Compositional analysis for an unbiased measure of soil aggregation

Soil aggregation is an index of soil structure measured by mean weight diameter (MWD) or scaling factors often interpreted as fragmentation fractal dimensions (D-f). However, the MWD provides a biased estimate of soil aggregation due to spurious correlations among aggregate-size fractions and scale-dependency. The scale-invariant D-f is based on weak assumptions to allow particle counts and sensitive to the selection of the fractal domain, and may frequently exceed a value of 3, implying that D-f is a biased estimate of aggregation. Aggregation indices based on mass may be computed without bias using compositional analysis techniques. Our objective was to elaborate compositional indices of soil aggregation and to compare them to MWD and D-f using a published dataset describing the effect of 7 cropping systems on aggregation. Six aggregate-size fractions were arranged into a sequence of D-1 balances of building blocks that portray the process of soil aggregation. Isometric log-ratios (ilrs) are scale-invariant and orthogonal log contrasts or balances that possess the Euclidean geometry necessary to compute a distance between any two aggregation states, known as the Aitchison distance (A(x,y)). Close correlations (r>0.98) were observed between MWD, D-f, and the ilr when contrasting large and small aggregate sizes. Several unbiased embedded ilrs can characterize the heterogeneous nature of soil aggregates and be related to soil properties or functions. Soil bulk density and penetrater resistance were closely related to A(x,y) with reference to bare fallow. The A(x,y) is easy to implement as unbiased index of soil aggregation using standard sieving methods and may allow comparisons between studies. (C) 2012 Elsevier B.V. All rights reserved.

Citrus and coffee strains of Xylella fastidiosa induce Pierce's disease in grapevine

Xylella fastidiosa causes citrus variegated chlorosis (CVC) disease in Brazil and Pierce's disease of grapevines in the United States. Both of these diseases cause significant production problems in the respective industries. The recent establishment of the glassy-winged sharpshooter in California has radically increased the threat posed by Pierces disease to California viticulture. Populations of this insect reach very high levels in citrus groves in California and move from the orchards into the vineyards, where they acquire inoculum and spread Pierce's disease in the vineyards. Here we show that strains of X. fastidiosa isolated from diseased citrus and coffee in Brazil can incite symptoms of Pierce's disease after mechanical inoculation into seven commercial Vitis vinifera varieties grown in Brazil and California. Thus, any future introduction of the CVC strains of X. fastidiosa into the United States would pose a threat to both the sweet orange and grapevine industries. Previous work has clearly shown that the strains of X. fastidiosa isolated from Pierce's disease- and CVC-affected plants are the most distantly related of all strains in the diverse taxon X. fastidiosa. The ability of citrus strains of X. fastidiosa to incite disease in grapevine is therefore surprising and creates an experimental system with which to dissect mechanisms used by X.,fastidiosa in plant colonization and disease development using the full genome sequence data that has recently become available for both the citrus and grapevine strains of this pathogen.

Peak Separation by Derivative Spectroscopy Applied to FTIR Analysis of Hydrolized Silica

Reliable spectral analysis is only achieved if the spectrum is thoroughly investigated in regard to all hidden and overlapped peaks. This paper describes the steps undertaken to find and separate such peaks in the range of 3000 to 4000 cm(-1) in the case of three different infrared absorption spectra of the glass surface of hydrolyzed silica optical fibers. Peak finding was done by the analysis of the second and fourth derivatives of the digital data, coupled with the available knowledge of infrared spectroscopy of silica-water interaction in the investigated range. Peak separation was accomplished by curve fitting with four different models. The model with the best fit was described by a sum of pure Gaussian peaks. Shoulder limit and detection limit maps were used to validate the revealed spectral features.

