Simulating maize phenology as a function of air temperature with a linear and a nonlinear model

The objective of this study was to adapt a nonlinear model (Wang and Engel - WE) for simulating the phenology of maize (Zea mays L.), and to evaluate this model and a linear one (thermal time), in order to predict developmental stages of a field-grown maize variety. A field experiment, during 2005/2006 and 2006/2007 was conducted in Santa Maria, RS, Brazil, in two growing seasons, with seven sowing dates each. Dates of emergence, silking, and physiological maturity of the maize variety BRS Missões were recorded in six replications in each sowing date. Data collected in 2005/2006 growing season were used to estimate the coefficients of the two models, and data collected in the 2006/2007 growing season were used as independent data set for model evaluations. The nonlinear WE model accurately predicted the date of silking and physiological maturity, and had a lower root mean square error (RMSE) than the linear (thermal time) model. The overall RMSE for silking and physiological maturity was 2.7 and 4.8 days with WE model, and 5.6 and 8.3 days with thermal time model, respectively.

THE INFLUENCE OF HIV-1 SUBTYPES C, CRF31_BC AND B ON DISEASE PROGRESSION AND INITIAL VIROLOGIC RESPONSE TO HAART IN A SOUTHERN BRAZILIAN COHORT

Background: Although most HIV-1 infections in Brazil are due to subtype B, Southern Brazil has a high prevalence of subtype C and recombinant forms, such as CRF31_BC. This study assessed the impact of viral diversity on clinical progression in a cohort of newly diagnosed HIV-positive patients. Methods: From July/2004 to December/2005, 135 HIV-infected patients were recruited. The partial pol region was subtyped by phylogeny. A generalized estimating equation (GEE) model was used to examine the relationship between viral subtype, CD4+ T cell count and viral load levels before antiretroviral therapy. Hazard ratio (Cox regression) was used to evaluate factors associated with viral suppression (viral load < 50 copies/mL at six months). Results: Main HIV-1 subtypes included B (29.4%), C (28.2%), and CRF31_BC (23.5%). Subtypes B and C showed a similar trend in CD4+ T cell decline. Comparison of non-B (C and CRF31_BC) and B subtypes revealed no significant difference in the proportion of patients with viral suppression at six months (week 24). Higher CD4+ T cell count and lower viral load were independently associated with viral suppression. Conclusion: No significant differences were found between subtypes; however, lower viral load and higher CD4+ T cell count before therapy were associated with better response.

Zinc adsorption in highly weathered soils

The objective of this work was to assess the effects of pH and ionic strength upon zinc adsorption, in three highly weathered variable charge soils. Adsorption isotherms were elaborated from batch adsorption experiments, with increasing Zn concentrations (0-80 mg L-1), and adsorption envelopes were constructed through soil samples reactions with 0.01, 0.1 and 1 mol L-1 Ca(NO3)2 solutions containing 5 mg L-1 of Zn, with an increasing pH value from 3 to 8. Driving force of reaction was quantified by Gibbs free energy and separation factor. Isotherms were C-, H- and L-type and experimental results were fitted to nonlinear Langmuir model. Maximum adsorption ranged from 59-810 mg kg-1, and Zn affinity was greater in subsoil (0.13-0.81 L kg-1) than in the topsoil samples (0.01-0.34 L kg-1). Zinc adsorption was favorable and spontaneous, and showed sharply increase (20-90%) in the 4-6 pH range. No effect of ionic strength was observed at pH values below 5, because specific adsorption mechanisms predominated in the 3-5 pH range. Above pH 5, and in subsoil samples, Zn was adsorbed by electrostatic mechanisms, since ionic strength effect was observed. Despite depth and ionic strength effects, Zn adsorption depends mainly on the pH.

Impact of increasing mean air temperature on the development of rice and red rice

The objective of this study was to assess the development response of cultivated rice and red rice to different increases in minimum and maximum daily air temperatures, in Santa Maria, Rio Grande do Sul State, Brazil. One hundred years climate scenarios of temperatures 0, +1, +2, +3, +4, and +5ºC, with symmetric and asymmetric increases in minimum and maximum daily air temperatures were created, using the LARS-WG Weather Generator, and a 1969-2003 database. Nine cultivated rice genotypes (IRGA 421, IRGA 416, IRGA 417, IRGA 420, BRS 7 TAIM, BR-IRGA 409, EPAGRI 109, EEA 406 and a hybrid), and two red rice biotypes (awned black hull-ABHRR, and awned yellow hull-AYHRR) were used. The dates of panicle differentiation (R1), anthesis (R4), and all grains with brown hulls (R9) were estimated with a nonlinear simulation model. Overall, the duration of the emergence-R1 phase decreased, whereas the duration of the R1-R4 and R4-R9 phases most often increased, as temperature increased in the climate change scenarios. The simulated rice development response to elevated temperature was not the same, when the increase in minimum and maximum temperature was symmetric or asymmetric.

Development of a weather-based model for Botrytis leaf blight of onion

ABSTRACT In the present study, onion plants were tested under controlled conditions for the development of a climate model based on the influence of temperature (10, 15, 20 and 25°C) and leaf wetness duration (6, 12, 24 and 48 hours) on the severity of Botrytis leaf blight of onion caused by Botrytis squamosa. The relative lesion density was influenced by temperature and leaf wetness duration (P <0.05). The disease was most severe at 20°C. Data were subjected to nonlinear regression analysis. Beta generalized function was used to adjust severity and temperature data, while a logistic function was chosen to represent the effect of leaf wetness on the severity of Botrytis leaf blight. The response surface obtained by the product of two functions was expressed as ES = 0.008192 * (((x-5)1.01089) * ((30-x)1.19052)) * (0.33859/(1+3.77989 * exp (-0.10923*y))), where ES represents the estimated severity value (0.1); x, the temperature (°C); and y, the leaf wetness (in hours). This climate model should be validated under field conditions to verify its use as a computational system for the forecasting of Botrytis leaf blight in onion.

