Does bacterial density in cystic fibrosis sputum increase prior to pulmonary exacerbation?

These findings strongly suggest that CFPE do not generally result from increased bacterial density within the airways. Instead, data presented here are consistent with alternative models of pulmonary exacerbation.

Effect of pair interactions on transition probabilities between inactive and active states: achieving collective behaviour via pair interactions in social insects

To understand the evolution of well-organized social behaviour, we must first understand the mechanism by which collective behaviour establishes. In this study, the mechanisms of collective behaviour in a colony of social insects were studied in terms of the transition probability between active and inactive states, which is linked to mutual interactions. The active and inactive states of the social insects were statistically extracted from the velocity profiles. From the duration distributions of the two states, we found that 1) the durations of active and inactive states follow an exponential law, and 2) pair interactions increase the transition probability from inactive to active states. The regulation of the transition probability by paired interactions suggests that such interactions control the populations of active and inactive workers in the colony.

Where were the monsoon regions and arid zones in Asia prior to the Tibetan Plateau uplift?

The impact of the Tibetan Plateau uplift on the Asian monsoons and inland arid climates is an important but also controversial question in studies of paleoenvironmental change during the Cenozoic. In order to achieve a good understanding of the background for the formation of the Asian monsoons and arid environments, it is necessary to know the characteristics of the distribution of monsoon regions and arid zones in Asia before the plateau uplift. In this study, we discuss in detail the patterns of distribution of the Asian monsoon and arid regions before the plateau uplift on the basis of modeling results without topography from a global coupled atmosphere–ocean general circulation model, compare our results with previous simulation studies and available biogeological data, and review the uncertainties in the current knowledge. Based on what we know at the moment, tropical monsoon climates existed south of 20°N in South and Southeast Asia before the plateau uplift, while the East Asian monsoon was entirely absent in the extratropics. These tropical monsoons mainly resulted from the seasonal shifts of the Inter-Tropical Convergence Zone. There may have been a quasi-monsoon region in central-southern Siberia. Most of the arid regions in the Asian continent were limited to the latitudes of 20–40°N, corresponding to the range of the subtropical high pressure year-around. In the meantime, the present-day arid regions located in the relatively high latitudes in Central Asia were most likely absent before the plateau uplift. The main results from the above modeling analyses are qualitatively consistent with the available biogeological data. These results highlight the importance of the uplift of the Tibetan Plateau in the Cenozoic evolution of the Asian climate pattern of dry–wet conditions. Future studies should be focused on effects of the changes in land–sea distribution and atmospheric CO2 concentrations before and after the plateau uplift, and also on cross-comparisons between numerical simulations and geological evidence, so that a comprehensive understanding of the evolution of the Cenozoic paleoenvironments in Asia can be achieved.

A Bayesian model for estimating the malaria transition probabilities considering individuals lost to follow-up

It is known that patients may cease participating in a longitudinal study and become lost to follow-up. The objective of this article is to present a Bayesian model to estimate the malaria transition probabilities considering individuals lost to follow-up. We consider a homogeneous population, and it is assumed that the considered period of time is small enough to avoid two or more transitions from one state of health to another. The proposed model is based on a Gibbs sampling algorithm that uses information of lost to follow-up at the end of the longitudinal study. To simulate the unknown number of individuals with positive and negative states of malaria at the end of the study and lost to follow-up, two latent variables were introduced in the model. We used a real data set and a simulated data to illustrate the application of the methodology. The proposed model showed a good fit to these data sets, and the algorithm did not show problems of convergence or lack of identifiability. We conclude that the proposed model is a good alternative to estimate probabilities of transitions from one state of health to the other in studies with low adherence to follow-up.

Efficient solutions to factored MDPs with imprecise transition probabilities

When modeling real-world decision-theoretic planning problems in the Markov Decision Process (MDP) framework, it is often impossible to obtain a completely accurate estimate of transition probabilities. For example, natural uncertainty arises in the transition specification due to elicitation of MOP transition models from an expert or estimation from data, or non-stationary transition distributions arising from insufficient state knowledge. In the interest of obtaining the most robust policy under transition uncertainty, the Markov Decision Process with Imprecise Transition Probabilities (MDP-IPs) has been introduced to model such scenarios. Unfortunately, while various solution algorithms exist for MDP-IPs, they often require external calls to optimization routines and thus can be extremely time-consuming in practice. To address this deficiency, we introduce the factored MDP-IP and propose efficient dynamic programming methods to exploit its structure. Noting that the key computational bottleneck in the solution of factored MDP-IPs is the need to repeatedly solve nonlinear constrained optimization problems, we show how to target approximation techniques to drastically reduce the computational overhead of the nonlinear solver while producing bounded, approximately optimal solutions. Our results show up to two orders of magnitude speedup in comparison to traditional ""flat"" dynamic programming approaches and up to an order of magnitude speedup over the extension of factored MDP approximate value iteration techniques to MDP-IPs while producing the lowest error of any approximation algorithm evaluated. (C) 2011 Elsevier B.V. All rights reserved.

