Movimentação financeira: a base de uma contribuição para o INSS em substituição à folha de pagamentos

Em média, os salários no Brasil são onerados em 42,5% do seu valor bruto, somando-se a parte que é descontada do salário do trabalhador com a que incide sobre a folha de pagamentos das empresas. Isso torna o país uma das economias que mais tributam rendimentos do trabalho assalariado no mundo. O maior ônus sobre os salários recai sobre as empresas, estimulando práticas como a contratação de empregados sem carteira de trabalho assinada e a terceirização, fazendo da informalidade um dos elementos determinantes dos crescentes déficits do INSS. A folha de pagamentos é tributada em média em 35%, sendo a contribuição previdenciária o tributo de maior peso. Após diagnosticar o problema, este texto discute aspectos relacionados aos regimes previdenciários e as bases de incidência adequadas a cada um deles. Mostra ainda que o regime geral da previdência no Brasil assumiu conotação de política pública de renda complementar. Nesse sentido, propõe-se a substituição do INSS patronal, uma base restrita, por uma contribuição de 0,61% sobre as movimentações nas contas-correntes bancárias, uma base universal, e compara os efeitos sobre a economia de um tributo cumulativo com os produzidos por um imposto sobre o valor agregado. Utilizando o modelo de input-output de Leontief como mecanismo de análise, o trabalho revela que uma contribuição sobre as transações bancárias implica menor carga tributária sobre os preços setoriais e menor distorção alocativa que os 20% cobrados sobre a folha de salários das empresas para o INSS. Por fim, o texto procura desmistificar a crítica envolvendo a cumulatividade tributária.

Non-Linear Unsteady Aerodynamic Response Approximation Using Multi-Layer Functionals

Non-linear functional representation of the aerodynamic response provides a convenient mathematical model for motion-induced unsteady transonic aerodynamic loads response, that accounts for both complex non-linearities and time-history effects. A recent development, based on functional approximation theory, has established a novel functional form; namely, the multi-layer functional. For a large class of non-linear dynamic systems, such multi-layer functional representations can be realised via finite impulse response (FIR) neural networks. Identification of an appropriate FIR neural network model is facilitated by means of a supervised training process in which a limited sample of system input-output data sets is presented to the temporal neural network. The present work describes a procedure for the systematic identification of parameterised neural network models of motion-induced unsteady transonic aerodynamic loads response. The training process is based on a conventional genetic algorithm to optimise the network architecture, combined with a simplified random search algorithm to update weight and bias values. Application of the scheme to representative transonic aerodynamic loads response data for a bidimensional airfoil executing finite-amplitude motion in transonic flow is used to demonstrate the feasibility of the approach. The approach is shown to furnish a satisfactory generalisation property to different motion histories over a range of Mach numbers in the transonic regime.

On-site calibration of a phase fraction meter by an inverse technique

The formal calibration procedure of a phase fraction meter is based on registering the outputs resulting from imposed phase fractions at known flow regimes. This can be straightforwardly done in laboratory conditions, but is rarely the case in industrial conditions, and particularly for on-site applications. Thus, there is a clear need for less restrictive calibration methods regarding to the prior knowledge of the complete set of inlet conditions. A new procedure is proposed in this work for the on-site construction of the calibration curve from total flown mass values of the homogeneous dispersed phase. The solution is obtained by minimizing a convenient error functional, assembled with data from redundant tests to handle the intrinsic ill-conditioned nature of the problem. Numerical simulations performed for increasing error levels demonstrate that acceptable calibration curves can be reconstructed, even from total mass measured within a precision of up to 2%. Consequently, the method can readily be applied, especially in on-site calibration problems in which classical procedures fail due to the impossibility of having a strict control of all the input/output parameters.

Building-up influence: post-war industrialization in the State of Minas Gerais, Brazil

This paper examines the post-War industrialization process in the Brazilian State of Minas Gerais, focusing on one of its desirable outcomes, namely the capacity to generate growth through the impact of strong input-output linkages. This process is placed into historical perspective considering the ideas that permeate the economic development debate throughout the period of analysis. Changes in the regional economic structure are assessed through the use of three input-output tables for the years of 1953, 1980 and 1995. By adopting the fields of influence methodology as the analytical core, it is shown that the efforts towards the creation of a more integrated regional economy have generated stronger influence of the targeted sectors (metal products, transportation equipment, chemical, and services). However, structural changes also contributed to strengthen leakage in the system originated in traditional economic activities.

