An hydrochemical answer to a legislative demand involving health risk related to water quality

Effluents and surface waters around an area involved with the inking of tissues at Itatiba municipality, São Paulo State, Brazil, were chemically analyzed with the purpose of evaluating the influence on the water quality of the chemicals released, as well to provide answers to legislative requirements related to the São Paulo State Register 997 published on 31 May 1976.

Performance of constructed wetland system for public water supply

The project is being conducted in the town of Analândia, São Paulo, Brazil. The constructed wetlands system for water supply consists of a channel with floating aquatic macrophytes, HDS system (Water Decontamination with Soil - Patent PI 850.3030), chlorinating system, filtering system and distribution. The project objectives include investigating the process variables to further optimize design and operation factors, evaluating the relation of nutrients and plants development, biomass production, shoot development, nutrient cycling and total and fecal coliforms removal, comparing the treatment efficiency among the seasons of the year; and moreover to compare the average values obtained between February and June 1998 (Salati et al., 1998) with the average obtained for the same parameters between March and June 2000. Studies have been developed in order to verify during one year the drinking quality of the water for the following parameters: turbidity, color, pH, dissolved oxygen, total of dissolved solids, COD, chloride, among others, according to the Ministry of Health's Regulation 36. This system of water supply projected to treat 15 L s-1 has been in continuous operation for 2 years, it was implemented with support of the National Environment Fund (FNMA), administered by the Center of Environmental Studies (CEA-UNESP), while the technical supervision and design were performed by the Institute of Applied Ecology. The actual research project is being supported by FAPESP.

A fast electric load forecasting using adaptive neural networks

This work presents a procedure for electric load forecasting based on adaptive multilayer feedforward neural networks trained by the Backpropagation algorithm. The neural network architecture is formulated by two parameters, the scaling and translation of the postsynaptic functions at each node, and the use of the gradient-descendent method for the adjustment in an iterative way. Besides, the neural network also uses an adaptive process based on fuzzy logic to adjust the network training rate. This methodology provides an efficient modification of the neural network that results in faster convergence and more precise results, in comparison to the conventional formulation Backpropagation algorithm. The adapting of the training rate is effectuated using the information of the global error and global error variation. After finishing the training, the neural network is capable to forecast the electric load of 24 hours ahead. To illustrate the proposed methodology it is used data from a Brazilian Electric Company. © 2003 IEEE.

Water table effects on bean yield and nitrate distribution in the soil profile

In order to evaluate the bean yield under different water table levels as well as the moisture and nitrate distribution in the soil profile, a field experiment was carried out at the experimental area from the College of Agronomic Sciences - UNESP, Botucatu, SP, Brazil. Beans were grown in field lysimeters and subjected to five water table depths:30; 40; 50; 60 and 70 cm. The moisture in the soil profile was gravimetrically determined through samples obtained at 10; 20; 30; 40; 50; 60 and 70cm of depth. The water table depths of 30cm and 40cm showed the highest productivities (3,228.4 kg.ha-1 and 3,422.1 kg.ha-1, respectively), showing no statistical differences between each other. The highest productivity was related to the two most elevated water table levels (30 and 40cm), which provided the highest moisture average values on basis of volume in the soil profile (33.3 e 31%) as well as the consumptive use of water (416 and 396 mm). The nitrate content during the bean cycle at the extraction depth of 60cm has been under the safe drinking limit of 10 mg.1-1 for water table depths of 30; 40; 50 and 60cm, showing the denitrification effectiveness as a way of controlling water table from nitrate pollution. The water table handling allowed the attainment of high bean productivity levels, as well as the reduction of the nitrate level.

An approach based on neural networks for identification of fault sections in radial distribution systems

The main objective involved with this paper consists of presenting the results obtained from the application of artificial neural networks and statistical tools in the automatic identification and classification process of faults in electric power distribution systems. The developed techniques to treat the proposed problem have used, in an integrated way, several approaches that can contribute to the successful detection process of faults, aiming that it is carried out in a reliable and safe way. The compilations of the results obtained from practical experiments accomplished in a pilot radial distribution feeder have demonstrated that the developed techniques provide accurate results, identifying and classifying efficiently the several occurrences of faults observed in the feeder.

