On the analysis of notched concrete beams: From measurement with digital image correlation to identification with boundary element method of a cohesive model

A way of coupling digital image correlation (to measure displacement fields) and boundary element method (to compute displacements and tractions along a crack surface) is presented herein. It allows for the identification of Young`s modulus and fracture parameters associated with a cohesive model. This procedure is illustrated to analyze the latter for an ordinary concrete in a three-point bend test on a notched beam. In view of measurement uncertainties, the results are deemed trustworthy thanks to the fact that numerous measurement points are accessible and used as entries to the identification procedure. (C) 2010 Elsevier Ltd. All rights reserved.

Parametric correlation functions to model the structure of permanent environmental (co)variances in milk yield random regression models

The objective of the present study was to estimate milk yield genetic parameters applying random regression models and parametric correlation functions combined with a variance function to model animal permanent environmental effects. A total of 152,145 test-day milk yields from 7,317 first lactations of Holstein cows belonging to herds located in the southeastern region of Brazil were analyzed. Test-day milk yields were divided into 44 weekly classes of days in milk. Contemporary groups were defined by herd-test-day comprising a total of 2,539 classes. The model included direct additive genetic, permanent environmental, and residual random effects. The following fixed effects were considered: contemporary group, age of cow at calving (linear and quadratic regressions), and the population average lactation curve modeled by fourth-order orthogonal Legendre polynomial. Additive genetic effects were modeled by random regression on orthogonal Legendre polynomials of days in milk, whereas permanent environmental effects were estimated using a stationary or nonstationary parametric correlation function combined with a variance function of different orders. The structure of residual variances was modeled using a step function containing 6 variance classes. The genetic parameter estimates obtained with the model using a stationary correlation function associated with a variance function to model permanent environmental effects were similar to those obtained with models employing orthogonal Legendre polynomials for the same effect. A model using a sixth-order polynomial for additive effects and a stationary parametric correlation function associated with a seventh-order variance function to model permanent environmental effects would be sufficient for data fitting.

Correlation of the in vitro antifungal drug susceptibility with the in vivo activity of fluconazole in a murine model of cerebral infection caused by Cryptococcus gattii

Forty Cryptococcus gattii strains were submitted to antifungal susceptibility testing with fluconazole, itraconazole, amphotericin B and terbinafine. The minimum inhibitory concentration (MIC) ranges were 0.5-64.0 for fluconazole, < 0.015-0.25 for itraconazole, 0.015-0.5 for amphotericin B and 0.062-2.0 for terbinafine. A bioassay for the quantitation of fluconazole in murine brain tissue was developed. Swiss mice received daily injections of the antifungal, and their brains were withdrawn at different times over the 14-day study period. The drug concentrations varied from 12.98 to 44.60 mu g/mL. This assay was used to evaluate the therapy with fluconazole in a model of infection caused by C. gattii. Swiss mice were infected intracranially and treated with fluconazole for 7, 10 or 14 days. The treatment reduced the fungal burden, but an increase in fungal growth was observed on day 14. The MIC for fluconazole against sequential isolates was 16 mu g/mL, except for the isolates obtained from animals treated for 14 days (MIC = 64 mu g/mL). The quantitation of cytokines revealed a predominance of IFN-gamma and IL-12 in the non-treated group and elevation of IL-4 and IL-10 in the treated group. Our data revealed the possibility of acquired resistance during the antifungal drug therapy.

Selecting salient objects in real scenes: An oscillatory correlation model

Attention is a critical mechanism for visual scene analysis. By means of attention, it is possible to break down the analysis of a complex scene to the analysis of its parts through a selection process. Empirical studies demonstrate that attentional selection is conducted on visual objects as a whole. We present a neurocomputational model of object-based selection in the framework of oscillatory correlation. By segmenting an input scene and integrating the segments with their conspicuity obtained from a saliency map, the model selects salient objects rather than salient locations. The proposed system is composed of three modules: a saliency map providing saliency values of image locations, image segmentation for breaking the input scene into a set of objects, and object selection which allows one of the objects of the scene to be selected at a time. This object selection system has been applied to real gray-level and color images and the simulation results show the effectiveness of the system. (C) 2010 Elsevier Ltd. All rights reserved.

