Simulation of irrigated Thanzania grass growth based on photothermal units, nitrogen fertilization and water availability

Simulation of irrigated Thanzania grass growth based on photothermal units, nitrogen fertilization and water availability. The mathematical model to predict the forage yield using photothennal units was utilized with success in Elephant grass, Thanzania and Brachiaria niziziensis in the absence of water stress and nitrogen stress. The aim of this study was to propose models to estimate the forage yield of Thanzania grass under different irrigation (25, 50,75, 100 e 125% of ETc) and nitrogen level in various regions of Brazil. As such, models were developed to estimate the dry matter production of Panicum maximum Jacq. frass cv Thanzania in different irrigation and nitrogen levels, using photothermal units. The models were adjusted to doses of 0, 30, 60, 110 and 270 kg of N ha(-1), doses were divided in applications after each evaluation, with a rest cycle of 35 days. The adjusted model presented good performance in predicting dry matter production of Thanzania grass, with r(2) = 0.9999. The results made it possible to verify that the proposed model can be used to predict forage production in different regions of Brazil. It can be estimated, with good precision. The production of Thanzania grass dry matter can be accurately estimated in specific places (in function of latitude and time of year), with the maximum and minimum temperature values.

Spatio-temporal modeling of agricultural yield data with an application to pricing crop insurance contracts

This article presents a statistical model of agricultural yield data based on a set of hierarchical Bayesian models that allows joint modeling of temporal and spatial autocorrelation. This method captures a comprehensive range of the various uncertainties involved in predicting crop insurance premium rates as opposed to the more traditional ad hoc, two-stage methods that are typically based on independent estimation and prediction. A panel data set of county-average yield data was analyzed for 290 counties in the State of Parana (Brazil) for the period of 1990 through 2002. Posterior predictive criteria are used to evaluate different model specifications. This article provides substantial improvements in the statistical and actuarial methods often applied to the calculation of insurance premium rates. These improvements are especially relevant to situations where data are limited.

Modeling of transpiration reduction in van Genuchten-Mualem type soils

We derive an analytic expression for the matric flux potential (M) for van Genuchten-Mualem (VGM) type soils which can also be written in terms of a converging infinite series. Considering the first four terms of this series, the accuracy of the approximation was verified by comparing it to values of M estimated by numerical finite difference integration. Using values of the parameters for three soils from different texture classes, the proposed four-term approximation showed an almost perfect match with the numerical solution, except for effective saturations higher than 0.9. Including more terms reduced the discrepancy but also increased the complexity of the equation. The four-term equation can be used for most applications. Cases with special interest in nearly saturated soils should include more terms from the infinite series. A transpiration reduction function for use with the VGM equations is derived by combining the derived expression for M with a root water extraction model. The shape of the resulting reduction function and its dependency on the derivative of the soil hydraulic diffusivity D with respect to the soil water content theta is discussed. Positive and negative values of dD/d theta yield concave and convex or S-shaped reduction functions, respectively. On the basis of three data sets, the hydraulic properties of virtually all soils yield concave reduction curves. Such curves based solely on soil hydraulic properties do not account for the complex interactions between shoot growth, root growth, and water availability.

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.

Molecular Modeling Suggests Cruzain Specificity for Peptide Primaquine Prodrugs

Chagas` disease, infection caused by the protozoan Trypanosoma cruzi, is an important, social and medical ailment in the Latin America. This disease is endemic in 21 countries, mostly Latin America countries, with more than 300,000 new cases every year and about 16-18 million infected people. Current therapy is not effective in the chronic phase of the disease. Thus, new and better drugs are urgently needed. In this sense, the in vitro activity of primaquine (PQ) was reported. Based on this, peptide prodrugs of primaquine containing dipeptides - lysine-arginine (LysArg), phenylalanine-alanine (PheAla) and phenylalanine-arginine (PheArg) -- as carriers, were designed to be selectively cleaved by cruzain, a specific cysteine protease of T. cruzi. The prodrugs have shown to be active against tripomastigote forms according to this order: LysArg-PQ> PheAla-PQ> PheArg-PQ. The molecular mechanism of action considered a probable nucleophilic attack of the catalytic residue of cruzain (Cys25) on the respective prodrug amide carbonyl carbon, releasing PQ. In order to test this hypothesis, molecular modeling studies were performed, physicochemical parameters and stereoelectronic features calculated by using the AM1 semi-empirical method suggest that the amide carbonyl carbon is favorable for cleavage, where the LysArg showed the most electronic reactive and sterically disposable, leading to the prodrug release and action. In addition, the docking study indicates the occurrence of specific interactions between prodrugs and the pockets S1 and S2 of cruzain through the dipeptides carriers, being the distance between cruzain Cys25 and the amide carbonyl group related to the biological activity of the prodrugs.

