997 resultados para FILLED PORE-SPACE
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Water transport in wood is vital for the survival of trees. With synchrotron radiation X-ray tomographic microscopy (SRXTM), it has become possible to characterize and quantify the three-dimensional (3D) network formed by vessels that are responsible for longitudinal transport. In the present study, the spatial size dependence of vessels and the organization inside single growth rings in terms of vessel-induced porosity was studied by SRXTM. Network characteristics, such as connectivity, were deduced by digital image analysis from the processed tomographic data and related to known complex network topologies.
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Understanding the influence of pore space characteristics on the hydraulic conductivity and spectral induced polarization (SIP) response is critical for establishing relationships between the electrical and hydrological properties of surficial unconsolidated sedimentary deposits, which host the bulk of the world's readily accessible groundwater resources. Here, we present the results of laboratory SIP measurements on industrial-grade, saturated quartz samples with granulometric characteristics ranging from fine sand to fine gravel, which can be regarded as proxies for widespread alluvial deposits. We altered the pore space characteristics by changing (i) the grain size spectra, (ii) the degree of compaction, and (iii) the level of sorting. We then examined how these changes affect the SIP response, the hydraulic conductivity, and the specific surface area of the considered samples. In general, the results indicate a clear connection between the SIP response and the granulometric as well as pore space characteristics. In particular, we observe a systematic correlation between the hydraulic conductivity and the relaxation time of the Cole-Cole model describing the observed SIP effect for the entire range of considered grain sizes. The results do, however, also indicate that the detailed nature of these relations depends strongly on variations in the pore space characteristics, such as, for example, the degree of compaction. The results of this study underline the complexity of the origin of the SIP signal as well as the difficulty to relate it to a single structural factor of a studied sample, and hence raise some fundamental questions with regard to the practical use of SIP measurements as site- and/or sample-independent predictors of the hydraulic conductivity.
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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
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Most available studies of interconnected matrix porosity of crystalline rocks are based on laboratory investigations; that is, work on samples that have undergone stress relaxation and were affected by drilling and sample preparation. The extrapolation of the results to in situ conditions is therefore associated with considerable uncertainty, and this was the motivation to conduct the ‘in situ Connected Porosity’ experiment at the Grimsel Test Site (Central Swiss Alps). An acrylic resin doped with fluorescent agents was used to impregnate the microporous granitic matrix in situ around an injection borehole, and samples were obtained by overcoring. The 3-D structure of the porespace, represented by microcracks, was studied by U-stage fluorescence microscopy. Petrophysical methods, including the determination of porosity, permeability and P -wave velocity, were also applied. Investigations were conducted both on samples that were impregnated in situ and on non-impregnated samples, so that natural features could be distinguished from artefacts. The investigated deformed granites display complex microcrack populations representing a polyphase deformation at varying conditions. The crack population is dominated by open cleavage cracks in mica and grain boundary cracks. The porosity of non-impregnated samples lies slightly above 1 per cent, which is 2–2.5 times higher than the in situ porosity obtained for impregnated samples. Measurements of seismic velocities (Vp ) on spherical rock samples as a function of confining pressure, spatial direction and water saturation for both non-impregnated and impregnated samples provide further constraints on the distinction between natural and induced crack types. The main conclusions are that (1) an interconnected network of microcracks exists in the whole granitic matrix, irrespective of the distance to ductile and brittle shear zones, and (2) conventional laboratory methods overestimate the matrix porosity. Calculations of contaminant transport through fractured media often rely on matrix diffusion as a retardation mechanism.
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The image by Computed Tomography is a non-invasive alternative for observing soil structures, mainly pore space. The pore space correspond in soil data to empty or free space in the sense that no material is present there but only fluids, the fluid transport depend of pore spaces in soil, for this reason is important identify the regions that correspond to pore zones. In this paper we present a methodology in order to detect pore space and solid soil based on the synergy of the image processing, pattern recognition and artificial intelligence. The mathematical morphology is an image processing technique used for the purpose of image enhancement. In order to find pixels groups with a similar gray level intensity, or more or less homogeneous groups, a novel image sub-segmentation based on a Possibilistic Fuzzy c-Means (PFCM) clustering algorithm was used. The Artificial Neural Networks (ANNs) are very efficient for demanding large scale and generic pattern recognition applications for this reason finally a classifier based on artificial neural network is applied in order to classify soil images in two classes, pore space and solid soil respectively.
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The study of soil structure, i.e., the pores, is of vital importance in different fields of science and technology. Total pore volume (porosity), pore surface, pore connectivity and pore size distribution are some (probably the most important) of the geometric measurements of pore space. The technology of X-ray computed tomography allows us to obtain 3D images of the inside of a soil sample enabling study of the pores without disturbing the samples. In this work we performed a set of geometrical measures, some of them from mathematical morphology, to assess and quantify any possible difference that tillage may have caused on the soil. We compared samples from tilled soil with samples from a soil with natural vegetation taken in a very close area. Our results show that the main differences between these two groups of samples are total surface area and pore connectivity per unit pore volume.
