973 resultados para Soil types


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Increasing threat of terrorism highlights the importance of enhancing the resilience of underground tunnels to all hazards. This paper develops, applies and compares the Arbitrary Lagrangian Eulerian (ALE) and Smooth Particle Hydrodynamics (SPH) techniques to treat the response of buried tunnels to surface explosions. The results and outcomes of the two techniques were compared, along with results from existing test data. The comparison shows that the ALE technique is a better method for describing the tunnel response for above ground explosion with regards to modeling accuracy and computational efficiency. The ALE technique was then applied to treat the blast response of different types of segmented bored tunnels buried in dry sand. Results indicate that the most used modern ring type segmented tunnels were more flexible for in-plane response, however, they suffered permanent drifts between the rings. Hexagonal segmented tunnels responded with negligible drifts in the longitudinal direction, but the magnitudes of in-plane drifts were large and hence hazardous for the tunnel. Interlocking segmented tunnels suffered from permanent drifts in both the longitudinal and transverse directions. Multi-surface radial joints in both the hexagonal and interlocking segments affected the flexibility of the tunnel in the transverse direction. The findings offer significant new information in the behavior of segmented bored tunnels to guide their future implementation in civil engineering applications.

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Background: Individuals who fear falling may restrict themselves from performing certain activities and may increase their risk of falling. Such fear, reflected in the form of falls efficacy, has been measured in only a small number of studies measuring the effectiveness of exercise interventions in the elderly. This may be due to the various types of exercise that can be performed. Hence the effectiveness of exercise on falls efficacy is relatively understudied. Therefore, there is a need to measure falls efficacy as an outcome variable when conducting exercise interventions in the elderly. Methods: A total of 43 elderly community-dwelling volunteers were recruited and randomly allocated to a conventional exercise intervention, a holistic exercise intervention, or a control group. The interventions were performed 2 days per week for 10 weeks. Falls efficacy was measured at baseline and at the completion of the interventions using the Modified Falls Efficacy Scale (MFES). Results: Within group comparisons between baseline and follow-up indicated no significant improvements in falls efficacy, however, the difference for the conventional exercise group approached statistical significance (baseline 8.9 to follow-up 9.3; P = 0.058). Within group comparisons of mean difference MFES scores showed a significant difference between the conventional exercise group and the control group (conventional exercise group 0.4 vs control group −0.6; P < 0.05). Conclusion: Given the lack of significant improvements in falls efficacy found for any of the groups, it cannot be concluded whether a conventional or a holistic exercise intervention is the best approach for improving falls efficacy. It is possible that the characteristics of the exercise interventions including specificity, intensity, frequency and duration need to be manipulated if the purpose is to bring about improvements in falls efficacy.

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Semantic perception and object labeling are key requirements for robots interacting with objects on a higher level. Symbolic annotation of objects allows the usage of planning algorithms for object interaction, for instance in a typical fetchand-carry scenario. In current research, perception is usually based on 3D scene reconstruction and geometric model matching, where trained features are matched with a 3D sample point cloud. In this work we propose a semantic perception method which is based on spatio-semantic features. These features are defined in a natural, symbolic way, such as geometry and spatial relation. In contrast to point-based model matching methods, a spatial ontology is used where objects are rather described how they "look like", similar to how a human would described unknown objects to another person. A fuzzy based reasoning approach matches perceivable features with a spatial ontology of the objects. The approach provides a method which is able to deal with senor noise and occlusions. Another advantage is that no training phase is needed in order to learn object features. The use-case of the proposed method is the detection of soil sample containers in an outdoor environment which have to be collected by a mobile robot. The approach is verified using real world experiments.

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Technological system evolution is marked by the uneven evolution of constituent sub-systems. Subsequently, system evolution is hampered by the resulting state of unevenness, or reverse salience, which results from the presence of the sub-system that delivers the lowest level of performance with respect to other sub-systems, namely, the reverse salient. In this paper, we develop absolute and proportional performance gap measures of reverse salience and, in turn, derive a typology of reverse salients that distinguishes alternative dynamics of change in the evolving system. We subsequently demonstrate the applicability of the measures and the typology through an illustrative empirical study of the PC (personal computer) technological system that functions as a gaming platform. Our empirical analysis demonstrates that patterns of temporal dynamics can be distinguished with the measurement of reverse salience, and that distinct paths of technological system evolution can be identified as different types of reverse salients emerge over time.

