Damage detection in beams by using artificial neural networks and dynamical parameters

In this paper is presented a multilayer perceptron neural network combined with the Nelder-Mead Simplex method to detect damage in multiple support beams. The input parameters are based on natural frequencies and modal flexibility. It was considered that only a number of modes were available and that only vertical degrees of freedom were measured. The reliability of the proposed methodology is assessed from the generation of random damages scenarios and the definition of three types of errors, which can be found during the damage identification process. Results show that the methodology can reliably determine the damage scenarios. However, its application to large beams may be limited by the high computational cost of training the neural network.

Contribution to economic evaluation of systems that value animal welfare at farm

The demand for "welfare friendly" products increases as public conscience and perception on livestock production systems grow. The public and policy-makers demand scientific information for education and to guide decision processes. This paper describes some of the last decade contributions made by scientists on the technical, economical and market areas of farm animal welfare. Articles on animal welfare were compiled on the following themes: 1) consumer behavior, 2) technical and economical viability, 3) public regulation, and 4) private certification policies. Most studies on the economic evaluation of systems that promote animal welfare involved species destined to produce export items, such as eggs, beef and pork. Few studies were found on broilers, dairy cows and fish, and data regarding other species, such as horses, sheep and goats were not found. Scientists understand that farm animal welfare is not only a matter of ethics, but also an essential tool to gain and maintain markets. However, it is unfortunate that little attention is paid to species that are not economically important for exports. Studies that emphasize on more humane ways to raise animals and that provide economic incentives to the producer are needed. An integrated multidisciplinary approach is necessary to highlight the benefits of introducing animal welfare techniques to existing production systems.

Advanced oxidation process H2O2/UV combined with anaerobic digestion to remove chlorinated organics from bleached kraft pulp mill wastewater

This study investigated the application of an advanced oxidation process combining hydrogen peroxide with ultraviolet radiation (H2O2/UV) to remove recalcitrant compounds from Kraft bleaching effluent. Anaerobic pre-treatment was performed to remove easily degraded organics using a horizontal-flow anaerobic immobilized biomass (HAIB) reactor. Bleaching plant effluent was treated in the HAIB reactor processed over 19 h of hydraulic retention time (HRT), reaching the expected removal efficiencies for COD (61 +/- 3%), TOC (69 +/- 9%), BOD5 (90 +/- 5%) and AOX (55 +/- 14%). However, the anaerobic treatment did not achieve acceptable removal of UV254 compounds. Furthermore, there was an increase of lignin, measured as total phenols. The H2O2/UV post-treatment provided a wide range of removal efficiencies depending on the dosage of hydrogen peroxide and UV irradiation: COD ranged from 0 to 11%, UV254 from 16 to 35%, lignin from 0 to 29% and AOX from 23 to 54%. All peroxide dosages applied in this work promoted an increase in the BOD5/COD ratio of the wastewater. The experiments demonstrate the technical feasibility of using H2O2/UV for post-treatment of bleaching effluents submitted to anaerobic pre-treatment.

Bayesian Analysis for Errors in Variables with Changepoint Models

Changepoint regression models have originally been developed in connection with applications in quality control, where a change from the in-control to the out-of-control state has to be detected based on the avaliable random observations. Up to now various changepoint models have been suggested for differents applications like reliability, econometrics or medicine. In many practical situations the covariate cannot be measured precisely and an alternative model are the errors in variable regression models. In this paper we study the regression model with errors in variables with changepoint from a Bayesian approach. From the simulation study we found that the proposed procedure produces estimates suitable for the changepoint and all other model parameters.