Due to natural or anthropogenic activities, various chemical contaminants, such as toxic metals and organic compounds, enter water systems and can have multiple deleterious effects on many living organisms. The Todos os Santos River (TSR) in Brazil receives a high discharge of untreated effluents from various sources. The purpose of this study was to determine trace element concentrations in water samples from the TSR, evaluate the toxicological effects of these elements by using the (onion) test, and verify the physical-chemical parameters to establish the risk of exposure related to the contaminated river. The samples were taken in 2011 at six selected points (two upstream of an urban area, two in the urban area, and two downstream of the urban area) with physical-chemical parameters evaluated. The concentrations of Al (21.63-1688.84 μg L), P (38.59-1760.87 μg L), and Fe (478.9-8296.3 μg L) were above the maximum levels permitted under Brazilian law (and the World Health Organization); little dissolved O was observed. Based on the test, genotoxic and mutagenic effects may occur in the river and could be due to anthropogenic increases in metal content. These important results have serious implications for the ecosystem as well as the health of the people who use the water.

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This paper presents equipment for early detection of failures in the insulation of power transformers, checking existing partial discharges inside. The equipment involves hardware, control and signal acquisition software, and signal analysis software. This equipment has a set of algorithms that were made with intelligent extraction techniques and interpretation of data. The degradation diagnosis of the equipment insulation is based on digital signal processing algorithms for extraction of features and also in artificial intelligence algorithms that allies a mining involving all the data linked to the equipment throughout its operating life can make an assessment of the operating conditions of the equipment and suggest interventions and provide an estimated time so that they have to be made.