Host-guest complexation of a nitroheterocyclic compound with cyclodextrins: a spectrofluorimetric and molecular modeling study

Nitroheterocyclic compounds (NC) were candidate drugs proposed for Chagas disease chemotherapy. In this study, we investigated the complexation of hydroxymethylnitrofurazone (NFOH), a potential antichagasic compound, with alpha-cyclodextrin (alpha-CD), beta-cyclodextrin (beta-CD), Hydroxypropyl-beta-cyclodextrin (HP-beta-CD), Dimethyl-beta-cyclodextrin (DM-beta-CD) and gamma-cyclodextrin (gamma-CD) by fluorescence spectroscopy and molecular modeling studies. Hildebrand-Benesi equation was used to calculate the formation constants of NFOH with cyclodextrins based on the fluorescence differences in the CDs solution. The complexing capacity of NFOH with different CDs was compared through the results of association constant according to the following order: DM-beta-CD > beta-CD > alpha-CD > HP-beta-CD > gamma-CD. Molecular modeling studies give support for the experimental assignments, in favor of the formation of an inclusion complex between cyclodextrins with NFOH. This is an important study to investigate the effects of different kinds of cyclodextrins on the inclusion complex formation with NFOH and to better characterize a potential formulations to be used as therapeutic options for the oral treatment of Chagas disease.

Design, synthesis, antimicrobial activity and molecular modeling studies of novel benzofuroxan derivatives against Staphylococcus aureus

Molecular modi. cation is a quite promising strategy in the design and development of drug analogs with better bioavailability, higher intrinsic activity and less toxicity. In the search of new leads with potential antimicrobial activity, a new series of 14 4-substituted [N`-(benzofuroxan-5-yl) methylene] benzohydrazides, nifuroxazide derivatives, were synthesized and tested against standard and multidrug-resistant Staphylococcus aureus strains. The selection of the substituent groups was based on physicochemical properties, such as hydrophobicity and electronic effect. These properties were also evaluated through the lipophilic and electrostatic potential maps, respectively, considering the compounds with better biological pro. le. Twelve compounds exhibited similar bacteriostatic activity against standard and multidrug-resistant strains. The most active compound was the 4-CF(3) substituted derivative, which presented a minimum inhibitory concentration (MIC) value of 14.6-13.1 mu g/mL, and a ClogP value of 1.87. The results highlight the benzofuroxan derivatives as potential leads for designing new future antimicrobial drug candidates. (C) 2009 Elsevier Ltd. All rights reserved.

Forward-looking versus recursive-dynamic modeling in climate policy analysis: A comparison

This paper develops a multi-regional general equilibrium model for climate policy analysis based on the latest version of the MIT Emissions Prediction and Policy Analysis (EPPA) model. We develop two versions so that we can solve the model either as a fully inter-temporal optimization problem (forward-looking, perfect foresight) or recursively. The standard EPPA model on which these models are based is solved recursively, and it is necessary to simplify some aspects of it to make inter-temporal solution possible. The forward-looking capability allows one to better address economic and policy issues such as borrowing and banking of GHG allowances, efficiency implications of environmental tax recycling, endogenous depletion of fossil resources, international capital flows, and optimal emissions abatement paths among others. To evaluate the solution approaches, we benchmark each version to the same macroeconomic path, and then compare the behavior of the two versions under a climate policy that restricts greenhouse gas emissions. We find that the energy sector and CO(2) price behavior are similar in both versions (in the recursive version of the model we force the inter-temporal theoretical efficiency result that abatement through time should be allocated such that the CO(2) price rises at the interest rate.) The main difference that arises is that the macroeconomic costs are substantially lower in the forward-looking version of the model, since it allows consumption shifting as an additional avenue of adjustment to the policy. On the other hand, the simplifications required for solving the model as an optimization problem, such as dropping the full vintaging of the capital stock and fewer explicit technological options, likely have effects on the results. Moreover, inter-temporal optimization with perfect foresight poorly represents the real economy where agents face high levels of uncertainty that likely lead to higher costs than if they knew the future with certainty. We conclude that while the forward-looking model has value for some problems, the recursive model produces similar behavior in the energy sector and provides greater flexibility in the details of the system that can be represented. (C) 2009 Elsevier B.V. All rights reserved.