Application of ARX neural networks to model the rate of penetration of petroleum wells drilling

Bit performance prediction has been a challenging problem for the petroleum industry. It is essential in cost reduction associated with well planning and drilling performance prediction, especially when rigs leasing rates tend to follow the projects-demand and barrel-price rises. A methodology to model and predict one of the drilling bit performance evaluator, the Rate of Penetration (ROP), is presented herein. As the parameters affecting the ROP are complex and their relationship not easily modeled, the application of a Neural Network is suggested. In the present work, a dynamic neural network, based on the Auto-Regressive with Extra Input Signals model, or ARX model, is used to approach the ROP modeling problem. The network was applied to a real oil offshore field data set, consisted of information from seven wells drilled with an equal-diameter bit.

Water table effects on bean yield and nitrate distribution in the soil profile

In order to evaluate the bean yield under different water table levels as well as the moisture and nitrate distribution in the soil profile, a field experiment was carried out in the experimental area of the College of Agricultural Sciences - UNESP, Botucatu, SP, Brazil. Beans were grown in field lysimeters under five water table depths: 30; 40; 50; 60 and 70 cm. The moisture in the soil profile was determined gravimetrically using samples collected at 10; 20; 30; 40; 50; 60 and 70 cm deep. The water table depths of 30cm and 40cm showed the highest productivities (3,228.4kg.ha-1 and 3,422.1kg.ha-1, respectively), with no statistical differences between them. The highest productivity was related to the two highest water table levels (30 and 40cm), which provided the highest moisture average values on the basis of volume in the soil profile (33.3 e 31%) as well as the consumptive use of water (416 and 396mm). The nitrate content during the bean cycle at the extraction depth of 60cm was below the safe drinking limit of 10mg.1-1 for water table depths of 30; 40; 50 and 60cm, which shows the denitrification efficiency as a way of controlling nitrate pollution in water tables. The management of water table can lead to high levels of bean yield and to a better control of nitrate pollution in underground water.

Transmission network expansion planning considering uncertainty in generation and demand

This paper presents a mathematical model and a methodology to solve a transmission network expansion planning problem considering uncertainty in demand and generation. The methodology used to solve the problem, finds the optimal transmission network expansion plan that allows the power system to operate adequately in an environment with uncertainty. The model presented results in an optimization problem that is solved using a specialized genetic algorithm. The results obtained for known systems from the literature show that cheaper plans can be found satisfying the uncertainty in demand and generation. ©2008 IEEE.

Millennium development goals: progress towards the right to health in Latin america and the Caribbean

Includes bibliography

Proposal of an On-demand Software Deployment System Based on Application Streaming, Virtualization Techniques and P2P Transport

This paper presents the work in progress of an on-demand software deployment system based on application virtualization concepts which eliminates the need of software installation and configuration on each computer. Some mechanisms were created, such as mapping of utilization of resources by the application to improve the software distribution and startup; a virtualization middleware which give all resources needed for the software execution; an asynchronous P2P transport used to optimizing distribution on the network; and off-line support where the user can execute the application even when the server is not available or when is out of the network. © Springer-Verlag Berlin Heidelberg 2010.

Traffic flow breakdown prediction using feature reduction through Rough-Neuro fuzzy Networks

The prediction of the traffic behavior could help to make decision about the routing process, as well as enables gains on effectiveness and productivity on the physical distribution. This need motivated the search for technological improvements in the Routing performance in metropolitan areas. The purpose of this paper is to present computational evidences that Artificial Neural Network ANN could be use to predict the traffic behavior in a metropolitan area such So Paulo (around 16 million inhabitants). The proposed methodology involves the application of Rough-Fuzzy Sets to define inference morphology for insertion of the behavior of Dynamic Routing into a structured rule basis, without human expert aid. The dynamics of the traffic parameters are described through membership functions. Rough Sets Theory identifies the attributes that are important, and suggest Fuzzy relations to be inserted on a Rough Neuro Fuzzy Network (RNFN) type Multilayer Perceptron (MLP) and type Radial Basis Function (RBF), in order to get an optimal surface response. To measure the performance of the proposed RNFN, the responses of the unreduced rule basis are compared with the reduced rule one. The results show that by making use of the Feature Reduction through RNFN, it is possible to reduce the need for human expert in the construction of the Fuzzy inference mechanism in such flow process like traffic breakdown. © 2011 IEEE.

