Animated solid model of the lung constructed from unsynchronized MR sequential images

This work discusses a 4D lung reconstruction method from unsynchronized MR sequential images. The lung, differently from the heart, does not have its own muscles, turning impossible to see its real movements. The visualization of the lung in motion is an actual topic of research in medicine. CT (Computerized Tomography) can obtain spatio-temporal images of the heart by synchronizing with electrocardiographic waves. The FOV of the heart is small when compared to the lung`s FOV. The lung`s movement is not periodic and is susceptible to variations in the degree of respiration. Compared to CT, MR (Magnetic Resonance) imaging involves longer acquisition times and it is not possible to obtain instantaneous 3D images of the lung. For each slice, only one temporal sequence of 2D images can be obtained. However, methods using MR are preferable because they do not involve radiation. In this paper, based on unsynchronized MR images of the lung an animated B-Repsolid model of the lung is created. The 3D animation represents the lung`s motion associated to one selected sequence of MR images. The proposed method can be divided in two parts. First, the lung`s silhouettes moving in time are extracted by detecting the presence of a respiratory pattern on 2D spatio-temporal MR images. This approach enables us to determine the lung`s silhouette for every frame, even on frames with obscure edges. The sequence of extracted lung`s silhouettes are unsynchronized sagittal and coronal silhouettes. Using our algorithm it is possible to reconstruct a 3D lung starting from a silhouette of any type (coronal or sagittal) selected from any instant in time. A wire-frame model of the lung is created by composing coronal and sagittal planar silhouettes representing cross-sections. The silhouette composition is severely underconstrained. Many wire-frame models can be created from the observed sequences of silhouettes in time. Finally, a B-Rep solid model is created using a meshing algorithm. Using the B-Rep solid model the volume in time for the right and left lungs were calculated. It was possible to recognize several characteristics of the 3D real right and left lungs in the shaded model. (C) 2007 Elsevier Ltd. All rights reserved.

A modified epidemiological model for computer viruses

Since the computer viruses pose a serious problem to individual and corporative computer systems, a lot of effort has been dedicated to study how to avoid their deleterious actions, trying to create anti-virus programs acting as vaccines in personal computers or in strategic network nodes. Another way to combat viruses propagation is to establish preventive policies based on the whole operation of a system that can be modeled with population models, similar to those that are used in epidemiological studies. Here, a modified version of the SIR (Susceptible-Infected-Removed) model is presented and how its parameters are related to network characteristics is explained. Then, disease-free and endemic equilibrium points are calculated, stability and bifurcation conditions are derived and some numerical simulations are shown. The relations among the model parameters in the several bifurcation conditions allow a network design minimizing viruses risks. (C) 2009 Elsevier Inc. All rights reserved.

Closed-loop model re-identification of processes under MPC with zone control

This work deals with a procedure for model re-identification of a process in closed loop with ail already existing commercial MPC. The controller considered here has a two-layer structure where the upper layer performs a target calculation based on a simplified steady-state optimization of the process. Here, it is proposed a methodology where a test signal is introduced in a tuning parameter of the target calculation layer. When the outputs are controlled by zones instead of at fixed set points, the approach allows the continuous operation of the process without an excessive disruption of the operating objectives as process constraints and product specifications remain satisfied during the identification test. The application of the method is illustrated through the simulation of two processes of the oil refining industry. (c) 2008 Elsevier Ltd. All rights reserved.

A log-extended Weibull regression model

A bathtub-shaped failure rate function is very useful in survival analysis and reliability studies. The well-known lifetime distributions do not have this property. For the first time, we propose a location-scale regression model based on the logarithm of an extended Weibull distribution which has the ability to deal with bathtub-shaped failure rate functions. We use the method of maximum likelihood to estimate the model parameters and some inferential procedures are presented. We reanalyze a real data set under the new model and the log-modified Weibull regression model. We perform a model check based on martingale-type residuals and generated envelopes and the statistics AIC and BIC to select appropriate models. (C) 2009 Elsevier B.V. All rights reserved.

The generalized log-gamma mixture model with covariates: local influence and residual analysis

In a sample of censored survival times, the presence of an immune proportion of individuals who are not subject to death, failure or relapse, may be indicated by a relatively high number of individuals with large censored survival times. In this paper the generalized log-gamma model is modified for the possibility that long-term survivors may be present in the data. The model attempts to separately estimate the effects of covariates on the surviving fraction, that is, the proportion of the population for which the event never occurs. The logistic function is used for the regression model of the surviving fraction. Inference for the model parameters is considered via maximum likelihood. Some influence methods, such as the local influence and total local influence of an individual are derived, analyzed and discussed. Finally, a data set from the medical area is analyzed under the log-gamma generalized mixture model. A residual analysis is performed in order to select an appropriate model.

