993 resultados para Distributions (Statistics).
Resumo:
Many studies have shown that the effectiveness of radiations of varying LET is similar when yields of dsb have been measured, despite large differences in biological response. Recent evidence has suggested however, that current techniques underestimate the yields of dsb. By monitoring the fragmentation of DNA over a wide range of fragment sizes ( 6 Mbp) by pulsed field electrophoresis, RBE values greater than 1.0 for radiations of around 100 keV/mm have been determined. The data provide evidence for the production of correlated breaks produced within cells as particle tracks traverse the nucleus. The highly ordered structure of DNA within mammalian cells may lead to clustering of breaks over distances related to the repeating unit structures of the chromatin. As well as these regionally damaged sites, a major contributor to radiation effectiveness will be the localised clustering of damage in the 1 - 20 bp region. A major effort is required to elucidate the relative importance of these levels of clustering and their importance in biological response.
Resumo:
Non-resonant multiphoton ionization combined with quadrupole and time-of-flight analysis has been used to study sputtering by both atomic and molecular ion beams. The mass spectra and energy distributions of both sputtered atoms and secondary ions produced by 3.6 keV Ar+, N+, N-2(+), CF2+ and CF3+ ion bombardment at 45 degrees to a polycrystalline copper target have been measured. The energy distributions of the copper ions and atoms are found to be different and quite complex. The ion distributions can generally be described by a linear collision cascade model, with possible evidence for a knock-on contribution. The sputtered atom distributions are partially described by a combination of linear collision cascade and dense cascade (thermal spike) models. This is interpreted as support for a time-evolving sputtering mechanism.
Resumo:
This paper presents a new algorithm for learning the structure of a special type of Bayesian network. The conditional phase-type (C-Ph) distribution is a Bayesian network that models the probabilistic causal relationships between a skewed continuous variable, modelled by the Coxian phase-type distribution, a special type of Markov model, and a set of interacting discrete variables. The algorithm takes a dataset as input and produces the structure, parameters and graphical representations of the fit of the C-Ph distribution as output.The algorithm, which uses a greedy-search technique and has been implemented in MATLAB, is evaluated using a simulated data set consisting of 20,000 cases. The results show that the original C-Ph distribution is recaptured and the fit of the network to the data is discussed.
Resumo:
1. We present a model of the ideal free distribution (IFD) where differences between phenotypes other than those involved in direct competition for resources are considered. We show that these post-acquisitional differences can have a dramatic impact on the predicted distributions of individuals.
2. Specifically, we predict that, when the relative abilities of phenotypes are independent of location, there will be a continuum of mixed evolutionarily stable strategy (ESS) distributions (where all phenotypes are present in all patches).
3, When the relative strengths of the post-acquisitional trait in the two phenotypes differ between patches, however, we predict only a single ESS at equilibrium. Further, this distribution may be fully or partially segregated (with the distribution of at least one phenotype being spatially restricted) but it will never be mixed.
4, Our results for post-acquisitional traits mirror those of Parker (1982) for direct competitive traits. This comparison illustrates that it does not matter whether individual differences are expressed before or after competition for resources, they will still exert considerable influence on the distribution of the individuals concerned.
Resumo:
Coxian phase-type distributions are becoming a popular means of representing survival times within a health care environment. They are favoured as they show a distribution as a system of phases and can allow for an easy visual representation of the rate of flow of patients through a system. Difficulties arise, however, in determining the parameter estimates of the Coxian phase-type distribution. This paper examines ways of making the fitting of the Coxian phase-type distribution less cumbersome by outlining different software packages and algorithms available to perform the fit and assessing their capabilities through a number of performance measures. The performance measures rate each of the methods and help in identifying the more efficient. Conclusions drawn from these performance measures suggest SAS to be the most robust package. It has a high rate of convergence in each of the four example model fits considered, short computational times, detailed output, convergence criteria options, along with a succinct ability to switch between different algorithms.
Resumo:
Conditional Gaussian (CG) distributions allow the inclusion of both discrete and continuous variables in a model assuming that the continuous variable is normally distributed. However, the CG distributions have proved to be unsuitable for survival data which tends to be highly skewed. A new method of analysis is required to take into account continuous variables which are not normally distributed. The aim of this paper is to introduce the more appropriate conditional phase-type (C-Ph) distribution for representing a continuous non-normal variable while also incorporating the causal information in the form of a Bayesian network.
