Evaluation of geostatistical techniques to estimate the spatial distribution of aboveground biomass in the Amazon rainforest using high-resolution remote sensing data

ABSTRACT The spatial distribution of forest biomass in the Amazon is heterogeneous with a temporal and spatial variation, especially in relation to the different vegetation types of this biome. Biomass estimated in this region varies significantly depending on the applied approach and the data set used for modeling it. In this context, this study aimed to evaluate three different geostatistical techniques to estimate the spatial distribution of aboveground biomass (AGB). The selected techniques were: 1) ordinary least-squares regression (OLS), 2) geographically weighted regression (GWR) and, 3) geographically weighted regression - kriging (GWR-K). These techniques were applied to the same field dataset, using the same environmental variables derived from cartographic information and high-resolution remote sensing data (RapidEye). This study was developed in the Amazon rainforest from Sucumbíos - Ecuador. The results of this study showed that the GWR-K, a hybrid technique, provided statistically satisfactory estimates with the lowest prediction error compared to the other two techniques. Furthermore, we observed that 75% of the AGB was explained by the combination of remote sensing data and environmental variables, where the forest types are the most important variable for estimating AGB. It should be noted that while the use of high-resolution images significantly improves the estimation of the spatial distribution of AGB, the processing of this information requires high computational demand.

Schistosomiasis risk mapping in the state of Minas Gerais, Brazil, using a decision tree approach, remote sensing data and sociological indicators

Schistosomiasis mansoni is not just a physical disease, but is related to social and behavioural factors as well. Snails of the Biomphalaria genus are an intermediate host for Schistosoma mansoni and infect humans through water. The objective of this study is to classify the risk of schistosomiasis in the state of Minas Gerais (MG). We focus on socioeconomic and demographic features, basic sanitation features, the presence of accumulated water bodies, dense vegetation in the summer and winter seasons and related terrain characteristics. We draw on the decision tree approach to infection risk modelling and mapping. The model robustness was properly verified. The main variables that were selected by the procedure included the terrain's water accumulation capacity, temperature extremes and the Human Development Index. In addition, the model was used to generate two maps, one that included risk classification for the entire of MG and another that included classification errors. The resulting map was 62.9% accurate.

Measuring mechanical impedance in clayey gravelly soils

Mechanical impedance of clayey and gravelly soils is often needed to interpret experimental results from tillage and other field experiments. Its measurement is difficult with manual and hydraulic penetrometers, which often bend or break in such soils. The purpose of this study was to evaluate the feasibility of a hand-operated "Stolf" impact penetrometer to measure mechanical impedance (soil resistance). The research was conducted in Raleigh, North Carolina, USA (35º 45'N, 78º 42'W, elevation 75 m). Corn was planted on April 19, 1991. Penetrometer measurements were taken on May 10, 1991, in 5 cm intervals to 60 cm at 33 locations on a transect perpendicular to the corn rows in each of four tillage treatments. The data permitted three-dimensional displays showing how mechanical impedance changed with depth and distance along the transect. The impact penetrometer proved to be a useful tool to collect quantitative mechanical impedance data on "hard" clayey and/or gravelly soils which previously were difficult to reliably quantify.

Estimation of soil moisture in the root-zone from remote sensing data

Field-based soil moisture measurements are cumbersome. Thus, remote sensing techniques are needed because allows field and landscape-scale mapping of soil moisture depth-averaged through the root zone of existing vegetation. The objective of the study was to evaluate the accuracy of an empirical relationship to calculate soil moisture from remote sensing data of irrigated soils of the Apodi Plateau, in the Brazilian semiarid region. The empirical relationship had previously been tested for irrigated soils in Mexico, Egypt, and Pakistan, with promising results. In this study, the relationship was evaluated from experimental data collected from a cotton field. The experiment was carried out in an area of 5 ha with irrigated cotton. The energy balance and evaporative fraction (Λ) were measured by the Bowen ratio method. Soil moisture (θ) data were collected using a PR2 - Profile Probe (Delta-T Devices Ltd). The empirical relationship was tested using experimentally collected Λ and θ values and was applied using the Λ values obtained from the Surface Energy Balance Algorithm for Land (SEBAL) and three TM - Landsat 5 images. There was a close correlation between measured and estimated θ values (p<0.05, R² = 0.84) and there were no significant differences according to the Student t-test (p<0.01). The statistical analyses showed that the empirical relationship can be applied to estimate the root-zone soil moisture of irrigated soils, i.e. when the evaporative fraction is greater than 0.45.