Double generalized linear model for tissue culture proportion data: a Bayesian perspective

Joint generalized linear models and double generalized linear models (DGLMs) were designed to model outcomes for which the variability can be explained using factors and/or covariates. When such factors operate, the usual normal regression models, which inherently exhibit constant variance, will under-represent variation in the data and hence may lead to erroneous inferences. For count and proportion data, such noise factors can generate a so-called overdispersion effect, and the use of binomial and Poisson models underestimates the variability and, consequently, incorrectly indicate significant effects. In this manuscript, we propose a DGLM from a Bayesian perspective, focusing on the case of proportion data, where the overdispersion can be modeled using a random effect that depends on some noise factors. The posterior joint density function was sampled using Monte Carlo Markov Chain algorithms, allowing inferences over the model parameters. An application to a data set on apple tissue culture is presented, for which it is shown that the Bayesian approach is quite feasible, even when limited prior information is available, thereby generating valuable insight for the researcher about its experimental results.

A Model for comparing reduced impact logging with conventional logging for an Eastern Amazonian Forest

Using data from a logging experiment in the eastern Brazilian Amazon region, we develop a matrix growth and yield model that captures the dynamic effects of harvest system choice on forest structure and composition. Multinomial logistic regression is used to estimate the growth transition parameters for a 10-year time step, while a Poisson regression model is used to estimate recruitment parameters. The model is designed to be easily integrated with an economic model of decisionmaking to perform tropical forest policy analysis. The model is used to compare the long-run structure and composition of a stand arising from the choice of implementing either conventional logging techniques or more carefully planned and executed reduced-impact logging (RIL) techniques, contrasted against a baseline projection of an unlogged forest. Results from log and leave scenarios show that a stand logged according to Brazilian management requirements will require well over 120 years to recover its initial commercial volume, regardless of logging technique employed. Implementing RIL, however, accelerates this recovery. Scenarios imposing a 40-year cutting cycle raise the possibility of sustainable harvest volumes, although at significantly lower levels than is implied by current regulations. Meeting current Brazilian forest policy goals may require an increase in the planned total area of permanent production forest or the widespread adoption of silvicultural practices that increase stand recovery and volume accumulation rates after RIL harvests. Published by Elsevier B.V.

WATER RESOURCES SITUATION AT PIRACICABA, CAPIVARI AND JUNDIAI WATERSHEDS USING A DYNAMIC SYSTEMS MODEL

Using a dynamic systems model specifically developed for Piracicaba, Capivari and Jundia River Water Basins (BH-PCJ) as a tool to help to analyze water resources management alternatives for policy makers and decision takers, five simulations for 50 years timeframe were performed. The model estimates water supply and demand, as well as wastewater generation from the consumers at BH-PCJ. A run was performed using mean precipitation value constant, and keeping the actual water supply and demand rates, the business as usual scenario. Under these considerations, it is expected an increment of about similar to 76% on water demand, that similar to 39% of available water volume will come from wastewater reuse, and that waste load increases to similar to 91%. Falkenmark Index will change from 1,403 m(3) person(-1) year(-1) in 2004, to 734 m(3) P(-1) year(-1) by 2054, and the Sustainability Index from 0.44 to 0.20. Another four simulations were performed by affecting the annual precipitation by 90 and 110%; considering an ecological flow equal to 30% of the mean daily flow; and keeping the same rates for all other factors except for ecological flow and household water consumption. All of them showed a tendency to a water crisis in the near future at BH-PCJ.

