSD) produce a very large number of observations and their analysis requires an efficient approach in order to produce results in the least possible time and with maximum accuracy. Clustering techniques are a family of sophisticated methods which have been recently employed to analyse PNSD data, however, very little information is available comparing the performance of different clustering techniques on PNSD data. This study aims to apply several clustering techniques (i.e. K-means, PAM, CLARA and SOM) to PNSD data, in order to identify and apply the optimum technique to PNSD data measured at 25 sites across Brisbane, Australia. A new method, based on the Generalised Additive Model (GAM) with a basis of penalised B-splines, was proposed to parameterise the PNSD data and the temporal weight of each cluster was also estimated using the GAM. In addition, each cluster was associated with its possible source based on the results of this parameterisation, together with the characteristics of each cluster. The performances of four clustering techniques were compared using the Dunn index and Silhouette width validation values and the K-means technique was found to have the highest performance, with five clusters being the optimum. Therefore, five clusters were found within the data using the K-means technique. The diurnal occurrence of each cluster was used together with other air quality parameters, temporal trends and the physical properties of each cluster, in order to attribute each cluster to its source and origin. The five clusters were attributed to three major sources and origins, including regional background particles, photochemically induced nucleated particles and vehicle generated particles. Overall, clustering was found to be an effective technique for attributing each particle size spectra to its source and the GAM was suitable to parameterise the PNSD data. These two techniques can help researchers immensely in analysing PNSD data for characterisation and source apportionment purposes.

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Knowledge of particle emission characteristics associated with forest fires and in general, biomass burning, is becoming increasingly important due to the impact of these emissions on human health. Of particular importance is developing a better understanding of the size distribution of particles generated from forest combustion under different environmental conditions, as well as provision of emission factors for different particle size ranges. This study was aimed at quantifying particle emission factors from four types of wood found in South East Queensland forests: Spotted Gum (Corymbia citriodora), Red Gum (Eucalypt tereticornis), Blood Gum (Eucalypt intermedia), and Iron bark (Eucalypt decorticans); under controlled laboratory conditions. The experimental set up included a modified commercial stove connected to a dilution system designed for the conditions of the study. Measurements of particle number size distribution and concentration resulting from the burning of woods with a relatively homogenous moisture content (in the range of 15 to 26 %) and for different rates of burning were performed using a TSI Scanning Mobility Particle Sizer (SMPS) in the size range from 10 to 600 nm and a TSI Dust Trak for PM2.5. The results of the study in terms of the relationship between particle number size distribution and different condition of burning for different species show that particle number emission factors and PM2.5 mass emission factors depend on the type of wood and the burning rate; fast burning or slow burning. The average particle number emission factors for fast burning conditions are in the range of 3.3 x 1015 to 5.7 x 1015 particles/kg, and for PM2.5 are in the range of 139 to 217 mg/kg.

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Size distributions of expiratory droplets expelled during coughing and speaking and the velocities of the expiration air jets of healthy volunteers were measured. Droplet size was measured using the Interferometric Mie imaging (IMI) technique while the Particle Image Velocimetry (PIV) technique was used for measuring air velocity. These techniques allowed measurements in close proximity to the mouth and avoided air sampling losses. The average expiration air velocity was 11.7 m/s for coughing and 3.9 m/s for speaking. Under the experimental setting, evaporation and condensation effects had negligible impact on the measured droplet size. The geometric mean diameter of droplets from coughing was 13.5m and it was 16.0m for speaking (counting 1 to 100). The estimated total number of droplets expelled ranged from 947 – 2085 per cough and 112 – 6720 for speaking. The estimated droplet concentrations for coughing ranged from 2.4 - 5.2cm-3 per cough and 0.004 – 0.223 cm-3 for speaking.

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A new Expiratory Droplet Investigation System (EDIS) was used to conduct the most comprehensive program of study to date, of the dilution corrected droplet size distributions produced during different respiratory activities.----- Distinct physiological processes were responsible for specific size distribution modes. The majority of particles for all activities were produced in one or more modes, with diameters below 0.8 µm. That mode occurred during all respiratory activities, including normal breathing. A second mode at 1.8 µm was produced during all activities, but at lower concentrations.----- Speech produced particles in modes near 3.5 µm and 5 µm. The modes became most pronounced during continuous vocalization, suggesting that the aerosolization of secretions lubricating the vocal chords is a major source of droplets in terms of number.----- Non-eqilibrium droplet evaporation was not detectable for particles between 0.5 and 20 μm implying that evaporation to the equilibrium droplet size occurred within 0.8 s.