Multispectral remote sensing for site-specific nitrogen fertilizer management

The objective of this work was to evaluate the use of multispectral remote sensing for site-specific nitrogen fertilizer management. Satellite imagery from the advanced spaceborne thermal emission and reflection radiometer (Aster) was acquired in a 23 ha corn-planted area in Iran. For the collection of field samples, a total of 53 pixels were selected by systematic randomized sampling. The total nitrogen content in corn leaf tissues in these pixels was evaluated. To predict corn canopy nitrogen content, different vegetation indices, such as normalized difference vegetation index (NDVI), soil-adjusted vegetation index (Savi), optimized soil-adjusted vegetation index (Osavi), modified chlorophyll absorption ratio index 2 (MCARI2), and modified triangle vegetation index 2 (MTVI2), were investigated. The supervised classification technique using the spectral angle mapper classifier (SAM) was performed to generate a nitrogen fertilization map. The MTVI2 presented the highest correlation (R²=0.87) and is a good predictor of corn canopy nitrogen content in the V13 stage, at 60 days after cultivating. Aster imagery can be used to predict nitrogen status in corn canopy. Classification results indicate three levels of required nitrogen per pixel: low (0-2.5 kg), medium (2.5-3 kg), and high (3-3.3 kg).

ANION-BINDING AND SENSING PROPERTIES OF NOVEL RECEPTORS BASED ON N-(INDOL-3-YLGLYOXYLYL)BENZYLAMINE

Indole-based receptors such as biindole, carbazole, and indolocarbazole are regarded as some of the most favorable anion receptors in molecular recognition. This is because indole groups possess N–H groups as hydrogen-bonding donors. The introduction of amide groups in the indole framework can induce strong binding properties and good water solubility. In this study, we designed and synthesized a series of N-(indol-3-ylglyoxylyl)benzylamine derivatives as novel and simple anion receptors. The receptors derived by aryl and aliphatic amines can selectively recognize F– based on a color change from colorless-to-yellow in DMSO. The receptors derived by hydrazine hydrate can recognize F–, AcO–, and H2PO4– by similar color changes in DMSO and can even enable the selective recognition of F– in a DMSO–H2O binary solution by the naked eye. Spectrographic data indicate that complexes are formed between receptors and anions through multiple hydrogen-bonding interactions in dual solutions.

Using an aerial system of remote sensing to detect different nutritional status in Brachiaria decumbens

The aim of this study was to use digital images acquired by cameras attached to a helium balloon to detect variation of the nutritional status in Brachiaria decumbens. The treatments consisted of five doses of nitrogen (0, 50, 100, 150 e 200kg ha-1) with six replications each, evaluated in a completely randomized statistical design. A remote sensing system composed of digital cameras and microcomputers was used for image acquisition, and a helium balloon lifted the cameras to the heights of 15, 20, 25 and 30m. A portable chlorophyll meter and analyses of leaf nitrogen content were used to make comparisons with data obtained by the remote sensing system. Data was acquired in two phases, in different climatic conditions. At the end of each phase, dry matter production was measured. Three vegetation indices were used to evaluate the detection of different nutritional status. The three indices were able to detect the effects of N doses. The indices constructed with the Green spectral band showed to be more efficient.

Geostatistics and remote sensing methods in the classification of images of areas cultivated with citrus

This study compares the precision of three image classification methods, two of remote sensing and one of geostatistics applied to areas cultivated with citrus. The 5,296.52ha area of study is located in the city of Araraquara - central region of the state of São Paulo (SP), Brazil. The multispectral image from the CCD/CBERS-2B satellite was acquired in 2009 and processed through the Geographic Information System (GIS) SPRING. Three classification methods were used, one unsupervised (Cluster), and two supervised (Indicator Kriging/IK and Maximum Likelihood/Maxver), in addition to the screen classification taken as field checking.. Reliability of classifications was evaluated by Kappa index. In accordance with the Kappa index, the Indicator kriging method obtained the highest degree of reliability for bands 2 and 4. Moreover the Cluster method applied to band 2 (green) was the best quality classification between all the methods. Indicator Kriging was the classifier that presented the citrus total area closest to the field check estimated by -3.01%, whereas Maxver overestimated the total citrus area by 42.94%.