Analyzing the connectivity between regions of interest: An approach based on cluster Granger causality for NRI data analysis

The identification, modeling, and analysis of interactions between nodes of neural systems in the human brain have become the aim of interest of many studies in neuroscience. The complex neural network structure and its correlations with brain functions have played a role in all areas of neuroscience, including the comprehension of cognitive and emotional processing. Indeed, understanding how information is stored, retrieved, processed, and transmitted is one of the ultimate challenges in brain research. In this context, in functional neuroimaging, connectivity analysis is a major tool for the exploration and characterization of the information flow between specialized brain regions. In most functional magnetic resonance imaging (fMRI) studies, connectivity analysis is carried out by first selecting regions of interest (ROI) and then calculating an average BOLD time series (across the voxels in each cluster). Some studies have shown that the average may not be a good choice and have suggested, as an alternative, the use of principal component analysis (PCA) to extract the principal eigen-time series from the ROI(s). In this paper, we introduce a novel approach called cluster Granger analysis (CGA) to study connectivity between ROIs. The main aim of this method was to employ multiple eigen-time series in each ROI to avoid temporal information loss during identification of Granger causality. Such information loss is inherent in averaging (e.g., to yield a single ""representative"" time series per ROI). This, in turn, may lead to a lack of power in detecting connections. The proposed approach is based on multivariate statistical analysis and integrates PCA and partial canonical correlation in a framework of Granger causality for clusters (sets) of time series. We also describe an algorithm for statistical significance testing based on bootstrapping. By using Monte Carlo simulations, we show that the proposed approach outperforms conventional Granger causality analysis (i.e., using representative time series extracted by signal averaging or first principal components estimation from ROIs). The usefulness of the CGA approach in real fMRI data is illustrated in an experiment using human faces expressing emotions. With this data set, the proposed approach suggested the presence of significantly more connections between the ROIs than were detected using a single representative time series in each ROI. (c) 2010 Elsevier Inc. All rights reserved.

Use of SVM Methods with Surface-Based Cortical and Volumetric Subcortical Measurements to Detect Alzheimer`s Disease

Here, we examine morphological changes in cortical thickness of patients with Alzheimer`s disease (AD) using image analysis algorithms for brain structure segmentation and study automatic classification of AD patients using cortical and volumetric data. Cortical thickness of AD patients (n = 14) was measured using MRI cortical surface-based analysis and compared with healthy subjects (n = 20). Data was analyzed using an automated algorithm for tissue segmentation and classification. A Support Vector Machine (SVM) was applied over the volumetric measurements of subcortical and cortical structures to separate AD patients from controls. The group analysis showed cortical thickness reduction in the superior temporal lobe, parahippocampal gyrus, and enthorhinal cortex in both hemispheres. We also found cortical thinning in the isthmus of cingulate gyrus and middle temporal gyrus at the right hemisphere, as well as a reduction of the cortical mantle in areas previously shown to be associated with AD. We also confirmed that automatic classification algorithms (SVM) could be helpful to distinguish AD patients from healthy controls. Moreover, the same areas implicated in the pathogenesis of AD were the main parameters driving the classification algorithm. While the patient sample used in this study was relatively small, we expect that using a database of regional volumes derived from MRI scans of a large number of subjects will increase the SVM power of AD patient identification.

A NEUROECONOMIC MODELING OF ATTENTION-DEFICIT/HYPERACTIVITY DISORDER (ADHD)

In this paper we present a new neuroeconomics model for decision-making applied to the Attention-Deficit/Hyperactivity Disorder (ADHD). The model is based on the hypothesis that decision-making is dependent on the evaluation of expected rewards and risks assessed simultaneously in two decision spaces: the personal (PDS) and the interpersonal emotional spaces (IDS). Motivation to act is triggered by necessities identified in PDS or IDS. The adequacy of an action in fulfilling a given necessity is assumed to be dependent on the expected reward and risk evaluated in the decision spaces. Conflict generated by expected reward and risk influences the easiness (cognitive effort) and the future perspective of the decision-making. Finally, the willingness (not) to act is proposed to be a function of the expected reward (or risk), adequacy, easiness and future perspective. The two most frequent clinical forms are ADHD hyperactive (AD/HDhyp) and ADHD inattentive (AD/HDdin). AD/HDhyp behavior is hypothesized to be a consequence of experiencing high rewarding expectancies for short periods of time, low risk evaluation, and short future perspective for decision-making. AD/HDin is hypothesized to be a consequence of experiencing high rewarding expectancies for long periods of time, low risk evaluation, and long future perspective for decision-making.

