Contribution to the marine propeller hydrodynamic design for small boats in the Amazon region

ABSTRACTIn the Amazon, river navigation is very important due to the length of navigable rivers and the lack of alternative road networks. Boats usually operate in unfavorable conditions, since there is no hydrodynamic relation among propellers, geometry, and the dimensions of the boat hull. Currently, there is no methodology for propeller hydrodynamic optimization with low computational cost and easy implementation in the region. The aim of this work was to develop a mathematical approach for marine propeller design applied to boats typically found on Amazon rivers. We developed an optimized formulation for the chord and pitch angle distributions, taking into account the classical model of Glauert. A theoretical analysis for the thrust and torque relationships on an annular control volume was performed. The mathematical model used was based on the Blade Element Momentum Theory (BEMT). We concluded that the new methodology proposed in this work demonstrates a good physical behavior when compared with the theory of Glauert and the experimental data of the Wageningen B3-50 propeller.

Application of artificial neural networks as an alternative to volumetric water balance in drip irrigation management in watermelon crop

Precision irrigation seeks to establish strategies which achieve an efficient ratio between the volume of water used (reduction in input) and the productivity obtained (increase in production). There are several studies in the literature on strategies for achieving this efficiency, such as those dealing with the method of volumetric water balance (VWB). However, it is also of great practical and economic interest to set up versatile implementations of irrigation strategies that: (i) maintain the performance obtained with other implementations, (ii) rely on few computational resources, (iii) adapt well to field conditions, and (iv) allow easy modification of the irrigation strategy. In this study, such characteristics are achieved when using an Artificial Neural Network (ANN) to determine the period of irrigation for a watermelon crop in the Irrigation Perimeter of the Lower Acaraú, in the state of Ceará, Brazil. The Volumetric Water Balance was taken as the standard for comparing the management carried out with the proposed implementation of ANN. The statistical analysis demonstrates the effectiveness of the proposed management, which is able to replace VWB as a strategy in automation.

Evaluation of follicular lymphoid depletion in the Bursa of Fabricius: an alternative methodology using digital image analysis and artificial neural networks

Fifty Bursa of Fabricius (BF) were examined by conventional optical microscopy and digital images were acquired and processed using Matlab® 6.5 software. The Artificial Neuronal Network (ANN) was generated using Neuroshell® Classifier software and the optical and digital data were compared. The ANN was able to make a comparable classification of digital and optical scores. The use of ANN was able to classify correctly the majority of the follicles, reaching sensibility and specificity of 89% and 96%, respectively. When the follicles were scored and grouped in a binary fashion the sensibility increased to 90% and obtained the maximum value for the specificity of 92%. These results demonstrate that the use of digital image analysis and ANN is a useful tool for the pathological classification of the BF lymphoid depletion. In addition it provides objective results that allow measuring the dimension of the error in the diagnosis and classification therefore making comparison between databases feasible.

Alternative approaches in schistosomiasis control

Measures for for the control of schistosomiasis were implemented in Egypt begining 1922. This shows that developing endemic countries are facing this problem for near 70 years. However, results in the control of this infection have not been satisfactorily obtained in spite of the technologies and strategies recently developed. The idea that the social and economic components are relevant in the control of schistosomiasis is not new although its extension and profundity have not usually been well understood. More recently; most of the workers have recognized that the distribution of the prevalence rates of schistosomiasis should not be neglected in the control of the infection. At present field work projects on the control of schistosomiasis are being developed in rural areas of two Brazilian states (Espirito Santo and Pernanbuco). The adopted strategy aims to interfere in the complex relationships between amn and his bio-social-cultural environment, without forgeting tha the unequal distribution of the space is a consequence of the political and economic organization of the Society.

Economic analysis of an agrosilvipastoral system for a mountainous area in Zona da Mata Mineira, Brazil

The objective of this work was to evaluate the economic viability of an agrosilvipastoral system developed for Zona da Mata mountainous areas in Minas Gerais state, Brazil, as well as to compare different options for wood (Eucalyptus grandis and Acacia mangium) commercialization of the second thinning. The data were obtained from a 10 year-old agrosilvipastoral system established in four hectares at Embrapa Gado de Leite station in Coronel Pacheco, MG, Brazil. As evaluation criteria for the economic viability analysis, the adopted methods were the net present value (NPV) and the internal rate of return (IRR), both calculated at 6% interest rate. Despite the small difference, adding value to forest products increased the attractiveness of the proposed system. Considered separately, the agricultural activity was impracticable, whereas the forestry and livestock activities were independently viable. The studied system seems to be equally tolerant to price variations for forest and livestock products, as well as strongly tolerant to variations in production costs.