Suitability of relative humidity as an estimator of leaf wetness duration

Leaf wetness duration (LWD) is a key parameter in agricultural meteorology since it is related to epidemiology of many important crops, controlling pathogen infection and development rates. Because LWD is not widely measured, several methods have been developed to estimate it from weather data. Among the models used to estimate LWD, those that use physical principles of dew formation and dew and/or rain evaporation have shown good portability and sufficiently accurate results, but their complexity is a disadvantage for operational use. Alternatively, empirical models have been used despite their limitations. The simplest empirical models use only relative humidity data. The objective of this study was to evaluate the performance of three RH-based empirical models to estimate LWD in four regions around the world that have different climate conditions. Hourly LWD, air temperature, and relative humidity data were obtained from Ames, IA (USA), Elora, Ontario (Canada), Florence, Toscany (Italy), and Piracicaba, Sao Paulo State (Brazil). These data were used to evaluate the performance of the following empirical LWD estimation models: constant RH threshold (RH >= 90%); dew point depression (DPD); and extended RH threshold (EXT_RH). Different performance of the models was observed in the four locations. In Ames, Elora and Piracicaba, the RH >= 90% and DPD models underestimated LWD, whereas in Florence these methods overestimated LWD, especially for shorter wet periods. When the EXT_RH model was used, LWD was overestimated for all locations, with a significant increase in the errors. In general, the RH >= 90% model performed best, presenting the highest general fraction of correct estimates (F(C)), between 0.87 and 0.92, and the lowest false alarm ratio (F(AR)), between 0.02 and 0.31. The use of specific thresholds for each location improved accuracy of the RH model substantially, even when independent data were used; MAE ranged from 1.23 to 1.89 h, which is very similar to errors obtained with published physical models for LWD estimation. Based on these results, we concluded that, if calibrated locally, LWD can be estimated with acceptable accuracy by RH above a specific threshold, and that the EXT_RH method was unsuitable for estimating LWD at the locations used in this study. (C) 2007 Elsevier B.V. All rights reserved.

The Infection of Soybean Leaves by Phakopsora pachyrhizi during Conditions of Discontinuous Wetness

The ability of Phakopsora pachyrhizi to cause infection under conditions of discontinuous wetness was investigated. In in vitro experiments, droplets of a uredospore suspension were deposited onto the surface of polystyrene. After an initial wetting period of either 1, 2 or 4 h, the drops were dried for different time intervals and then the wetness was restored for 11, 10 or 8 h. Germination and appressorium formation were evaluated. In in vivo experiments, soybean plants were inoculated with a uredospore suspension. Leaf wetness was interrupted for 1, 3 or 6 h after initial wetting periods of 1, 2 or 4 h. Then, the wetting was re-established for 11, 10 or 8 h, respectively. Rust severity was evaluated 14 days after inoculation. The germination of the spores and the formation of the appressoria on the soybean leaves after different periods of wetness were also quantified in vivo by scanning electron microscopy. P. pachyrhizi showed a high infective capacity during short periods of time. An interruption of wetness after 1 h caused average reductions in germination from 56 to 75% and in appressorium formation from 84 to 96%. Rust severity was lower in all of the in vivo treatments with discontinuous wetness when compared to the control plants. Rust severity was zero when the interruption of wetness occurred 4 h after the initial wetting. Wetting interruptions after 1 and 2 h reduced the average rust severity by 83 and 77%, respectively. The germination of the uredospores on the soybean leaves occurred after 2 h of wetness, with a maximum germination appearing after 4 h of wetness. Wetness interruption affected mainly the spores that had initiated the germination.

Natural infection of Nicandra physaloides by Tomato severe rugose virus in Brazil

Nicandra physaloides, a common weed in South America, was found to be infected by an isolate of Tomato severe rugose virus (ToSRV), a bipartite begomovirus. The plants developed severe yellow rugose mosaic and were collected in So Paulo State, Brazil. This isolate of ToSRV was transmitted by Bemisia tabaci B biotype from infected plants of N. physaloides to healthy plants of N. physaloides and tomato in a glasshouse. This is the first report of natural infection of N. physaloides by ToSRV in Brazil.

Inheritance of resistance to Puccinia psidii G. Winter in a eucalyptus interspecific hybrid progeny evaluated under conditions of natural infection

Inheritance of resistance to Puccinia psidii G. Winter in a eucalyptus interspecific hybrid progeny evaluated under conditions of natural infection Rust caused by the fungus Puccinia psidii is currently the most important disease of eucalyptus. It is widely disseminated in Brazil, and causes serious damage in nurseries and plantation areas. The identification of resistant germplasm along with knowledge of the genetic basis of resistance heredity are the first requirements for the success of breeding programs aiming to develop resistant varieties. Earlier studies carried out under controlled conditions suggested a monogenic control as well as the participation of at least two genes promoting resistance to rust. The goal of this study was to evaluate the resistance to P. psidii under field conditions in fourteen progenies from controlled crosses and self-crosses among four hybrid clones of Eucalyptus grandis Hill ex Maiden x Eucalyptus urophylla ST Blake that contrast for resistance to the fungus. Results indicated that resistance could be explained by one locus with main effects and at least three different alleles. However, loci with minor effects may influence the resistance, since variation on severity classes was observed. Differences in segregation of resistance between reciprocal crosses were not observed, indicating absence of cytoplasmic effects.

