Fractionation of Zn, Cd and Pb in a Tropical Soil After Nine-Year Sewage Sludge Applications

A long-term field experiment was carried out in the experiment farm of the Sao Paulo State University, Brazil, to evaluate the phytoavailability of Zn, Cd and Pb in a Typic Eutrorthox soil treated with sewage sludge for nine consecutive years, using the sequential extraction and organic matter fractionation methods. During 2005-2006, maize (Zea mays L.) was used as test plants and the experimental design was in randomized complete blocks with four treatments and five replicates. The treatments consisted of four sewage sludge rates (in a dry basis): 0.0 (control, with mineral fertilization), 45.0, 90.0 and 127.5 t ha(-1), annually for nine years. Before maize sowing, the sewage sludge was manually applied to the soil and incorporated at 10 cm depth. Soil samples (0-20 cm layer) for Zn, Cd and Pb analysis were collected 60 days after sowing. The successive applications of sewage sludge to the soil did not affect heavy metal (Cd and Pb) fractions in the soil, with exception of Zn fractions. The Zn, Cd and Pb distributions in the soil were strongly associated with humin and residual fractions, which are characterized by stable chemical bonds. Zinc, Cd and Pb in the soil showed low phytoavailability after nine-year successive applications of sewage sludge to the soil.

Correlation of Modified Natural Rubber Properties by Artificial Neural Networks

Natural rubber (NR) is a raw material largely used by the modern industry; however, it is common that chemical modifications must be made to NR in order to improve properties such as hydrophobicity or mechanical resistance. This work deals with the correlation of properties of NR modified with dimethylaminoethylmethacrylate or methylmethacrylate as grafting agents. Dynamic-mechanical behavior and stress/strain relations are very important properties because they furnish essential characteristics of the material such as glass transition temperature and rupture point. These properties are concerned with different physical principles; for this reason, normally they are not related to each other. This work showed that they can be correlated by artificial neural networks (ANN). So, from one type of assay, the properties that as a rule only could be obtained from the other can be extracted by ANN correlation. POLYM. ENG. SCI., 49:499-505, 2009. (c) 2009 Society of Plastics Engineers

Sequential production of amylolytic and lipolytic enzymes by bacterium strain isolated from petroleum contaminated soil

Amylases and lipases are highly demanded industrial enzymes in various sectors such as food, pharmaceuticals, textiles, and detergents. Amylases are of ubiquitous occurrence and hold the maximum market share of enzyme sales. Lipases are the most versatile biocatalyst and bring about a range of bioconversion reactions such as hydrolysis, inter-esterification, esterification, alcoholysis, acidolysis, and aminolysis. The objective of this work was to study the feasibility for amylolitic and lipolytic production using a bacterium strain isolated from petroleum contaminated soil in the same submerged fermentation. This was a sequential process based on starch and vegetable oils feedstocks. Run were performed in batchwise using 2% starch supplemented with suitable nutrients and different vegetable oils as a lipase inducers. Fermentation conditions were pH 5.0; 30 degrees C, and stirred speed (200 rpm). Maxima activities for amyloglucosidase and lipase were, respectively, 0.18 and 1,150 U/ml. These results showed a promising methodology to obtain both enzymes using industrial waste resources containing vegetable oils.

Optimization of Heat Treatment Profiles Applied to Nanometric-Scale Nb(3)Sn Wires With Cu-Sn Artificial Pinning Centers

Nb(3)Sn is one of the most used superconducting materials for applications in high magnetic fields. The improvement of the critical current densities (J(c)) is important, and must be analyzed together with the optimization of the flux pinning acting in the material. For Nb(3)Sn, it is known that the grain boundaries are the most effective pinning centers. However, the introduction of artificial pinning centers (APCs) with different superconducting properties has been proved to be beneficial for J(c). As these APCs are normally in the nanometric-scale, the conventional heat treatment profiles used for Nb(3)Sn wires cannot be directly applied, leading to excessive grain growth and/or increase of the APCs cross sections. In this work, the heat treatment profiles for Nb(3)Sn superconductor wires with Cu(Sn) artificial pinning centers in nanometric-scale were analyzed in an attempt to improve J(c) . It is described a methodology to optimize the heat treatment profiles in respect to diffusion, reaction and formation of the superconducting phases. Microstructural, transport and magnetic characterization were performed in an attempt to find the pinning mechanisms acting in the samples. It was concluded that the maximum current densities were found when normal phases (due to the introduction of the APCs) are acting as main pinning centers in the global behavior of the Nb(3)Sn superconducting wire.

