The effect of pretreatments on the drying rate and quality of dried bananas

The effects that four pretreatments (blanching, chilling, freezing, and combined blanching and freezing), used prior to drying, had on the drying rate and quality of bananas were investigated. An untreated sample was used as a control. The bananas were dried at 50 degreesC in a heat pump dehumidifier dryer, using an air velocity of 3.1 m s(-1), until a final moisture content of approximately 25% dry weight basis was attained. While the initial drying rate was highest for the blanched treatment, the two pretreatments involving freezing resulted in the shortest drying times. The blanched sample was most preferred in terms of colour while the frozen samples exhibited extensive browning. The texture and flavour was significantly (P < 0.05) reduced in all samples that involved blanching and/or freezing.

Simultaneous FT-NIR and ESR analyses to yield propagation rate coefficients for polymerization of methyl methacrylate based monomers

A hyphenated instrumental approach has been used to obtain reliable values for the propagation rate coefficients as a function of conversion for polymerizations of methyl methacrylate (MMA) and a mixture of MMA and ethyleneglycol dimethacrylate (EGDMA) with a 1:1 concentration of double bonds, from near the onset of the Trommsdorf region into the glass region. ESR spectroscopy was used to measure the radical concentration while FT-NIR fibre-optic spectroscopy was employed to measure instantaneously the double-bond concentration within the temperature-controlled cavity of the ESR instrument during polymerization. The advantage of this approach to the measurement of the rate coefficient is that it is equally applicable to branching and linear polymerizations. For the polymerization of methyl methacrylate, the values of the rate coefficient at the lowest conversions at which reliable values could be obtained were in agreement with recently reported values obtained by the PLP-SEC method. For the lowest conversions, the values obtained were 403 1 mol(-1) s(-1) at 306 K for MMA and 5201 mol(-1) s(-1) at 310 K for a 1:1 mixture of MMA and EGDMA. (C) 2003 Society of Chemical Industry.

Mapping the royal road and other hierarchical functions

In this paper we present a technique for visualising hierarchical and symmetric, multimodal fitness functions that have been investigated in the evolutionary computation literature. The focus of this technique is on landscapes in moderate-dimensional, binary spaces (i.e., fitness functions defined over {0, 1}(n), for n less than or equal to 16). The visualisation approach involves an unfolding of the hyperspace into a two-dimensional graph, whose layout represents the topology of the space using a recursive relationship, and whose shading defines the shape of the cost surface defined on the space. Using this technique we present case-study explorations of three fitness functions: royal road, hierarchical-if-and-only-if (H-IFF), and hierarchically decomposable functions (HDF). The visualisation approach provides an insight into the properties of these functions, particularly with respect to the size and shape of the basins of attraction around each of the local optima.

A yield architecture framework to explain adaptation of pearl millet to environmental stress

Functional knowledge of the physiological basis of crop adaptation to stress is a prerequisite for exploiting specific adaptation to stress environments in breeding programs. This paper presents an analysis of yield components for pearl millet, to explain the specific adaptation of local landraces to stress environments in Rajasthan, India. Six genotypes, ranging from high-tillering traditional landraces to low-tillering open-pollinated modern cultivars, were grown in 20 experiments, covering a range of nonstress and drought stress patterns. In each experiment, yield components (particle number, grain number, 100 grain mass) were measured separately for main shoots, basal tillers, and nodal tillers. Under optimum conditions, landraces had a significantly lower grain yield than the cultivars, but no significant differences were observed at yield levels around 1 ton ha(-1). This genotype x environment interaction for grain yield was due to a difference in yield strategy, where landraces aimed at minimising the risk of a crop failure under stress conditions, and modem cultivars aimed at maximising yield potential under optimum conditions. A key aspect of the adaptation of landraces was the small size of the main shoot panicle, as it minimised (1) the loss of productive tillers during stem elongation; (2) the delay in anthesis if mid-season drought occurs; and (3) the reduction in panicle productivity of the basal tillers under stress. In addition, a low investment in structural panicle weight, relative to vegetative crop growth rate, promoted the production of nodal tillers, providing a mechanism to compensate for reduced basal tiller productivity if stress occurred around anthesis. A low maximum 100 grain mass also ensured individual grain mass was little affected by environmental conditions. The strategy of the high-tillering landraces carries a yield penalty under optimum conditions, but is expected to minimise the risk of a crop failure, particularly if mid-season drought stress occurs. The yield architecture of low-tillering varieties, by contrast, will be suited to end-of-season drought stress, provided anthesis is early. Application of the above adaptation mechanisms into a breeding program could enable the identification of plant types that match the prevalent stress patterns in the target environments. (C) 2003 E.J. van Oosterom. Published by Elsevier Science B.V. All rights reserved.