Environmental and agricultural benefits of a management system designed for sandy loam soils of the humid tropics

A sustainable management of soils with low natural fertility on family farms in the humid tropics is a great challenge and overcoming it would be an enormous benefit for the environment and the farmers. The objective of this study was to assess the environmental and agronomic benefits of alley cropping, based on the evaluation of C sequestration, soil quality indicators, and corn yields. Combinations of four legumes were used in alley cropping systems in the following treatments: Clitoria fairchildiana + Cajanus cajan; Acacia mangium + Cajanus cajan; Leucaena leucocephala + Cajanus cajan; Clitoria fairchildiana + Leucaena leucocephala; Leucaena leucocephala + Acacia mangium and a control. Corn was used as a cash crop. The C content was determined in the different compartments of soil organic matter, CEC, available P, base saturation, percentage of water saturation, the period of the root hospitality factor below the critical level and corn yield. It was concluded that alley cropping could substitute the slash and burn system in the humid tropics. The main environmental benefit of alley cropping is the maintenance of a dynamic equilibrium between C input and output that could sustain up to 10 Mg ha-1 of C in the litter layer, decreasing atmospheric CO2 levels. Alley cropping is also beneficial from the agricultural point of view, because it increases base saturation and decreases physical resistance to root penetration in the soil layer 0 - 10 cm, which ensures the increase and sustainability of corn yield.

Sugarcane crop efficiency in two growing seasons in São Paulo State, Brazil

A conceptual framework for crop production efficiency was derived using thermodynamic efficiency concept, in order to generate a tool for performance evaluation of agricultural systems and to quantify the interference of determining factors on this performance. In Thermodynamics, efficiency is the ratio between the output and input of energy. To establish this relationship in agricultural systems, it was assumed that the input energy is represented by the attainable crop yield, as predicted through simulation models based on environmental variables. The method of FAO's agroecological zones was applied to the assessment of the attainable sugarcane yield, while Instituto Brasileiro de Geografia e Estatística (IBGE) data were used as observed yield. Sugarcane efficiency production in São Paulo state was evaluated in two growing seasons, and its correlation with some physical factors that regulate production was calculated. A strong relationship was identified between crop production efficiency and soil aptitude. This allowed inferring the effect of agribusiness factors on crop production efficiency. The relationships between production efficiency and climatic variables were also quantified and indicated that solar radiation, annual rainfall, water deficiency, and maximum air temperature are the main factors affecting the sugarcane production efficiency.

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.

SSPBE: um programa para solução numérica da equação de Poisson-Boltzmann em simetria esférica com modelo de adsorção

A Fortran77 program, SSPBE, designed to solve the spherically symmetric Poisson-Boltzmann equation using cell model for ionic macromolecular aggregates or macroions is presented. The program includes an adsorption model for ions at the aggregate surface. The working algorithm solves the Poisson-Boltzmann equation in the integral representation using the Picard iteration method. Input parameters are introduced via an ASCII file, sspbe.txt. Output files yield the radial distances versus mean field potentials and average molar ion concentrations, the molar concentration of ions at the cell boundary, the self-consistent degree of ion adsorption from the surface and other related data. Ion binding to ionic, zwitterionic and reverse micelles are presented as representative examples of the applications of the SSPBE program.

NCT: pacote de tratamento de coordenadas normais (versão 7)

A new version of the normal coordinate analysis package NCT is presented. The upgrade was mainly devised to enable the NCT package to manipulate easily the Hessian matrix evaluated by quantum chemical calculations. Program codes were almost wholly rewritten to be more efficient with GNU Fortran77, or g77, and compiled under FreeBSD and MS-DOS with the DJGPP implementation. Three typical usages of the program package are presented by giving the related input and output files. Functionality of the programs was carefully and satisfactorily checked for some sample calculations.

Quimiometria II: planilhas eletrônicas para cálculos de planejamentos experimentais, um tutorial

This work describes, through examples, a simple way to carry out experimental design calculations applying an spreadsheets. The aim of this tutorial is to introduce an alternative to sophisticated commercial programs that normally are too complex in data input and output. An overview of the principal methods is also briefly presented. The spreadsheets are suitable to handle different types of computations such as screening procedures applying factorial design and the optimization procedure based on response surface methodology. Furthermore, the spreadsheets are sufficiently versatile to be adapted to specific experimental designs.

