Sequential extraction of phosphorus in an Oxisol amended with biosolids in a long-term field experiment in Brazil

The continued growth of large cities is producing increasing volumes of urban sewage sludge. Disposing of this waste without damaging the environment requires careful management. The application of large quantities of biosolids (treated sewage sludge) to agricultural lands for many years may result in the excessive accumulation of nutrients like phosphorus (P) and thereby raise risks of eutrophication in nearby water bodies. We evaluated the fractionation of P in samples of an Oxisol collected as part of a field experiment in which biosolids were added at three rates to a maize (Zea mays L) plantation over four consecutive years. The biosolids treatments were equivalent to one, two and four times the recommended N rate for maize crops. In a fourth treatment, mineral fertilizer was applied at the rate recommended for maize. Inorganic P forms were extracted with ammonium chloride to remove soluble and loosely bound P; P bound to aluminum oxide (P-Al) was extracted with ammonium fluoride; P bound to iron oxide (P-Fe) was extracted with sodium hydroxide; and P bound to calcium (P-Ca) was extracted with sulfuric acid. Organic P was calculated as the difference between total P and inorganic P. The predominant fraction of P was P-Fe, followed by P-Al and P-Ca. P fractions were positively correlated to the amounts of P applied, except for P-Ca. The low values of P-Ca were due to the advanced weathering processes to which the Oxisol have been subjected, under which forms of P-Ca are converted to P-Fe and P-Al. The fertilization with P via biosolids increased P availability for maize plants even when a large portion of P was converted to more stable forms. Phosphorus content in maize leaves and grains was positively correlated with P fractions in soils. From these results it can be concluded that the application of biosolids in highly weathered tropical clayey soils for many years, even above the recommended rate based on N requirements for maize, tend to be less potentially hazardous to the environment than in less weathered sandy soils because the non-readily P fractions are predominant after the addition of biosolids. (C) 2012 Elsevier B.V. All rights reserved.

Bioprocess and biotecnology: effect of xylanase from Aspergillus niger and Aspergillus flavus on pulp biobleaching and enzyme production using agroindustrial residues as substract

This study compares two xylanases produced by filamentous fungi such as A. niger and A. flavus using agroindustrial residues as substract and evaluated the effect of these enzymes on cellulose pulp biobleaching process. Wheat bran was the best carbon source for xylanase production by A. niger and A. flavus. The production of xylanase was 18 and 21% higher on wheat bran when we compare the xylanase production with xylan. At 50°C, the xylanase of A. niger retained over 85% activity with 2 h of incubation, and A. flavus had a half-life of more than 75 minutes. At 55°C, the xylanase produced by A. niger showed more stable than from A. flavus showing a half-life of more than 45 minutes. The xylanase activity of A. niger and A. flavus were somehow protected in the presence of glycerol 5% when compared to the control (without additives). On the biobleaching assay it was observed that the xylanase from A. flavus was more effective in comparison to A. niger. The kappa efficiency corresponded to 36.32 and 25.93, respectively. That is important to emphasize that the cellulase activity was either analyzed and significant levels were not detected, which explain why the viscosity was not significantly modified.

Characterization of polysaccharides from Hypnea spinella (Gigartinales) and Halopithys incurva (Ceramiales) and their effect on RAW 264.7 macrophage activity

[EN] Red algae have been reported to be an important source of polysaccharides with potential immunomodulatory properties. The objective of this study was to characterize the polysaccharides from Halopithys incurva and Hypnea spinella and to evaluate their effect on the synthesis of cytokines by murine cell line RAW 264.7 macrophages. Polysaccharides were obtained by N-cetylpyridiniumbromide precipitation and characterized by Fourier transform-infrared spectroscopy. Their effect on the activity of RAW 264.7 macrophages was examined by quantification of tumor necrosis factor (TNF)-α, interleukin (IL)-6, and nitric oxide (NO) production using enzyme-linked immunosorbent assays. The activation of the cytokine IL-6 and NO increased linearly as the concentration of polysaccharides from H. incurva and Hy. spinella increased. In general, the activation of IL-6 and NO was tenfold greater when macrophages were exposed to polysaccharides from H. incurva than when exposed to polysaccharides from Hy. spinella. In contrast, TNF-α concentration did not increase when macrophages were exposed to increasing polysaccharide levels. These results indicate that polysaccharides are strong cytokine IL-6 inducers.

