Modeling and identification of fertility maps using artificial neural networks

The application of agricultural fertilizers using variable rates along the field can be made through fertility maps previously elaborated or through real-time sensors. In most of the cases applies maps previously elaborated. These maps are identified from analyzes done in soil samples collected regularly (a sample for each field cell) or irregularly along the field. At the moment, mathematical interpolation methods such as nearest neighbor, local average, weighted inverse distance, contouring and kriging are used for predicting the variables involved with elaboration of fertility maps. However, some of these methods present deficiencies that can generate different fertility maps for a same data set. Moreover, such methods can generate inprecise maps to be used in precision farming. In this paper, artificial neural networks have been applied for elaboration and identification of precise fertility maps which can reduce the production costs and environmental impacts.

Comparative study of disk diffusion and microdilution methods for evaluation of antifungal activity of natural compounds against medical yeasts Candida spp and Cryptococcus sp

Antifungal activity of natural products has been tested by adapting methods designed for synthetic drugs. In this study, two methods for the determination of antifungal activity of natural products, agar diffusion and broth microdilution, the CLSI reference methods for synthetic drugs, are compared and discussed. The microdilution method was more sensitive. The minimal inhibitory concentrations (MIC) of crude extracts, fractions and pure substances from different species of the plant families Piperaceae, Rubiaceae, Clusiaceae, Fabaceae and Lauraceae, from the Biota project, were determined. Antifungal activities against Candida albicans, C.krusei, C.parapsilosis and Cryptococcus neoformans were produced by several samples.

Virtues and limitations of census maps for identifying critical deficiencies

Includes bibliography

Geotechnology applied to land use and sealing in urban areas

Through the geotechnology's use, the aim of this study was to characterize the urban occupation interference and occurrence of floods in the upstream area of watershed from the stream Wenzel (Rio Claro-SP/Brazil). Urbanized watersheds are composed of a variety of features and the development of cartographic material allowed the analysis of the evolution of land used for 1958 and 2006 scenarios. The thematic maps were generated using software Spring 4.3.3, wherein it got the separation of matters from vegetation cover and other intra urban features. Procedures of digital processes and classification of surface cover allowed quantifying the occupied area by each coverage type: woody vegetation, grass, grass with bare soil, bare soil, building, asphaltic sheets and exposed soil. Quantification of the different covers' occupied areas allowed relating the parameter Curve Number (Soil Conservation Service) as efficient methodology for runoff values estimative. The results indicate vegetation cover's reduction, intensive surface's sealing and suppression of water bodies. These factors imply changes of hydrological dynamics of the source, increasing flow and transfer of larger volumes of water and flood peaks to downstream sectors. The use of geotechnology allowed analyzing the evolution of urbanization and it permits also to infer about trends for future or inadequate occupancy to hydrological and environmental point of view. © 2013 IEEE.

Digital soil mapping: evaluation of sampling systems for soil surveys and refinement of soil maps at lower cost using legacy data

In soil surveys, several sampling systems can be used to define the most representative sites for sample collection and description of soil profiles. In recent years, the conditioned Latin hypercube sampling system has gained prominence for soil surveys. In Brazil, most of the soil maps are at small scales and in paper format, which hinders their refinement. The objectives of this work include: (i) to compare two sampling systems by conditioned Latin hypercube to map soil classes and soil properties; (II) to retrieve information from a detailed scale soil map of a pilot watershed for its refinement, comparing two data mining tools, and validation of the new soil map; and (III) to create and validate a soil map of a much larger and similar area from the extrapolation of information extracted from the existing soil map. Two sampling systems were created by conditioned Latin hypercube and by the cost-constrained conditioned Latin hypercube. At each prospection place, soil classification and measurement of the A horizon thickness were performed. Maps were generated and validated for each sampling system, comparing the efficiency of these methods. The conditioned Latin hypercube captured greater variability of soils and properties than the cost-constrained conditioned Latin hypercube, despite the former provided greater difficulty in field work. The conditioned Latin hypercube can capture greater soil variability and the cost-constrained conditioned Latin hypercube presents great potential for use in soil surveys, especially in areas of difficult access. From an existing detailed scale soil map of a pilot watershed, topographical information for each soil class was extracted from a Digital Elevation Model and its derivatives, by two data mining tools. Maps were generated using each tool. The more accurate of these tools was used for extrapolation of soil information for a much larger and similar area and the generated map was validated. It was possible to retrieve the existing soil map information and apply it on a larger area containing similar soil forming factors, at much low financial cost. The KnowledgeMiner tool for data mining, and ArcSIE, used to create the soil map, presented better results and enabled the use of existing soil map to extract soil information and its application in similar larger areas at reduced costs, which is especially important in development countries with limited financial resources for such activities, such as Brazil.