Biometric relationship analysis of the wet weight by carapace width to the swimming crab Arenaeus-cribrarius (Lamarck, 1818) (Crustacea, Brachyura, Portunidae)

The biometric relationship between the weigth and the carapace width in the swimming crab A. cribrarius was compared with the results from other portunid crabs studied previously. During November/1988 to October/1989, a total of 403 specimens (189 males and 214 females) were collected with otter-trawl nets in north coast of the São Paulo State, Brazil. The animals were measured (carapace width excluding lateral spines = LC! and weighed (wet weight = PE). The empiric points of this relation were fit according to the power function (Y = a.X(b)) for each sex, maturation phases and total of individuals. The relation PE x LC indicates that the mole's growth changes during the ontogenesys from isometric (in juvenile phase) to allometric positive (in adult phase). For the females the growth is isometric in the two phases. The weight grows in a higher proportion than the carapace width variable (allometric positive growth). The data can be grouped in a single equation (PE = 7.85.10(-5).LC(3.14)) for the convertion between the variables there was a greater similarity between the equations obtained far each sex. In spite of this, the males present the fattening grade value (''a'') slightly higher than that of the females, possibly because of the greater size reached in its devellopment. The mean weight of the males is greater than the females one (p < 0.01). In the range 80 proves 90mm the males were more abundant, probably due to the females terminal ecdysis is near this size. The females only have the mean weight greater than the males in the 60 proves 70mm range (p < 0.01) when the puberty molt occurs and they present morphological changes in their reproductive system.

Applying spatial analysis of genetic and environmental data to predict connection corridors to the New World screwworm populations in South America

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

pH-cycling Model to Verify the Efficacy of Fluoride-releasing Materials in Enamel Demineralization

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Late morfofunctional alterations of the Sertoli cell caused by doxorubicin administered to prepubertal rats

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Statistical methods applied to the analysis of blasting vibrations in a diabase quarry in the city of Campinas, (SP) Brazil

Statistical methods of multiple regression analysis, trend surface analysis and principal components analysis were applied to seismographic data recorded during production blasting at a diabase quarry in the urban area of Campinas (SP), Brazil. The purpose of these analyses was to determine the influence of the following variables: distance (D), charge weight per delay (W), and scaled distance (SD) associated with properties of the rock body (orientation, frequency and angle of geological discontinuities; depth of bedrock and thickness of the soil overburden) in the variation of the peak particle velocity (PPV). This approach yielded variables with larger influences (loads) on the variation of ground vibration, as well as behavior and space tendency of this variation. The results showed a better relationship between PPV and D, with D being the most important factor in the attenuation of the ground vibrations. The geological joints and the depth to bedrock have a larger influence than the explosive charges in the variation of the vibration levels, but frequencies appear to be more influenced by the amount of soil overburden.

An intelligent system to detect drilling problems through drilled cuttings return analysis

Cuttings return analysis is an important tool to detect and prevent problems during the petroleum well drilling process. Several measurements and tools have been developed for drilling problems detection, including mud logging, PWD and downhole torque information. Cuttings flow meters were developed in the past to provide information regarding cuttings return at the shale shakers. Their use, however, significantly impact the operation including rig space issues, interferences in geological analysis besides, additional personel required. This article proposes a non intrusive system to analyze the cuttings concentration at the shale shakers, which can indicate problems during drilling process, such as landslide, the collapse of the well borehole walls. Cuttings images are acquired by a high definition camera installed above the shakers and sent to a computer coupled with a data analysis system which aims the quantification and closure of a cuttings material balance in the well surface system domain. No additional people at the rigsite are required to operate the system. Modern Artificial intelligence techniques are used for pattern recognition and data analysis. Techniques include the Optimum-Path Forest (OPF), Artificial Neural Network using Multilayer Perceptrons (ANN-MLP), Support Vector Machines (SVM) and a Bayesian Classifier (BC). Field test results conducted on offshore floating vessels are presented. Results show the robustness of the proposed system, which can be also integrated with other data to improve the efficiency of drilling problems detection. Copyright 2010, IADC/SPE Drilling Conference and Exhibition.