Frame-driven Extraction of Linked Data and Ontologies from Text

Ontology design and population -core aspects of semantic technologies- re- cently have become fields of great interest due to the increasing need of domain-specific knowledge bases that can boost the use of Semantic Web. For building such knowledge resources, the state of the art tools for ontology design require a lot of human work. Producing meaningful schemas and populating them with domain-specific data is in fact a very difficult and time-consuming task. Even more if the task consists in modelling knowledge at a web scale. The primary aim of this work is to investigate a novel and flexible method- ology for automatically learning ontology from textual data, lightening the human workload required for conceptualizing domain-specific knowledge and populating an extracted schema with real data, speeding up the whole ontology production process. Here computational linguistics plays a fundamental role, from automati- cally identifying facts from natural language and extracting frame of relations among recognized entities, to producing linked data with which extending existing knowledge bases or creating new ones. In the state of the art, automatic ontology learning systems are mainly based on plain-pipelined linguistics classifiers performing tasks such as Named Entity recognition, Entity resolution, Taxonomy and Relation extraction [11]. These approaches present some weaknesses, specially in capturing struc- tures through which the meaning of complex concepts is expressed [24]. Humans, in fact, tend to organize knowledge in well-defined patterns, which include participant entities and meaningful relations linking entities with each other. In literature, these structures have been called Semantic Frames by Fill- 6 Introduction more [20], or more recently as Knowledge Patterns [23]. Some NLP studies has recently shown the possibility of performing more accurate deep parsing with the ability of logically understanding the structure of discourse [7]. In this work, some of these technologies have been investigated and em- ployed to produce accurate ontology schemas. The long-term goal is to collect large amounts of semantically structured information from the web of crowds, through an automated process, in order to identify and investigate the cognitive patterns used by human to organize their knowledge.

Automatic extraction of femur contours from calibrated fluoroscopic images

Automatic identification and extraction of bone contours from X-ray images is an essential first step task for further medical image analysis. In this paper we propose a 3D statistical model based framework for the proximal femur contour extraction from calibrated X-ray images. The automatic initialization is solved by an estimation of Bayesian network algorithm to fit a multiple component geometrical model to the X-ray data. The contour extraction is accomplished by a non-rigid 2D/3D registration between a 3D statistical model and the X-ray images, in which bone contours are extracted by a graphical model based Bayesian inference. Preliminary experiments on clinical data sets verified its validity

Screening, optimization and extraction of polyhydroxyalkanoates and peptidoglycan from Bacillus megaterium

Bioplastics are polymers (such as polyesters) produced from bacterial fermentations that are biodegradable and nonhazardous. They are produced by a wide variety of bacteria and are made only when stress conditions allow, such as when nutrient levels are low, more specifically levels of nitrogen and oxygen. These stress conditions cause certain bacteria to build up excess carbon deposits as energy reserves in the form of polyhydroxyalkanoates (PHAs). PHAs can be extracted and formed into actual plastic with the same strength of conventional, synthetic-based plastics without the need to rely on foreign petroleum. The overall goal of this project was to select for a bacteria that could grow on sugars found in the lignocellulosic biomass, and get the bacteria to produce PHAs and peptidoglycan. Once this was accomplished the goal was to extract PHAs and peptidoglycan in order to make a stronger more rigid plastic, by combing them into a co-polymer. The individual goals of this project were to: (1) Select and screen bacteria that are capable of producing PHAs by utilizing the carbon/energy sources found in lignocellulosic biomass; (2) Maximize the utilization of those sugars present in woody biomass in order to produce optimal levels of PHAs. (3) Use room temperature ionic liquids (RTILs) in order to separate the cell membrane and peptidoglycan, allowing for better extraction of PHAs and more intact peptidoglycan. B. megaterium a Gram-positive PHA-producing bacterium was selected for study in this project. It was grown on a variety of different substrates in order to maximize both its growth and production of PHAs. The optimal conditions were found to be 30°C, pH 6.0 and sugar concentration of either 30g/L glucose or xylose. After optimal growth was obtained, both RTILs and enzymatic treatments were used to break the cell wall, in order to extract the PHAs, and peptidoglycan. PHAs and peptidoglycan were successfully extracted from the cell, and will be used in the future to create a new stronger co-polymer. Peptidoglycan recovery yield was 16% of the cells’ dry weight.

The Extraction of Chromate Salts from Montana Chromite

In this thesis I have tried to determine the suit­able temperature, time and the amount of soda ash and lime needed for the calcining process. The leaching and purification tests were studied experimentally. The earlier process for making chromate from chromite was not the same as is used today. There­fore I have found it useful to put into this thesis the newest method for making chromate salts and their important uses.

EXTRACTION OF PICTORIAL ENERGY INFORMATION FROM CAMPUS UNMETERED BUILDINGS USING IMAGE PROCESSING TECHNIQUES

In recent years, advanced metering infrastructure (AMI) has been the main research focus due to the traditional power grid has been restricted to meet development requirements. There has been an ongoing effort to increase the number of AMI devices that provide real-time data readings to improve system observability. Deployed AMI across distribution secondary networks provides load and consumption information for individual households which can improve grid management. Significant upgrade costs associated with retrofitting existing meters with network-capable sensing can be made more economical by using image processing methods to extract usage information from images of the existing meters. This thesis presents a new solution that uses online data exchange of power consumption information to a cloud server without modifying the existing electromechanical analog meters. In this framework, application of a systematic approach to extract energy data from images replaces the manual reading process. One case study illustrates the digital imaging approach is compared to the averages determined by visual readings over a one-month period.