Infection of guava by Colletotrichum gloeosporioides and Colletotrichum acutatum under different temperatures and wetting periods

Anthracnose, caused by Colletotrichum gloeosporioides and C acutatum, is one of file main post-harvest diseases in guavas. This study aimed to determine the influence of environmental variables oil germination and appressorium formation of Colletotrichum gloeosporioides and C acutatum and infection of Kumagai guavas by these pathogens. The germination rate and the apressorium formation rate in vitro were determined under temperatures of 10, 15, 20, 25, 30, 35 and 40 degrees C, with wetting periods of 6, 12 and 24 hours, The infection of guavas was determined under temperatures of 15, 20, 25 and 30 degrees C and wetting period of 24 hours. There was no germination at 40 degrees C for either species. The germination and apressorium formation rate were rather high in the range of 15 to 30 degrees C for C. gloeosporioides, with a maximum at 25 degrees C. For the species C. acutatum, germination and apressorium formation rates were more sensitive to variations in temperature, with a maximum at 20 degrees C. The wetting periods tested somewhat influenced the germination of C. gloeosporioides, whereas in C acutatum the germination was significantly lower with 6 hours of wetting than 12 and 24 hours. The infection of guavas, for both fungal species, increased with the temperature, unlike conidium germination and apressorium formation. Incidences of 100% occurred with 30 degrees C, at 10 days after the inoculation.

Spatial pattern of black spot incidence within citrus trees related to disease severity and pathogen dispersal

Guignardia citricarpa, the causal agent of citrus black spot, forms airborne ascospores on decomposing citrus leaves and water-spread conidia on fruits, leaves and twigs. The spatial pattern of diseased fruit in citrus tree canopies was used to assess the importance of ascospores and conidia in citrus black spot epidemics in Sao Paulo State, Brazil. The aggregation of diseased fruit in the citrus tree canopy was quantified by the binomial dispersion index (D) and the binary form of Taylor`s Power Law for 303 trees in six groves. D was significantly greater than 1 in 251 trees. The intercept of the regression line of Taylor`s Power Law was significantly greater than 0 and the slope was not different from 1, implying that diseased fruit was aggregated in the canopy independent of disease incidence. Disease incidence (p) and severity (S) were assessed in 2875 citrus trees. The incidence-severity relationship was described (R-2 = 88.7%) by the model ln(S) = ln(a) + bCLL(p) where CLL = complementary log-log transformation. The high severity at low incidence observed in many cases is also indicative of low distance spread of G. citricarpa spores. For the same level of disease incidence, some trees had most of the diseased fruit with many lesions and high disease severity, whereas other trees had most of the fruit with few lesions and low disease severity. Aggregation of diseased fruit in the trees suggests that splash-dispersed conidia have an important role in increasing the disease in citrus trees in Brazil.

Peach brown rot incidence related to pathogen infection at different stages of fruit development in an organic peach production system

Brown rot, caused by Monilinia fructicola, is the most widespread disease for organic peach production systems in Brazil. The objective of this study was to determine the favorable periods for latent infection by M. fructicola in organic systems. The field experiment was carried out during 2006, 2007 and 2008 using the cultivar Aurora. After thinning fruits were bagged using white paraffin bags, and the treatments were performed by removing the bags and exposing the fruit for four days to the natural infection during each of seven fruit stages from pit hardening to harvest. Throughout the entire growing season, the conidial density and the weather variables were measured and related to the disease incidence using multiple regression analyses. At the fourth day after harvest in each season, the cumulative disease incidence was assessed, and it ranged from 40 to 98%. The incidence of brown rot on fruit that were exposed during the embryo growing stage was lower than that of unbagged fruit throughout the entire season in 2006 and 2008. The relative humidity and the conidia density were significantly correlated to disease incidence. Based on our results, M. fructicola can infect peaches during any stage of fruit development, and control of the disease must be revised to account for organic peach production systems. (C) 2011 Elsevier Ltd. All rights reserved.