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Soil structure plays an important role in flow and transport phenomena, and a quantitative characterization of the spatial heterogeneity of the pore space geometry is beneficial for prediction of soil physical properties. Morphological features such as pore-size distribution, pore space volume or pore?solid surface can be altered by different soil management practices. Irregularity of these features and their changes can be described using fractal geometry. In this study, we focus primarily on the characterization of soil pore space as a 3D geometrical shape by fractal analysis and on the ability of fractal dimensions to differentiate between two a priori different soil structures. We analyze X-ray computed tomography (CT) images of soils samples from two nearby areas with contrasting management practices. Within these two different soil systems, samples were collected from three depths. Fractal dimensions of the pore-size distributions were different depending on soil use and averaged values also differed at each depth. Fractal dimensions of the volume and surface of the pore space were lower in the tilled soil than in the natural soil but their standard deviations were higher in the former as compared to the latter. Also, it was observed that soil use was a factor that had a statistically significant effect on fractal parameters. Fractal parameters provide useful complementary information about changes in soil structure due to changes in soil management. Read More: http://www.worldscientific.com/doi/abs/10.1142/S0218348X14400118?queryID=%24%7BresultBean.queryID%7D&
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During the last few decades, new imaging techniques like X-ray computed tomography have made available rich and detailed information of the spatial arrangement of soil constituents, usually referred to as soil structure. Mathematical morphology provides a plethora of mathematical techniques to analyze and parameterize the geometry of soil structure. They provide a guide to design the process from image analysis to the generation of synthetic models of soil structure in order to investigate key features of flow and transport phenomena in soil. In this work, we explore the ability of morphological functions built over Minkowski functionals with parallel sets of the pore space to characterize and quantify pore space geometry of columns of intact soil. These morphological functions seem to discriminate the effects on soil pore space geometry of contrasting management practices in a Mediterranean vineyard, and they provide the first step toward identifying the statistical significance of the observed differences.
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Studies on hacking have typically focused on motivational aspects and general personality traits of the individuals who engage in hacking; little systematic research has been conducted on predispositions that may be associated not only with the choice to pursue a hacking career but also with performance in either naïve or expert populations. Here, we test the hypotheses that two traits that are typically enhanced in autism spectrum disorders—attention to detail and systemizing—may be positively related to both the choice of pursuing a career in information security and skilled performance in a prototypical hacking task (i.e., crypto-analysis or code-breaking). A group of naïve participants and of ethical hackers completed the Autism Spectrum Quotient, including an attention to detail scale, and the Systemizing Quotient (Baron-Cohen et al., 2001, 2003). They were also tested with behavioral tasks involving code-breaking and a control task involving security X-ray image interpretation. Hackers reported significantly higher systemizing and attention to detail than non-hackers. We found a positive relation between self-reported systemizing (but not attention to detail) and code-breaking skills in both hackers and non-hackers, whereas attention to detail (but not systemizing) was related with performance in the X-ray screening task in both groups, as previously reported with naïve participants (Rusconi et al., 2015). We discuss the theoretical and translational implications of our findings.
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It has been shown that cover crops can enhance soil nitrous oxide (N(2)O) emissions, but the magnitude of increase depends on the quantity and quality of the crop residues. Therefore, this study aimed to evaluate the effect of long-term (19 and 21 years) no-till maize crop rotations including grass [black oat (Avena strigosa Schreb)] and legume cover crops [vetch (Vigna sativa L), cowpea (Vigna unguiculata L. Walp), pigeon pea (Cajanus cajan L. Millsp.) and lablab (Dolichos lablab)] on annual soil N(2)O emissions in a subtropical Acrisol in Southern Brazil. Greater soil N(2)O emissions were observed in the first 45 days after the cover crop residue management in all crop rotations, varying from -20.2 +/- 1.9 to 163.9 +/- 24.3 mu g N m(-2) h(-1). Legume-based crop rotations had the largest cumulative emissions in this period, which were directly related to the quantity of N (r(2) = 0.60, p = 0.13)and inversely related to the lignin:N ratio(r(2) = 0.89,p = 0.01) of the cover crop residues. After this period, the mean fluxes were smaller and were closely related to the total soil N stocks (r(2) = 0.96, p = 0.002). The annual soil N(2)O emission represented 0.39-0.75% of the total N added by the legume cover crops. Management-control led soil variables such as mineral N (NO(3)(-) and NH(4)(+)) and dissolved organic C influenced more the N(2)O fluxes than environmental-related variables as water-filled pore space and air and soil temperature. Consequently, the synchronization between N mineralization and N uptake by plants seems to be the main challenge to reduce N(2)O emissions while maintaining the environmental and agronomic services provided by legume cover crops in agricultural systems. (C) 2009 Elsevier B.V. All rights reserved.
