Fourth order pseudo maximum likelihood methods

We extend PML theory to account for information on the conditional moments up to order four, but without assuming a parametric model, to avoid a risk of misspecification of the conditional distribution. The key statistical tool is the quartic exponential family, which allows us to generalize the PML2 and QGPML1 methods proposed in Gourieroux et al. (1984) to PML4 and QGPML2 methods, respectively. An asymptotic theory is developed. The key numerical tool that we use is the Gauss-Freud integration scheme that solves a computational problem that has previously been raised in several fields. Simulation exercises demonstrate the feasibility and robustness of the methods [Authors]

Genetic variability analysis among clinical Candida spp. isolates using random amplified polymorphic DNA

The patterns of genetic variation of samples of Candida spp. isolated from patients infected with human immunodeficiency virus in Vitória, state of Espírito Santo, Brazil, were examined. Thirty-seven strains were isolated from different anatomical sites obtained from different infection episodes of 11 patients infected with the human immunodeficiency virus (HIV). These samples were subjected to randomly amplified polymorphic DNA (RAPD) analysis using 9 different primers. Reproducible and complex DNA banding patterns were obtained. The experiments indicated evidence of dynamic process of yeast colonization in HIV-infected patients, and also that certain primers are efficient in the identification of species of the Candida genus. Thus, we conclude that RAPD analysis may be useful in providing genotypic characters for Candida species typing in epidemiological investigations, and also for the rapid identification of pathogenic fungi.

Identification of a genetic marker associated with the resistance to Schistosoma mansoni infection using random amplified polymorphic DNA analysis

In schistosomiasis, the host/parasite interaction remains not completely understood. Many questions related to the susceptibility of snails to infection by respective trematode still remain unanswered. The control of schistosomiasis requires a good understanding of the host/parasite association. In this work, the susceptibility/resistance to Schistosoma mansoni infection within Biomphalaria alexandrina snails were studied starting one month post infection and continuing thereafter weekly up to 10 weeks after miracidia exposure. Genetic variations between susceptible and resistant strains to Schistosoma infection within B. alexandrina snails using random amplified polymorphic DNA analysis technique were also carried out. The results showed that 39.8% of the examined field snails were resistant, while 60.2% of these snails showed high infection rates.In the resistant genotype snails, OPA-02 primer produced a major low molecular weight marker 430 bp. Among the two snail strains there were interpopulational variations, while the individual specimens from the same snail strain, either susceptible or resistant, record semi-identical genetic bands. Also, the resistant character was ascendant in contrast to a decline in the susceptibility of snails from one generation to the next.

A population genetics study of Anopheles darlingi (Diptera: Culicidae) from Colombia based on random amplified polymorphic DNA-polymerase chain reaction and amplified fragment lenght polymorphism markers

The genetic variation and population structure of three populations of Anopheles darlingi from Colombia were studied using random amplified polymorphic markers (RAPDs) and amplified fragment length polymorphism markers (AFLPs). Six RAPD primers produced 46 polymorphic fragments, while two AFLP primer combinations produced 197 polymorphic fragments from 71 DNA samples. Both of the evaluated genetic markers showed the presence of gene flow, suggesting that Colombian An. darlingi populations are in panmixia. Average genetic diversity, estimated from observed heterozygosity, was 0.374 (RAPD) and 0.309 (AFLP). RAPD and AFLP markers showed little evidence of geographic separation between eastern and western populations; however, the F ST values showed high gene flow between the two western populations (RAPD: F ST = 0.029; Nm: 8.5; AFLP: F ST = 0.051; Nm: 4.7). According to molecular variance analysis (AMOVA), the genetic distance between populations was significant (RAPD:phiST = 0.084; AFLP:phiST = 0.229, P < 0.001). The F ST distances and AMOVAs using AFLP loci support the differentiation of the Guyana biogeographic province population from those of the Chocó-Magdalena. In this last region, Chocó and Córdoba populations showed the highest genetic flow.

Genetic diversity of environmental Aspergillus flavus strains in the state of São Paulo, Brazil by random amplified polymorphic DNA

Aspergillus flavus is a very important toxigenic fungus that produces aflatoxins, a group of extremely toxic substances to man and animals. Toxigenic fungi can grow in feed crops, such as maize, peanuts, and soybeans, being thus of high concern for public health. There are toxigenic and non-toxigenic A. flavus variants, but the necessary conditions for expressing the toxigenic potential are not fully understood. Therefore, we have studied total-DNA polymorphism from toxigenic and non toxigenic A. flavus strains isolated from maize crops and soil at two geographic locations, 300 km apart, in the Southeast region of Brazil. Total DNA from each A. flavus isolate was extracted and subjected to polymerase chain reaction amplification with five randomic primers through the RAPD (random amplified polymorphic DNA) technique. Phenetic and cladistic analyses of the data, based on bootstrap analyses, led us to conclude that RAPD was not suitable to discriminate toxigenic from non toxigenic strains. But the present results support the use of RAPD for strain characterization, especially for preliminary evaluation over extensive collections.