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Management of sodic soils under irrigation often requires application of chemical ameliorants to improve permeability combined with leaching of excess salts. Modeling irrigation, soil treatments, and leaching in these sodic soils requires a model that can adequately represent the physical and chemical changes in the soil associated with the amelioration process. While there are a number of models that simulate reactive solute transport, UNSATCHEM and HYDRUS-1D are currently the only models that also include an ability to simulate the impacts of soil chemistry on hydraulic conductivity. Previous researchers have successfully applied these models to simulate amelioration experiments on a sodic loam soil. To further gauge their applicability, we extended the previous work by comparing HYDRUS simulations of sodic soil amelioration with the results from recently published laboratory experiments on a more reactive, repacked sodic clay soil. The general trends observed in the laboratory experiments were able to be simulated using HYDRUS. Differences between measured and simulated results were attributed to the limited flexibility of the function that represents chemistry-dependent hydraulic conductivity in HYDRUS. While improvements in the function could be made, the present work indicates that HYDRUS-UNSATCHEM captures the key changes in soil hydraulic properties that occur during sodic clay soil amelioration and thus extends the findings of previous researchers studying sodic loams.

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Amelioration of sodic soils is commonly achieved by applying gypsum, which increases soil hydraulic conductivity by altering soil chemistry. The magnitude of hydraulic conductivity increases expected in response to gypsum applications depends on soil properties including clay content, clay mineralogy, and bulk density. The soil analyzed in this study was a kaolinite rich sodic clay soil from an irrigated area of the Lower Burdekin coastal floodplain in tropical North Queensland, Australia. The impact of gypsum amelioration was investigated by continuously leaching soil columns with a saturated gypsum solution, until the hydraulic conductivity and leachate chemistry stabilized. Extended leaching enabled the full impacts of electrolyte effects and cation exchange to be determined. For the columns packed to 1.4 g/cm3, exchangeable sodium concentrations were reduced from 5.0 ± 0.5 mEq/100 g to 0.41 ± 0.06 mEq/100 g, exchangeable magnesium concentrations were reduced from 13.9 ± 0.3 mEq/100 g to 4.3 ± 2.12 mEq/100 g, and hydraulic conductivity increased to 0.15 ± 0.04 cm/d. For the columns packed to 1.3 g/cm3, exchangeable sodium concentrations were reduced from 5.0 ± 0.5 mEq/100 g to 0.51 ± 0.03 mEq/100 g, exchangeable magnesium concentrations were reduced from 13.9 ± 0.3 mEq/100 g to 0.55 ± 0.36 mEq/100 g, and hydraulic conductivity increased to 0.96 ± 0.53 cm/d. The results of this study highlight that both sodium and magnesium need to be taken into account when determining the suitability of water quality for irrigation of sodic soils and that soil bulk density plays a major role in controlling the extent of reclamation that can be achieved using gypsum applications.