Heat treatment influence on the superconducting properties of nanometric-scale Nb(3)Sn wires with Cu-Sn artificial pinning centers

Since the discovery of Nb(3)Sn superconductors many efforts have been expended to improve the transport properties in these materials. In this work, the heat treatment profiles for Nb(3)Sn superconductor wires with Cu(Sn) artificial pinning centers (APCs) with nanometric-scale sizes were analyzed in an attempt to improve the critical current densities and upper critical magnetic field. The methodology to optimize the heat treatment profiles in respect to the diffusion, reaction and formation of the superconducting phases is described. Microstructural characterization, transport and magnetic measurements were performed in an attempt to relate the microstructure to the pinning mechanisms acting in the samples. It was concluded that the maximum current densities occur due to normal phases (APCs) that act as the main pinning centers in the global behavior of the Nb(3)Sn superconducting wire. The APC technique was shown to be very powerful because it permitted mixing of the pinning mechanism. This achievement was not possible in other studies in Nb(3)Sn wires reported up to now.

EIS study of Ti-23Ta alloy in artificial saliva

Although titanium and Ti-6Al-4V alloy have been widely used as dental materials, possible undesirable effects such as cytotoxic reactions and neurological disorder due to metal release led to the development of more corrosion resistant and V and Al free titanium alloys, containing Nb, Zr, Mo and Ta atoxic elements. Fluoride containing products used in the prevention of plaque formation and dental caries can affect the stability of the passive oxide films formed on the Ti alloys. In this work, the corrosion behaviour of the new Ti-23Ta alloy has been evaluated in artificial saliva of different pH and fluoride concentration using electrochemical impedance spectroscopy. Electrochemical impedance spectroscopy study showed that the oxide film formed on the alloy in artificial saliva consists of an inner compact film and an outer porous layer. The corrosion resistance of Ti-23Ta alloy which is reduced by increasing F concentration or decreasing pH is related to the resistance of the inner compact layer. The presence of fluoride and low pH of the saliva enhance the porosity of the oxide film and its dissolution.

Artificial Pinning Center Studies in BI2212 Tapes and Bulks With Zirconium Oxide Inclusion

Zirconium oxide inclusion in Bi2212 superconducting tapes and bulks was studied as possible artificial pinning centers (APC). In order to analyze the zirconium oxide APC addition in Bi2212 samples, magnetization measurements were performed in bulks and transport properties measurements were performed on tapes. In magnetization measurements, the critical current densities are proportional to the width of the magnetization loop at each applied magnetic field. Addition of ZrO(2) in Bi2212 superconductors broadened the magnetization loop and enhanced the critical current densities at 4.2 K in bulks, as a clear indication that ZrO(2) addition improved the pinning and acted as APCs. In contrast, the transport critical current densities decreased in tapes.

Artificial neural networks analysis of Sao Paulo subway tunnel settlement data

Artificial neural networks have been used to analyze a number of engineering problems, including settlement caused by different tunneling methods in various types of ground mass. This paper focuses on settlement over shotcrete- supported tunnels on Sao Paulo subway line 2 (West Extension) that were excavated in Tertiary sediments using the sequential excavation method. The adjusted network is a good tool for predicting settlement above new tunnels to be excavated in similar conditions. The influence of network training parameters on the quality of results is also discussed. (C) 2007 Elsevier Ltd. All rights reserved.

Failure Mechanisms in Sand over a Deep Active Trapdoor

An experimental testing program was undertaken to investigate failure mechanisms induced by the active movement of a deep rectangular trapdoor underlying a granular soil. Reduced-scale models were tested under normal gravity as well as under an increased gravitational field using a centrifuge facility. Some models were used to evaluate the performance of both flexible and rigid pipes undergoing a localized loss of support. Failure mechanisms in the longitudinal direction of the models were characterized by a single, well-defined failure surface that developed within the limits of the trapdoor. However, failure mechanisms in the transverse direction of the models were characterized by multiple failure surfaces extending outside the limits of the trapdoor. Significant dilation of the soil located immediately above the trapdoor was identified in the failure of the models. The pattern of the failure mechanisms was found to be affected by the stress level and backfill density. Higher stress levels were found to lead to well-developed failure zones. The influence of backfill density was found to be more relevant in models involving flexible pipes. Pipes embedded within loose backfill were severely damaged after loss of support, while pipes embedded in dense backfill experienced negligible deformations. These results indicate that damage to pipelines caused by ground loss of support can be significantly minimized by controlling the compaction of the fill.

