Substâncias húmicas: sistema de fracionamento sequencial por ultrafiltração com base no tamanho molecular

A sequential system for fractionation by ultrafiltration (SSFU) equipped with advanced membranes filters (molecular size cut-off: 5, 10, 30, 50 and 100 kDalton) of the polyethersulfone type was developed for analytical fractionation of humic substances (HS) extracted from aquatic systems or soils. The device consists of five membrane filters (Sartocon® Micro) operated by a multi-channel peristaltic pump, enabling an easy handling, working in a closed system and with simple collection of the six obtained fractions (F1>100; F2: 100-50; F3: 50-30; F4:30-10; F5: 10-5 and F6 <5 kDalton). Then, the HS sample (250 mL solution 1.0 mg/mL, pH 5.0 to 6.0) to be fractionated is pumped by pump through the series of membrane filters with a tangential flow of 85 mL/min, initial pressure 0.2 to 0.3 bar and permeation flux through the membranes of 0.8 to 1.4 mL/min. The overall time for fractionation and cleaning of the device is about 10 h and 25 mL of each fraction is obtained.

Inhibitory effects in the detection of 1 cpd jo targets superimposed to angular frequency stimuli or sinewave gratings

Independence among channels processing different aspects of spatial information, including orthogonal stimuli, has been generally assumed in the literature. We tested independence between the processing of jo targets and the processing of either vertical sinusoidal gratings or angular frequency stimuli with suprathreshold summation. We found the detection of a jo target at 1 cpd to be affected in an inhibitory fashion by either background angular frequencies in the range of 3-96 cycles or sinewave gratings in the range of 0.8-3.0 cpd. These results demonstrate interactions both among orthogonal stimuli and among channels processing vertical sinewave gratings and jo target stimuli. Our discussion focuses on the hypothesis of frequency decomposition in polar coordinates

Multi-temporal analysis of radiometric changes in satellite images of forest edges to infer selective-logging areas in the Amazon forest

Radiometric changes observed in multi-temporal optical satellite images have an important role in efforts to characterize selective-logging areas. The aim of this study was to analyze the multi-temporal behavior of spectral-mixture responses in satellite images in simulated selective-logging areas in the Amazon forest, considering red/near-infrared spectral relationships. Forest edges were used to infer the selective-logging infrastructure using differently oriented edges in the transition between forest and deforested areas in satellite images. TM/Landsat-5 images acquired at three dates with different solar-illumination geometries were used in this analysis. The method assumed that the radiometric responses between forest with selective-logging effects and forest edges in contact with recent clear-cuts are related. The spatial frequency attributes of red/near infrared bands for edge areas were analyzed. Analysis of dispersion diagrams showed two groups of pixels that represent selective-logging areas. The attributes for size and radiometric distance representing these two groups were related to solar-elevation angle. The results suggest that detection of timber exploitation areas is limited because of the complexity of the selective-logging radiometric response. Thus, the accuracy of detecting selective logging can be influenced by the solar-elevation angle at the time of image acquisition. We conclude that images with lower solar-elevation angles are less reliable for delineation of selecting logging.

Land cover classification of Lago Grande de Curuai floodplain (Amazon, Brazil) using multi-sensor and image fusion techniques

Given the limitations of different types of remote sensing images, automated land-cover classifications of the Amazon várzea may yield poor accuracy indexes. One way to improve accuracy is through the combination of images from different sensors, by either image fusion or multi-sensor classifications. Therefore, the objective of this study was to determine which classification method is more efficient in improving land cover classification accuracies for the Amazon várzea and similar wetland environments - (a) synthetically fused optical and SAR images or (b) multi-sensor classification of paired SAR and optical images. Land cover classifications based on images from a single sensor (Landsat TM or Radarsat-2) are compared with multi-sensor and image fusion classifications. Object-based image analyses (OBIA) and the J.48 data-mining algorithm were used for automated classification, and classification accuracies were assessed using the kappa index of agreement and the recently proposed allocation and quantity disagreement measures. Overall, optical-based classifications had better accuracy than SAR-based classifications. Once both datasets were combined using the multi-sensor approach, there was a 2% decrease in allocation disagreement, as the method was able to overcome part of the limitations present in both images. Accuracy decreased when image fusion methods were used, however. We therefore concluded that the multi-sensor classification method is more appropriate for classifying land cover in the Amazon várzea.

