195 resultados para charged particle detector


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Infectious diseases such as SARS, influenza and bird flu may spread exponentially throughout communities. In fact, most infectious diseases remain major health risks due to the lack of vaccine or the lack of facilities to deliver the vaccines. Conventional vaccinations are based on damaged pathogens, live attenuated viruses and viral vectors. If the damage was not complete, the vaccination itself may cause adverse effects. Therefore, researchers have been prompted to prepare viable replacements for the attenuated vaccines that would be more effective and safer to use. DNA vaccines are generally composed of a double stranded plasmid that includes a gene encoding the target antigen under the transcriptional directory and control of a promoter region which is active in cells. Plasmid DNA (pDNA) vaccines allow the foreign genes to be expressed transiently in cells, mimicking intracellular pathogenic infection and inducing both humoral and cellular immune responses. Currently, because of their highly evolved and specialized components, viral systems are the most effective means for DNA delivery, and they achieve high efficiencies (generally >90%), for both DNA delivery and expression. As yet, viral-mediated deliveries have several limitations, including toxicity, limited DNA carrying capacity, restricted target to specific cell types, production and packing problems, and high cost. Thus, nonviral systems, particularly a synthetic DNA delivery system, are highly desirable in both research and clinical 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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There is considerable scientific interest in personal exposure to ultrafine particles. Owing to their small size, these particles are able to penetrate deep into the lungs, where they may cause adverse respiratory, pulmonary and cardiovascular health effects. This article presents Bayesian hierarchical models for estimating and comparing inhaled particle surface area in the lung.

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The role of different chemical compounds, particularly organics, involved in the new particle formation (NPF) and its consequent growth are not fully understood. Therefore, this study was conducted to investigate the chemistry of aerosol particles during NPF events in an urban subtropical environment. Aerosol chemical composition was measured along with particle number size distribution (PNSD) and several other air quality parameters at five sites across an urban subtropical environment. An Aerodyne compact Time-of-Flight Aerosol Mass Spectrometer (c-TOF-AMS) and a TSI Scanning Mobility Particle Sizer (SMPS) measured aerosol chemical composition and PNSD, respectively. Five NPF events, with growth rates in the range 3.3-4.6 nm, were detected at two sites. The NPF events happened on relatively warmer days with lower humidity and higher solar radiation. Temporal percent fractions of nitrate, sulphate, ammonium and organics were modelled using the Generalised Additive Model (GAM), with a basis of penalised spline. Percent fractions of organics increased after the NPF events, while the mass fraction of ammonium and sulphate decreased. This uncovered the important role of organics in the growth of newly formed particles. Three organic markers, factors f43, f44 and f57, were calculated and the f44 vs f43 trends were compared between nucleation and non-nucleation days. f44 vs f43 followed a different pattern on nucleation days compared to non-nucleation days, whereby f43 decreased for vehicle emission generated particles, while both f44 and f43 decreased for NPF generated particles. It was found for the first time that vehicle generated and newly formed particles cluster in different locations on f44 vs f43 plot and this finding can be used as a tool for source apportionment of measured particles.

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This thesis presents a comprehensive study on the influences of biodiesel chemical composition and physical properties on diesel engine exhaust particle emissions. It examines biodiesels from several feedstocks having wide variations in their chemical composition (carbon chain length, unsaturation and oxygen content) and physical properties (density, viscosity, surface tension, boiling point etc.), and evaluates their influence on exhaust particle emissions. The outcome of this thesis is significant since it reveals the importance of regulating biodiesels chemical composition in order to ensure lowest possible emissions with better overall performance.

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A series of rubber composites were prepared by blending styrene-butadiene rubber (SBR) latex and the different particle sized kaolinites. The thermal stabilities of the rubber composites were characterized using thermogravimetry, digital photography, scanning electron microscopy, X-ray diffraction, Fourier transform infrared spectroscopy, and Raman spectroscopy. Kaolinite SBR composites showed much greater thermal stability when compared with that of the pure SBR. With the increase of kaolinite particle size, the pyrolysis products became much looser; the char layer and crystalline carbon content gradually decreased in the pyrolysis residues. The pyrolysis residues of the SBR composites filled with the different particle sized kaolinites showed some remarkable changes in structural characteristics. The increase of kaolinite particle size was not beneficial to form the compact and stable crystalline carbon in the pyrolysis process, and resulted in a negative influence in improving the thermal stability of kaolinite/SBR composites.

