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.

Impedance e-tongue instrument for rapid liquid assessment

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

Estimation using 18O of the water residence time in small watersheds

From the 18O hydrograph separation method, it was found that groundwater contribution is the principal component of the total discharge produced by these two catchment areas. The weighted mean of the 18O concentration in the precipitation, obtained for a four year period, was close to -6.0‰, with a variation in range of +2.3‰ to -16.3‰. For Bufalos stream water the weighted mean of 18O values during the same period (1984-1987) was -6.3‰, with a variation from -2.5‰ to -10.1‰, whereas for Paraiso this mean was -6.4‰, with extreme values of -3.1‰ and -9.8‰. From these values it was found that the amplitude damping (Ariver/Aprecipitation) was 0.41 for the Bufalos watershed and 0.36 for Paraiso. Using the appropriate equation to estimate the mean residence time of water in the subsurface reservoir of the Bufalos and Paraiso watersheds, the results of 4.3 and 5.0 months, respectively, were obtained. -from Authors

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.

Comparative studies of the sample decomposition of green and roasted coffee for determination of nutrients and data exploratory analysis

The contents of some nutrients in 35 Brazilian green and roasted coffee samples were determined by flame atomic absorption spectrometry (Ca, Mg, Fe, Cu, Mn, and Zn), flame atomic emission photometry (Na and K) and Kjeldahl (N) after preparing the samples by wet digestion procedures using i) a digester heating block and ii) a conventional microwave oven system with pressure and temperature control. The accuracy of the procedures was checked using three standard reference materials (National Institute of Standards and Technology, SRM 1573a Tomato Leaves, SRM 1547 Peach Leaves, SRM 1570a Trace Elements in Spinach). Analysis of data after application of t-test showed that results obtained by microwave-assisted digestion were more accurate than those obtained by block digester at 95% confidence level. Additionally to better accuracy, other favorable characteristics found were lower analytical blanks, lower reagent consumption, and shorter digestion time. Exploratory analysis of results using Principal Component Analysis (PCA) and Hierarchical Cluster Analysis (HCA) showed that Na, K, Ca, Cu, Mg, and Fe were the principal elements to discriminate between green and roasted coffee samples. ©2007 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.

Nest defense behavior against the attack of ants in colonies of pre-emergent Mischocyttarus cerberus (hymenoptera, vespidae)

The study was carried out at the UNESP Rio Claro campus (SP), where biotests consisting of simulated ant attacks were performed in colonies of Mischocyttarus cerberus. The behaviors of the wasps were recorded with a camcorder, for further analysis. This analysis was done using the Mann-Whitney U test and the Principal Component Analysis. In the pre-emergence development stage, colonies with a single foundress defend the nest only after the first larvae appear. When there are only eggs in the nest, the wasp abandons the nest. Before leaving, the wasp rubs its gaster against the nest, releasing the ant repellent secretion. When the nest contains larvae or larvae and pupae, the foundress defends the colony, vibrating its wings, pumping her abdomen and biting the ant.

Uso de indicadores hidrológicos para classificação de trechos de estradas florestais quanto ao escoamento superficial

Forest roads are frequently pointed as source of environmental problems related to erosion and they also influence harvest cost due to maintenance operations. Roads not well designed are sources of hydrological problems on catchments and the current attention to sustainability of forest exploration projects point out to the need of diagnostics tools for guiding the redesign of the road system. At this study, runoff hydrological indicators for forest road segments were assessed in order to identify critical points of erosion and water concentration on soils. A road network of a forest production area was divided into 252 road segments that were used as observations of four variables: mean terrain slope, main segment slope, LS factor and topographic index. The data analysis was based on descriptive statistics for outliers' identification, principal component analysis and for variability study between variables and between observations, and cluster analysis for similar segments groups' identification. The results allowed classifying roads segments into five mains road types: road on the ridge, on the valley, on the slopes, on the slopes but in a contour line and on the steepest slope. The indicators were able to highlight the most critical segments that differ of others and are potential sources of erosion and water accumulation problems on forest roads. The principal component analysis showed two main variability sources related to terrain topographic characteristics and also road design, showing that indicators represent well those elements. The methodology seems to be appropriated for identification of critical road segments that need to be redesigned and also for road network planning at new forest exploration projects.