WATER BALANCE and SPATIAL DISTRIBUTION of AN ANURAN COMMUNITY FROM BRAZIL

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Wet deposition of major ions in a rural area impacted by biomass burning emissions

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

Influence of Intensive Agriculture on Dry Deposition of Aerosol Nutrients

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Correlation of properties of Brazilian Haplustalfs with magnetic susceptibility measurements

Magnetic susceptibility (chi, mass specific) is useful for easy indirect estimation of other soil properties at a low cost. The aim of this study was to assess the use of chi as measured with an analytical balance for predicting properties with a substantial influence on the management of Typic Haplustalfs in southern Brazil. To achieve this 48 topsoil samples were taken at the intersection points in a rectangular grid of 20 m x 20 m cells, with 38 of these used for calibration and 10 for validation in regression analyses. The obtained chi values were slightly higher than, and highly correlated (r = 0.970; P < 0.001) with those measured with a susceptibility meter. Highly significant (P < 0.001) correlations were also found between chi and other soil properties relevant to soil classification and management such as clay content (r = 0.68), cation exchange capacity (r = 0.62), P sorption capacity (r = 0.76) and haematite content (r = 0.82). Results from a principal component analysis of eight properties important for soil classification explained 11% of the variance in the data set. The good predictive ability of chi was consistent with current knowledge on the formation pathways for pedogenic ferrimagnets. In summary, chi, which can be readily measured with an analytical balance, has the potential for quantifying soil attributes and may therefore be used in pedotransfer functions.

Probabilistic neural network to predict cracks in taphole mud used in blast furnaces

One of the major problems facing Blast Furnaces is the occurrence of cracks in taphole mud, as the underlying causes are not easily identifiable. The absence of this knowledge makes it difficult the use of conventional techniques for predictability and mitigation. This paper will address the application of Probabilistic Neural Network using the Matlab software as a means to detect and control such cracks. The most relevant BF operational variables were picked through the statistic tool "Principal Component Analysis - PCA." Based upon the selection of these variables a probabilistic neural network was built. A set of BF operational data, consisting of 30 controlling variables, was divided into 2 groups, one of which for network training, and the other one to validate the neural network. The neural network got 98% of the cases right. The results show the effectiveness of this tool for crack prediction in relation to clay intrinsic properties and as a result of the fluctuation in operational variables.

Water quality monitoring by nanostructured films in a sensing unit system

Presented here is a study about the capability of a sensing unit to detect changes in river water quality. In order to determine its accuracy, water quality was monitored at 11 points along the Veado River in Presidente Prudente, Brazil. To have a basis for comparison, a water quality index (WQI) was developed following methods previously applied in different watersheds. Results showed an accurate relationship between WQI and electric impedance readings detected by the sensing unit. Principal components analysis (PCA) was used to derive results in a form that can be correlated with WQI calculated for each sample point, which showed the potential application of this device.

Impedance e-tongue instrument for rapid liquid assessment

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

Bayesian and multivariate methods applied to favorability quantification in recôncavo Basin and Ribeira Belt, Brazil

A methodology to define favorable areas in petroleum and mineral exploration is applied, which consists in weighting the exploratory variables, in order to characterize their importance as exploration guides. The exploration data are spatially integrated in the selected area to establish the association between variables and deposits, and the relationships among distribution, topology, and indicator pattern of all variables. Two methods of statistical analysis were compared. The first one is the Weights of Evidence Modeling, a conditional probability approach (Agterberg, 1989a), and the second one is the Principal Components Analysis (Pan, 1993). In the conditional method, the favorability estimation is based on the probability of deposit and variable joint occurrence, with the weights being defined as natural logarithms of likelihood ratios. In the multivariate analysis, the cells which contain deposits are selected as control cells and the weights are determined by eigendecomposition, being represented by the coefficients of the eigenvector related to the system's largest eigenvalue. The two techniques of weighting and complementary procedures were tested on two case studies: 1. Recôncavo Basin, Northeast Brazil (for Petroleum) and 2. Itaiacoca Formation of Ribeira Belt, Southeast Brazil (for Pb-Zn Mississippi Valley Type deposits). The applied methodology proved to be easy to use and of great assistance to predict the favorability in large areas, particularly in the initial phase of exploration programs. © 1998 International Association for Mathematical Geology.

Anatomical and biochemical characterization of the calcium effect on eucalyptus urophylla callus morphogenesis in vitro

Calcium chloride concentrations from 0.0 to 12.12 mM were added to the culture medium and calcium content in calluses were determined directly by X-ray fluorescence spectrometry, a non-destructive method, allowing the processing of the same tissue for histological analysis. A multivariate statistical analysis (PCA - Principal Components Analysis) grouped the treatments into 5 blocks and indicated the most responsive group. Lack of calcium supply caused a complete absence of a morphogenic process and tissue collapse. An increase in calcium concentration gave higher total protein and sugar contents, an increase in peroxidase specific activity and changes in the histological characteristics. It was possible to verify that calcium stimulated globular somatic embryo formation at concentration of 6.62 mM.