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The use of nitrification inhibitors, in combination with ammonium based fertilisers, has been promoted recently as an effective method to reduce nitrous oxide (N2O) emissions from fertilised agricultural fields, whilst increasing yield and nitrogen use efficiency. Vegetable cropping systems are often characterised by high inputs of nitrogen fertiliser and consequently elevated emissions of nitrous oxide (N2O) can be expected. However, to date only limited data is available on the use of nitrification inhibitors in sub-tropical vegetable systems. A field experiment investigated the effect of the nitrification inhibitors (DMPP & 3MP+TZ) on N2O emissions and yield from a typical vegetable production system in sub-tropical Australia. Soil N2O fluxes were monitored continuously over an entire year with a fully automated system. Measurements were taken from three subplots for each treatment within a randomized complete blocks design. There was a significant inhibition effect of DMPP and 3MP+TZ on N2O emissions and soil mineral N content directly following the application of the fertiliser over the vegetable cropping phase. However this mitigation was offset by elevated N2O emissions from the inhibitor treatments over the post-harvest fallow period. Cumulative annual N2O emissions amounted to 1.22 kg-N/ha, 1.16 kg-N/ha, 1.50 kg-N/ha and 0.86 kg-N/ha in the conventional fertiliser (CONV), the DMPP treatment, the 3MP+TZ treatment and the zero fertiliser (0N) respectively. Corresponding fertiliser induced emission factors (EFs) were low with only 0.09 - 0.20% of the total applied fertiliser lost as N2O. There was no significant effect of the nitrification inhibitors on yield compared to the CONV treatment for the three vegetable crops (green beans, broccoli, lettuce) grown over the experimental period. This study highlights that N2O emissions from such vegetable cropping system are primarily controlled by post-harvest emissions following the incorporation of vegetable crop residues into the soil. It also shows that the use of nitrification inhibitors can lead to elevated N2O emissions by storing N in the soil profile that is available to soil microbes during the decomposition of the vegetable residues over the post-harvest phase. Hence the use of nitrification inhibitors in vegetable systems has to be treated carefully and fertiliser rates need to be adjusted to avoid excess soil nitrogen during the postharvest phase.

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The microbial mediated production of nitrous oxide (N2O) and its reduction to dinitrogen (N2) via denitrification represents a loss of nitrogen (N) from fertilised agro-ecosystems to the atmosphere. Although denitrification has received great interest by biogeochemists in the last decades, the magnitude of N2lossesand related N2:N2O ratios from soils still are largely unknown due to methodical constraints. We present a novel 15N tracer approach, based on a previous developed tracer method to study denitrification in pure bacterial cultures which was modified for the use on soil incubations in a completely automated laboratory set up. The method uses a background air in the incubation vessels that is replaced with a helium-oxygen gas mixture with a 50-fold reduced N2 background (2 % v/v). This method allows for a direct and sensitive quantification of the N2 and N2O emissions from the soil with isotope-ratio mass spectrometry after 15N labelling of denitrification N substrates and minimises the sensitivity to the intrusion of atmospheric N2 at the same time. The incubation set up was used to determine the influence of different soil moisture levels on N2 and N2O emissions from a sub-tropical pasture soil in Queensland/Australia. The soil was labelled with an equivalent of 50 μg-N per gram dry soil by broadcast application of KNO3solution (4 at.% 15N) and incubated for 3 days at 80% and 100% water filled pore space (WFPS), respectively. The headspace of the incubation vessel was sampled automatically over 12hrs each day and 3 samples (0, 6, and 12 hrs after incubation start) of headspace gas analysed for N2 and N2O with an isotope-ratio mass spectrometer (DELTA V Plus, Thermo Fisher Scientific, Bremen, Germany(. In addition, the soil was analysed for 15N NO3- and NH4+ using the 15N diffusion method, which enabled us to obtain a complete N balance. The method proved to be highly sensitive for N2 and N2O emissions detecting N2O emissions ranging from 20 to 627 μN kg-1soil-1hr-1and N2 emissions ranging from 4.2 to 43 μN kg-1soil-1hr-1for the different treatments. The main end-product of denitrification was N2O for both water contents with N2 accounting for 9% and 13% of the total denitrification losses at 80% and 100%WFPS, respectively. Between 95-100% of the added 15N fertiliser could be recovered. Gross nitrification over the 3 days amounted to 8.6 μN g-1 soil-1 and 4.7 μN g-1 soil-1, denitrification to 4.1 μN g-1 soil-1 and 11.8 μN g-1 soil-1at 80% and 100%WFPS, respectively. The results confirm that the tested method allows for a direct and highly sensitive detection of N2 and N2O fluxes from soils and hence offers a sensitive tool to study denitrification and N turnover in terrestrial agro-ecosystems.