Development of a three-dimensional nonlinear viscoelastic constitutive model of solid propellant

A three dimensional nonlinear viscoelastic constitutive model for the solid propellant is developed. In their earlier work, the authors have developed an isotropic constitutive model and verified it for one dimensional case. In the present work, the validity of the model is extended to three-dimensional cases. Large deformation, dewetting and cyclic loading effects are treated as the main sources of nonlinear behavior of the solid propellant. Viscoelastic dewetting criteria is used and the softening of the solid propellant due to dewetting is treated by the modulus decrease. The nonlinearities during cyclic loading are accounted for by the functions of the octahedral shear strain measure. The constitutive equation is implemented into a finite element code for the analysis of propellant grains. A commercial finite element package ‘ABAQUS’ is used for the analysis and the model is introduced into the code through a user subroutine. The model is evaluated with different loading conditions and the predicted values are in good agreement with the measured ones. The resulting model applied to analyze a solid propellant grain for the thermal cycling load.

Estimating Attractor Dimension on the Nonlinear Pendulum Time Series

Chaotic dynamical systems exhibit trajectories in their phase space that converges to a strange attractor. The strangeness of the chaotic attractor is associated with its dimension in which instance it is described by a noninteger dimension. This contribution presents an overview of the main definitions of dimension discussing their evaluation from time series employing the correlation and the generalized dimension. The investigation is applied to the nonlinear pendulum where signals are generated by numerical integration of the mathematical model, selecting a single variable of the system as a time series. In order to simulate experimental data sets, a random noise is introduced in the time series. State space reconstruction and the determination of attractor dimensions are carried out regarding periodic and chaotic signals. Results obtained from time series analyses are compared with a reference value obtained from the analysis of mathematical model, estimating noise sensitivity. This procedure allows one to identify the best techniques to be applied in the analysis of experimental data.

Principal components and generalized linear modeling in the correlation between hospital admissions and air pollution

OBJECTIVE To analyze the association between concentrations of air pollutants and admissions for respiratory causes in children. METHODS Ecological time series study. Daily figures for hospital admissions of children aged < 6, and daily concentrations of air pollutants (PM10, SO2, NO2, O3 and CO) were analyzed in the Região da Grande Vitória, ES, Southeastern Brazil, from January 2005 to December 2010. For statistical analysis, two techniques were combined: Poisson regression with generalized additive models and principal model component analysis. Those analysis techniques complemented each other and provided more significant estimates in the estimation of relative risk. The models were adjusted for temporal trend, seasonality, day of the week, meteorological factors and autocorrelation. In the final adjustment of the model, it was necessary to include models of the Autoregressive Moving Average Models (p, q) type in the residuals in order to eliminate the autocorrelation structures present in the components. RESULTS For every 10:49 μg/m3 increase (interquartile range) in levels of the pollutant PM10 there was a 3.0% increase in the relative risk estimated using the generalized additive model analysis of main components-seasonal autoregressive – while in the usual generalized additive model, the estimate was 2.0%. CONCLUSIONS Compared to the usual generalized additive model, in general, the proposed aspect of generalized additive model − principal component analysis, showed better results in estimating relative risk and quality of fit.

Cholestasis in a murine experimental model: lesions include hepatocyte ischemic necrosis

OBJECTIVE: To establish a murine experimental model of bile duct obstruction that would enable controlled observations of the acute and subacute phases of cholestasis. METHODOLOGY: Adult male isogenic BALB/c mice underwent a bile duct ligation (22 animals) or a sham operation (10 animals). Fifteen days after surgery, or immediately after the animal's death, macroscopic findings were noted and histological study of the liver, biliary tree, and pancreas was performed (hematoxylin-eosin and Masson trichromic staining). RESULTS: Beginning 24 hours after surgery, all animals from the bile duct ligation group presented progressive generalized malaise. All animals presented jaundice in the parietal and visceral peritoneum, turgid and enlarged liver, and accentuated dilatation of gallbladder and common bile duct. Microscopic findings included marked dilatation and proliferation of bile ducts with accentuated collagen deposits, frequent areas of ischemic necrosis, hepatic microabscesses, and purulent cholangitis. Animals from the sham operation group presented no alterations. CONCLUSION: We established a murine experimental model of induced cholestasis, which made it possible to study acute and subacute tissue lesions. Our data suggests that in cholestasis, hepatic functional ischemia plays an important role in inducing hepatic lesions, and it also suggests that the infectious process is an important factor in morbidity and mortality.

Economic threshold levels for the velvetbean caterpillar on soybeans in Brazil: the social and the private perspectives

Pest Control is treated as a economic problem. The social and the private perspectives differ due to the consideration of the environmental and social impacts as well as technical aspects such as resistance, resurgence and secondary pests. A mathematical model is developed to determine and compare the social and the private optimum control strategies (which define the Economic Thereshold Levels) for the velvetbean caterpillar on soybeans in Brazil. The crop/pest system incorporates effects of predators and parasites, the soybean natural capacity to compensate for injury and the pesticide effects on both pests and its natural enemies; in the social case, the environmental and social impacts and the effects of pest resistance to the pesticide are incorporated. Consideration of density dependence, weather effects, randomnes of pest attack and risk aversion are discussed. The results can be compared with current control practices and IPM programme recomendations.