163 resultados para soil rhizobia population


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Glucose-6-phosphate dehydrogenase (G6PD) deficiency is seen at a higher frequency in many national and ethnic groups in areas of current or former malaria endemicity. A screening programme undertaken to evaluate the gene frequencies for this deficiency in the highly inbred South Indian population of Karnataka revealed that of the 5140 neonates screened, 7.8% were G6PD deficient with no correlation between the reported level of inbreeding and enzyme deficiency. An interesting finding was the equal number of male (198) and female (207) individuals, with G6PD activity of less than 3 IU. The possible implications of this finding with regard to the expression of G6PD gene is discussed.

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Glucose-6-phosphate dehydrogenase (G6PD) is coded by a gene on the X-chromosome. Earlier studies have shown that the South Indian population has a high incidence of this enzyme deficiency. The electrophoretic mobility, pH optimum and the K-m values for G6PD from normal and variant individuals were identical. However, the specific activity of the variant enzyme was 8 times less compared to the value of the normal enzyme. Western blot analysis of partially purified G6PD from normal and variant individuals performed using equal amounts of total protein showed that the variant protein was 3 times less in concentration. Similar analysis performed using protein corresponding to equal enzyme activity units in the normal and variant samples showed that the variant enzyme was 2.25 times less efficient compared to the normal enzyme. RNA dot blot analysis using full length G6PD cDNA probe (PGDT5B, a kind gift from Prof. L Luzzatto) revealed that lymphocytes from normal and variant individuals had equal amounts of G6PD specific mRNA.

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Beavers are often found to be in conflict with human interests by creating nuisances like building dams on flowing water (leading to flooding), blocking irrigation canals, cutting down timbers, etc. At the same time they contribute to raising water tables, increased vegetation, etc. Consequently, maintaining an optimal beaver population is beneficial. Because of their diffusion externality (due to migratory nature), strategies based on lumped parameter models are often ineffective. Using a distributed parameter model for beaver population that accounts for their spatial and temporal behavior, an optimal control (trapping) strategy is presented in this paper that leads to a desired distribution of the animal density in a region in the long run. The optimal control solution presented, imbeds the solution for a large number of initial conditions (i.e., it has a feedback form), which is otherwise nontrivial to obtain. The solution obtained can be used in real-time by a nonexpert in control theory since it involves only using the neural networks trained offline. Proper orthogonal decomposition-based basis function design followed by their use in a Galerkin projection has been incorporated in the solution process as a model reduction technique. Optimal solutions are obtained through a "single network adaptive critic" (SNAC) neural-network architecture.

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An interaction analysis of an axially loaded single pile and pile group with and without a pile cap in a layered soil medium has been investigated using the two-dimensional photoelastic method. A study of the pile or pile group behaviour has been made, varying the pile cap thickness as well as the embedded length of the pile in the hard stratum. The shear stress distribution along the pile-soil interface, non-dimensionalized settlement values of the single pile and the interaction factor for the pile group have been presented. Wherever possible, the results of the present analysis have been compared with available numerical solutions.

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This study describes two machine learning techniques applied to predict liquefaction susceptibility of soil based on the standard penetration test (SPT) data from the 1999 Chi-Chi, Taiwan earthquake. The first machine learning technique which uses Artificial Neural Network (ANN) based on multi-layer perceptions (MLP) that are trained with Levenberg-Marquardt backpropagation algorithm. The second machine learning technique uses the Support Vector machine (SVM) that is firmly based on the theory of statistical learning theory, uses classification technique. ANN and SVM have been developed to predict liquefaction susceptibility using corrected SPT (N-1)(60)] and cyclic stress ratio (CSR). Further, an attempt has been made to simplify the models, requiring only the two parameters (N-1)(60) and peck ground acceleration (a(max)/g)], for the prediction of liquefaction susceptibility. The developed ANN and SVM models have also been applied to different case histories available globally. The paper also highlights the capability of the SVM over the ANN models.

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Competition between seeds within a fruit for parental resources is described using one-locus-two-allele models. While a �normal� allele leads to an equitable distribution of resources between seeds (a situation which also corresponds to the parental optimum), the �selfish� allele is assumed to cause the seed carrying it to usurp a higher proportion of the resources. The outcome of competition between �selfish� alleles is also assumed to lead to an asymmetric distribution of resources, the �winner� being chosen randomly. Conditions for the spread of an initially rare selfish allele and the optimal resource allocation corresponding to the evolutionarily stable strategy, derived for species with n-seeded fruits, are in accordance with expectations based on Hamilton�s inclusive fitness criteria. Competition between seeds is seen to be most intense when there are only two seeds, and decreases with increasing number of seeds, suggesting that two-seeded fruits would be rarer than one-seeded or many-seeded ones. Available data from a large number of plant species are consistent with this prediction of the model.