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Introducing nitrogen (N)-fixing legumes into cereal-based crop rotations reduces synthetic fertiliser-N use and may mitigate soil emissions of nitrous oxide (N2O). Current IPCC calculations assume 100% of legume biomass N as the anthropogenic N input and use 1% of this as an emission factor (EF)—the percentage of input N emitted as N2O. However, legumes also utilise soil inorganic N, so legume-fixed N is typically less than 100% of legume biomass N. In two field experiments, we measured soil N2O emissions from a black Vertosol in sub-tropical Australia for 12 months after sowing of chickpea (Cicer arietinum L.), canola (Brassica napus L.), faba bean (Vicia faba L.), and field pea (Pisum sativum L.). Cumulative N2O emissions from N-fertilised canola (624 g N2O-N ha−1) greatly exceeded those from chickpea (127 g N2O-N ha−1) in Experiment 1. Similarly, N2O emitted from canola (385 g N2O-N ha−1) in Experiment 2 was significantly greater than chickpea (166 g N2O-N ha−1), faba bean (166 g N2O-N ha−1) or field pea (135 g N2O-N ha−1). Highest losses from canola were recorded during the growing season, whereas 75% of the annual N2O losses from the legumes occurred post-harvest. Legume N2-fixation provided 37–43% (chickpea), 54% (field pea) and 64% (faba bean) of total plant biomass N. Using only fixed-N inputs, we calculated EFs for chickpea (0.13–0.31%), field pea (0.18%) and faba bean (0.04%) that were significantly less than N-fertilised canola (0.48–0.78%) (P < 0.05), suggesting legume-fixed N is a less emissive form of N input to the soil than fertiliser N. Inputs of legume-fixed N should be more accurately quantified to properly gauge the potential for legumes to mitigate soil N2O emissions. EF’s from legume crops need to be revised and should include a factor for the proportion of the legume’s N derived from the atmosphere.

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Soil microorganisms are critical to ecosystem functioning and the maintenance of soil fertility. However, despite global increases in the inputs of nitrogen (N) and phosphorus (P) to ecosystems due to human activities, we lack a predictive understanding of how microbial communities respond to elevated nutrient inputs across environmental gradients. Here we used high-throughput sequencing of marker genes to elucidate the responses of soil fungal, archaeal, and bacterial communities using an N and P addition experiment replicated at 25 globally distributed grassland sites. We also sequenced metagenomes from a subset of the sites to determine how the functional attributes of bacterial communities change in response to elevated nutrients. Despite strong compositional differences across sites, microbial communities shifted in a consistent manner with N or P additions, and the magnitude of these shifts was related to the magnitude of plant community responses to nutrient inputs. Mycorrhizal fungi and methanogenic archaea decreased in relative abundance with nutrient additions, as did the relative abundances of oligotrophic bacterial taxa. The metagenomic data provided additional evidence for this shift in bacterial life history strategies because nutrient additions decreased the average genome sizes of the bacterial community members and elicited changes in the relative abundances of representative functional genes. Our results suggest that elevated N and P inputs lead to predictable shifts in the taxonomic and functional traits of soil microbial communities, including increases in the relative abundances of faster-growing, copiotrophic bacterial taxa, with these shifts likely to impact belowground ecosystems worldwide.

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An understanding of the influence of soil chemistry on soil hydraulic properties is of critical importance for the management of sodic soils under irrigation. The hydraulic conductivity of sodic soils has been shown to be affected by properties of the applied solution including pH (Suarez et al. 1984), sodicity and salt concentration (McNeal and Coleman 1966). The changes in soil hydraulic conductivity are the result of changes in the spacing between clay layers in response to changes in soil solution chemistry. While the importance o f soil chemistry in controlling hydraulic conductivity is known, the exact impacts of sodic soil amelioration on hydraulic conductivity and deep drainage at a given location are difficult to predict. This is because the relationships between soil chemical factors and hydraulic conductivity are soil specific and because local site specific factors also need to be considered to determine the actual impacts on deep drainage rates.