Extracellular calcium-sensing receptor: structural and functional features and association with diseases

The recently cloned extracellular calcium-sensing receptor (CaR) is a G protein-coupled receptor that plays an essential role in the regulation of extracellular calcium homeostasis. This receptor is expressed in all tissues related to this control (parathyroid glands, thyroid C-cells, kidneys, intestine and bones) and also in tissues with apparently no role in the maintenance of extracellular calcium levels, such as brain, skin and pancreas. The CaR amino acid sequence is compatible with three major domains: a long and hydrophilic aminoterminal extracellular domain, where most of the activating and inactivating mutations described to date are located and where the dimerization process occurs, and the agonist-binding site is located, a hydrophobic transmembrane domain involved in the signal transduction mechanism from the extracellular domain to its respective G protein, and a carboxyterminal intracellular tail, with a well-established role for cell surface CaR expression and for signal transduction. CaR cloning was immediately followed by the association of genetic human diseases with inactivating and activating CaR mutations: familial hypocalciuric hypercalcemia and neonatal severe hyperparathyroidism are caused by CaR-inactivating mutations, whereas autosomal dominant hypoparathyroidism is secondary to CaR-activating mutations. Finally, we will comment on the development of drugs that modulate CaR function by either activating (calcimimetic drugs) or antagonizing it (calcilytic drugs), and on their potential therapeutic implications, such as medical control of specific cases of primary and uremic hyperparathyroidism with calcimimetic drugs and a potential treatment for osteoporosis with a calcilytic drug.

Bioelectrical impedance spectroscopy for the assessment of body fluid volumes of term neonates

The assessment of fluid volume in neonates by a noninvasive, inexpensive, and fast method can contribute significantly to increase the quality of neonatal care. The objective of the present study was to calibrate an acquisition system and software to estimate the bioelectrical impedance parameters obtained by a method of bioelectrical impedance spectroscopy based on step response and to develop specific equations for the neonatal population to determine body fluid compartments. Bioelectric impedance measurements were performed by a laboratory homemade instrument. The volumes were estimated in a clinical study on 30 full-term neonates at four different times during the first month of life. During the first 24 hours of life the total body water, extracellular water and intracellular water were 2.09 ± 0.25, 1.20 ± 0.19, and 0.90 ± 0.25 liters, respectively. By the 48th hour they were 1.87 ± 0.27, 1.08 ± 0.17, and 0.79 ± 0.21 liters, respectively. On the 10th day they were 2.02 ± 0.25, 1.29 ± 0.21, and 0.72 ± 0.14 liters, respectively, and after 1 month they were 2.34 ± 0.27, 1.62 ± 0.20, and 0.72 ± 0.13 liters, respectively. The behavior of the estimated volume was correlated with neonatal body weight changes, leading to a better interpretation of such changes. In conclusion, this study indicates the feasibility of bioelectrical impedance spectroscopy as a method to help fluid administration in intensive care neonatal units, and also contribute to the development of new equations to estimate neonatal body fluid contents.

An acid-sensing ion channel that detects ischemic pain

Ischemic pain occurs when there is insufficient blood flow for the metabolic needs of an organ. The pain of a heart attack is the prototypical example. Multiple compounds released from ischemic muscle likely contribute to this pain by acting on sensory neurons that innervate muscle. One such compound is lactic acid. Here, we show that ASIC3 (acid-sensing ion channel #3) has the appropriate expression pattern and physical properties to be the detector of this lactic acid. In rats, it is expressed only in sensory neurons and then only on a minority (~40%) of these. Nevertheless, it is expressed at extremely high levels on virtually all dorsal root ganglion sensory neurons that innervate the heart. It is extraordinarily sensitive to protons (Hill slope 4, half-activating pH 6.7), allowing it to readily respond to the small changes in extracellular pH (from 7.4 to 7.0) that occur during muscle ischemia. Moreover, both extracellular lactate and extracellular ATP increase the sensitivity of ASIC3 to protons. This final property makes ASIC3 a "coincidence detector" of three molecules that appear during ischemia, thereby allowing it to better detect acidosis caused by ischemia than other forms of systemic acidosis such as hypercapnia.

