Desfolha artificial simulando danos de pragas na cultura do girassol (Helianthus annuus L., Asteraceae)

O girassol está sujeito às perdas de área foliar por diferentes fatores, dentre eles os insetos desfolhadores, contra aos quais geralmente são dirigidas aplicações de inseticidas na cultura. A desfolha artificial em plantas de importância econômica é uma metodologia útil na simulação de ataques dessas pragas em lavouras na determinação dos níveis de dano econômico. O objetivo deste estudo foi avaliar componentes de produção das plantas de girassol submetidas a níveis crescentes de desfolha de 0, 10, 25, 50, 75 e 100%, realizada em três distintos estádios fenológicos da cultura, a saber: V6 (seis folhas com no mínimo 4,0 cm de comprimento), R1 (quando a inflorescência circundada pela bráctea imatura torna-se visível) e R5.5 (50% das flores do disco estão fertilizadas ou em antese), perfazendo um total de 18 tratamentos, os quais foram dispostos em blocos ao acaso, com quatro repetições. Para todos os componentes de produção avaliados (diâmetro do capítulo, biomassa total de sementes da planta e biomassa de 100 aquênios) houve efeito significativo da interação dos tratamentos, evidenciando que o efeito da desfolha será dependente do estágio fenológico da planta. O estádio R5.5 foi mais sensível à desfolha, ocasionando perdas em todos os componentes de produção avaliados.

Dose inseminante utilizada na fertilização artificial de ovócito de piracanjuba (Brycon orbignyanus)

A piracanjuba (Brycon orbignyanus Valenciennes, 1849) é uma espécie de peixe migratória, ameaçada de extinção. O objetivo do presente estudo foi determinar a dose inseminante na fertilização artificial de ovócitos de piracanjuba. Para isso, utilizou-se delineamento em blocos casualizados, com quatro tratamentos e três repetições. Três casais de piracanjuba, selecionados dos tanques de reprodutores da Estação Ambiental de Itutinga (EAI - CEMIG), no período de piracema 2006/2007, receberam aplicação de hormônio extrato bruto de hipófise de carpa (EBHC) para obtenção dos gametas. Adotaram-se quatro tratamentos diferentes para a fertilização de 0,1 grama de ovócitos: 10µL, 20µL, 30µL e 40µL de sêmen. As amostras foram ativadas com 5 mL de água do próprio tanque e, em seguida, levadas para incubadoras, dotadas de renovação constante de água, à temperatura de 28ºC. Após 8 e 16 horas, analisaram-se as taxas de fertilização (ovos viáveis) e de eclosão dos ovos, respectivamente. Os resultados obtidos foram comparados pelo teste de Tukey a 5%. As relações sêmen-ovócitos testadas não alteraram as taxas de fertilização e eclosão (P>0,05). O número de espermatozoides-ovócitos, variando de 10,4 x10(5) a 41,6 x10(5), foi eficiente para obtenção de boas taxas de fertilidade.

Automatic modeling of pectus excavatum corrective prosthesis using artificial neural networks

Pectus excavatum is the most common deformity of the thorax. Pre-operative diagnosis usually includes Computed Tomography (CT) to successfully employ a thoracic prosthesis for anterior chest wall remodeling. Aiming at the elimination of radiation exposure, this paper presents a novel methodology for the replacement of CT by a 3D laser scanner (radiation-free) for prosthesis modeling. The complete elimination of CT is based on an accurate determination of ribs position and prosthesis placement region through skin surface points. The developed solution resorts to a normalized and combined outcome of an artificial neural network (ANN) set. Each ANN model was trained with data vectors from 165 male patients and using soft tissue thicknesses (STT) comprising information from the skin and rib cage (automatically determined by image processing algorithms). Tests revealed that ribs position for prosthesis placement and modeling can be estimated with an average error of 5.0 ± 3.6 mm. One also showed that the ANN performance can be improved by introducing a manually determined initial STT value in the ANN normalization procedure (average error of 2.82 ± 0.76 mm). Such error range is well below current prosthesis manual modeling (approximately 11 mm), which can provide a valuable and radiation-free procedure for prosthesis personalization.

Automatic modeling of pectus excavatum corrective prosthesis using artificial neural networks

Pectus excavatum is the most common deformity of the thorax. Pre-operative diagnosis usually includes Computed Tomography (CT) to successfully employ a thoracic prosthesis for anterior chest wall remodeling. Aiming at the elimination of radiation exposure, this paper presents a novel methodology for the replacement of CT by a 3D laser scanner (radiation-free) for prosthesis modeling. The complete elimination of CT is based on an accurate determination of ribs position and prosthesis placement region through skin surface points. The developed solution resorts to a normalized and combined outcome of an artificial neural network (ANN) set. Each ANN model was trained with data vectors from 165 male patients and using soft tissue thicknesses (STT) comprising information from the skin and rib cage (automatically determined by image processing algorithms). Tests revealed that ribs position for prosthesis placement and modeling can be estimated with an average error of 5.0 ± 3.6 mm. One also showed that the ANN performance can be improved by introducing a manually determined initial STT value in the ANN normalization procedure (average error of 2.82 ± 0.76 mm). Such error range is well below current prosthesis manual modeling (approximately 11 mm), which can provide a valuable and radiation-free procedure for prosthesis personalization.