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The root-colonizing bacterium Pseudomonas fluorescens CHA0 was used to construct an oxygen-responsive biosensor. An anaerobically inducible promoter of Pseudomonas aeruginosa, which depends on the FNR (fumarate and nitrate reductase regulation)-like transcriptional regulator ANR (anaerobic regulation of arginine deiminase and nitrate reductase pathways), was fused to the structural lacZ gene of Escherichia coli. By inserting the reporter fusion into the chromosomal attTn7 site of P. fluorescens CHA0 by using a mini-Tn7 transposon, the reporter strain, CHA900, was obtained. Grown in glutamate-yeast extract medium in an oxystat at defined oxygen levels, the biosensor CHA900 responded to a decrease in oxygen concentration from 210 x 10(2) Pa to 2 x 10(2) Pa of O(2) by a nearly 100-fold increase in beta-galactosidase activity. Half-maximal induction of the reporter occurred at about 5 x 10(2) Pa. This dose response closely resembles that found for E. coli promoters which are activated by the FNR protein. In a carbon-free buffer or in bulk soil, the biosensor CHA900 still responded to a decrease in oxygen concentration, although here induction was about 10 times lower and the low oxygen response was gradually lost within 3 days. Introduced into a barley-soil microcosm, the biosensor could report decreasing oxygen concentrations in the rhizosphere for a 6-day period. When the water content in the microcosm was raised from 60% to 85% of field capacity, expression of the reporter gene was elevated about twofold above a basal level after 2 days of incubation, suggesting that a water content of 85% caused mild anoxia. Increased compaction of the soil was shown to have a faster and more dramatic effect on the expression of the oxygen reporter than soil water content alone, indicating that factors other than the water-filled pore space influenced the oxygen status of the soil. These experiments illustrate the utility of the biosensor for detecting low oxygen concentrations in the rhizosphere and other soil habitats.
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Agricultural soils can act as a source or sink of atmospheric C, according to the soil management. This long-term experiment (22 years) was evaluated during 30 days in autumn, to quantify the effect of tillage systems (conventional tillage-CT and no-till-NT) on the soil CO2-C flux in a Rhodic Hapludox in Rio Grande do Sul State, Southern Brazil. A closed-dynamic system (Flux Chamber 6400-09, Licor) and a static system (alkali absorption) were used to measure soil CO2-C flux immediately after soybean harvest. Soil temperature and soil moisture were measured simultaneously with CO2-C flux, by Licor-6400 soil temperature probe and manual TDR, respectively. During the entire month, a CO2-C emission of less than 30 % of the C input through soybean crop residues was estimated. In the mean of a 30 day period, the CO2-C flux in NT soil was similar to CT, independent of the chamber type used for measurements. Differences in tillage systems with dynamic chamber were verified only in short term (daily evaluation), where NT had higher CO2-C flux than CT at the beginning of the evaluation period and lower flux at the end. The dynamic chamber was more efficient than the static chamber in capturing variations in CO2-C flux as a function of abiotic factors. In this chamber, the soil temperature and the water-filled pore space (WFPS), in the NT soil, explained 83 and 62 % of CO2-C flux, respectively. The Q10 factor, which evaluates CO2-C flux dependence on soil temperature, was estimated as 3.93, suggesting a high sensitivity of the biological activity to changes in soil temperature during fall season. The CO2-C flux measured in a closed dynamic chamber was correlated with the static alkali adsorption chamber only in the NT system, although the values were underestimated in comparison to the other, particularly in the case of high flux values. At low soil temperature and WFPS conditions, soil tillage caused a limited increase in soil CO2-C flux.
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Nitrous oxide (N2O) is the most important non-CO2 greenhouse gas and soil management systems should be evaluated for their N2O mitigation potential. This research evaluated a long-term (22 years) experiment testing the effect of soil management systems on N2O emissions in the postharvest period (autumn) from a subtropical Rhodic Hapludox at the research center FUNDACEP, in Cruz Alta, state of Rio Grande do Sul. Three treatments were evaluated, one under conventional tillage with soybean residues (CTsoybean) and two under no-tillage with soybean (NTsoybean) and maize residues (NTmaize). N2O emissions were measured eight times within 24 days (May 2007) using closed static chambers. Gas flows were obtained based on the relations between gas concentrations in the chamber at regular intervals (0, 15, 30, 45 min) analyzed by gas chromatography. After soybean harvest, accumulated N2O emissions in the period were approximately three times higher in the untilled soil (164 mg m-2 N) than under CT (51 mg m-2 N), with a short-lived N2O peak of 670 mg m-2 h-1 N. In contrast, soil N2O emissions in NT were lower after maize than after soybean, with a N2O peak of 127 g m-2 h-1 N. The multivariate analysis of N2O fluxes and soil variables, which were determined simultaneously with air sampling, demonstrated that the main driving variables of soil N2O emissions were soil microbial activity, temperature, water-filled pore space, and NO3- content. To replace soybean monoculture, crop rotation including maize must be considered as a strategy to decrease soil N2O emissions from NT soils in Southern Brazil in a Autumn.
