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 generalized multi-period mean-variance portfolio optimization with Markov switching parameters

In this paper, we deal with a generalized multi-period mean-variance portfolio selection problem with market parameters Subject to Markov random regime switchings. Problems of this kind have been recently considered in the literature for control over bankruptcy, for cases in which there are no jumps in market parameters (see [Zhu, S. S., Li, D., & Wang, S. Y. (2004). Risk control over bankruptcy in dynamic portfolio selection: A generalized mean variance formulation. IEEE Transactions on Automatic Control, 49, 447-457]). We present necessary and Sufficient conditions for obtaining an optimal control policy for this Markovian generalized multi-period meal-variance problem, based on a set of interconnected Riccati difference equations, and oil a set of other recursive equations. Some closed formulas are also derived for two special cases, extending some previous results in the literature. We apply the results to a numerical example with real data for Fisk control over bankruptcy Ill a dynamic portfolio selection problem with Markov jumps selection problem. (C) 2008 Elsevier Ltd. All rights reserved.

The beta modified Weibull distribution

A five-parameter distribution so-called the beta modified Weibull distribution is defined and studied. The new distribution contains, as special submodels, several important distributions discussed in the literature, such as the generalized modified Weibull, beta Weibull, exponentiated Weibull, beta exponential, modified Weibull and Weibull distributions, among others. The new distribution can be used effectively in the analysis of survival data since it accommodates monotone, unimodal and bathtub-shaped hazard functions. We derive the moments and examine the order statistics and their moments. We propose the method of maximum likelihood for estimating the model parameters and obtain the observed information matrix. A real data set is used to illustrate the importance and flexibility of the new distribution.

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.

Bias-corrected Pearson estimating functions for Taylor`s power law applied to benthic macrofauna data

Estimation of Taylor`s power law for species abundance data may be performed by linear regression of the log empirical variances on the log means, but this method suffers from a problem of bias for sparse data. We show that the bias may be reduced by using a bias-corrected Pearson estimating function. Furthermore, we investigate a more general regression model allowing for site-specific covariates. This method may be efficiently implemented using a Newton scoring algorithm, with standard errors calculated from the inverse Godambe information matrix. The method is applied to a set of biomass data for benthic macrofauna from two Danish estuaries. (C) 2011 Elsevier B.V. All rights reserved.

General results for the beta-modified Weibull distribution

We study in detail the so-called beta-modified Weibull distribution, motivated by the wide use of the Weibull distribution in practice, and also for the fact that the generalization provides a continuous crossover towards cases with different shapes. The new distribution is important since it contains as special sub-models some widely-known distributions, such as the generalized modified Weibull, beta Weibull, exponentiated Weibull, beta exponential, modified Weibull and Weibull distributions, among several others. It also provides more flexibility to analyse complex real data. Various mathematical properties of this distribution are derived, including its moments and moment generating function. We examine the asymptotic distributions of the extreme values. Explicit expressions are also derived for the chf, mean deviations, Bonferroni and Lorenz curves, reliability and entropies. The estimation of parameters is approached by two methods: moments and maximum likelihood. We compare by simulation the performances of the estimates from these methods. We obtain the expected information matrix. Two applications are presented to illustrate the proposed distribution.

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.

Validation of a root water uptake model to estimate transpiration constraints

Experimental results obtained from a greenhouse trial with common bean (Phaseolus vulgaris L) plants performed to test model hypotheses regarding the onset of limiting hydraulic conditions and the shape of the transpiration reduction curve in the falling rate phase are presented. According to these hypotheses based on simulations with an upscaled single-root model, the matric flux potential at the onset of limiting hydraulic conditions is as a function of root length density and potential transpiration rate, while the relative transpiration in the falling rate phase equals the relative matric flux potential. Transpiration of bean plants in water stressed pots with four different soils was determined daily by weighing and compared to values obtained from non-stressed pots. This procedure allowed determining the onset of the falling rate phase and corresponding soil hydraulic conditions. At the onset of the falling rate phase, the value of matric flux potential M(I) showed to differ in order of magnitude from the model predicted value for three out of four soils. This difference between model and experiment can be explained by the heterogeneity of the root distribution which is not considered by the model. An empirical factor to deal with this heterogeneity should be included in the model to improve predictions. Comparing the predictions of relative transpiration in the falling rate phase using a linear shape with water content, pressure head or matric flux potential, the matric flux potential based reduction function, in agreement with the hypothesis, showed the best performance, while the pressure head based equation resulted in the highest deviations between observed and predicted values of relative transpiration rates. (C) 2010 Elsevier B.V. All rights reserved.