Aproximação numérica – analítica para a modelagem da conversão termoquímica de combustíveis sólidos

Um algoritmo numérico foi criado para apresentar a solução da conversão termoquímica de um combustível sólido. O mesmo foi criado de forma a ser flexível e dependente do mecanismo de reação a ser representado. Para tanto, um sistema das equações características desse tipo de problema foi resolvido através de um método iterativo unido a matemática simbólica. Em função de não linearidades nas equações e por se tratar de pequenas partículas, será aplicado o método de Newton para reduzir o sistema de equações diferenciais parciais (EDP’s) para um sistema de equações diferenciais ordinárias (EDO’s). Tal processo redução é baseado na união desse método iterativo à diferenciação numérica, pois consegue incorporar nas EDO’s resultantes funções analíticas. O modelo reduzido será solucionado numericamente usando-se a técnica do gradiente bi-conjugado (BCG). Tal modelo promete ter taxa de convergência alta, se utilizando de um número baixo de iterações, além de apresentar alta velocidade na apresentação das soluções do novo sistema linear gerado. Além disso, o algoritmo se mostra independente do tamanho da malha constituidora. Para a validação, a massa normalizada será calculada e comparada com valores experimentais de termogravimetria encontrados na literatura, , e um teste com um mecanismo simplificado de reação será realizado.

Inércia da taxa de juros : teoria e evidência para a economia brasileira (2005-2013)

No âmbito da condução da política monetária, as funções de reação estimadas em estudos empíricos, tanto para a economia brasileira como para outras economias, têm mostrado uma boa aderência aos dados. Porém, os estudos mostram que o poder explicativo das estimativas aumenta consideravelmente quando se inclui um componente de suavização da taxa de juros, representado pela taxa de juros defasada. Segundo Clarida, et. al. (1998) o coeficiente da taxa de juros defasada (situado ente 0,0 e 1,0) representaria o grau de inércia da política monetária, e quanto maior esse coeficiente, menor e mais lenta é a resposta da taxa de juros ao conjunto de informações relevantes. Por outro lado, a literatura empírica internacional mostra que esse componente assume um peso expressivo nas funções de reação, o que revela que os BCs ajustam o instrumento de modo lento e parcimonioso. No entanto, o caso brasileiro é de particular interesse porque os trabalhos mais recentes têm evidenciado uma elevação no componente inercial, o que sugere que o BCB vem aumentando o grau de suavização da taxa de juros nos últimos anos. Nesse contexto, mais do que estimar uma função de reação forward looking para captar o comportamento global médio do Banco Central do Brasil no período de Janeiro de 2005 a Maio de 2013, o trabalho se propôs a procurar respostas para uma possível relação de causalidade dinâmica entre a trajetória do coeficiente de inércia e as variáveis macroeconômicas relevantes, usando como método a aplicação do filtro de Kalman para extrair a trajetória do coeficiente de inércia e a estimação de um modelo de Vetores Autorregressivos (VAR) que incluirá a trajetória do coeficiente de inércia e as variáveis macroeconômicas relevantes. De modo geral, pelas regressões e pelo filtro de Kalman, os resultados mostraram um coeficiente de inércia extremamente elevado em todo o período analisado, e coeficientes de resposta global muito pequenos, inconsistentes com o que é esperado pela teoria. Pelo método VAR, o resultado de maior interesse foi o de que choques positivos na variável de inércia foram responsáveis por desvios persistentes no hiato do produto e, consequentemente, sobre os desvios de inflação e de expectativas de inflação em relação à meta central.

Comparative analysis between statistical and artificial intelligence models in business failure prediction

A growing number of predicting corporate failure models has emerged since 60s. Economic and social consequences of business failure can be dramatic, thus it is not surprise that the issue has been of growing interest in academic research as well as in business context. The main purpose of this study is to compare the predictive ability of five developed models based on three statistical techniques (Discriminant Analysis, Logit and Probit) and two models based on Artificial Intelligence (Neural Networks and Rough Sets). The five models were employed to a dataset of 420 non-bankrupt firms and 125 bankrupt firms belonging to the textile and clothing industry, over the period 2003–09. Results show that all the models performed well, with an overall correct classification level higher than 90%, and a type II error always less than 2%. The type I error increases as we move away from the year prior to failure. Our models contribute to the discussion of corporate financial distress causes. Moreover it can be used to assist decisions of creditors, investors and auditors. Additionally, this research can be of great contribution to devisers of national economic policies that aim to reduce industrial unemployment.

