951 resultados para PROBABILITIES


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Risks of the introduction of highly pathogenic avian influenza (HPAI) H5N1 through migratory birds to the main wintering site for wild birds in southern Brazil and its consequences were assessed. Likelihoods were estimated by a qualitative scale ranging from negligible to high. Northern migrants that breed in Alaska and regularly migrate to South America (primary Charadriiformes) can have contact with birds from affected areas in Asia. The likelihood of the introduction of HPAI H5N1 through migratory birds was found to be very low as it is a probability conditioned to successful transmission in breeding areas and the probabilities of an infected bird migrating and shedding the virus as far as southern Brazil. The probability of wild species becoming exposed to H5N1-infected birds is high as they nest with northern migrants from Alaska, whereas for backyard poultry it is moderate to high depending on proximity to wetlands and the presence of species that could increase the likelihood of contact with wild birds such as domestic duck. The magnitude of the biological and economic consequences of successful transmission to poultry or wild birds would be low to severe depending on the probability of the occurrence of outbreak scenarios described. As a result, the risk estimate is greater than negligible, and HPAI H5N1 prevention strategy in the region should always be carefully considered by the veterinary services in Brazil.

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In this paper we use Markov chain Monte Carlo (MCMC) methods in order to estimate and compare GARCH models from a Bayesian perspective. We allow for possibly heavy tailed and asymmetric distributions in the error term. We use a general method proposed in the literature to introduce skewness into a continuous unimodal and symmetric distribution. For each model we compute an approximation to the marginal likelihood, based on the MCMC output. From these approximations we compute Bayes factors and posterior model probabilities. (C) 2012 IMACS. Published by Elsevier B.V. All rights reserved.

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The purpose of this study is to estimate the survival probability of patients following their first admission for the treatment of AIDS to an infectious disease reference hospital in Belo Horizonte, Brazil, during 2005. Study subjects were monitored during a 12-month period to identify factors associated with survival probability. Late diagnosis was recorded among many of the 250 study subjects: almost half (44.8%) were diagnosed less than 30 days prior to or during their hospitalization. A high mortality rate was also detected: 39.6% of the subjects died during the 12 months of monitoring. The cumulative survival probability of the cohort group was estimated at 68.0% after 3 months and at 61.2% after 12 months. However, certain patient subgroups analyzed had even lower cumulative survival probabilities after 12 months of monitoring: if diagnosed during hospitalization, it was estimated at only 48.0% and those with no record of antiretroviral treatment had a 48.5% cumulative survival probability. Patients with severe anemia had the lowest survival probability, similar among the two lymphocyte count groups (<1000 mm(3) and >= 1000 mm(3)), the former with a 45.5% survival probability and the latter with a 46.7% one. The proportional death risk was 2.5-fold higher for men residing in other area than the capital city of the State of Minas Gerais and greater metropolitan region when compared with women residing there. The findings of this study highlight the importance of early diagnosis for predicting patient survival and reinforce the necessity off acilitating HIV diagnosis.

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In this work, we correlate the daily number of human leptospirosis cases with several climatic factors. We used a negative binomial model that considers hospital daily admissions due to leptospirosis as the dependent variable, and the climatic variables of daily precipitation pattern, and maximum and minimum temperature as independent variables. We calculated the monthly leptospirosis admission probabilities from the precipitation and maximum temperature variables. The month of February showed the highest probability, although values were also high during the spring months. The month of February also showed the highest number of hospital admissions. Another interesting result is that, for every 20 mm precipitation, there was an average increase of 31.5% in hospital admissions. Additionally, the relative risk of leptospirosis varied from 1.1 to 2.0 when the precipitation varied from 20 to 140 mm.

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We study the firing rate properties of a cellular automaton model for a neuronal network with chemical synapses. We propose a simple mechanism in which the nonlocal connections are included, through electrical and chemical synapses. In the latter case, we introduce a time delay which produces self-sustained activity. Nonlocal connections, or shortcuts, are randomly introduced according to a specified connection probability. There is a range of connection probabilities for which neuron firing occurs, as well as a critical probability for which the firing ceases in the absence of time delay. The critical probability for nonlocal shortcuts depends on the network size according to a power-law. We also compute the firing rate amplification factor by varying both the connection probability and the time delay for different network sizes. (C) 2011 Elsevier B.V. All rights reserved.