Resumo:
The influence of bottom topography on the distribution of temperature and salinity in the Indonesian seas region has been studied with a high-resolution model based on the Princeton Ocean Model. One of the distinctive properties of the model is an adequate reproduction of all major topographic features in the region by the model bottom relief. The three major routes of flow of Pacific water through the region have been identified. The western route follows the flow of North Pacific Water through the Sulawesi Sea, Makassar Strait, Flores Sea, and Banda Sea. This is the main branch of the Indonesian Throughflow. The eastern routes follow the flow of South Pacific water through the eastern Indonesian seas. This water enters the region either through the Halmahera Sea or by flowing to the north around Halmahera Island into the Morotai Basin and then into the Maluku Sea. A deep southward flow of South Pacific Water fills the Seram Sea below 1200 m through the Lifamatola Passage. As it enters the Seram Sea, this overflow turns eastward at depths greater than 2000 m, then upwells in the eastern part of the Seram Sea before returning westward at ~1500-2000 m. The flow continues westward across the Seram Sea, spreading to greater depths before entering the Banda Sea at the Buru-Mangole passage. It is this water that shapes the temperature and salinity of the deep Banda Sea. Topographic elevations break the Indonesian seas region down into separate basins. The difference in the distributions of potential temperature, ?, and salinity, S, in adjacent basins is primarily due to specific properties of advection of ? and S across a topographic rise. By and large, the topographic rise blocks deep flow between basins whereas water shallower than the depth of the rise is free to flow between basins. To understand this process, the structure of simulated fields of temperature and salinity has been analyzed. To identify a range of advected ? or S, special sections over the sills with isotherms or isohalines and isotachs of normal velocity have been considered. Following this approach the impact of various topographic rises on the distribution of ? and S has been identified. There are no substantial structural changes of potential temperature and salinity distributions between seasons, though values of some parameters of temperature and salinity distributions, e.g., magnitudes of maxima and minima, can change. It is shown that the main structure of the observed distributions of temperature and salinity is satisfactorily reproduced by the model throughout the entire domain.
Resumo:
In three studies we looked at two typical misconceptions of probability: the representativeness heuristic, and the equiprobability bias. The literature on statistics education predicts that some typical errors and biases (e.g., the equiprobability bias) increase with education, whereas others decrease. This is in contrast with reasoning theorists’ prediction who propose that education reduces misconceptions in general. They also predict that students with higher cognitive ability and higher need for cognition are less susceptible to biases. In Experiments 1 and 2 we found that the equiprobability bias increased with statistics education, and it was negatively correlated with students’ cognitive abilities. The representativeness heuristic was mostly unaffected by education, and it was also unrelated to cognitive abilities. In Experiment 3 we demonstrated through an instruction manipulation (by asking participants to think logically vs. rely on their intuitions) that the reason for these differences was that these biases originated in different cognitive processes.
Resumo:
Near-infrared diffuse tomography was used in order to observe dynamic behaviour of flowing gases by measuring the 3D distributions of composition and temperature in a weakly scattering packed bed reactor, subject to wall effects and non-isothermal conditions. The technique was applied to the vapour phase hydrogen isotopic exchange reaction in a hydrophobic packing of low aspect ratio made of platinum on styrene divinyl benzene sulphonate copolymer resin. The results of tomography revealed uneven temperature and composition maps of water and deuterated water vapours in the core-packed bed and in the vicinity of the wall owing to flow maldistribution. The dynamic lag between the near-wall water vapour and deuterated water vapour compositions were observed suggesting that the convective transfer which was significant near the wall at the start, owing to high porosity, was also effective at large conversions. (C) 2012 Elsevier B.V. All rights reserved.
Resumo:
Emission line fluxes from cool stars are widely used to establish an apparent emission measure distribution, EmdApp(Te), between temperatures characteristic of the low transition region and the low corona. The true emission measure distribution, EmdTrue(Te), is determined by the energy balance and geometry adopted and, with a numerical model, can be used to predict EmdApp(Te), to guide further modelling. The scaling laws that exist between coronal parameters arise from the dimensions of the terms in the energy balance equation. Here, analytical approximations to numerical solutions for EmdTrue(Te) are presented, which show how the constants in the coronal scaling laws are determined. The apparent emission measure distributions show a minimum value at some T0 and a maximum at the mean coronal temperature Tc (although in some stars, emission from active regions can contribute). It is shown that, for the energy balance and geometry adopted, the analytical values of the emission measure and electron pressure at T0 and Tc depend on only three parameters: the stellar surface gravity and the values of T0 and Tc. The results are tested against full numerical solutions for e Eri (K2 V) and are applied to Procyon (a CMi, F5 IV/V). The analytical approximations can be used to restrict the required range of full numerical solutions, to check the assumed geometry and to show where the adopted energy balance may not be appropriate. © 2011 The Authors Monthly Notices of the Royal Astronomical Society © 2011 RAS.