Predicting random level and seasonality of hotel prices. A structural equation growth curve approach

This article examines the effect on price of different characteristics of holiday hotels in the sun-and-beach segment, under the hedonic function perspective. Monthly prices of the majority of hotels in the Spanish continental Mediterranean coast are gathered from May to October 1999 from the tour operator catalogues. Hedonic functions are specified as random-effect models and parametrized as structural equation models with two latent variables, a random peak season price and a random width of seasonal fluctuations. Characteristics of the hotel and the region where they are located are used as predictors of both latent variables. Besides hotel category, region, distance to the beach, availability of parking place and room equipment have an effect on peak price and also on seasonality. 3- star hotels have the highest seasonality and hotels located in the southern regions the lowest, which could be explained by a warmer climate in autumn

Medical image registration based on random line sampling

One of the key aspects in 3D-image registration is the computation of the joint intensity histogram. We propose a new approach to compute this histogram using uniformly distributed random lines to sample stochastically the overlapping volume between two 3D-images. The intensity values are captured from the lines at evenly spaced positions, taking an initial random offset different for each line. This method provides us with an accurate, robust and fast mutual information-based registration. The interpolation effects are drastically reduced, due to the stochastic nature of the line generation, and the alignment process is also accelerated. The results obtained show a better performance of the introduced method than the classic computation of the joint histogram

Error and complexity of random walk Monte Carlo radiosity

The author studies the error and complexity of the discrete random walk Monte Carlo technique for radiosity, using both the shooting and gathering methods. The author shows that the shooting method exhibits a lower complexity than the gathering one, and under some constraints, it has a linear complexity. This is an improvement over a previous result that pointed to an O(n log n) complexity. The author gives and compares three unbiased estimators for each method, and obtains closed forms and bounds for their variances. The author also bounds the expected value of the mean square error (MSE). Some of the results obtained are also shown

Influencia de los esquemas cognitivos implícitos y explícitos en la manifestación de experiencias pseudo-psicóticas positivas

El presente estudio evalúa la influencia de los esquemas implícitos y explícitos, tanto acerca de uno mismo como de los demás, sobre la experimentación de experiencias pseudo-psicóticas positivas; tomando como marco de referencia dos destacados modelos explicativos: el modelo atribucional de auto-representación y el modelo de la anticipación cognitiva de la amenaza. Los análisis se realizaron sobre una muestra de 185 estudiantes de psicología de la UAB. Los resultados obtenidos apoyaron la influencia de los esquemas explícitos positivos del yo y los negativos de los otros sobre las experiencias pseudo-psicóticas positivas; aportando así un apoyo parcial para ambos modelos.

The average inter-crossing number of equilateral random walks and polygons

In this paper, we study the average inter-crossing number between two random walks and two random polygons in the three-dimensional space. The random walks and polygons in this paper are the so-called equilateral random walks and polygons in which each segment of the walk or polygon is of unit length. We show that the mean average inter-crossing number ICN between two equilateral random walks of the same length n is approximately linear in terms of n and we were able to determine the prefactor of the linear term, which is a = (3 In 2)/(8) approximate to 0.2599. In the case of two random polygons of length n, the mean average inter-crossing number ICN is also linear, but the prefactor of the linear term is different from that of the random walks. These approximations apply when the starting points of the random walks and polygons are of a distance p apart and p is small compared to n. We propose a fitting model that would capture the theoretical asymptotic behaviour of the mean average ICN for large values of p. Our simulation result shows that the model in fact works very well for the entire range of p. We also study the mean ICN between two equilateral random walks and polygons of different lengths. An interesting result is that even if one random walk (polygon) has a fixed length, the mean average ICN between the two random walks (polygons) would still approach infinity if the length of the other random walk (polygon) approached infinity. The data provided by our simulations match our theoretical predictions very well.

Subknots in ideal knots, random knots, and knotted proteins.

We introduce disk matrices which encode the knotting of all subchains in circular knot configurations. The disk matrices allow us to dissect circular knots into their subknots, i.e. knot types formed by subchains of the global knot. The identification of subknots is based on the study of linear chains in which a knot type is associated to the chain by means of a spatially robust closure protocol. We characterize the sets of observed subknot types in global knots taking energy-minimized shapes such as KnotPlot configurations and ideal geometric configurations. We compare the sets of observed subknots to knot types obtained by changing crossings in the classical prime knot diagrams. Building upon this analysis, we study the sets of subknots in random configurations of corresponding knot types. In many of the knot types we analyzed, the sets of subknots from the ideal geometric configurations are found in each of the hundreds of random configurations of the same global knot type. We also compare the sets of subknots observed in open protein knots with the subknots observed in the ideal configurations of the corresponding knot type. This comparison enables us to explain the specific dispositions of subknots in the analyzed protein knots.

Cell size distribution in a random tessellation of space governed by the Kolmogorov-Johnson-Mehl-Avrami model: Grain size distribution in crystallization

The space subdivision in cells resulting from a process of random nucleation and growth is a subject of interest in many scientific fields. In this paper, we deduce the expected value and variance of these distributions while assuming that the space subdivision process is in accordance with the premises of the Kolmogorov-Johnson-Mehl-Avrami model. We have not imposed restrictions on the time dependency of nucleation and growth rates. We have also developed an approximate analytical cell size probability density function. Finally, we have applied our approach to the distributions resulting from solid phase crystallization under isochronal heating conditions

Detecció automàtica de punts facials característics utilitzant Random Ferns i el criteri de la información mútua simplificada

En aquest article comparem el rendiment que presenten dos sistemes de reconeixement de punts característics en imatges: en el primer utilitzem la tècnica Random Ferns bàsica i en el segon (que anomenem Ferns amb Informació Mútua o FIM) apliquem una tècnica d'obtenció de Ferns utilitzant un criteri simplificat de la informació mútua.