Production of defects in ZBLAN, ZBLAN : Tm3+ and ZBLAN : Cr3+ glasses by ultra-short pulses laser interaction

In this work we have studied pure and thulium- and chromium-doped ZBLAN glasses irradiated by ultra-short laser pulses. A Ti:sapphire CPA system was used, producing a 500 Hz train of pulses, centered at 830 nm, with 375 mu J of energy and 50 fs of duration (FWHM). The beam was focused by a 20 Him lens, producing a converging beam with a waist of 12 pin. The absorption spectra before and after laser irradiation were obtained showing production of color centers in pure, thulium-doped and chromium-doped ZBLAN glasses. A damage threshold of 9.56 TW/cm(2) was determined for ZBLAN. (C) 2007 Elsevier Ltd. All rights reserved.

Corn yield with reduction of insecticidal sprayings against fall armyworm Spodoptera frugiperda (Lepidoptera: Noctuidae)

The ideal time is more important than amount of insecticidal spraying to adequate the control of Spodoptera frugiperda J.E. Smith (Lepidoptera: Noctuidae) in corn. This study aimed to evaluate lufenuron sequential sprayings effect and its rotation with other active ingredients on the population, damage caused by S. frugiperda and the impact on corn yield. The experiment was carried out in the field with six treatments: (1) one lufenuron spraying, (2) two lufenuron sprayings, (3) three lufenuron sprayings (4) four lufenuron sprayings, (5) sprayings with spinosad, lufenuron, thiamethoxam+lambdacyhalothrin and deltamethrin (in sequence, at ten days intervals) (6) control treatment. Sprayings started twenty days after the seedling had emerged and then every ten days for a maximum of four sprays. Both caterpillar population (20.9-21.7 larvae/plot) and index of damage (1.2-1.7) observed in corn plants were significantly lower in treated plots compared to control (untreated) (31.7 larvae/plot and index of damage 2.7), regardless of spraying amount. The results showed that multiple insecticide applications to control S. frugiperda do not guarantee higher yields in corn, ranging from 6375.2 to 7650.1 kg ha -1. Only one spraying of lufenuron was enough to prevent significant reduction in corn yield (6749.9 kg ha -1). © 2012 Asian Network for Scientific Information.

Automatic detection of thermal damage in grinding process by artificial neural network

Esse trabalho tem por objetivo o desenvolvimento de um sistema inteligente para detecção da queima no processo de retificação tangencial plana através da utilização de uma rede neural perceptron multi camadas, treinada para generalizar o processo e, conseqüentemente, obter o limiar de queima. em geral, a ocorrência da queima no processo de retificação pode ser detectada pelos parâmetros DPO e FKS. Porém esses parâmetros não são eficientes nas condições de usinagem usadas nesse trabalho. Os sinais de emissão acústica e potência elétrica do motor de acionamento do rebolo são variáveis de entrada e a variável de saída é a ocorrência da queima. No trabalho experimental, foram empregados um tipo de aço (ABNT 1045 temperado) e um tipo de rebolo denominado TARGA, modelo ART 3TG80.3 NVHB.

Muscle damage slows oxygen uptake kinetics during moderate-intensity exercise performed at high pedal rate

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Damage detection in a benchmark structure using AR-ARX models and statistical pattern recognition

Structural health monitoring (SHM) is related to the ability of monitoring the state and deciding the level of damage or deterioration within aerospace, civil and mechanical systems. In this sense, this paper deals with the application of a two-step auto-regressive and auto-regressive with exogenous inputs (AR-ARX) model for linear prediction of damage diagnosis in structural systems. This damage detection algorithm is based on the. monitoring of residual error as damage-sensitive indexes, obtained through vibration response measurements. In complex structures there are. many positions under observation and a large amount of data to be handed, making difficult the visualization of the signals. This paper also investigates data compression by using principal component analysis. In order to establish a threshold value, a fuzzy c-means clustering is taken to quantify the damage-sensitive index in an unsupervised learning mode. Tests are made in a benchmark problem, as proposed by IASC-ASCE with different damage patterns. The diagnosis that was obtained showed high correlation with the actual integrity state of the structure. Copyright © 2007 by ABCM.