Bleaching effectiveness, hydrogen peroxide diffusion, and cytotoxicity of a chemically activated bleaching gel

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

Evaluation of diffusive gradients in thin films technique (DGT) for measuring Al, Cd, Co, Cu, Mn, Ni, and Zn in Amazonian rivers

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

Diffusion of oxygen in Ti-15Mo-xZr alloys studied by anelastic spectroscopy

Because of their low elasticity modulus, titanium alloys have excellent biocompatibility, and are largely used in orthopedic prostheses. Among the properties that are beneficial for use in orthopedic implants is the elasticity modulus, which is closely connected to the crystal structure of the material. Interstitial elements, such as oxygen, change the mechanical properties of the material. Anelastic spectroscopy measurements are a powerful tool for the study of the interaction of these elements with the metallic matrix and substitutional solutes, providing information on the diffusion and concentration of interstitial elements. In this study, the effect of oxygen on the anelastic properties of alloys in the Ti-15Mo-Zr system was analyzed using anelastic spectroscopy measurements. The diffusion coefficients, pre-exponential factors, and activation energies of these alloys were calculated for oxygen.

Diffusion of oxygen in some binary Ti-Based alloys used as biomaterials

Ti and its alloys are widely used as biomaterials. Their main properties are excellent corrosion resistance, relatively low elastic modulus, high specific strength, and good biocompatibility. The development of new Ti alloys with properties favorable for use in the human body is desired. To this end, Ti alloys with Mo, Nb, Zr, and Ta are being developed, because these elements do not cause cytotoxicity. The presence of interstitial elements (such as oxygen and nitrogen) induces strong changes in the elastic properties of the material, which leads to hardening or softening of the alloy. By means of anelastic spectroscopy, we are able to obtain information on the diffusion of these interstitial elements present in the crystalline lattice. In this paper, the effect of oxygen on the anelastic properties of some binary Ti-based alloys was analyzed with anelastic spectroscopy. The diffusion coefficients, pre-exponential factors, and activation energies were calculated for oxygen and nitrogen in these alloys.

On the formation of carbonate adducts of fatty alcohols, sterols, and sugars in biological conditions

The formation and properties of carbonate adducts of some organic hydroxy compounds in aqueous medium were investigated. Fatty alcohols and sugars were chosen as representative classes of biological interest, and the medium was carbonated aqueous solution with pH ranging from 3.0 to 8.3. Capillary electrophoresis with two capacitively coupled contactless conductivity detectors (C4Ds) was used for quantitation and to obtain the mobility of the monoalkyl carbonates (MACs), which were used to determine the equilibrium and kinetic constants of the reaction as well as the diffusion coefficients. For increasing chain length of the alcohols, the equilibrium constant tends to the unit, which suggests that fatty alcohols can form the corresponding MACs. The formation of MACs for cyclohexanol and cyclopentanol also suggest the existence of similar species for sterols. Carbonate adducts of fructose, glucose, and sucrose were also detected, which suggests that these counterparts of the well-known phosphates can also occur in the cytosol. Our calculations suggest that one in 1000 to one in 10 000 molecules of these hydroxy compounds would be available as the corresponding MAC in such a medium. Experiments carried out at pH values less than 3.0 showed that there is a catalytic effect of hydronium on the interconversion of bicarbonate and a MAC. Taking into account the great number of hydroxy compounds similar to the ones investigated and that bicarbonate is ubiquitous in living cells, one can anticipate the existence of a whole new class of carbonate adducts of these metabolites.