Modeling soil organic carbon dynamics in Oxisols of Ibiruba (Brazil) with the Century Model

introduction of conservation practices in degraded agricultural land will generally recuperate soil quality, especially by increasing soil organic matter. This aspect of soil organic C (SOC) dynamics under distinct cropping and management systems can be conveniently analyzed with ecosystem models such as the Century Model. In this study, Century was used to simulate SOC stocks in farm fields of the Ibiruba region of north central Rio Grande do Sul state in Southern Brazil. The region, where soils are predominantly Oxisols, was originally covered with subtropical woodlands and grasslands. SOC dynamics was simulated with a general scenario developed with historical data on soil management and cropping systems beginning with the onset of agriculture in 1900. From 1993 to 2050, two contrasting scenarios based on no-tillage soil management were established: the status quo scenario, with crops and agricultural inputs as currently practiced in the region and the high biomass scenario with increased frequency of corn in the cropping system, resulting in about 80% higher biomass addition to soils. Century simulations were in close agreement with SOC stocks measured in 2005 in the Oxisols with finer texture surface horizon originally under woodlands. However, simulations in the Oxisols with loamy surface horizon under woodlands and in the grassland soils were not as accurate. SOC stock decreased from 44% to 50% in fields originally under woodland and from 20% to 27% in fields under grasslands with the introduction of intensive annual grain crops with intensive tillage and harrowing operations. The adoption of conservation practices in the 1980s led to a stabilization of SOC stocks followed by a partial recovery of native stocks. Simulations to 2050 indicate that maintaining status quo would allow SOC stocks to recover from 81% to 86% of the native stocks under woodland and from 80% to 91 % of the native stocks under grasslands. Adoption of a high biomass scenario would result in stocks from 75% to 95% of the original stocks under woodlands and from 89% to 102% in the grasslands by 2050. These simulations outcomes underline the importance of cropping system yielding higher biomass to further increase SOC content in these Oxisols. This application of the Century Model could reproduce general trends of SOC loss and recovery in the Oxisols of the Ibiruba region. Additional calibration and validation should be conducted before extensive usage of Century as a support tool for soil carbon sequestration projects in this and other regions can be recommended. (C) 2009 Elsevier B.V. All rights reserved.

Deciphering the weathering processes using environmental mineralogy and geochemistry: Towards an integrated model of laterite and podzol genesis in the Upper Amazon Basin

This article reports major results from collaborative research between France and Brazil on soil and water systems, carried out in the Upper Amazon Basin. It reveals the weathering processes acting in the partly inundated, low elevation plateaus of the Basin, mostly covered by evergreen forest. Our findings are based on geochemical data and mineral spectroscopy that probe the crystal chemistry of Fe and Al in mineral phases (mainly kaolinite, Al- and Fe-(hydr)oxides) of tropical soils (laterites). These techniques reveal crystal alterations in mineral populations of different ages and changes of metal speciation associated with mineral or organic phases. These results provide an integrated model of soil formation and changes (from laterites to podzols) in distinct hydrological compartments of the Amazon landscapes and under altered water regimes. (C) 2010 Academie des sciences. Published by Elsevier Masson SAS. 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.

Parameterization and Evaluation of Predictions of DSSAT/CANEGRO for Brazilian Sugarcane

The DSSAT/CANEGRO model was parameterized and its predictions evaluated using data from five sugarcane (Sacchetrum spp.) experiments conducted in southern Brazil. The data used are from two of the most important Brazilian cultivars. Some parameters whose values were either directly measured or considered to be well known were not adjusted. Ten of the 20 parameters were optimized using a Generalized Likelihood Uncertainty Estimation (GLUE) algorithm using the leave-one-out cross-validation technique. Model predictions were evaluated using measured data of leaf area index (LA!), stalk and aerial dry mass, sucrose content, and soil water content, using bias, root mean squared error (RMSE), modeling efficiency (Eff), correlation coefficient, and agreement index. The Decision Support System for Agrotechnology Transfer (DSSAT)/CANEGRO model simulated the sugarcane crop in southern Brazil well, using the parameterization reported here. The soil water content predictions were better for rainfed (mean RMSE = 0.122mm) than for irrigated treatment (mean RMSE = 0.214mm). Predictions were best for aerial dry mass (Eff = 0.850), followed by stalk dry mass (Eff = 0.765) and then sucrose mass (Eff = 0.170). Number of green leaves showed the worst fit (Eff = -2.300). The cross-validation technique permits using multiple datasets that would have limited use if used independently because of the heterogeneity of measures and measurement strategies.

Adapting the CROPGRO perennial forage model to predict growth of Brachiaria brizantha

Warm-season grasses are economically important for cattle production in tropical regions, and tools to aid in management and research of these forages would be highly beneficial. Crop simulation models synthesize numerous physiological processes and are important research tools for evaluating production of warm-season grasses. This research was conducted to adapt the perennial CROPGRO Forage model to simulate growth of the tropical species palisadegrass [Brachiaria brizantha (A. Rich.) Stapf. cv. Xaraes] and to describe model adaptation for this species. In order to develop the CROPGRO parameters for this species, we began with values and relationships reported in the literature. Some parameters and relationships were calibrated by comparison with observed growth, development, dry matter accumulation and partitioning during a 2-year experiment with Xaraes palisadegrass in Piracicaba, SP, Brazil. Starting with parameters for the bahiagrass (Paspalum notatum Flugge) perennial forage model, dormancy effects had to be minimized, and partitioning to storage tissue/root decreased, and partitioning to leaf and stem increased to provide for more leaf and stem growth and less root. Parameters affecting specific leaf area (SLA) and senescence of plant tissues were improved. After these changes were made to the model, biomass accumulation was better simulated, mean predicted herbage yield per cycle was 3573 kg ha(-1), with a RMSE of 538 kg DM ha(-1) (D-Stat = 0.838, simulated/observed ratio = 1.028). The results of the adaptation suggest that the CROPGRO model is an efficient tool to integrate physiological aspects of palisadegrass and can be used to simulate growth. (C) 2010 Elsevier B.V. All rights reserved.