Chaotic model and memory in single calcium-activated potassium channel kinetics

Ion channels are pores formed by proteins and responsible for carrying ion fluxes through cellular membranes. The ion channels can assume conformational states thereby controlling ion flow. Physically, the conformational transitions from one state to another are associated with energy barriers between them and are dependent on stimulus, such as, electrical field, ligands, second messengers, etc. Several models have been proposed to describe the kinetics of ion channels. The classical Markovian model assumes that a future transition is independent of the time that the ion channel stayed in a previous state. Others models as the fractal and the chaotic assume that the rate of transitions between the states depend on the time that the ionic channel stayed in a previous state. For the calcium activated potassium channels of Leydig cells the R/S Hurst analysis has indicated that the channels are long-term correlated with a Hurst coefficient H around 0.7, showing a persistent memory in this kinetic. Here, we applied the R/S analysis to the opening and closing dwell time series obtained from simulated data from a chaotic model proposed by L. Liebovitch and T. Toth [J. Theor. Biol. 148, 243 (1991)] and we show that this chaotic model or any model that treats the set of channel openings and closings as independent events is inadequate to describe the long-term correlation (memory) already described for the experimental data. (C) 2008 American Institute of Physics.

A New Mouse Model for Marfan Syndrome Presents Phenotypic Variability Associated with the Genetic Background and Overall Levels of Fbn1 Expression

Marfan syndrome is an autosomal dominant disease of connective tissue caused by mutations in the fibrillin-1 encoding gene FBN1. Patients present cardiovascular, ocular and skeletal manifestations, and although being fully penetrant, MFS is characterized by a wide clinical variability both within and between families. Here we describe a new mouse model of MFS that recapitulates the clinical heterogeneity of the syndrome in humans. Heterozygotes for the mutant Fbn1 allele mg Delta(loxPneo), carrying the same internal deletion of exons 19-24 as the mg Delta mouse model, present defective microfibrillar deposition, emphysema, deterioration of aortic wall and kyphosis. However, the onset of a clinical phenotypes is earlier in the 129/Sv than in C57BL/6 background, indicating the existence of genetic modifiers of MFS between these two mouse strains. In addition, we characterized a wide clinical variability within the 129/Sv congenic heterozygotes, suggesting involvement of epigenetic factors in disease severity. Finally, we show a strong negative correlation between overall levels of Fbn1 expression and the severity of the phenotypes, corroborating the suggested protective role of normal fibrillin-1 in MFS pathogenesis, and supporting the development of therapies based on increasing Fbn1 expression.

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.

Physical signatures of discontinuities of the time-dependent exchange-correlation potential

The exact exchange-correlation (XC) potential in time-dependent density-functional theory (TDDFT) is known to develop steps and discontinuities upon change of the particle number in spatially confined regions or isolated subsystems. We demonstrate that the self-interaction corrected adiabatic local-density approximation for the XC potential has this property, using the example of electron loss of a model quantum well system. We then study the influence of the XC potential discontinuity in a real-time simulation of a dissociation process of an asymmetric double quantum well system, and show that it dramatically affects the population of the resulting isolated single quantum wells. This indicates the importance of a proper account of the discontinuities in TDDFT descriptions of ionization, dissociation or charge transfer processes.

Multifractality in the random parameter model for multivariate time series

The Random Parameter model was proposed to explain the structure of the covariance matrix in problems where most, but not all, of the eigenvalues of the covariance matrix can be explained by Random Matrix Theory. In this article, we explore the scaling properties of the model, as observed in the multifractal structure of the simulated time series. We use the Wavelet Transform Modulus Maxima technique to obtain the multifractal spectrum dependence with the parameters of the model. The model shows a scaling structure compatible with the stylized facts for a reasonable choice of the parameter values. (C) 2009 Elsevier B.V. All rights reserved.

A BEM model applied to failure analysis of multi-fractured structures

Due to manufacturing or damage process, brittle materials present a large number of micro-cracks which are randomly distributed. The lifetime of these materials is governed by crack propagation under the applied mechanical and thermal loadings. In order to deal with these kinds of materials, the present work develops a boundary element method (BEM) model allowing for the analysis of multiple random crack propagation in plane structures. The adopted formulation is based on the dual BEM, for which singular and hyper-singular integral equations are used. An iterative scheme to predict the crack growth path and crack length increment is proposed. This scheme enables us to simulate the localization and coalescence phenomena, which are the main contribution of this paper. Considering the fracture mechanics approach, the displacement correlation technique is applied to evaluate the stress intensity factors. The propagation angle and the equivalent stress intensity factor are calculated using the theory of maximum circumferential stress. Examples of multi-fractured domains, loaded up to rupture, are considered to illustrate the applicability of the proposed method. (C) 2011 Elsevier Ltd. All rights reserved.