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Nitrogen fertilizers increase the nitrous oxide (N2O) emission and can reduce the methane (CH4) oxidation from agricultural soils. However, the magnitude of this effect is unknown in Southern Brazilian edaphoclimatic conditions, as well as the potential of different sources of mineral N fertilizers in such an effect. The aim of this study was to investigate the effects of different mineral N sources (urea, ammonium sulphate, calcium nitrate, ammonium nitrate, Uran, controlled- release N fertilizer, and urea with urease inhibitor) on N2O and CH4 fluxes from Gleysol in the South of Brazil (Porto Alegre, RS), in comparison to a control treatment without a N application. The experiment was arranged in a randomized block with three replications, and the N fertilizer was applied to corn at the V5 growth stage. Air samples were collected from a static chambers for 15 days after the N application and the N2O and CH4 concentration were determined by gas chromatography. The topmost emissions occurred three days after the N fertilizer application and ranged from 187.8 to 8587.4 µg m-2 h-1 N. The greatest emissions were observed for N-nitric based fertilizers, while N sources with a urease inhibitor and controlled release N presented the smallest values and the N-ammonium and amidic were intermediate. This peak of N2O emissions was related to soil NO3--N (R² = 0.56, p < 0.08) when the soil water-filled pore space was up to 70 % and it indicated that N2O was predominantly produced by a denitrification process in the soil. Soil CH4 fluxes ranged from -30.1 µg m-2 h-1 C (absorption) to +32.5 µg m-2 h-1 C (emission), and the accumulated emission in the period was related to the soil NH4+-N concentration (R² = 0.82, p < 0.001), probably due to enzymatic competition between nitrification and metanotrophy processes. Despite both of the gas fluxes being affected by N fertilizers, in the average of the treatments, the impact on CH4 emission (0.2 kg ha-1 equivalent CO2-C ) was a hundredfold minor than for N2O (132.8 kg ha-1 equivalent CO2-C). Accounting for the N2O and CH4 emissions plus energetic costs of N fertilizers of 1.3 kg CO2-C kg-1 N regarding the manufacture, transport and application, we estimated an environmental impact of N sources ranging from 220.4 to 664.5 kg ha-1 CO2 -C , which can only be partially offset by C sequestration in the soil, as no study in South Brazil reported an annual net soil C accumulation rate larger than 160 kg ha-1 C due to N fertilization. The N2O mitigation can be obtained by the replacement of N-nitric sources by ammonium and amidic fertilizers. Controlled release N fertilizers and urea with urease inhibitor are also potential alternatives to N2O emission mitigation to atmospheric and systematic studies are necessary to quantify their potential in Brazilian agroecosystems.
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The soil CO2 emission has high spatial variability because it depends strongly on soil properties. The purpose of this study was to (i) characterize the spatial variability of soil respiration and related properties, (ii) evaluate the accuracy of results of the ordinary kriging method and sequential Gaussian simulation, and (iii) evaluate the uncertainty in predicting the spatial variability of soil CO2 emission and other properties using sequential Gaussian simulations. The study was conducted in a sugarcane area, using a regular sampling grid with 141 points, where soil CO2 emission, soil temperature, air-filled pore space, soil organic matter and soil bulk density were evaluated. All variables showed spatial dependence structure. The soil CO2 emission was positively correlated with organic matter (r = 0.25, p < 0.05) and air-filled pore space (r = 0.27, p < 0.01) and negatively with soil bulk density (r = -0.41, p < 0.01). However, when the estimated spatial values were considered, the air-filled pore space was the variable mainly responsible for the spatial characteristics of soil respiration, with a correlation of 0.26 (p < 0.01). For all variables, individual simulations represented the cumulative distribution functions and variograms better than ordinary kriging and E-type estimates. The greatest uncertainties in predicting soil CO2 emission were associated with areas with the highest estimated values, which produced estimates from 0.18 to 1.85 t CO2 ha-1, according to the different scenarios considered. The knowledge of the uncertainties generated by the different scenarios can be used in inventories of greenhouse gases, to provide conservative estimates of the potential emission of these gases.