Phylogenetic relationships among species of Anopheles (Nyssorhynchus) (Diptera, Culicidae) based on nuclear and mitochondrial gene sequences

Phylogenetic relationships among 21 species of mosquitoes in subgenus Nyssorhynchus were inferred from the nuclear white and mitochondrial NADH dehydrogenase subunit 6 (ND6) genes. Bayestan phylogenetic methods found that none of the three Sections within Nyssorhynchus (Albimanus, Argyritarsis, Myzorhynchella) were supported in all analyses, although Myzorhynchella was found to be monophyletic at the combined genes Within the Albimanus Section the monophyly of the Stroder Subgroup was strongly supported and within the Myzorhynchella Section Anopheles anrunesi and An lutzu formed a strongly supported monophyletic group The epidemiologically significant Albitarsis Complex showed evidence of paraphyly (relative to An lanet-Myzorhynchella) and discordance across gene trees, and the previously synonomized species of An. dunhami and An goeldii were recovered as sister species Finally, there was evidence of complexes in several species, including An antunesi, An deaneorum, and An. strodei (c) 2010 Elsevier B.V. All rights reserved

Understanding three-dimensional effects in polarized observations with the ground-based ADMIRARI radiometer during the CHUVA campaign

Measurements of down-welling microwave radiation from raining clouds performed with the Advanced Microwave Radiometer for Rain Identification (ADMIRARI) radiometer at 10.7-21-36.5 GHz during the Global Precipitation Measurement Ground Validation ""Cloud processes of the main precipitation systems in Brazil: A contribution to cloud resolving modeling and to the Global Precipitation Measurement"" (CHUVA) campaign held in Brazil in March 2010 represent a unique test bed for understanding three-dimensional (3D) effects in microwave radiative transfer processes. While the necessity of accounting for geometric effects is trivial given the slant observation geometry (ADMIRARI was pointing at a fixed 30 elevation angle), the polarization signal (i.e., the difference between the vertical and horizontal brightness temperatures) shows ubiquitousness of positive values both at 21.0 and 36.5 GHz in coincidence with high brightness temperatures. This signature is a genuine and unique microwave signature of radiation side leakage which cannot be explained in a 1D radiative transfer frame but necessitates the inclusion of three-dimensional scattering effects. We demonstrate these effects and interdependencies by analyzing two campaign case studies and by exploiting a sophisticated 3D radiative transfer suited for dichroic media like precipitating clouds.

TOWARD UNDERSTANDING THE B[e] PHENOMENON. IV. MODELING OF IRAS 00470+6429

FS CMa type stars are a recently described group of objects with the B[e] phenomenon which exhibits strong emission-line spectra and strong IR excesses. In this paper, we report the first attempt for a detailed modeling of IRAS 00470+6429, for which we have the best set of observations. Our modeling is based on two key assumptions: the star has a main-sequence luminosity for its spectral type (B2) and the circumstellar (CS) envelope is bimodal, composed of a slowly outflowing disklike wind and a fast polar wind. Both outflows are assumed to be purely radial. We adopt a novel approach to describe the dust formation site in the wind that employs timescale arguments for grain condensation and a self-consistent solution for the dust destruction surface. With the above assumptions we were able to satisfactorily reproduce many observational properties of IRAS 00470+6429, including the Hi line profiles and the overall shape of the spectral energy distribution. Our adopted recipe for dust formation proved successful in reproducing the correct amount of dust formed in the CS envelope. Possible shortcomings of our model, as well as suggestions for future improvements, are discussed.

MODELING VERY LONG BASELINE INTERFEROMETRIC IMAGES WITH THE CROSS-ENTROPY GLOBAL OPTIMIZATION TECHNIQUE

We present a new technique for obtaining model fittings to very long baseline interferometric images of astrophysical jets. The method minimizes a performance function proportional to the sum of the squared difference between the model and observed images. The model image is constructed by summing N(s) elliptical Gaussian sources characterized by six parameters: two-dimensional peak position, peak intensity, eccentricity, amplitude, and orientation angle of the major axis. We present results for the fitting of two main benchmark jets: the first constructed from three individual Gaussian sources, the second formed by five Gaussian sources. Both jets were analyzed by our cross-entropy technique in finite and infinite signal-to-noise regimes, the background noise chosen to mimic that found in interferometric radio maps. Those images were constructed to simulate most of the conditions encountered in interferometric images of active galactic nuclei. We show that the cross-entropy technique is capable of recovering the parameters of the sources with a similar accuracy to that obtained from the very traditional Astronomical Image Processing System Package task IMFIT when the image is relatively simple (e. g., few components). For more complex interferometric maps, our method displays superior performance in recovering the parameters of the jet components. Our methodology is also able to show quantitatively the number of individual components present in an image. An additional application of the cross-entropy technique to a real image of a BL Lac object is shown and discussed. Our results indicate that our cross-entropy model-fitting technique must be used in situations involving the analysis of complex emission regions having more than three sources, even though it is substantially slower than current model-fitting tasks (at least 10,000 times slower for a single processor, depending on the number of sources to be optimized). As in the case of any model fitting performed in the image plane, caution is required in analyzing images constructed from a poorly sampled (u, v) plane.