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The measurement of submicrometre (< 1.0 m) and ultrafine particles (diameter < 0.1 m) number concentration have attracted attention since the last decade because the potential health impacts associated with exposure to these particles can be more significant than those due to exposure to larger particles. At present, ultrafine particles are not regularly monitored and they are yet to be incorporated into air quality monitoring programs. As a result, very few studies have analysed their long-term and spatial variations in ultrafine particle concentration, and none have been in Australia. To address this gap in scientific knowledge, the aim of this research was to investigate the long-term trends and seasonal variations in particle number concentrations in Brisbane, Australia. Data collected over a five-year period were analysed using weighted regression models. Monthly mean concentrations in the morning (6:00-10:00) and the afternoon (16:00-19:00) were plotted against time in months, using the monthly variance as the weights. During the five-year period, submicrometre and ultrafine particle concentrations increased in the morning by 105.7% and 81.5% respectively whereas in the afternoon there was no significant trend. The morning concentrations were associated with fresh traffic emissions and the afternoon concentrations with the background. The statistical tests applied to the seasonal models, on the other hand, indicated that there was no seasonal component. The spatial variation in size distribution in a large urban area was investigated using particle number size distribution data collected at nine different locations during different campaigns. The size distributions were represented by the modal structures and cumulative size distributions. Particle number peaked at around 30 nm, except at an isolated site dominated by diesel trucks, where the particle number peaked at around 60 nm. It was found that ultrafine particles contributed to 82%-90% of the total particle number. At the sites dominated by petrol vehicles, nanoparticles (< 50 nm) contributed 60%-70% of the total particle number, and at the site dominated by diesel trucks they contributed 50%. Although the sampling campaigns took place during different seasons and were of varying duration these variations did not have an effect on the particle size distributions. The results suggested that the distributions were rather affected by differences in traffic composition and distance to the road. To investigate the occurrence of nucleation events, that is, secondary particle formation from gaseous precursors, particle size distribution data collected over a 13 month period during 5 different campaigns were analysed. The study area was a complex urban environment influenced by anthropogenic and natural sources. The study introduced a new application of time series differencing for the identification of nucleation events. To evaluate the conditions favourable to nucleation, the meteorological conditions and gaseous concentrations prior to and during nucleation events were recorded. Gaseous concentrations did not exhibit a clear pattern of change in concentration. It was also found that nucleation was associated with sea breeze and long-range transport. The implications of this finding are that whilst vehicles are the most important source of ultrafine particles, sea breeze and aged gaseous emissions play a more important role in secondary particle formation in the study area.

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Mechanical harmonic transmissions are relatively new kind of drives having several unusual features. For example, they can provide reduction ratio up to 500:1 in one stage, have very small teeth module compared to conventional drives and very large number of teeth (up to 1000) on a flexible gear. If for conventional drives manufacturing methods are well-developed, fabrication of large size harmonic drives presents a challenge. For example, how to fabricate a thin shell of 1.7m in diameter and wall thickness of 30mm having high precision external teeth at one end and internal splines at the other end? It is so flexible that conventional fabrication methods become unsuitable. In this paper special fabrication methods are discussed that can be used for manufacturing of large size harmonic drive components. They include electro-slag welding and refining, the use of special expandable devices to locate and hold a flexible gear, welding peripheral parts of disks with wear resistant materials with subsequent machining and others. These fabrication methods proved to be effective and harmonic drives built with the use of these innovative technologies have been installed on heavy metallurgical equipment and successfully tested.

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Motor vehicles are major emitters of gaseous and particulate pollution in urban areas, and exposure to particulate pollution can have serious health effects, ranging from respiratory and cardiovascular disease to mortality. Motor vehicle tailpipe particle emissions span a broad size range from 0.003-10µm, and are measured as different subsets of particle mass concentrations or particle number count. However, no comprehensive inventories currently exist in the international published literature covering this wide size range. This paper presents the first published comprehensive inventory of motor vehicle tailpipe particle emissions covering the full size range of particles emitted. The inventory was developed for urban South-East Queensland by combining two techniques from distinctly different disciplines, from aerosol science and transport modelling. A comprehensive set of particle emission factors were combined with traffic modelling, and tailpipe particle emissions were quantified for particle number (ultrafine particles), PM1, PM2.5 and PM10 for light and heavy duty vehicles and buses. A second aim of the paper involved using the data derived in this inventory for scenario analyses, to model the particle emission implications of different proportions of passengers travelling in light duty vehicles and buses in the study region, and to derive an estimate of fleet particle emissions in 2026. It was found that heavy duty vehicles (HDVs) in the study region were major emitters of particulate matter pollution, and although they contributed only around 6% of total regional vehicle kilometres travelled, they contributed more than 50% of the region’s particle number (ultrafine particles) and PM1 emissions. With the freight task in the region predicted to double over the next 20 years, this suggests that HDVs need to be a major focus of mitigation efforts. HDVs dominated particle number (ultrafine particles) and PM1 emissions; and LDV PM2.5 and PM10 emissions. Buses contributed approximately 1-2% of regional particle emissions.