New prediction methods for CO2 evaporation inside tubes: Part I - A two-phase flow pattern map and a flow pattern based phenomenological model for two-phase flow frictional pressure drops

An updated flow pattern map was developed for CO2 on the basis of the previous Cheng-Ribatski-Wojtan-Thome CO2 flow pattern map [1,2] to extend the flow pattern map to a wider range of conditions. A new annular flow to dryout transition (A-D) and a new dryout to mist flow transition (D-M) were proposed here. In addition, a bubbly flow region which generally occurs at high mass velocities and low vapor qualities was added to the updated flow pattern map. The updated flow pattern map is applicable to a much wider range of conditions: tube diameters from 0.6 to 10 mm, mass velocities from 50 to 1500 kg/m(2) s, heat fluxes from 1.8 to 46 kW/m(2) and saturation temperatures from -28 to +25 degrees C (reduced pressures from 0.21 to 0.87). The updated flow pattern map was compared to independent experimental data of flow patterns for CO2 in the literature and it predicts the flow patterns well. Then, a database of CO2 two-phase flow pressure drop results from the literature was set up and the database was compared to the leading empirical pressure drop models: the correlations by Chisholm [3], Friedel [4], Gronnerud [5] and Muller-Steinhagen and Heck [6], a modified Chisholm correlation by Yoon et al. [7] and the flow pattern based model of Moreno Quiben and Thome [8-10]. None of these models was able to predict the CO2 pressure drop data well. Therefore, a new flow pattern based phenomenological model of two-phase flow frictional pressure drop for CO2 was developed by modifying the model of Moreno Quiben and Thome using the updated flow pattern map in this study and it predicts the CO2 pressure drop database quite well overall. (C) 2007 Elsevier Ltd. All rights reserved.

New prediction methods for CO2 evaporation inside tubes: Part II - An updated general flow boiling heat transfer model based on flow patterns

Corresponding to the updated flow pattern map presented in Part I of this study, an updated general flow pattern based flow boiling heat transfer model was developed for CO2 using the Cheng-Ribatski-Wojtan-Thome [L. Cheng, G. Ribatski, L. Wojtan, J.R. Thome, New flow boiling heat transfer model and flow pattern map for carbon dioxide evaporating inside horizontal tubes, Int. J. Heat Mass Transfer 49 (2006) 4082-4094; L. Cheng, G. Ribatski, L. Wojtan, J.R. Thome, Erratum to: ""New flow boiling heat transfer model and flow pattern map for carbon dioxide evaporating inside tubes"" [Heat Mass Transfer 49 (21-22) (2006) 4082-4094], Int. J. Heat Mass Transfer 50 (2007) 391] flow boiling heat transfer model as the starting basis. The flow boiling heat transfer correlation in the dryout region was updated. In addition, a new mist flow heat transfer correlation for CO2 was developed based on the CO2 data and a heat transfer method for bubbly flow was proposed for completeness sake. The updated general flow boiling heat transfer model for CO2 covers all flow regimes and is applicable to a wider range of conditions for horizontal tubes: tube diameters from 0.6 to 10 mm, mass velocities from 50 to 1500 kg/m(2) s, heat fluxes from 1.8 to 46 kW/m(2) and saturation temperatures from -28 to 25 degrees C (reduced pressures from 0.21 to 0.87). The updated general flow boiling heat transfer model was compared to a new experimental database which contains 1124 data points (790 more than that in the previous model [Cheng et al., 2006, 2007]) in this study. Good agreement between the predicted and experimental data was found in general with 71.4% of the entire database and 83.2% of the database without the dryout and mist flow data predicted within +/-30%. However, the predictions for the dryout and mist flow regions were less satisfactory due to the limited number of data points, the higher inaccuracy in such data, scatter in some data sets ranging up to 40%, significant discrepancies from one experimental study to another and the difficulties associated with predicting the inception and completion of dryout around the perimeter of the horizontal tubes. (C) 2007 Elsevier Ltd. All rights reserved.

Correlation Between Autofluorescence Intensity and Tumor Area in Mice Bearing Renal Cell Carcinoma

Protoporphyrin IX (PpIX) is a porphyrin derivative that is accumulated in cancerous tissue in consequence of the tumor-specific metabolic alterations. The aim of this study was to evaluate the accumulation of PpIX in mice bearing renal cell carcinoma by spectroscopy analysis. A total of 24 male Balb/c mice, 6 weeks old, were divided into six groups: Normal (without inoculation of tumor cells) and 4, 8, 13, 16, and 20 days after inoculation of tumor cells. The orthotopic tumor model of renal cancer was used. Murine renal cell carcinoma (Renca cells) were inoculated into the subcapsular space of the kidney. Normal and tumor-bearing kidneys in different progression stages were removed and analyzed by ex-vivo spectroscopy and by microscopy, for tumor histometric analysis. Emission spectra were obtained by exciting the samples at 405 nm. Significant differences between normal and tumor-bearing kidneys in autofluorescence shape occurred in the 600-700 nm spectral region. A good correlation was found between emission band intensity at 635 nm and the tumor area.

