Time correlation function in systems with two coexisting biological species

We study a stochastic lattice model describing the dynamics of coexistence of two interacting biological species. The model comprehends the local processes of birth, death, and diffusion of individuals of each species and is grounded on interaction of the predator-prey type. The species coexistence can be of two types: With self-sustained coupled time oscillations of population densities and without oscillations. We perform numerical simulations of the model on a square lattice and analyze the temporal behavior of each species by computing the time correlation functions as well as the spectral densities. This analysis provides an appropriate characterization of the different types of coexistence. It is also used to examine linked population cycles in nature and in experiment.

Value of real time three-dimensional echocardiography in patients with hypertrophic cardiomyopathy: Comparison with two-dimensional echocardiography and magnetic resonance imaging

Real time three-dimensional echocardiography (RT3DE) has been demonstrated to be an accurate technique to quantify left ventricular (LV) volumes and function in different patient populations. We sought to determine the value of RT3DE for evaluating patients with hypertrophic cardiomyopathy (HCM), in comparison with cardiac magnetic resonance imaging (MRI). Methods: We studied 20 consecutive patients with HCM who underwent two-dimensional echocardiography (2DE), RT3DE, and MRI. Parameters analyzed by echocardiography and MRI included: wall thickness, LV volumes, ejection fraction (LVEF), mass, geometric index, and dyssynchrony index. Statistical analysis was performed by Lin agreement coefficient, Pearson linear correlation and Bland-Altman model. Results: There was excellent agreement between 2DE and RT3DE (Rc = 0.92), 2DE and MRI (Rc = 0.85), and RT3DE and MRI (Rc = 0.90) for linear measurements. Agreement indexes for LV end-diastolic and end-systolic volumes were Rc = 0.91 and Rc = 0.91 between 2DE and RT3DE, Rc = 0.94 and Rc = 0.95 between RT3DE and MRI, and Rc = 0.89 and Rc = 0.88 between 2DE and MRI, respectively. Satisfactory agreement was observed between 2DE and RT3DE (Rc = 0.75), RT3DE and MRI (Rc = 0.83), and 2DE and MRI (Rc = 0.73) for determining LVEF, with a mild underestimation of LVEF by 2DE, and smaller variability between RT3DE and MRI. Regarding LV mass, excellent agreement was observed between RT3DE and MRI (Rc = 0.96), with bias of -6.3 g (limits of concordance = 42.22 to -54.73 g). Conclusion: In patients with HCM, RT3DE demonstrated superior performance than 2DE for the evaluation of myocardial hypertrophy, LV volumes, LVEF, and LV mass.

Cavity QED analog of the harmonic-oscillator probability distribution function and quantum collapses

We establish a connection between the simple harmonic oscillator and a two-level atom interacting with resonant, quantized cavity and strong driving fields, which suggests an experiment to measure the harmonic-oscillator's probability distribution function. To achieve this, we calculate the Autler-Townes spectrum by coupling the system to a third level. We find that there are two different regions of the atomic dynamics depending on the ratio of the: Rabi frequency Omega (c) of the cavity field to that of the Rabi frequency Omega of the driving field. For Omega (c)

Composition and energy density of eggs from two species of freshwater turtle with twofold ranges in egg size

Lipid, protein, ash, carbohydrate and water content and energy density of eggs were measured from different clutches over a range of egg size in two species of freshwater turtle. Dry egg contents consisted of protein (54-60%), lipid (25-31%) and ash (5-6%) while carbohydrate was found to be negligible (

Tissue composition and density impact on the clinical parameters for 125I prostate implants dosimetry

The MCNPX code was used to calculate the TG-43U1 recommended parameters in water and prostate tissue in order to quantify the dosimetric impact in 30 patients treated with (125)I prostate implants when replacing the TG-43U1 formalism parameters calculated in water by a prostate-like medium in the planning system (PS) and to evaluate the uncertainties associated with Monte Carlo (MC) calculations. The prostate density was obtained from the CT of 100 patients with prostate cancer. The deviations between our results for water and the TG-43U1 consensus dataset values were -2.6% for prostate V100, -13.0% for V150, and -5.8% for D90; -2.0% for rectum V100, and -5.1% for D0.1; -5.0% for urethra D10, and -5.1% for D30. The same differences between our water and prostate results were all under 0.3%. Uncertainties estimations were up to 2.9% for the gL(r) function, 13.4% for the F(r,θ) function and 7.0% for Λ, mainly due to seed geometry uncertainties. Uncertainties in extracting the TG-43U1 parameters in the MC simulations as well as in the literature comparison are of the same order of magnitude as the differences between dose distributions computed for water and prostate-like medium. The selection of the parameters for the PS should be done carefully, as it may considerably affect the dose distributions. The seeds internal geometry uncertainties are a major limiting factor in the MC parameters deduction.

Describing function of two masses with backlash

This paper analyzes the dynamical properties of systems with backlash and impact phenomena based on the describing function method. It is shown that this type of nonlinearity can be analyzed in the perspective of the fractional calculus theory. The fractional dynamics is compared with that of standard models.