Study of the water retention properties of a tropical soil

Some peculiarities of water retention in a tropical lateritic soil of clayey nature are presented and discussed. The typical soil microstructure is shown through thin-layer plates emphasizing soil microaggregation and pore distribution and their repercussion on the soil-water retention curve and on hysteresis. It is shown that the clayey soil has a behavior that to a large extent resembles sandy soil, which is characterized by the relatively high saturated hydraulic conductivity, low air-entry value, and small suction range at which water drainage takes place. The severe weathering processes that originated this soil have produced an altered soil that seems to be homogeneous in terms of physical indices, hydraulic conductivity, and soil-water retention characteristics, up to 4.5 m in depth.

Influence of the microstructure in the collapse of a residual clayey tropical soil

A typical residual clayey soil originating from basalt in southern Brazil has been analyzed in order to assess the influence of wetting-induced deformation and microstructural features on the collapse behavior. Single and double oedometer tests were undertaken on a soil profile to 9 m depth. The results indicated collapsible behaviour at all profile depths. The influence of pre-consolidation stress and pedogenetic factors in the variability of the physical characteristics of the soil and in the magnitude of the collapse was noted. The collapse coefficient has been shown to be related to the both the microaggregate plasma and the varying nature of the pores and their interconnectivity.

Collapse behavior of soil in a Brazilian region affected by a rising water table

Collapsible soils are usually nonsaturated, low density, and metastable-structured soils that are known to exhibit a volume reduction following an episode of moisture increase or suction reduction. This paper describes the collapsible behavior of clayey sand based on controlled soil suction tests carried out on undisturbed samples from the city of Pereira Barreto, in the State of Sao Paulo, Brazil. Foundation settlements due to soil collapse are common in this region and occurred during the filling of the reservoir of the Tres Irmaos Dam, which induced the elevation of the groundwater table in different parts of Pereira Barreto. This paper shows that collapse strains depend on the stress and soil suction acting in the sample and that saturation is not necessary for a collapse to occur. The influence of soil suction, gradual wetting, and the wetting and drying cycle on the collapsible behavior of the soil is also shown and discussed.

Transmission lines distance protection using artificial neural networks

This work presents the development and implementation of an artificial neural network based algorithm for transmission lines distance protection. This algorithm was developed to be used in any transmission line regardless of its configuration or voltage level. The described ANN-based algorithm does not need any topology adaptation or ANN parameters adjustment when applied to different electrical systems. This feature makes this solution unique since all ANN-based solutions presented until now were developed for particular transmission lines, which means that those solutions cannot be implemented in commercial relays. (c) 2011 Elsevier Ltd. All rights reserved.

Inertia in two simple problems of soil hydrodynamics

In the present paper the dynamic solutions of two non-steady seepage problems are discussed. It is shown that the acceleration term in the equation of motion is important for a correct qualitative description of the flow.

Comparison between detailed model simulation and artificial neural network for forecasting building energy consumption

There are several ways to attempt to model a building and its heat gains from external sources as well as internal ones in order to evaluate a proper operation, audit retrofit actions, and forecast energy consumption. Different techniques, varying from simple regression to models that are based on physical principles, can be used for simulation. A frequent hypothesis for all these models is that the input variables should be based on realistic data when they are available, otherwise the evaluation of energy consumption might be highly under or over estimated. In this paper, a comparison is made between a simple model based on artificial neural network (ANN) and a model that is based on physical principles (EnergyPlus) as an auditing and predicting tool in order to forecast building energy consumption. The Administration Building of the University of Sao Paulo is used as a case study. The building energy consumption profiles are collected as well as the campus meteorological data. Results show that both models are suitable for energy consumption forecast. Additionally, a parametric analysis is carried out for the considered building on EnergyPlus in order to evaluate the influence of several parameters such as the building profile occupation and weather data on such forecasting. (C) 2008 Elsevier B.V. All rights reserved.