Caracterização das fases de desenvolvimento de células gigantes induzidas por Meloidogyne exigua em raiz de seringueira (Hevea brasiliensis Muell. Arg.)

The developmental phases of giant cells induced by root-knot nematodes (Meloidogyne exigua) in rubber plant (Hevea brasiliensis) root were studied in relation to its number and size evaluated in eight sample dates. The results were subject to cluster analysis and principal component analysis. Sample dates were clearly distinct regarding giant cell development. As a result, the nematode infestation cycle was characterized by the following sequential phases: initial, equilibrium, choice and final.

Relationship between Constrictotermes cyphergaster and Inquiline Termites in the Cerrado (Isoptera: Termitidae)

Constrictotermes cyphergaster builds arboreal nests in Cerrado sensu stricto of Brazil; inquiline termites and termitophiles frequently inhabit their nests. Measurements of the nests and the support trees (nest width and diameter; tree trunk circumference and inclination), colony size of C. cyphergaster and of Inquilinitermes and number of termitophiles were studied at the Parque Estadual da Serra de Caldas Novas. These variables were subjected to a Principal Component Analysis, producing four principal components. The first principal component refers to a multidimensional axis of nest size, encompassing variables related to nest and colony size, such as abundance per caste of C. cyphergaster and I. microcerus, number of termitophile species and the measurements of the nest. The number of soldiers and workers of C. cyphergaster and soldiers of Inquilinitermes increased proportionally to the axis of nest size, while the number of Inquilinitermes workers increased more quickly then the increase in the nest size. Both Inquilinitermes occurred mainly in larger nests. Almost half of the nests (47,5%) were inhabited by I. microcerus and 10% by I. fur.

Nanostructured films of perylene derivatives: High performance materials for taste sensor applications

Four perylene derivatives (PTCD) have been used as transducing materials in taste sensors fabricated with nanostructured Langmuir-Blodgett (LB) films deposited onto interdigitated gold electrodes. The Langmuir monolayers of PTCDs display considerable collapse pressures, with areas per molecule indicative of an edge-on or head-on arrangement for the molecules at the air/water interface. The sensing units for the electronic tongue were produced from 5-layer LB films of the four PTCDs, whose electrical response was characterized with impedance spectroscopy. The distinct responses of the PTCDs, attributed to differences in their molecular structures, allowed one to obtain a finger printing system that was able to distinguish tastes (salty, sweet, bitter and sour) at 1 μM concentrations, which, in some cases, are three orders of magnitude below the human threshold. Using Principal Component Analysis (PCA) data analysis, the electronic tongue also detected trace amounts of a pesticide and could distinguish among samples of ultrapure, distilled and tap water, and two brands of mineral water. © 2004 by American Scientific Publishers. All rights reserved.

Studies on the interaction between humic substances and conducting polymers for sensor application

The interaction between humic substances and poly(o-ethoxyaniline) (POEA), a conducting polymer, was investigated for both solution and self-assembled films. The results have shown that the humic substances induce a doping of POEA by protonation, as indicated by UV-Vis and Raman spectroscopies. The atomic force microscopy (AFM) studies on the self-assembled films have shown that the average roughness of the polymer film has increased after exposing it to humic substances (fulvic and humic acids), consistent with the interaction between POEA and humic substances. However, this change in morphology is reversible by washing the films with water in agreement with the electrical data allowing using this system in sensor applications. Here, the sensor formed by an array of different sensing units was able to detect and distinguish humic substances in aqueous solution, as shown by multivariate analysis (principal component analysis). The motivation to detect humic substance comes due to its importance in terms of quality control of water or soil. ©2005 Sociedade Brasileira de Química.

Damage detection in a benchmark structure using AR-ARX models and statistical pattern recognition

Structural health monitoring (SHM) is related to the ability of monitoring the state and deciding the level of damage or deterioration within aerospace, civil and mechanical systems. In this sense, this paper deals with the application of a two-step auto-regressive and auto-regressive with exogenous inputs (AR-ARX) model for linear prediction of damage diagnosis in structural systems. This damage detection algorithm is based on the. monitoring of residual error as damage-sensitive indexes, obtained through vibration response measurements. In complex structures there are. many positions under observation and a large amount of data to be handed, making difficult the visualization of the signals. This paper also investigates data compression by using principal component analysis. In order to establish a threshold value, a fuzzy c-means clustering is taken to quantify the damage-sensitive index in an unsupervised learning mode. Tests are made in a benchmark problem, as proposed by IASC-ASCE with different damage patterns. The diagnosis that was obtained showed high correlation with the actual integrity state of the structure. Copyright © 2007 by ABCM.