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Exclusive paternal care is the rarest form of parental investment in nature and theory predicts that the maintenance of this behavior depends on the balance between costs and benefits to males. Our goal was to assess costs of paternal care in the harvestman Iporangaia pustulosa, for which the benefits of this behavior in terms of egg survival have already been demonstrated. We evaluated energetic costs and mortality risks associated to paternal egg-guarding in the field. We quantified foraging activity of males and estimated how their body condition is influenced by the duration of the caring period. Additionally, we conducted a one-year capture-mark-recapture study and estimated apparent survival probabilities of caring and non-caring males to assess potential survival costs of paternal care. Our results indicate that caring males forage less frequently than non-caring individuals (males and females) and that their body condition deteriorates over the course of the caring period. Thus, males willing to guard eggs may provide to females a fitness-enhancing gift of cost-free care of their offspring. Caring males, however, did not show lower survival probabilities when compared to both non-caring males and females. Reduction in mortality risks as a result of remaining stationary, combined with the benefits of improving egg survival, may have played an important and previously unsuspected role favoring the evolution of paternal care. Moreover, males exhibiting paternal care could also provide an honest signal of their quality as offspring defenders, and thus female preference for caring males could be responsible for maintaining the trait.

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Known as the "king of spices", black pepper (Piper nigrum), a perennial crop of the tropics, is economically the most important and the most widely used spice crop in the world. To understand its suitable bioclimatic distribution, maximum entropy based on ecological niche modeling was used to model the bioclimatic niches of the species in its Asian range. Based on known occurrences, bioclimatic areas with higher probabilities are mainly located in the eastern and western coasts of the Indian Peninsula, the east of Sumatra Island, some areas in the Malay Archipelago, and the southeast coastal areas of China. Some undocumented places were also predicted as suitable areas. According to the jackknife procedure, the minimum temperature of the coldest month, the mean monthly temperature range, and the precipitation of the wettest month were identified as highly effective factors in the distribution of black pepper and could possibly account for the crop's distribution pattern. Such climatic requirements inhibited this species from dispersing and gaining a larger geographical range.

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We report a morphology-based approach for the automatic identification of outlier neurons, as well as its application to the NeuroMorpho.org database, with more than 5,000 neurons. Each neuron in a given analysis is represented by a feature vector composed of 20 measurements, which are then projected into a two-dimensional space by applying principal component analysis. Bivariate kernel density estimation is then used to obtain the probability distribution for the group of cells, so that the cells with highest probabilities are understood as archetypes while those with the smallest probabilities are classified as outliers. The potential of the methodology is illustrated in several cases involving uniform cell types as well as cell types for specific animal species. The results provide insights regarding the distribution of cells, yielding single and multi-variate clusters, and they suggest that outlier cells tend to be more planar and tortuous. The proposed methodology can be used in several situations involving one or more categories of cells, as well as for detection of new categories and possible artifacts.

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Electronic states of a new molecular species, SiAs, correlating with the three lowest dissociation channels are characterized at a high-level of theory using the CASSCF/MRCI approach along with quintuple-xi quality basis sets. This characterization includes potential energy curves, vibrational energy levels, spectroscopic parameters, dipole and transition dipole moment functions, transition probabilities, and radiative lifetimes. For the ground state (X-2 Pi), an assessment of spin-orbit effects and the interaction with the close-lying A(2)Sigma(+) state is also reported. Similarities and differences with other isovalent species such as SiP and CAs are also discussed.

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Validation of parentage and horse breed registries through DNA typing relies on estimates of random match probabilities with DNA profiles generated from multiple polymorphic loci. Of the twenty-seven microsatellite loci recommended by the International Society for Animal Genetics for parentage testing in Thoroughbred horses, eleven are located on five chromosomes. An important aspect in determining combined exclusion probabilities is the ascertainment of the genetic linkage status of syntenic markers, which may affect reliable use of the product rule in estimating random match probabilities. In principle, linked markers can be in gametic phase disequilibrium (GD). We aimed at determining the extent, by frequency and strength, of GD between the HTG4 and HMS3 multiallelic loci, syntenic on chromosome 9. We typed the qualified offspring (n (1) = 27; n (2) = 14) of two Quarter Bred stallions (registered by the Brazilian Association of Quarter Horse Breeders) and 121 unrelated horses from the same breed. In the 41 informative meioses analyzed, the frequency of recombination between the HTG4 and HMS3 loci was 0.27. Consistent with genetic map distances, this recombination rate does not fit to the theoretical distribution for independently segregated markers. We estimated sign-based D' coefficients as a measure of GD, and showed that the HTG4 and HMS3 loci are in significant, yet partial and weak, disequilibrium, with two allele pairs involved (HTG4*M/HMS3*P, D'(+) = 0.6274; and HTG4*K/HMS3*P, D'(-) = -0.6096). These results warn against the inadequate inclusion of genetically linked markers in the calculation of combined power of discrimination for Thoroughbred parentage validation.

