On Building a Memory Evolutive System for Application to Learning and Cognition Modeling

We address here aspects of the implementation of a memory evolutive system (MES), based on the model proposed by A. Ehresmann and J. Vanbremeersch (2007), by means of a simulated network of spiking neurons with time dependent plasticity. We point out the advantages and challenges of applying category theory for the representation of cognition, by using the MES architecture. Then we discuss the issues concerning the minimum requirements that an artificial neural network (ANN) should fulfill in order that it would be capable of expressing the categories and mappings between them, underlying the MES. We conclude that a pulsed ANN based on Izhikevich`s formal neuron with STDP (spike time-dependent plasticity) has sufficient dynamical properties to achieve these requirements, provided it can cope with the topological requirements. Finally, we present some perspectives of future research concerning the proposed ANN topology.

Novel sources of witches` broom resistance (causal agent Moniliophthora perniciosa) from natural populations of Theobroma cacao from the Brazilian Amazon

Witches` broom is a severe disease of Theobroma cacao L. (cacao), caused by the basidiomycete Moniliophthora perniciosa. The use of resistant cultivars is the ultimate method of control, but there are limited sources of resistance. Further, resistance from the most widely used source (`Scavina 6`) has been overcome after a few years of deployment. New sources of resistance have been intensively searched for in the Amazon basin. Here, we evaluated for witches` broom resistance, cacao accessions from various natural cacao populations originally collected in the Brazilian Amazon. Resistance of 43 families was evaluated under nursery and/or field conditions by artificial or natural infection, respectively, based on disease incidence. Screening for resistance by artificial inoculation under nursery conditions appeared to be efficient in identifying these novel resistance sources, confirmed by natural field evaluation over a nine-year period. The increase in natural field infection of `Scavina 6` was clearly demonstrated. Among the evaluated families with the least witches` broom incidence, there were accessions originally collected from distinct river basins, including the Jamari river (`CAB 0371`; `CAB 0388`; `CAB 0392`; and `CAB 0410`); Acre (`CAB 0169`); Javari (`CAB 0352`); Solimes (`CAB 0270`); and from the Purus river basin, the two most outstanding resistant accessions, `CAB 0208` and `CAB 0214`. The large genetic diversity found in cacao populations occurring at river basins from Acre and Amazonas states, Brazil, increased the chance that the selected resistant accessions would be genetically more dissimilar, and represent distinct sources of resistance to M. perniciosa from `Scavina 6`.

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.

QSAR Modeling of a Set of Pyrazinoate Esters as Antituberculosis Prodrugs

Tuberculosis is an infection caused mainly by Mycobacterium tuberculosis. A first-line antimycobacterial drug is pyrazinamide (PZA), which acts partially as a prodrug activated by a pyrazinamidase releasing the active agent, pyrazinoic acid (POA). As pyrazinoic acid presents some difficulty to cross the mycobacterial cell wall, and also the pyrazinamide-resistant strains do not express the pyrazinamidase, a set of pyrazinoic acid esters have been evaluated as antimycobacterial agents. In this work, a QSAR approach was applied to a set of forty-three pyrazinoates against M. tuberculosis ATCC 27294, using genetic algorithm function and partial least squares regression (WOLF 5.5 program). The independent variables selected were the Balaban index (I), calculated n-octanol/water partition coefficient (ClogP), van-der-Waals surface area, dipole moment, and stretching-energy contribution. The final QSAR model (N = 32, r(2) = 0.68, q(2) = 0.59, LOF = 0.25, and LSE = 0.19) was fully validated employing leave-N-out cross-validation and y-scrambling techniques. The test set (N = 11) presented an external prediction power of 73%. In conclusion, the QSAR model generated can be used as a valuable tool to optimize the activity of future pyrazinoic acid esters in the designing of new antituberculosis agents.

Molecular modeling as a promising tool to study dendrimer prodrugs delivery

Molecular modeling methodologies were applied to perform preliminary studies concerning the release of active agents from potentially antichagasic and antileishmanial dendrimer prodrugs. The dendrimer was designed having myo-inositol as a core, L-malic acid as a spacer group, and hydroxymethylnitrofurazone (NFOH), 3-hydroxyflavone or quercetin, as active compounds. Each dendrimer presented a particular behavior concerning to the following investigated properties: spatial hindrance, map of electrostatic potential (MEP), and the lowest unoccupied molecular orbital energy (E(LUMO)). Additionally, the findings suggested that the carbonyl group next to the active agent seems to be the most promising ester breaking point. (C) 2009 Elsevier B.V. All rights reserved.