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Membrane proteins play important roles in many biochemical processes and are also attractive targets of drug discovery for various diseases. The elucidation of membrane protein types provides clues for understanding the structure and function of proteins. Recently we developed a novel system for predicting protein subnuclear localizations. In this paper, we propose a simplified version of our system for predicting membrane protein types directly from primary protein structures, which incorporates amino acid classifications and physicochemical properties into a general form of pseudo-amino acid composition. In this simplified system, we will design a two-stage multi-class support vector machine combined with a two-step optimal feature selection process, which proves very effective in our experiments. The performance of the present method is evaluated on two benchmark datasets consisting of five types of membrane proteins. The overall accuracies of prediction for five types are 93.25% and 96.61% via the jackknife test and independent dataset test, respectively. These results indicate that our method is effective and valuable for predicting membrane protein types. A web server for the proposed method is available at http://www.juemengt.com/jcc/memty_page.php

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Chlamydia pecorum is globally associated with several ovine diseases including keratoconjunctivitis and polyarthritis. The exact relationship between the variety of C. pecorum strains reported and the diseases described in sheep remains unclear, challenging efforts to accurately diagnose and manage infected flocks. In the present study, we applied C. pecorum multi-locus sequence typing (MLST) to C. pecorum positive samples collected from sympatric flocks of Australian sheep presenting with conjunctivitis, conjunctivitis with polyarthritis, or polyarthritis only and with no clinical disease (NCD) in order to elucidate the exact relationships between the infecting strains and the range of diseases. Using Bayesian phylogenetic and cluster analyses on 62 C. pecorum positive ocular, vaginal and rectal swab samples from sheep presenting with a range of diseases and in a comparison to C. pecorum sequence types (STs) from other hosts, one ST (ST 23) was recognised as a globally distributed strain associated with ovine and bovine diseases such as polyarthritis and encephalomyelitis. A second ST (ST 69) presently only described in Australian animals, was detected in association with ovine as well as koala chlamydial infections. The majority of vaginal and rectal C. pecorum STs from animals with NCD and/or anatomical sites with no clinical signs of disease in diseased animals, clustered together in a separate group, by both analyses. Furthermore, 8/13 detected STs were novel. This study provides a platform for strain selection for further research into the pathogenic potential of C. pecorum in animals and highlights targets for potential strain-specific diagnostic test development.

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A method for the determination of imidacloprid in paddy water and soil was developed using liquid chromatography electrospray ionization-tandem mass spectrometry (LC/ESI-MS/MS). Separation of imidacloprid was carried out on a Shimadzu C18 column (150 mm × 4.6 mm, 4.6 μm) with an acetonitrile?water (50 : 50, v/v) mobile phase containing 0.1% of acetic acid. The flow rate was 0.3 mL/min in isocratic mode. The product ion at 209 m/z was selected for quantification in multiple-reaction monitoring scan mode. Imidacloprid residues in soil were extracted by a solid-liquid extraction method with acetonitrile. Water samples were filtered and directly injected for analysis without extraction. Detection limits of 0.5 μg/kg and 0.3 μg/L were achieved for soil and water samples, respectively. The method had recoveries of 90 ± 2% (n = 4) for soil samples and 100 ± 2% (n = 4) for water samples. A linear relationship was observed throughout the investigated range of concentrations (1-200 μg/L), with the correlation coefficients ranging from 0.999 to 1.000. © Pleiades Publishing, Ltd., 2010.

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The micro paddy lysimeter (MPL) was developed and evaluated for its performance to simulate solute transport in paddy environment under laboratory conditions. MPLs were constructed using soil collected from Field Museum Honmachi of Tokyo University of Agriculture and Technology, Japan. For the physical characteristics of the hardpan layer, parameters such as thickness, and soil aggregate size, affecting the percolation rate were studied. For the plow layer, two types of plow soils, sieved and un-sieved soils were compared. The sieved soil plow layer was produced by mixing air-dried soils of different aggregate sizes of D > 9.50, 9.50 ≥ D > 4.75, 4.75 ≥ D > 2.0 mm and D ≤ 2.0 mm at 47.1, 19.5, 20.6, and 12.8%, respectively. The un-sieved plow layer soil was directly used after collecting from the field. Inert tracer was applied to ponding water with controlled boundary conditions to evaluate the reproducibility of the soil hydraulic characteristics. HYDRUS-1D was used to evaluate the movement of bromide tracer in the MPL. The proposed conditions of the MPL were that the hardpan layer can be made from soil aggregates smaller than 0.425 mm with 2 cm thickness and that the plow layer can be prepared with sieved or un-sieved soils. With these conditions, the obtained results proved that MPLs can be a useful tool to simulate solute transport in paddy environment.