Investigations on the full polarimetric PALSAR data to discriminate macrophytes species in the Amazon floodplain wetland

The purpose of this work is to evaluate the capacity of full polarimetric L band data to discriminate macrophyte species in Amazon wetland. Fieldwork was carried out almost simultaneously to the acquisition of the full polarimetric PALSAR data. Coherent and incoherent attributes were extracted from the image, and macrophyte morphological variables were measured on the ground. The image attributes and the macrophyte variables were compared in order to evaluate their application for discriminating macrophytes species. The findings suggest that polarimetric information could be adopted to discriminate plant species based on morphology, and that estimation of plant biomass and productivity could be improved by using the polarimetric information. © 2010 IEEE.

Artificial Immune Systems Applied to the Analysis of Structural Integrity of a Building

This paper presents the application of artificial immune systems for analysis of the structural integrity of a building. Inspired by a biological process, it uses the negative selection algorithm to perform the identification and characterization of structural failure. This paper presents the application of artificial immune systems for analysis of the structural integrity of a building. Inspired by a biological process, it uses the negative selection algorithm to perform the identification and characterization of structural failure. This methodology can assist professionals in the inspection of mechanical and civil structures, to identify and characterize flaws, in order to perform preventative maintenance to ensure the integrity of the structure and decision-making. In order to evaluate the methodology was made modeling a two-story building and several situations were simulated (base-line condition and improper conditions), yielding a database of signs, which were used as input data for the negative selection algorithm. The results obtained by the present method efficiency, robustness and accuracy.

Evaluation of measurement errors of temperature and relative humidity from HOBO data logger under different conditions of exposure to solar radiation

This study aimed to assess measurements of temperature and relative humidity obtained with HOBO a data logger, under various conditions of exposure to solar radiation, comparing them with those obtained through the use of a temperature/relative humidity probe and a copper-constantan thermocouple psychrometer, which are considered the standards for obtaining such measurements. Data were collected over a 6-day period (from 25 March to 1 April, 2010), during which the equipment was monitored continuously and simultaneously. We employed the following combinations of equipment and conditions: a HOBO data logger in full sunlight; a HOBO data logger shielded within a white plastic cup with windows for air circulation; a HOBO data logger shielded within a gill-type shelter (multi-plate prototype plastic); a copper-constantan thermocouple psychrometer exposed to natural ventilation and protected from sunlight; and a temperature/relative humidity probe under a commercial, multi-plate radiation shield. Comparisons between the measurements obtained with the various devices were made on the basis of statistical indicators: linear regression, with coefficient of determination; index of agreement; maximum absolute error; and mean absolute error. The prototype multi-plate shelter (gill-type) used in order to protect the HOBO data logger was found to provide the best protection against the effects of solar radiation on measurements of temperature and relative humidity. The precision and accuracy of a device that measures temperature and relative humidity depend on an efficient shelter that minimizes the interference caused by solar radiation, thereby avoiding erroneous analysis of the data obtained.

The application of neural networks to the analysis of dissolved gases in insulating oil used in transformers

The state of insulating oils used in transformers is determined through the accomplishment of physical-chemical tests, which determine the state of the oil, as well as the chromatography test, which determines possible faults in the equipment. This article concentrate on determining, from a new methodology, a relationship among the variation of the indices obtained from the physical-chemical tests with those indices supplied by the chromatography tests.The determination of the relationship among the tests is accomplished through the application of neural networks. From the data obtained by physical-chemical tests, the network is capable to determine the relationship among the concentration of the main gases present in a certain sample, which were detected by the chromatography tests.More specifically, the proposed approach uses neural networks of perceptron type constituted of multiple layers. After the process of network training, it is possible to determine the existent relationship between the physical-chemical tests and the amount of gases present in the insulating oil.

Comparison of Polar(®) RS800G3(™) heart rate monitor with Polar(®) S810i(™) and electrocardiogram to obtain the series of RR intervals and analysis of heart rate variability at rest

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)