Nest distribution varies with dispersal method and familiarity-mediated aggression for two sympatric ants

Dispersal mechanisms and competition together play a key role in the spatial distribution of a population. Species that disperse via fission are likely to experience high levels of localized competitive pressure from conspecifics relative to species that disperse in other ways. Although fission dispersal occurs in many species, its ecological and behavioural effects remain unclear. We compared foraging effort, nest spatial distribution and aggression of two sympatric ant species that differ in reproductive dispersal: Streblognathus peetersi, which disperse by group fission, and Plectroctena mandibularis, which disperse by solitary wingless queens. We found that although both species share space and have similar foraging strategies, they differ in nest distribution and aggressive behaviour. The spatial distribution of S. peetersi nests was extremely aggregated, and workers were less aggressive towards conspecifics from nearby nests than towards distant conspecifics and all heterospecific workers. By contrast, the spatial distribution of P. mandibularis nests was overdispersed, and workers were equally aggressive towards conspecific and heterospecific competitors regardless of nest distance. Finally, laboratory experiments showed that familiarity led to the positive relationship between aggression and nest distance in S. peetersi. While unfamiliar individuals were initially aggressive, the level of aggression decreased within 1 h of contact, and continued to decrease over 24 h. Furthermore, individuals from near nests that were not aggressive could be induced to aggression after prolonged isolation. Overall, these results suggest that low aggression mediated by familiarity could provide benefits for a species with fission reproduction and an aggregated spatial distribution.

Spatial distribution of Schistosoma mansoni infection before and after chemotherapy with two praziquantel doses in a community of Pernambuco, Brazil

Praziquantel chemotherapy has been the focus of the Schistosomiasis Control Program in Brazil for the past two decades. Nevertheless, information on the impact of selective chemotherapy against Schistosoma mansoni infection under the conditions confronted by the health teams in endemic municipalities remains scarce. This paper compares the spatial pattern of infection before and after treatment with either a 40 mg/kg or 60 mg/kg dose of praziquantel by determining the intensity of spatial cluster among patients at 180 and 360 days after treatment. The spatial-temporal distribution of egg-positive patients was analysed in a Geographic Information System using the kernel smoothing technique. While all patients became egg-negative after 21 days, 17.9% and 30.9% reverted to an egg-positive condition after 180 and 360 days, respectively. Both the prevalence and intensity of infection after treatment were significantly lower in the 60 mg/kg than in the 40 mg/kg treatment group. The higher intensity of the kernel in the 40 mg/kg group compared to the 60 mg/kg group, at both 180 and 360 days, reflects the higher number of reverted cases in the lower dose group. Auxiliary, preventive measures to control transmission should be integrated with chemotherapy to achieve a more enduring impact.

Monte Carlo Tests with Nuisance Parameters: A General Approach to Finite-Sample Inference and Nonstandard Asymptotics

The technique of Monte Carlo (MC) tests [Dwass (1957), Barnard (1963)] provides an attractive method of building exact tests from statistics whose finite sample distribution is intractable but can be simulated (provided it does not involve nuisance parameters). We extend this method in two ways: first, by allowing for MC tests based on exchangeable possibly discrete test statistics; second, by generalizing the method to statistics whose null distributions involve nuisance parameters (maximized MC tests, MMC). Simplified asymptotically justified versions of the MMC method are also proposed and it is shown that they provide a simple way of improving standard asymptotics and dealing with nonstandard asymptotics (e.g., unit root asymptotics). Parametric bootstrap tests may be interpreted as a simplified version of the MMC method (without the general validity properties of the latter).

Study on tropical rain with special reference to rain Drop Size Distribution and integral rain parameters using ground-based and satellite measurements

Department of Physics, Cochin University of Science and Technology

Bayes quadratic unbiased estimator of spatial covariance parameters

This work presents Bayes invariant quadratic unbiased estimator, for short BAIQUE. Bayesian approach is used here to estimate the covariance functions of the regionalized variables which appear in the spatial covariance structure in mixed linear model. Firstly a brief review of spatial process, variance covariance components structure and Bayesian inference is given, since this project deals with these concepts. Then the linear equations model corresponding to BAIQUE in the general case is formulated. That Bayes estimator of variance components with too many unknown parameters is complicated to be solved analytically. Hence, in order to facilitate the handling with this system, BAIQUE of spatial covariance model with two parameters is considered. Bayesian estimation arises as a solution of a linear equations system which requires the linearity of the covariance functions in the parameters. Here the availability of prior information on the parameters is assumed. This information includes apriori distribution functions which enable to find the first and the second moments matrix. The Bayesian estimation suggested here depends only on the second moment of the prior distribution. The estimation appears as a quadratic form y'Ay , where y is the vector of filtered data observations. This quadratic estimator is used to estimate the linear function of unknown variance components. The matrix A of BAIQUE plays an important role. If such a symmetrical matrix exists, then Bayes risk becomes minimal and the unbiasedness conditions are fulfilled. Therefore, the symmetry of this matrix is elaborated in this work. Through dealing with the infinite series of matrices, a representation of the matrix A is obtained which shows the symmetry of A. In this context, the largest singular value of the decomposed matrix of the infinite series is considered to deal with the convergence condition and also it is connected with Gerschgorin Discs and Poincare theorem. Then the BAIQUE model for some experimental designs is computed and compared. The comparison deals with different aspects, such as the influence of the position of the design points in a fixed interval. The designs that are considered are those with their points distributed in the interval [0, 1]. These experimental structures are compared with respect to the Bayes risk and norms of the matrices corresponding to distances, covariance structures and matrices which have to satisfy the convergence condition. Also different types of the regression functions and distance measurements are handled. The influence of scaling on the design points is studied, moreover, the influence of the covariance structure on the best design is investigated and different covariance structures are considered. Finally, BAIQUE is applied for real data. The corresponding outcomes are compared with the results of other methods for the same data. Thereby, the special BAIQUE, which estimates the general variance of the data, achieves a very close result to the classical empirical variance.