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Measurements of aerosol particle number size distributions (15-700 nm), CO and NOx were performed in a bus tunnel, Australia. Daily mean particle size distributions of mixed diesel/CNG (Compressed Natural Gas) buses traffic flow were determined in 4 consecutive measurement days. EFs (Emission Factors) of Particle size distribution of diesel buses and CNG buses were obtained by MLR (Multiple Linear Regression) methods, particle distributions of diesel buses and CNG buses were observed as single accumulation mode and nuclei-mode separately. Particle size distributions of mixed traffic flow were decomposed by two log-normal fitting curves for each 30 minutes interval mean scans, all the mix fleet PSD emission can be well fitted by the summation of two log-normal distribution curves, and these were composed of nuclei mode curve and accumulation curve, which were affirmed as the CNG buses and diesel buses PN emission curves respectively. Finally, particle size distributions of diesel buses and CNG buses were quantified by statistical whisker-box charts. For log-normal particle size distribution of diesel buses, accumulation mode diameters were 74.5~87.5nm, geometric standard deviations were 1.89~1.98. As to log-normal particle size distribution of CNG buses, nuclei-mode diameters were 21~24 nm, geometric standard deviations were 1.27~1.31.

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On the basis of the growing interest on the impact of airborne particles on human exposure as well as the strong debate in Western countries on the emissions of waste incinerators, this work reviewed existing literature to: (i) show the emission factors of ultrafine particles (particles with a diameter less than 100 nm) of waste incinerators, and; (ii) assess the contribution of waste incinerators in terms of ultrafine particles to exposure and dose of people living in the surrounding areas of the plants in order to estimate eventual risks. The review identified only a limited number of studies measuring ultrafine particle emissions, and in general they report low particle number concentrations at the stack (the median value was equal to 5.5×103 part cm-3), in most cases higher than the outdoor background value. The lowest emissions were achieved by utilization of the bag-house filter which has an overall number-based filtration efficiency higher than 99%. Referring to reference case, the corresponding emission factor is equal to 9.1×1012 part min-1, that is lower than one single high-duty vehicle. Since the higher particle number concentrations found in the most contributing microenvironments to the exposure (indoor home, transportation, urban outdoor), the contribution of the waste incinerators to the daily dose can be considered as negligible.

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The main aim of the present study was to estimate size segregated doses from e-cigarette aerosols as a function of the airway generation number in lung lobes.. After a 2-second puff, 7.7×1010 particles (DTot) with a surface area of 3.6×103 mm2 (STot), and 3.3×1010 particles with a surface area of 4.2×103 mm2 were deposited in the respiratory system for the electronic and conventional cigarettes, respectively. Alveolar and tracheobronchial deposited doses were compared to the ones received by non-smoking individuals in Western countries, showing a similar order of magnitude. Total regional doses (DR), in head and lobar tracheobronchial and alveolar regions, ranged from 2.7×109 to 1.3×1010 particles and 1.1×109 to 5.3×1010 particles, for the electronic and conventional cigarettes, respectively. DR in the right-upper lung lobe was about twice that found in left-upper lobe and 20% greater in right-lower lobe than the left-lower lobe.

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The aim of this paper is to determine the suitability of solely stationary measurements for exposure assessment and management applications. For this purpose, quantified inhaled particle surface area (IPSA) doses using both stationary and personal particle exposure monitors were evaluated and compared.

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The Air Pollution Model and Chemical Transport Model (TAPM-CTM) framework has been tested and applied originally in Sydney to quantify particle and gaseous concentration (Cope et al, 2014). However, the model performance had not been tested in the south-eastern Queensland region (SEQR), Australia.

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Cross-link density, microstructure and mechanical properties of styrene butadiene rubber (SBR) composites filled with different particle sized kaolinites are investigated. With the increase of kaolinite particle size, the cross-link density of the filled SBR composites, the dispersibility and orientation degree of kaolinite particles gradually decrease. Some big cracks in filled rubber composites are distributed along the fringe of kaolinite aggregates, and the absorbance of all the absorption bands of kaolinites gradually increase with the increase of kaolinite particle size. All mechanical property indexes of kaolinite filled SBR composites decrease due to the decrease of cross-linking and reduction of interface interaction between filler and rubber matrix.

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Particle Swarm Optimization (PSO) is a biologically inspired computational search and optimization method based on the social behaviors of birds flocking or fish schooling. Although, PSO is represented in solving many well-known numerical test problems, but it suffers from the premature convergence. A number of basic variations have been developed due to solve the premature convergence problem and improve quality of solution founded by the PSO. This study presents a comprehensive survey of the various PSO-based algorithms. As part of this survey, the authors have included a classification of the approaches and they have identify the main features of each proposal. In the last part of the study, some of the topics within this field that are considered as promising areas of future research are listed.