INCLUDING RISK IN ECONOMIC FEASIBILITY ANALYSIS:A STOCHASTIC SIMULATION MODEL FOR BLUEBERRY INVESTMENT DECISIONS IN CHILE

ABSTRACT The traditional method of net present value (NPV) to analyze the economic profitability of an investment (based on a deterministic approach) does not adequately represent the implicit risk associated with different but correlated input variables. Using a stochastic simulation approach for evaluating the profitability of blueberry (Vaccinium corymbosum L.) production in Chile, the objective of this study is to illustrate the complexity of including risk in economic feasibility analysis when the project is subject to several but correlated risks. The results of the simulation analysis suggest that the non-inclusion of the intratemporal correlation between input variables underestimate the risk associated with investment decisions. The methodological contribution of this study illustrates the complexity of the interrelationships between uncertain variables and their impact on the convenience of carrying out this type of business in Chile. The steps for the analysis of economic viability were: First, adjusted probability distributions for stochastic input variables (SIV) were simulated and validated. Second, the random values of SIV were used to calculate random values of variables such as production, revenues, costs, depreciation, taxes and net cash flows. Third, the complete stochastic model was simulated with 10,000 iterations using random values for SIV. This result gave information to estimate the probability distributions of the stochastic output variables (SOV) such as the net present value, internal rate of return, value at risk, average cost of production, contribution margin and return on capital. Fourth, the complete stochastic model simulation results were used to analyze alternative scenarios and provide the results to decision makers in the form of probabilities, probability distributions, and for the SOV probabilistic forecasts. The main conclusion shown that this project is a profitable alternative investment in fruit trees in Chile.

Description of epidemics of coffee rust with neural networks

The objective of this paper was to evaluate the potential of neural networks (NN) as an alternative method to the basic epidemiological approach to describe epidemics of coffee rust. The NN was developed from the intensities of coffee (Coffea arabica) rust along with the climatic variables collected in Lavras-MG between 13 February 1998 and 20 April 2001. The NN was built with climatic variables that were either selected in a stepwise regression analysis or by the Braincel® system, software for NN building. Fifty-nine networks and 26 regression models were tested. The best models were selected based on small values of the mean square deviation (MSD) and of the mean prediction error (MPE). For the regression models, the highest coefficients of determination (R²) were used. The best model developed with neural networks had an MSD of 4.36 and an MPE of 2.43%. This model used the variables of minimum temperature, production, relative humidity of the air, and irradiance 30 days before the evaluation of disease. The best regression model was developed from 29 selected climatic variables in the network. The summary statistics for this model were: MPE=6.58%, MSE=4.36, and R²=0.80. The elaborated neural networks from a time series also were evaluated to describe the epidemic. The incidence of coffee rust at four previous fortnights resulted in a model with MPE=4.72% and an MSD=3.95.

Classification of antimicrobial resistance using artificial neural networks and the relationship of 38 genes associated with the virulence of Escherichia coli isolates from broilers

Avian pathogenic Escherichia coli (APEC) is responsible for various pathological processes in birds and is considered as one of the principal causes of morbidity and mortality, associated with economic losses to the poultry industry. The objective of this study was to demonstrate that it is possible to predict antimicrobial resistance of 256 samples (APEC) using 38 different genes responsible for virulence factors, through a computer program of artificial neural networks (ANNs). A second target was to find the relationship between (PI) pathogenicity index and resistance to 14 antibiotics by statistical analysis. The results showed that the RNAs were able to make the correct classification of the behavior of APEC samples with a range from 74.22 to 98.44%, and make it possible to predict antimicrobial resistance. The statistical analysis to assess the relationship between the pathogenic index (PI) and resistance against 14 antibiotics showed that these variables are independent, i.e. peaks in PI can happen without changing the antimicrobial resistance, or the opposite, changing the antimicrobial resistance without a change in PI.

Brazil and the economic, political, and environmental multilateralism: the Lula years (2003-2010)

This article discusses Brazil's multilateral policy under Luiz Inácio Lula da Silva's administration, highlighting economic, political and environmental themes. The main argument is that Brazil's multilateral relations during this government reached a new significance with the reinforcement of international coalitions and the articulation with the country's new development model. The country has been using multilateral forums as a way to achieve international projection and support for its development project, highlighting bargaining aspects, variable geometry coalitions and the strengthening of South-South cooperation

Economic sanctions and human rights: an analysis of competing enforcement strategies in Latin America

This article addresses the consequences of economic sanctions for the protection of human rights in Latin America. The literature on sanctions and compliance informs three hypotheses, which investigate the relationship between sanctions and the level of rights protection in two groups of countries: those that were targeted by sanctions and those that were not. Using data from the Political Terror Scale (PTS) and from Freedom House, I find empirical evidence that sanctions do improve the level of protection in countries that were not targeted. This finding can be explained by the deterrent effect attributed to sanctions by the compliance literature, broadly interpreted. The presence of economic sanctions in a given year increases the probability of observing better human rights practices by almost 50%. These results hold for the 12 Latin American countries that were not subject to economic sanctions for the period 1976-2004.