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.

Negative ion `chip-based` nanospray tandem mass spectrometry for the analysis of flavonoids in glandular trichomes of Lychnophora ericoides Mart. (Asteraceae)

This paper reports a method for the analysis of secondary metabolites stored in glandular trichomes, employing negative ion `chip-based` nanospray tandem mass spectrometry. The analyses of glandular trichomes from Lychnophora ericoides, a plant endemic to the Brazilian `cerrado` and used in traditional medicine as an anti-inflammatory and analgesic agent, led to the identification of five flavonoids (chrysin, pinocembrin, pinostrobin, pinobanksin and 3-O-acetylpinobanksin) by direct infusion of the extracts of glandular trichomes into the nanospray ionisation source. All the flavonoids have no oxidation at ring B, which resulted in a modification of the fragmentation pathways compared with that of the oxidised 3,4-dihydroflavonoids already described in the literature. The absence of the anti-inflammatory and antioxidant di-C-glucosylflavone vicenin-2, or any other flavonoid glycosides, in the glandular trichomes was also demonstrated. The use of the,`chip-based` nanospray QqTOF apparatus is a new fast and useful tool for the identification of secondary metabolites stored in the glandular trichomes, which can be useful for chemotaxonomic studies based on metabolites from glandular trichomes. Copyright (C) 2008 John Wiley & Sons, Ltd.

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.

Streptokinase and Enoxaparin as an Alternative to Fibrin-Specific Lytic-Based Regimens An ExTRACT-TIMI 25 Analysis

Background: Enoxaparin was superior to unfractionated heparin (UFH), regardless of fibrinolytic agent in ST-elevation myocardial infarction (STEMI) patients receiving fibrinolytic therapy in ExTRACT-TIMI 25 (Enoxaparin and Thrombolysis Reperfusion for Acute Myocardial Infarction Treatment Thrombolysis in Myocardial Infarction 25) trial. Objective: This post hoc analysis compared outcomes with streptokinase plus enoxaparin to the standard regimen of fibrin-specific lytic (FSL) plus UFH and to the newer combination of FSL plus enoxaparin. Methods: In ExTRACT-TIMI 25, STEMI patients received either streptokinase or a FSL (alteplase, reteplase or tenecteplase) at the physician`s discretion and were randomized to enoxaparin or UFH, stratified by fibrinolytic type. Thirty-day outcomes were adjusted for baseline characteristics, region, in-hospital percutaneous coronary intervention (PCI) and a propensity score for the choice of lytic. Results: The primary trial endpoint of 30-day death/myocardial infarction (MI) occurred in fewer patients in the streptokinase-enoxaparin cohort (n = 2083) compared with FSL-UFH (n = 8141) [10.2% vs 12.0%, adjusted odds ratio [OR(adj)] 0.76; 95% CI 0.62, 0.93; p = 0.008]. Major bleeding was significantly increased with streptokinase-enoxaparin compared with FSL-UFH (ORadj 2.74; 95% CI 1.81; 4.14; p < 0.001) but intracranial haemorrhage (ICH) was similar (OR(adj) 0.90; 95% CI 0.40, 2.01; p = 0.79). Net clinical outcomes, defined as either death/MI/major bleeding or as death/MI/ICH tended to favour streptokinase-enoxaparin compared with FSL-UFH (OR(adj) 0.88; 95% CI 0.73, 1.06; p = 0.17; and OR(adj) 0.77; 95% CI 0.63, 0.93; p = 0.008, respectively). Patients receiving FSL-enoxaparin (n = 8142) and streptokinase-enoxaparin therapies experienced similar adjusted rates of the primary endpoint (OR(adj) 1.08; 95% CI 0.87, 1.32; p = 0.49) and net clinical outcomes. Conclusions: Our results suggest that fibrinolytic therapy with the combination of streptokinase and the potent anticoagulant agent enoxaparin resulted in similar adjusted outcomes compared with more costly regimens utilizing a FSL.

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.