Application of Gage R&R methodology for improving the training and evaluation of automatic optical inspection machine operators

The current level of demand by customers in the electronics industry requires the production of parts with an extremely high level of reliability and quality to ensure complete confidence on the end customer. Automatic Optical Inspection (AOI) machines have an important role in the monitoring and detection of errors during the manufacturing process for printed circuit boards. These machines present images of products with probable assembly mistakes to an operator and him decide whether the product has a real defect or if in turn this was an automated false detection. Operator training is an important aspect for obtaining a lower rate of evaluation failure by the operator and consequently a lower rate of actual defects that slip through to the following processes. The Gage R&R methodology for attributes is part of a Six Sigma strategy to examine the repeatability and reproducibility of an evaluation system, thus giving important feedback on the suitability of each operator in classifying defects. This methodology was already applied in several industry sectors and services at different processes, with excellent results in the evaluation of subjective parameters. An application for training operators of AOI machines was developed, in order to be able to check their fitness and improve future evaluation performance. This application will provide a better understanding of the specific training needs for each operator, and also to accompany the evolution of the training program for new components which in turn present additional new difficulties for the operator evaluation. The use of this application will contribute to reduce the number of defects misclassified by the operators that are passed on to the following steps in the productive process. This defect reduction will also contribute to the continuous improvement of the operator evaluation performance, which is seen as a quality management goal.

Comparative Analysis between Statistical and Artificial Intelligence Models in Business Failure Prediction

A growing number of predicting corporate failure models has emerged since 60s. Economic and social consequences of business failure can be dramatic, thus it is not surprise that the issue has been of growing interest in academic research as well as in business context. The main purpose of this study is to compare the predictive ability of five developed models based on three statistical techniques (Discriminant Analysis, Logit and Probit) and two models based on Artificial Intelligence (Neural Networks and Rough Sets). The five models were employed to a dataset of 420 non-bankrupt firms and 125 bankrupt firms belonging to the textile and clothing industry, over the period 2003–09. Results show that all the models performed well, with an overall correct classification level higher than 90%, and a type II error always less than 2%. The type I error increases as we move away from the year prior to failure. Our models contribute to the discussion of corporate financial distress causes. Moreover it can be used to assist decisions of creditors, investors and auditors. Additionally, this research can be of great contribution to devisers of national economic policies that aim to reduce industrial unemployment.

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.

How logrolling can explain the failure of the government coalition in Brazil

This article presents an analysis of the behavior of federal representatives in the Brazilian House of Representatives between 1995 and 1998, when a series of constitutional amendments were presented by the president to be voted on by Congress. The objective is to show that the lack of a stable government coalition resulted in costs to society that were not anticipated by the government. The study argues that a logroll - a trade of votes - was the strategy used by the government in order to guarantee the number of votes necessary to approve the amendments. This strategy created a vicious system in which representatives would only vote with the government if they had benefits in return.

Dilema da repetência e da evasão em escolas rurais de um município sergipano (2006-2008)

RESUMO: Diversos estudos realizados na área educativa têm demonstrado a importância de escolaridade para a melhoria da qualidade de vida das pessoas. Apesar disso, o alto índice de repetência e evasão escolar está presente em diversas escolas do país. Para tanto, este trabalho tem como tema central o dilema da repetência e da evasão em escolas rurais de um município sergipano. Assim, o trabalho desenvolve uma análise sobre os altos índices de evasão e de repetência em escolas rurais, apoiada numa revisão de literatura que discute essa temática. Participaram dessa pesquisa 10 alunos evadidos da 1° a 4° séries do Ensino Fundamental, no qual, o processo de coleta de dados foi a entrevista semi-estruturada, onde os questionamentos foram formulados através de um roteiro prévio de cinco questões. Através dessas questões, procurou-se discutir e refletir as causas da agravante repetência e evasão com alunos rurais, além da possibilidade de seus retornos às escolas vencendo os obstáculos que a educação local impõe. Trabalhamos também a história de vida de cada entrevistado. Por fim, buscou-se oferecer subsídios para a compreensão das condições em que educação rural se encontra. ABSTRACT: Several studies in the field of education have demonstrated the importance of education to improve the quality of life. Nevertheless, the high rate of grade repetition and dropping out is present in several schools in the country. Therefore, this work is focused on the dilemma of grade repetition and dropping out in rural schools in the municipality of Sergipe. Thus, this paper provides an analysis of the high grade repetition and dropout rates in rural schools, including a literature review which discusses this theme. Ten students who stopped their education after elementary school grades 1st to 4th participated in this study, where the process of data collection was a semi-structured interview with questions formulated from a script of the previous five questions. Through these questions, we sought to discuss and reflect upon the causes of aggravated student grade repetition and dropping out in rural areas, beyond the possibility of their return to the schools by overcoming the obstacles that the local education imposes. We worked also their life story. Finally, we attempted to provide background information on the conditions which constitute a rural education.