Excited Electronic States, Transition Probabilities, and Radiative Lifetimes of CAs: A Theoretical Contribution and Challenge to Experimentalists

High-level CASSCF/MRCI calculations with a quintuple-zeta quality basis set are reported by characterizing for the first time a manifold of electronic states of the CAs radical yet to be investigated experimentally. Along with the potential energy curves and the associated spectroscopic constants, the dipole moment functions for selected electronic states as well as the transition dipole moment functions for the most relevant electronic transitions are also presented. Estimates of radiative transition probabilities and lifetimes complement this investigation, which also assesses the effect of spin-orbit interaction on the A (2)Pi state. Whenever pertinent, comparisons of similarities and differences with the isovalent CN and CP radicals are made.

Dynamic Fuzzy Logic Control of GeneticAlgorithm Probabilities

Genetic algorithms are commonly used to solve combinatorial optimizationproblems. The implementation evolves using genetic operators (crossover, mutation,selection, etc.). Anyway, genetic algorithms like some other methods have parameters(population size, probabilities of crossover and mutation) which need to be tune orchosen.In this paper, our project is based on an existing hybrid genetic algorithmworking on the multiprocessor scheduling problem. We propose a hybrid Fuzzy-Genetic Algorithm (FLGA) approach to solve the multiprocessor scheduling problem.The algorithm consists in adding a fuzzy logic controller to control and tunedynamically different parameters (probabilities of crossover and mutation), in anattempt to improve the algorithm performance. For this purpose, we will design afuzzy logic controller based on fuzzy rules to control the probabilities of crossoverand mutation. Compared with the Standard Genetic Algorithm (SGA), the resultsclearly demonstrate that the FLGA method performs significantly better.

On Qualitative Probabilities for Legal Reasoning about Evidence

A crucial aspect of evidential reasoning in crime investigation involves comparing the support that evidence provides for alternative hypotheses. Recent work in forensic statistics has shown how Bayesian Networks (BNs) can be employed for this purpose. However, the specification of BNs requires conditional probability tables describing the uncertain processes under evaluation. When these processes are poorly understood, it is necessary to rely on subjective probabilities provided by experts. Accurate probabilities of this type are normally hard to acquire from experts. Recent work in qualitative reasoning has developed methods to perform probabilistic reasoning using coarser representations. However, the latter types of approaches are too imprecise to compare the likelihood of alternative hypotheses. This paper examines this shortcoming of the qualitative approaches when applied to the aforementioned problem, and identifies and integrates techniques to refine them.

A Complexity Based Model for Quantifying Forensic Evidential Probabilities

An operational complexity model (OCM) is proposed to enable the complexity of both the cognitive and the computational components of a process to be determined. From the complexity of formation of a set of traces via a specified route a measure of the probability of that route can be determined. By determining the complexities of alternative routes leading to the formation of the same set of traces, the odds ratio indicating the relative plausibility of the alternative routes can be found. An illustrative application to a BitTorrent piracy case is presented, and the results obtained suggest that the OCM is capable of providing a realistic estimate of the odds ratio for two competing hypotheses. It is also demonstrated that the OCM can be straightforwardly refined to encompass a variety of circumstances.

Developing a Credit for Prior Learning Program: System-Wide Strategies for Program Creation, Operations, and Recruitment

Credit for prior learning programs help students complete degrees more quickly and for less money. This report addresses the challenges of scaling up a credit for prior learning program at the university system level, and explores the delineation of responsibilities between system staff and institutional staff.

Laws of large numbers for non-additive probabilities

We apply the concept of exchangeable random variables to the case of non-additive robability distributions exhibiting ncertainty aversion, and in the lass generated bya convex core convex non-additive probabilities, ith a convex core). We are able to rove two versions of the law of arge numbers (de Finetti's heorems). By making use of two efinitions. of independence we rove two versions of the strong law f large numbers. It turns out that e cannot assure the convergence of he sample averages to a constant. e then modal the case there is a true" probability distribution ehind the successive realizations of the uncertain random variable. In this case convergence occurs. This result is important because it renders true the intuition that it is possible "to learn" the "true" additive distribution behind an uncertain event if one repeatedly observes it (a sufficiently large number of times). We also provide a conjecture regarding the "Iearning" (or updating) process above, and prove a partia I result for the case of Dempster-Shafer updating rule and binomial trials.

Os paradoxos de Prior e o calculo proposicional deôntico relevante E¹.

Cruz, Ângela Maria Paiva. Os paradoxos de Prior e o cálculo proposicional deôntico relevante. Princípios, Natal, v. 4, p. 05-18, 1996.