Paper-based diffusive gradients in thin films technique coupled to energy dispersive X-ray fluorescence spectrometry for the determination of labile Mn, Co, Ni, Cu, Zn and Pb in river water

The diffusive gradients in thin films (DGT) technique has shown enormous potential for labile metal monitoring in fresh water due to the preconcentration, time-integrated, matrix interference removal and speciation analytical features. In this work, the coupling of energy dispersive X-ray fluorescence (EDXRF) with paper-based DGT devices was evaluated for the direct determination of Mn, Co. Ni, Cu, Zn and Pb in fresh water. The DGT samplers were assembled with cellulose (Whatman 3 MM chromatography paper) as the diffusion layer and a cellulose phosphate ion exchange membrane (Whatman P 81 paper) as the binding agent. The diffusion coefficients of the analytes on 3 MM chromatography paper were calculated by deploying the DGT samplers in synthetic solutions containing 500 mu g L-1 of Mn. Co, Ni, Cu, Zn and Pb (4 L at pH 5.5 and ionic strength at 0.05 mol L-1). After retrieval, the DGT units were disassembled and the P81 papers were dried and analysed by EDXRF directly. The 3 MM chromatographic paper diffusion coefficients of the analytes ranged from 1.67 to 1.87 x 10(-6) cm(2) s(-1). The metal retention and phosphate group homogeneities on the P81 membrane was studied by a spot analysis with a diameter of 1 mm. The proposed approach (DGT-EDXRF coupling) was applied to determine the analytes at five sampling sites (48 h in situ deployment) on the Piracicaba river basin, and the results (labile fraction) were compared with 0.45 mu m dissolved fractions determined by synchrotron radiation-excited total reflection X-ray fluorescence (SR-TXRF). The limits of detection of DGT-EDXRF coupling for the analytes (from 7.5 to 26 mu g L-1) were similar to those obtained by the sensitive SR-TXRF technique (3.8 to 9.1 mu g L-1). (C) 2012 Elsevier B.V. All rights reserved.

Enzyme Microheterogeneous Hydration and Stabilization in Supercritical Carbon Dioxide

Supercritical carbon dioxide is a promising green-chemistry solvent for many enzyme-catalyzed chemical reactions, yet the striking stability of some enzymes in such unconventional environments is not well understood. Here, we investigate the stabilization of the Candida antarctica Lipase B (CALB) in supercritical carbon dioxide-water biphasic systems using molecular dynamics simulations. The preservation of the enzyme structure and optimal activity depend on the presence of small amounts of water in the supercritical dispersing medium. When the protein is at least partially hydrated, water molecules bind to specific sites on the enzyme surface and prevent carbon dioxide from penetrating its catalytic core. Strikingly, water and supercritical carbon dioxide cover the protein surface quite heterogeneously. In the first solvation layer, the hydrophilic residues at the surface of the protein are able to pin down patches of water, whereas carbon dioxide solvates preferentially hydrophobic surface residues. In the outer solvation shells, water molecules tend to cluster predominantly on top of the larger water patches of the first solvation layer instead of spreading evenly around the remainder of the protein surface. For CALB, this exposes the substrate-binding region of the enzyme to carbon dioxide, possibly facilitating diffusion of nonpolar substrates into the catalytic funnel. Therefore, by means of microheterogeneous solvation, enhanced accessibility of hydrophobic substrates to the active site can be achieved, while preserving the functional structure of the enzyme. Our results provide a molecular picture on the nature of the stability of proteins in nonaqueous media.

Kinetic of water diffusion and color stability of a resin composite as a function of the curing tip distance

The influence of curing tip distance and storage time in the kinetics of water diffusion (water sorption-W SP, solubility-W SB, and net water uptake) and color stability of a composite were evaluated. Composite samples were polymerized at different distances (5, 10, and 15 mm) and compared to a control group (0 mm). After desiccation, the specimens were stored in distilled water to evaluate the water diffusion over a 120-day period. Net water uptake was calculated (sum of WSP and WSB). The color stability after immersion in a grape juice was compared to distilled water. Data were submitted to three-way ANOVA/Tukey's test (α = 5%). The higher distances caused higher net water uptake (p < 0.05). The immersion in the juice caused significantly higher color change as a function of curing tip distance and the time (p < 0.05). The distance of photoactivation and storage time provide the color alteration and increased net water uptake of the resin composite tested.

