999 resultados para Equilibrium distributions


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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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Aiming at the shortage of prevailing prediction methods about highway truck conveyance configuration in over-limit freight research that transferring the goods attributed to over-limit portion to another fully loaded truck of the same configuration and developing the truck traffic volume synchronously, a new way to get accumulated probability function of truck power tonnage in basal year by highway truck classified by wheel and axle type load mass spectrum investigation was presented. Logit models were used to forecast overall highway freight diversion and single cargo tonnage diversion when the weight rules and strict of enforcement intensity of overload were changed in scheme year. Assumption that the probability distribution of single truck loadage should be consistent with the probability distribution of single goods freighted, the model describes the truck conveyance configuration in the future under strict over-limit prohibition. The model was used and tested in Highway Over-limit Research Project in Anhui by World Bank.

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Phase-type distributions represent the time to absorption for a finite state Markov chain in continuous time, generalising the exponential distribution and providing a flexible and useful modelling tool. We present a new reversible jump Markov chain Monte Carlo scheme for performing a fully Bayesian analysis of the popular Coxian subclass of phase-type models; the convenient Coxian representation involves fewer parameters than a more general phase-type model. The key novelty of our approach is that we model covariate dependence in the mean whilst using the Coxian phase-type model as a very general residual distribution. Such incorporation of covariates into the model has not previously been attempted in the Bayesian literature. A further novelty is that we also propose a reversible jump scheme for investigating structural changes to the model brought about by the introduction of Erlang phases. Our approach addresses more questions of inference than previous Bayesian treatments of this model and is automatic in nature. We analyse an example dataset comprising lengths of hospital stays of a sample of patients collected from two Australian hospitals to produce a model for a patient's expected length of stay which incorporates the effects of several covariates. This leads to interesting conclusions about what contributes to length of hospital stay with implications for hospital planning. We compare our results with an alternative classical analysis of these data.

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In the region of self-organized criticality (SOC) interdependency between multi-agent system components exists and slight changes in near-neighbor interactions can break the balance of equally poised options leading to transitions in system order. In this region, frequency of events of differing magnitudes exhibits a power law distribution. The aim of this paper was to investigate whether a power law distribution characterized attacker-defender interactions in team sports. For this purpose we observed attacker and defender in a dyadic sub-phase of rugby union near the try line. Videogrammetry was used to capture players’ motion over time as player locations were digitized. Power laws were calculated for the rate of change of players’ relative position. Data revealed that three emergent patterns from dyadic system interactions (i.e., try; unsuccessful tackle; effective tackle) displayed a power law distribution. Results suggested that pattern forming dynamics dyads in rugby union exhibited SOC. It was concluded that rugby union dyads evolve in SOC regions suggesting that players’ decisions and actions are governed by local interactions rules.

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The effects of particulate matter on environment and public health have been widely studied in recent years. A number of studies in the medical field have tried to identify the specific effect on human health of particulate exposure, but agreement amongst these studies on the relative importance of the particles’ size and its origin with respect to health effects is still lacking. Nevertheless, air quality standards are moving, as the epidemiological attention, towards greater focus on the smaller particles. Current air quality standards only regulate the mass of particulate matter less than 10 μm in aerodynamic diameter (PM10) and less than 2.5 μm (PM2.5). The most reliable method used in measuring Total Suspended Particles (TSP), PM10, PM2.5 and PM1 is the gravimetric method since it directly measures PM concentration, guaranteeing an effective traceability to international standards. This technique however, neglects the possibility to correlate short term intra-day variations of atmospheric parameters that can influence ambient particle concentration and size distribution (emission strengths of particle sources, temperature, relative humidity, wind direction and speed and mixing height) as well as human activity patterns that may also vary over time periods considerably shorter than 24 hours. A continuous method to measure the number size distribution and total number concentration in the range 0.014 – 20 μm is the tandem system constituted by a Scanning Mobility Particle Sizer (SMPS) and an Aerodynamic Particle Sizer (APS). In this paper, an uncertainty budget model of the measurement of airborne particle number, surface area and mass size distributions is proposed and applied for several typical aerosol size distributions. The estimation of such an uncertainty budget presents several difficulties due to i) the complexity of the measurement chain, ii) the fact that SMPS and APS can properly guarantee the traceability to the International System of Measurements only in terms of number concentration. In fact, the surface area and mass concentration must be estimated on the basis of separately determined average density and particle morphology. Keywords: SMPS-APS tandem system, gravimetric reference method, uncertainty budget, ultrafine particles.