International drivers of Brazilian agricultural cooperation in Africa in the post-2008 economic crisis

This text focuses on the major drivers of Brazilian agricultural cooperation in Africa as conceived and pursued from 2004 to 2014, with emphasis on the impacts of political and economic international changes that took place in that period, and particularly the impacts of the 2008 economic crisis, in framing Brazil's foreign policy and development assistance initiatives. It addresses current international forces and developments at the systemic level, but also analyses recent economic domestic developments, in particular those directly related to Brazilian agriculture and those related to the policy framework of its evolving internationalization. Special attention is paid to the dual dimensions of Brazilian agricultural policy and to its projection in agricultural cooperation as pursed in Africa.

Influence of nitrogen fertilization and green manure on the economic feasibility of no-tilled wheat in the Cerrado

The search for higher profitability in wheat crop with cost reduction technologies that may promote sustainability is an important matter in Brazilian agriculture. This study evaluated the profitability of no-tilled wheat, reducing nitrogen topdressing doses with the cultivation of green manure before the wheat crop. The experiment was carried out in Selvíria (MS), Brazil, in 2009/10. The experiment was arranged in a randomized block design with 36 treatments in splitplots and four replicates. The plots were formed by six types of green manure: Cajanus cajan L. BRS Mandarin, Crotalaria juncea L., Pennisetum americanum L. BRS 1501, fallow area and mixed cropping of Pennisetum americanum L. + Cajanus cajan L. and Pennisetum americanum L. + crotalaria which provided straw for no-tilled wheat in the winter, following the rice crop in the summer. The subplots were formed by six levels of topdressing nitrogen (0, 25, 50, 75, 100 and 125 kg N ha-1) using urea as a nitrogen source. The wheat grown after green manure in the previous winter crop, with no nitrogen topdressing and a rate of 25 kg ha-1 N, had more frequently production costs above the gross income. Wheat production cost after the mixed cropping Pennisetum americanum L. + Cajanus cajan L. and Pennisetum americanum L. + Crotalaria juncea L. from the previous winter crop, combined with nitrogen rates of 50 and 75 kg N ha-1, provided better profitability compared with the other green manures evaluated.

Economic viability of the third milking in systems of production using closed-circuit mechanical milking

This study aimed to analyze the economic viability of the third milking in production systems using mechanical milking in a closed circuit, aiming to provide technicians and farmers with information to assist them in decision-making. Specifically, it intended: (a) to estimate the cost of one milking; (b) to estimate the cost of the third milking; (c) to develop a mathematical equation to estimate the minimum amount of milk produced with two milkings, from which it would be economically feasible to do the third milking. Data were collected from three dairy farms, from November 2010 to March 2011, keeping a twice-a-day milking frequency, with three data collections in each farm, totalizing nine collections. Considering the average data, it would be feasible to do the third milking if the average milk yield per day of lactating cows in a twice-a-day milking frequency was greater than or equal to 24.43 kg of milk.

Use efficiency of variable rate of nitrogen prescribed by optical sensor in corn

ABSTRACT The efficiency of nitrogen fertilizer in corn is usually low, negatively affecting plant nutrition, the economic return, and the environment. In this context, a variable rate of nitrogen, prescribed by crop sensors, has been proposed as an alternative to the uniform rate of nitrogen traditionally used by farmers. This study tested the hypothesis that variable rate of nitrogen, prescribed by optical sensor, increases the nitrogen use efficiency and grain yield as compared to uniform rate of nitrogen. The following treatments were evaluated: 0; 70; 140; and 210 kg ha-1 under uniform rate of nitrogen, and 140 kg ha -1 under variable rate of nitrogen. The nitrogen source was urea applied on the soil surface using a distributor equipped with the crop sensor. In this study, the grain yield ranged from 10.2 to 15.5 Mg ha-1, with linear response to nitrogen rates. The variable rate of nitrogen increased by 11.8 and 32.6% the nitrogen uptake and nitrogen use efficiency, respectively, compared to the uniform rate of nitrogen. However, no significant increase in grain yield was observed, indicating that the major benefit of the variable rate of nitrogen was reducing the risk of environmental impact of fertilizer.