Education in Latin America: demand and distribution are factors that matter

Includes bibliography

Root distribution, nutrient uptake, and yield of two upland rice cultivars under two water regimes

Upland rice (Oryza sativa L.) cultivation has been increasing in global importance due to the decreasing water availability for flood- irrigated rice. The use of sprinkler irrigation to supplement rainfall and the identification of cultivars more adapted to lower water availability could be effective alternatives for producing upland rice without yield losses while using less water. The objective of this field study was to evaluate the root distribution, plant nutrition, and grain yield of two drought tolerant upland rice cultivars under two water regimes in the Cerrado Region of Brazil during two growing seasons. The main plots were two water regimes (rainfed and sprinkler-irrigation plus rainfall). Subplots were two upland rice cultivars Carajás and IAC 201. Low water availability reduced root growth by 7% and grain yields were from 2644 to 4002 kg ha-1 on average for rainfed and sprinkler irrigation treatments, respectively. Carajás had a significantly better root distribution, nutrient uptake, and higher grain yield (3732 kg ha-1) compared with IAC 201 (2914 kg ha-1) averaged over two growing seasons and water regimes. There were no treatment interactions. Our results suggest that, even when cultivars with a higher tolerance to less water availability are used, using sprinkler irrigation to augment limited rainfall during dry periods may be a viable method to increase upland rice grain yields. © 2013 by the American Society of Agronomy.

Methodology for forecasting electric power demand

Includes bibliography

An assessment of the economic impact of climate change on the water sector in Saint Vincent and The Grenadines

Water security which is essential to life and livelihood, health and sanitation, is determined not only by the water resource, but also by the quality of water, the ability to store surplus from precipitation and runoff, as well as access to and affordability of supply. All of these measures have financial implications for national budgets. The water sector in the context of the assessment and discussion on the impact of climate change in this paper includes consideration of the existing as well as the projected available water resource and the demand in terms of: quantity and quality of surface and ground water, water supply infrastructure - collection, storage, treatment, distribution, and potential for adaptation. Wastewater management infrastructure is also considered a component of the water sector. Saint Vincent and the Grenadines has two distinct hydrological regimes: mainland St Vincent is one of the wetter islands of the eastern Caribbean whereas the Grenadines have a drier climate than St Vincent. Surface water is the primary source of water supply on St Vincent, whereas the Grenadines depend on man-made catchments, rainwater harvesting, wells, and desalination. The island state is considered already water stressed as marked seasonality in rainfall, inadequate supply infrastructure, and institutional capacity constrains water supply. Economic modelling approaches were implemented to estimate sectoral demand and supply between 2011 and 2050. Residential, tourism and domestic demand were analysed for the A2, B2 and BAU scenarios. In each of the three scenarios – A2, B2 and BAU Saint Vincent and the Grenadines will have a water gap represented by the difference between the two curves during the forecast period of 2011 and 2050. The amount of water required increases steadily between 2011 and 2050 implying an increasing demand on the country‘s resources as reflected by the fact that the water supply that is available cannot respond adequately to the demand. The Global Water Partnership in its 2005 policy brief suggested that the best way for countries to build the capacity to adapt to climate change will be to improve their ability to cope with today‘s climate variability (GWP, 2005). This suggestion is most applicable for St Vincent and the Grenadines, as the variability being experienced has already placed the island nation under water stress. Strategic priorities should therefore be adopted to increase water production, increase efficiency, strengthen the institutional framework, and decrease wastage. Cost benefit analysis was stymied by data availability, but the ―no-regrets approach‖ which intimates that adaptation measures will be beneficial to the land, people and economy of Saint Vincent and the Grenadines with or without climate change should be adopted.