Non-Markovian stochastic processes and their applications: from anomalous diffusion to time series analysis

This work provides a forward step in the study and comprehension of the relationships between stochastic processes and a certain class of integral-partial differential equation, which can be used in order to model anomalous diffusion and transport in statistical physics. In the first part, we brought the reader through the fundamental notions of probability and stochastic processes, stochastic integration and stochastic differential equations as well. In particular, within the study of H-sssi processes, we focused on fractional Brownian motion (fBm) and its discrete-time increment process, the fractional Gaussian noise (fGn), which provide examples of non-Markovian Gaussian processes. The fGn, together with stationary FARIMA processes, is widely used in the modeling and estimation of long-memory, or long-range dependence (LRD). Time series manifesting long-range dependence, are often observed in nature especially in physics, meteorology, climatology, but also in hydrology, geophysics, economy and many others. We deepely studied LRD, giving many real data examples, providing statistical analysis and introducing parametric methods of estimation. Then, we introduced the theory of fractional integrals and derivatives, which indeed turns out to be very appropriate for studying and modeling systems with long-memory properties. After having introduced the basics concepts, we provided many examples and applications. For instance, we investigated the relaxation equation with distributed order time-fractional derivatives, which describes models characterized by a strong memory component and can be used to model relaxation in complex systems, which deviates from the classical exponential Debye pattern. Then, we focused in the study of generalizations of the standard diffusion equation, by passing through the preliminary study of the fractional forward drift equation. Such generalizations have been obtained by using fractional integrals and derivatives of distributed orders. In order to find a connection between the anomalous diffusion described by these equations and the long-range dependence, we introduced and studied the generalized grey Brownian motion (ggBm), which is actually a parametric class of H-sssi processes, which have indeed marginal probability density function evolving in time according to a partial integro-differential equation of fractional type. The ggBm is of course Non-Markovian. All around the work, we have remarked many times that, starting from a master equation of a probability density function f(x,t), it is always possible to define an equivalence class of stochastic processes with the same marginal density function f(x,t). All these processes provide suitable stochastic models for the starting equation. Studying the ggBm, we just focused on a subclass made up of processes with stationary increments. The ggBm has been defined canonically in the so called grey noise space. However, we have been able to provide a characterization notwithstanding the underline probability space. We also pointed out that that the generalized grey Brownian motion is a direct generalization of a Gaussian process and in particular it generalizes Brownain motion and fractional Brownain motion as well. Finally, we introduced and analyzed a more general class of diffusion type equations related to certain non-Markovian stochastic processes. We started from the forward drift equation, which have been made non-local in time by the introduction of a suitable chosen memory kernel K(t). The resulting non-Markovian equation has been interpreted in a natural way as the evolution equation of the marginal density function of a random time process l(t). We then consider the subordinated process Y(t)=X(l(t)) where X(t) is a Markovian diffusion. The corresponding time-evolution of the marginal density function of Y(t) is governed by a non-Markovian Fokker-Planck equation which involves the same memory kernel K(t). We developed several applications and derived the exact solutions. Moreover, we considered different stochastic models for the given equations, providing path simulations.

A dynamical system approach to data assimilation in chaotic models

The Assimilation in the Unstable Subspace (AUS) was introduced by Trevisan and Uboldi in 2004, and developed by Trevisan, Uboldi and Carrassi, to minimize the analysis and forecast errors by exploiting the flow-dependent instabilities of the forecast-analysis cycle system, which may be thought of as a system forced by observations. In the AUS scheme the assimilation is obtained by confining the analysis increment in the unstable subspace of the forecast-analysis cycle system so that it will have the same structure of the dominant instabilities of the system. The unstable subspace is estimated by Breeding on the Data Assimilation System (BDAS). AUS- BDAS has already been tested in realistic models and observational configurations, including a Quasi-Geostrophicmodel and a high dimensional, primitive equation ocean model; the experiments include both fixed and“adaptive”observations. In these contexts, the AUS-BDAS approach greatly reduces the analysis error, with reasonable computational costs for data assimilation with respect, for example, to a prohibitive full Extended Kalman Filter. This is a follow-up study in which we revisit the AUS-BDAS approach in the more basic, highly nonlinear Lorenz 1963 convective model. We run observation system simulation experiments in a perfect model setting, and with two types of model error as well: random and systematic. In the different configurations examined, and in a perfect model setting, AUS once again shows better efficiency than other advanced data assimilation schemes. In the present study, we develop an iterative scheme that leads to a significant improvement of the overall assimilation performance with respect also to standard AUS. In particular, it boosts the efficiency of regime’s changes tracking, with a low computational cost. Other data assimilation schemes need estimates of ad hoc parameters, which have to be tuned for the specific model at hand. In Numerical Weather Prediction models, tuning of parameters — and in particular an estimate of the model error covariance matrix — may turn out to be quite difficult. Our proposed approach, instead, may be easier to implement in operational models.