Síntese de cristais líquidos derivados do nitroazobenzeno: uma proposta de síntese multi-etapas aplicada às aulas de química orgânica experimental

We describe a synthetic route consisting of five steps from aniline to obtain liquid crystal compounds derived from nitroazobenzene. Syntheses were performed during the second half of the semester in organic chemistry laboratory classes. Students characterized the liquid crystal phase by the standard melting point techniques, differential scanning calorimetry and polarized optical microscopy. These experiments allow undergraduate students to explore fundamentally important reactions in Organic Chemistry, as well as modern concepts in Chemistry such as self-assembly and self-organization, nanostructured materials and molecular electronics.

LOW COST ANALYZER FOR THE DETERMINATION OF PHOSPHORUS BASED ON OPEN-SOURCE HARDWARE AND PULSED FLOWS

The need for automated analyzers for industrial and environmental samples has triggered the research for new and cost-effective strategies of automation and control of analytical systems. The widespread availability of open-source hardware together with novel analytical methods based on pulsed flows have opened the possibility of implementing standalone automated analytical systems at low cost. Among the areas that can benefit from this approach are the analysis of industrial products and effluents and environmental analysis. In this work, a multi-pumping flow system is proposed for the determination of phosphorus in effluents and polluted water samples. The system employs photometric detection based on the formation of molybdovanadophosphoric acid, and the fluidic circuit is built using three solenoid micropumps. The detection is implemented with a low cost LED-photodiode photometric detection system and the whole system is controlled by an open-source Arduino Uno microcontroller board. The optimization of the timing to ensure the color development and the pumping cycle is discussed for the proposed implementation. Experimental results to evaluate the system behavior are presented verifying a linear relationship between the relative absorbance and the phosphorus concentrations for levels as high as 50 mg L-1.

Multi-level governance and social cohesion in the European Union: the assessment of local agents, a study case inside Galicia

Implementing multi-level governance has been a key priority in EU cohesion policy. This study assesses the perceived achievements and shortcomings in implementing European Social Fund by analyzing the deficits and weaknesses as well as the poor participation of local agents who are in direct contact with the beneficiaries in order to design and implement this fund, which is the main financial instrument of EU social policy.

Use efficiency of variable rate of nitrogen prescribed by optical sensor in corn

ABSTRACT The efficiency of nitrogen fertilizer in corn is usually low, negatively affecting plant nutrition, the economic return, and the environment. In this context, a variable rate of nitrogen, prescribed by crop sensors, has been proposed as an alternative to the uniform rate of nitrogen traditionally used by farmers. This study tested the hypothesis that variable rate of nitrogen, prescribed by optical sensor, increases the nitrogen use efficiency and grain yield as compared to uniform rate of nitrogen. The following treatments were evaluated: 0; 70; 140; and 210 kg ha-1 under uniform rate of nitrogen, and 140 kg ha -1 under variable rate of nitrogen. The nitrogen source was urea applied on the soil surface using a distributor equipped with the crop sensor. In this study, the grain yield ranged from 10.2 to 15.5 Mg ha-1, with linear response to nitrogen rates. The variable rate of nitrogen increased by 11.8 and 32.6% the nitrogen uptake and nitrogen use efficiency, respectively, compared to the uniform rate of nitrogen. However, no significant increase in grain yield was observed, indicating that the major benefit of the variable rate of nitrogen was reducing the risk of environmental impact of fertilizer.