Influence of a probiotic soy product on fecal microbiota and its association with cardiovascular risk factors in an animal model

Background: Previous work showed that daily ingestion of an aqueous soy extract fermented with Enterococcus faecium CRL 183 and Lactobacillus helveticus 416, supplemented or not with isoflavones, reduced the total cholesterol and non-HDL-cholesterol levels, increased the high-density lipoprotein (HDL) concentration and inhibited the raising of autoantibody against oxidized low-density lipoprotein (ox-LDL Ab) and the development of atherosclerotic lesions. Objective: The aim of this study was to characterize the fecal microbiota in order to investigate the possible correlation between fecal microbiota, serum lipid parameters and atherosclerotic lesion development in rabbits with induced hypercholesterolemia, that ingested the aqueous soy extract fermented with Enterococcus faecium CRL 183 and Lactobacillus helveticus 416. Methods: The rabbits were randomly allocated to five experimental groups (n = 6): control (C), hypercholesterolemic (H), hypercholesterolemic plus unfermented soy product (HUF), hypercholesterolemic plus fermented soy product (HF) and hypercholesterolemic plus isoflavone-supplemented fermented soy product (HIF). Lipid parameters and microbiota composition were analyzed on days 0 and 60 of the treatment and the atherosclerotic lesions were quantified at the end of the experiment. The fecal microbiota was characterized by enumerating the Lactobacillus spp., Bifidobacterium spp., Enterococcus spp., Enterobacteria and Clostridium spp. populations. Results: After 60 days of the experiment, intake of the probiotic soy product was correlated with significant increases (P < 0.05) on Lactobacillus spp., Bifidobacterium spp. and Enterococcus spp. and a decrease in the Enterobacteria population. A strong correlation was observed between microbiota composition and lipid profile. Populations of Enterococcus spp., Lactobacillus spp. and Bifidobacterium spp. were negatively correlated with total cholesterol, non-HDL-cholesterol, autoantibodies against oxidized LDL (ox-LDL Ab) and lesion size. HDL-C levels were positively correlated with Lactobacillus spp., Bifidobacterium spp., and Enterococcus spp. populations. Conclusion: In conclusion, daily ingestion of the probiotic soy product, supplemented or not with isoflavones, may contribute to a beneficial balance of the fecal microbiota and this modulation is associated with an improved cholesterol profile and inhibition of atherosclerotic lesion development.

Impact of Stent-Graft Oversizing on the Thoracic Aorta: Experimental Study in a Porcine Model

Purpose: To analyze in an experimental animal model the effect of 4 different levels of stents-graft oversizing on non-atherosclerotic aortas such as those found in young individuals who undergo stent-graft repair for traumatic aortic injuries. Methods: The diameter of the porcine thoracic aorta is similar to the aorta of young adults (18-20 mm), so 25 pigs were randomized into 5 groups: 1 control (without stent-graft) and 4 oversizing groups (A: 10%-19%, B: 20%-29%, C: 30%-39%, and D: >40%). Two types of biomechanical tests were performed on all aortas 4 weeks after endoprosthesis deployment. Results: The results of the detachment test, which analyzed the strength necessary to remove the stent-graft from the aorta, were similar in the 4 groups (A: 42 N, B: 41 N, C: 46 N, and D: 46 N). However, 2 aortas ruptured during the tests (groups C and D). The second test was performed in 3 aortic segments. Maximum shear strength, maximum stress, and maximum tension supported by the aortic wall had a negative and linear correlation with oversizing. There were significant differences in all 4 groups when compared with the control group. Strain, which reflects the elastic properties of the aortic wall, was very similar in all 4 groups, but a great difference was found when compared with the control group (p<0.0001). Conclusion: The study showed an important subacute change in the biomechanical properties of the aortic wall after implantation of an oversized endoprosthesis. This weakness of the aortic wall was confirmed by 2 ruptures during the detachment test. These results partially explain the interaction of stent-grafts with non-atherosclerotic thoracic aortas and may serve as a basis for further studies and the development of specific material to be used in vascular trauma and young patients. J Endovasc Ther. 2011; 18: 576-584