Body composition measures of obese adolescents by the deuterium oxide dilution method and by bioelectrical impedance

The objectives of the present study were to describe and compare the body composition variables determined by bioelectrical impedance (BIA) and the deuterium dilution method (DDM), to identify possible correlations and agreement between the two methods, and to construct a linear regression model including anthropometric measures. Obese adolescents were evaluated by anthropometric measures, and body composition was assessed by BIA and DDM. Forty obese adolescents were included in the study. Comparison of the mean values for the following variables: fat body mass (FM; kg), fat-free mass (FFM; kg), and total body water (TBW; %) determined by DDM and by BIA revealed significant differences. BIA overestimated FFM and TBW and underestimated FM. When compared with data provided by DDM, the BIA data presented a significant correlation with FFM (r = 0.89; P < 0.001), FM (r = 0.93; P < 0.001) and TBW (r = 0.62; P < 0.001). The Bland-Altman plot showed no agreement for FFM, FM or TBW between data provided by BIA and DDM. The linear regression models proposed in our study with respect to FFM, FM, and TBW were well adjusted. FFM obtained by DDM = 0.842 x FFM obtained by BIA. FM obtained by DDM = 0.855 x FM obtained by BIA + 0.152 x weight (kg). TBW obtained by DDM = 0.813 x TBW obtained by BIA. The body composition results of obese adolescents determined by DDM can be predicted by using the measures provided by BIA through a regression equation.

Prevalence of child malnutrition at a university hospital using the World Health Organization criteria and bioelectrical impedance data

Malnutrition constitutes a major public health concern worldwide and serves as an indicator of hospitalized patients’ prognosis. Although various methods with which to conduct nutritional assessments exist, large hospitals seldom employ them to diagnose malnutrition. The aim of this study was to understand the prevalence of child malnutrition at the University Hospital of the Ribeirão Preto Medical School, University of São, Brazil. A cross-sectional descriptive study was conducted to compare the nutritional status of 292 hospitalized children with that of a healthy control group (n=234). Information regarding patients’ weight, height, and bioelectrical impedance (i.e., bioelectrical impedance vector analysis) was obtained, and the phase angle was calculated. Using the World Health Organization (WHO) criteria, 35.27% of the patients presented with malnutrition; specifically, 16.10% had undernutrition and 19.17% were overweight. Classification according to the bioelectrical impedance results of nutritional status was more sensitive than the WHO criteria: of the 55.45% of patients with malnutrition, 51.25% exhibited undernutrition and 4.20% were overweight. After applying the WHO criteria in the unpaired control group (n=234), we observed that 100.00% of the subjects were eutrophic; however, 23.34% of the controls were malnourished according to impedance analysis. The phase angle was significantly lower in the hospitalized group than in the control group (P<0.05). Therefore, this study suggests that a protocol to obtain patients’ weight and height must be followed, and bioimpedance data must be examined upon hospital admission of all children.

Anti-quorum sensing activity of phenolic extract from Eugenia brasiliensis (Brazilian cherry)

Abstract The aim of this study was to assess the anti-quorum sensing activity of phenolic extracts from grumixama (Eugenia brasiliensis), also known as Brazilian cherry, in concentrations that did not interfere with bacterial growth. The pulp phenolic compounds were extracted by using solid phage extraction in a mini-collumn C18 and quantified by spectrophotometry. The anti-quorum sensing activity was evaluated by testing the inhibition of violacein production in Chromobacterium violaceum and by evaluating the swarming motility in Aeromonas hydrophila and Serratia marcescens, both phenotypes regulated by quorum sensing. The phenolic extract strongly inhibited the production of violacein in C. violaceum, reducing its production in comparison with a control with no extract. No inhibition of growth was observed at the concentrations tested for quorum sensing inhibition. Confirming the quorum sensing inhibition phenotype, the extract was also able to inhibit swarming motility in S. marcescens and in A. hydrophila, although in the later the effect was marginal. Overall, these results indicate that phenolic extract from E. brasiliensis presents quorum sensing inhibitory activity most likely due to the presence of fruit phenolics which have been implicated as quorum sensing inhibitors in Gram negative bacteria.