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The amount of information exchanged per unit of time between two nodes in a dynamical network or between two data sets is a powerful concept for analysing complex systems. This quantity, known as the mutual information rate (MIR), is calculated from the mutual information, which is rigorously defined only for random systems. Moreover, the definition of mutual information is based on probabilities of significant events. This work offers a simple alternative way to calculate the MIR in dynamical (deterministic) networks or between two time series (not fully deterministic), and to calculate its upper and lower bounds without having to calculate probabilities, but rather in terms of well known and well defined quantities in dynamical systems. As possible applications of our bounds, we study the relationship between synchronisation and the exchange of information in a system of two coupled maps and in experimental networks of coupled oscillators.

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A new molecular species, MgAs, is investigated theoretically for the first time at the CASSCF/MRCI level using quintuple-zeta quality basis sets. Potential energy curves for the lowest-lying electronic states are presented as well as the associated spectroscopic constants. Dipole and transition moment functions for selected states complement this characterization. Estimates of transition probabilities and radiative life-times for the most important transitions are also reported. The effect of spin-orbit interactions is clearly reflected on the potential energy curves. Comparisons with BeAs, BeN, and BeP are made where pertinent. (C) 2011 Elsevier B.V. All rights reserved.

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In this paper, we give a possible solution to the cosmological constant problem. It is shown that the traditional approach, based on volume weighting of probabilities, leads to an incoherent conclusion: the probability that a randomly chosen observer measures Lambda = 0 is exactly equal to 1. Using an alternative, volume averaging measure, instead of volume weighting can explain why the cosmological constant is non-zero.

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Background: Genome-wide association studies (GWAS) require large sample sizes to obtain adequate statistical power, but it may be possible to increase the power by incorporating complementary data. In this study we investigated the feasibility of automatically retrieving information from the medical literature and leveraging this information in GWAS. Methods: We developed a method that searches through PubMed abstracts for pre-assigned keywords and key concepts, and uses this information to assign prior probabilities of association for each single nucleotide polymorphism (SNP) with the phenotype of interest - the Adjusting Association Priors with Text (AdAPT) method. Association results from a GWAS can subsequently be ranked in the context of these priors using the Bayes False Discovery Probability (BFDP) framework. We initially tested AdAPT by comparing rankings of known susceptibility alleles in a previous lung cancer GWAS, and subsequently applied it in a two-phase GWAS of oral cancer. Results: Known lung cancer susceptibility SNPs were consistently ranked higher by AdAPT BFDPs than by p-values. In the oral cancer GWAS, we sought to replicate the top five SNPs as ranked by AdAPT BFDPs, of which rs991316, located in the ADH gene region of 4q23, displayed a statistically significant association with oral cancer risk in the replication phase (per-rare-allele log additive p-value [p(trend)] = 2.5 x 10(-3)). The combined OR for having one additional rare allele was 0.83 (95% CI: 0.76-0.90), and this association was independent of previously identified susceptibility SNPs that are associated with overall UADT cancer in this gene region. We also investigated if rs991316 was associated with other cancers of the upper aerodigestive tract (UADT), but no additional association signal was found. Conclusion: This study highlights the potential utility of systematically incorporating prior knowledge from the medical literature in genome-wide analyses using the AdAPT methodology. AdAPT is available online (url: http://services.gate.ac.uk/lld/gwas/service/config).

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A set of predictor variables is said to be intrinsically multivariate predictive (IMP) for a target variable if all properly contained subsets of the predictor set are poor predictors of the. target but the full set predicts the target with great accuracy. In a previous article, the main properties of IMP Boolean variables have been analytically described, including the introduction of the IMP score, a metric based on the coefficient of determination (CoD) as a measure of predictiveness with respect to the target variable. It was shown that the IMP score depends on four main properties: logic of connection, predictive power, covariance between predictors and marginal predictor probabilities (biases). This paper extends that work to a broader context, in an attempt to characterize properties of discrete Bayesian networks that contribute to the presence of variables (network nodes) with high IMP scores. We have found that there is a relationship between the IMP score of a node and its territory size, i.e., its position along a pathway with one source: nodes far from the source display larger IMP scores than those closer to the source, and longer pathways display larger maximum IMP scores. This appears to be a consequence of the fact that nodes with small territory have larger probability of having highly covariate predictors, which leads to smaller IMP scores. In addition, a larger number of XOR and NXOR predictive logic relationships has positive influence over the maximum IMP score found in the pathway. This work presents analytical results based on a simple structure network and an analysis involving random networks constructed by computational simulations. Finally, results from a real Bayesian network application are provided. (C) 2012 Elsevier Inc. All rights reserved.