Application of fuzzy logic for the evaluation of livestock slaughtering

The fuzzy logic admits infinite intermediate logical values between false and true. With this principle, it developed in this study a system based on fuzzy rules, which indicates the body mass index of ruminant animals in order to obtain the best time to slaughter. The controller developed has as input the variables weight and height, and as output a new body mass index, called Fuzzy Body Mass Index (Fuzzy BMI), which may serve as a detection system at the time of livestock slaughtering, comparing one another by the linguistic variables "Very Low", "Low", "Average ", "High" and "Very High". For demonstrating the use application of this fuzzy system, an analysis was made with 147 Nellore beeves to determine Fuzzy BMI values for each animal and indicate the location of body mass of any herd. The performance validation of the system was based on a statistical analysis using the Pearson correlation coefficient of 0.923, representing a high positive correlation, indicating that the proposed method is appropriate. Thus, this method allows the evaluation of the herd comparing each animal within the group, thus providing a quantitative method of farmer decision. It was concluded that this study established a computational method based on fuzzy logic that mimics part of human reasoning and interprets the body mass index of any bovine species and in any region of the country.

Sensibility analysis of the pearl model for pesticide leaching in the State of Mato Grosso do Sul, Brazil

For an accurate use of pesticide leaching models it is necessary to assess the sensitivity of input parameters. The aim of this work was to carry out sensitivity analysis of the pesticide leaching model PEARL for contrasting soil types of Dourados river watershed in the state of Mato Grosso do Sul, Brazil. Sensitivity analysis was done by carrying out many simulations with different input parameters and calculating their influence on the output values. The approach used was called one-at-a-time sensitivity analysis, which consists in varying independently input parameters one at a time and keeping all others constant with the standard scenario. Sensitivity analysis was automated using SESAN tool that was linked to the PEARL model. Results have shown that only soil characteristics influenced the simulated water flux resulting in none variation of this variable for scenarios with different pesticides and same soil. All input parameters that showed the greatest sensitivity with regard to leached pesticide are related to soil and pesticide properties. Sensitivity of all input parameters was scenario dependent, confirming the need of using more than one standard scenario for sensitivity analysis of pesticide leaching models.

Determination of the influence of the variation of reducing and non-reducing sugars on coffee quality with use of artificial neural network

The present study aimed at evaluating the use of Artificial Neural Network to correlate the values resulting from chemical analyses of samples of coffee with the values of their sensory analyses. The coffee samples used were from the Coffea arabica L., cultivars Acaiá do Cerrado, Topázio, Acaiá 474-19 and Bourbon, collected in the southern region of the state of Minas Gerais. The chemical analyses were carried out for reducing and non-reducing sugars. The quality of the beverage was evaluated by sensory analysis. The Artificial Neural Network method used values from chemical analyses as input variables and values from sensory analysis as output values. The multiple linear regression of sensory analysis values, according to the values from chemical analyses, presented a determination coefficient of 0.3106, while the Artificial Neural Network achieved a level of 80.00% of success in the classification of values from the sensory analysis.

Energetic efficiency of a deep bed swine production system

The aim of this work was to evaluate the energy flows of a commercial production system of swine deep bed in its finishing phase, located in Juiz de Fora, in the State of Minas Gerais, Brazil. Thus, an energy efficiency study was carried out by monitoring a lot of animals, during a 94-day period. The energy rate of each compound involved in the production process was quantified and the matrixes of energy consumption were determined in the form of animal feeding, electrical energy, piglets, material used as deep bed, human labor, equipment, swine buildings, production of alive swine for slaughter, organic fertilizer production (swine deep bed or swine deep litter). From the direct input energy, 80.57% correspond to animal feeding, 11.90% to pigs for slaughter and 6.76% to piglets, while from the energy output 53.45% correspond to the terminating swine and 46.55% to organic fertilizer (swine deep bed). By the results obtained, we can conclude that such production system has corresponded to an industrial and highly specialized agro ecosystem, importing a great part of the energy consumed in the production process, with 41% of energy efficiency.

Electrically driven fertilizer applicator controlled by fuzzy logic

The present study shows the development, simulation and actual implementation of a closed-loop controller based on fuzzy logic that is able to regulate and standardize the mass flow of a helical fertilizer applicator. The control algorithm was developed using MATLAB's Fuzzy Logic Toolbox. Both open and closed-loop simulations of the controller were performed in MATLAB's Simulink environment. The instantaneous deviation of the mass flow from the set point (SP), its derivative, the equipment´s translation velocity and acceleration were all used as input signals for the controller, whereas the voltage of the applicator's DC electric motor (DCEM) was driven by the controller as output signal. Calibration and validation of the rules and membership functions of the fuzzy logic were accomplished in the computer simulation phase, taking into account the system's response to SP changes. The mass flow variation coefficient, measured in experimental tests, ranged from 6.32 to 13.18%. The steady state error fell between -0.72 and 0.13g s-1 and the recorded average rise time of the system was 0.38 s. The implemented controller was able to both damp the oscillations in mass flow that are characteristic of helical fertilizer applicators, and to effectively respond to SP variations.