Artificial neural networks for automatic modelling of the pectus excavatum corrective prosthesis

Pectus excavatum is the most common deformity of the thorax and usually comprises Computed Tomography (CT) examination for pre-operative diagnosis. Aiming at the elimination of the high amounts of CT radiation exposure, this work presents a new methodology for the replacement of CT by a laser scanner (radiation-free) in the treatment of pectus excavatum using personally modeled prosthesis. The complete elimination of CT involves the determination of ribs external outline, at the maximum sternum depression point for prosthesis placement, based on chest wall skin surface information, acquired by a laser scanner. The developed solution resorts to artificial neural networks trained with data vectors from 165 patients. Scaled Conjugate Gradient, Levenberg-Marquardt, Resilient Back propagation and One Step Secant gradient learning algorithms were used. The training procedure was performed using the soft tissue thicknesses, determined using image processing techniques that automatically segment the skin and rib cage. The developed solution was then used to determine the ribs outline in data from 20 patient scanners. Tests revealed that ribs position can be estimated with an average error of about 6.82±5.7 mm for the left and right side of the patient. Such an error range is well below current prosthesis manual modeling (11.7±4.01 mm) even without CT imagiology, indicating a considerable step forward towards CT replacement by a 3D scanner for prosthesis personalization.

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.

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.

Inteligência empresarial: a revolução informacional da ação competitiva

Esta pesquisa apresenta o estado da arte da Inteligência Empresarial, discutindo sua imporiãncia no Planejamento Estratégico, Processo Decisório, Implantação de Programas de Qualidade Total e Competitividade. Analisa os diversos arranjos organizacionais necessários e os recursos tecnológicos disponfveis para uma bem-sucedida atividade de Inteligência Empresarial. Destaca a importância das fontes de informações, indicando que é necessário um correto monitoramento das mesmas. Por fim, discute temas mais abrangentes como Implicações Legais e Éticas, diferenças entre Inteligência Empresarial e Espionagem e o papel da Inteligência Empresarial para as Estratégias de Globalização.

Applications of artificial intelligence to condition-based maintenance

In this paper we discuss interesting developments of expert systems for machine diagnosis and condition-based maintenance. We review some elements of condition-based maintenance and its applications, expert systems for machine diagnosis, and an example of machine diagnosis. In the last section we note some problems to be resolved so that expert systems for machine diagnosis may gain wider acceptance in the future.

Inteligência emocional e satisfação com a vida

RESUMO: O constructo Inteligência Emocional tem gerado um interesse crescente na Psicologia, e de um modo simplificado pode descrever-se como a capacidade que as pessoas têm para processar e utilizar informação carregada de afecto. Com este estudo pretendeu-se estudar as relações entre a Inteligência Emocional e a Satisfação com a Vida. Estudou-se também a natureza do teste Trait Meta-Mood Scale (TMMS). Foi utilizada uma amostra composta por 586 participantes, 212 do sexo masculino, com média de idade 34.55 (DP=14.77), e 374 do sexo feminino, com média de idade 33.28 (DP=15.21). Em relação à natureza do Trait Meta-Mood Scale, os resultados obtidos não foram totalmente de encontro aos resultados de estudos anteriores, tendo-se conhecido um novo factor, o Desprendimento Emocional e tendo desaparecido o factor Reparação Emocional. No que diz respeito à relação entre os factores da Inteligência Emocional encontrados no Trait Meta-Mood Scale, e a Satisfação com a Vida, encontrou-se uma correlação negativa e significativa com o Desprendimento Emocional, e uma correlação positiva e significativa com a Atenção Emocional e com a Clareza Emocional. Encontrou-se também uma correlação positiva e estatisticamente significativa entre a Inteligência Emocional e a Satisfação com a Vida, o que era esperado. ABSTRACT: The Emotional Intelligence construct has been creating a rising interest in psychology, in a simplified way it can be described like the hability that people have to process and utilize affection loaded information. In this study, it was pretended to study the relations between Emotional Intelligence and Life Satisfaction. It has also been studied the nature of the Trait Meta-Mood Scale (TMMS). The used sample was composed by 586 participants, 212 males, with an average age of 34.55 years old (DP=14.77) and 374 females, with an average age of 33.28 years old (DP=15.21). Relative to the nature of Trait Meta-Mood Scale, the results did not totally met previous investigations, with a new factor, the Emotional Falling, and having a vanished factor, the Emotional Repair. Due to the relation between the Emotional Intelligence factors found in the Trait Meta-Mood Scale, and Life Satisfaction, it was found a negative and significant correlation with the Emotional Falling and a positive and significant correlation with the Emotional Attention and the Emotional Clarity. It was also found a positive and significant correlation between Emotional Intelligence and Life Satisfaction that was previously expected.