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As a seepage barrier slurry trench material should have a relatively low coefficient of permeability, in the range of 10(-7) cm/s, and at the same time should be compatible with surrounding material with regard to compressibility. Although bentonite-sand/soil mixes are used widely, there is no specific engineering approach to proportion these mixes that satisfies the above practical requirements. In this paper, a generalized approach is presented for predicting the permeability and compressibility characteristics of mixes with minimum input parameters. This approach will be helpful in proportioning mixes and predicting corresponding changes in engineering behavior. It is possible to proportion a mix to arrive at the required compressibility without affecting the permeability. This is explained using an illustrative example.

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This paper critically appraises the limitations of the liquid-limit water content of clayey soils determined conventionally either by percussion cup or by the cone penetration method. It is shown that the conventional liquid limit and plastic limit are arbitrary, strength-based water contents and that they cannot represent the plasticity limits, and that the state of the soil-water system at the conventional liquid limit does not correspond to a stress-free reference state. The present investigation identifies three characteristic limiting water contents for a soil-water system which have well-defined, unique mechanisms controlling them, namely the free swell limit, settling limit and shrinkage limit. Simple procedures for the determination of the free swell limit and settling limit of natural soils are presented. The settling limit is shown to be the 'real liquid limit' of any clayey soil. With a number of experimental illustrations, it is clearly shown that the settling limit represents the maximum water-holding capacity of clayey soils and that it corresponds to the stress-free reference state.

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The soil moisture characteristic (SMC) forms an important input to mathematical models of water and solute transport in the unsaturated-soil zone. Owing to their simplicity and ease of use, texture-based regression models are commonly used to estimate the SMC from basic soil properties. In this study, the performances of six such regression models were evaluated on three soils. Moisture characteristics generated by the regression models were statistically compared with the characteristics developed independently from laboratory and in-situ retention data of the soil profiles. Results of the statistical performance evaluation, while providing useful information on the errors involved in estimating the SMC, also highlighted the importance of the nature of the data set underlying the regression models. Among the models evaluated, the one possessing an underlying data set of in-situ measurements was found to be the best estimator of the in-situ SMC for all the soils. Considerable errors arose when a textural model based on laboratory data was used to estimate the field retention characteristics of unsaturated soils.

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Geophysical methods are becoming more popular nowadays in the field of hydrology due to their time and space efficiency. So an attempt has been made here to relate electrical resistivity with soil moisture content in the field. The experiments were carried out in an experimental watershed `Mulehole' in southern India, which is a forested watershed with approximately 80% red soil. Five auger holes were drilled to perform the soil moisture and electrical resistivity measurements in a toposequence having red and black soils, with sandy weathered soil at the bottom. Soil moisture was measured using neutron probe and electrical resistivity was measured using electrical logging tool. The results indicate that electrical resistivity measurements can be used to measure soil moisture content for red soils only.

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A discussion of a technical note with the aforementioned title by Day and Marsh, published in this journal (Volume 121, Number 7, July 1995), is presented. Discussers Robinson and Allam assert that the authors' application of the pore-pressure parameter A to predict and quantify swell or collapse of compacted soils is hard to use because the authors visualize the collapse-swell phenomenon to occur in compacted soils broadly classified as sands and clays. The literature demonstrates that mineralogy has an important role in the volume change behavior of fine-grained soils. Robinson and Allam state that the A-value measurements may not completely predict the type of volume change anticipated in compacted soils on soaking without soil clay mineralogy details. Discussion is followed by closure from the authors.

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Thermal power stations using pulverized coal as fuel generate large quantities of fly ash as a byproduct, which has created environmental and disposal problems. Using fly ash for gainful applications will solve these problems. Among the various possible uses for fly ash, the most massive and effective utilization is in geotechnical engineering applications like backfill material, construction of embankments, as a subbase material, etc. A proper understanding of fly ash-soil mixes is likely to provide viable solutions for its large-scale utilization. Earlier studies initiated in the laboratory have resulted in a good understanding of the California Bearing Ratio (CBR) behavior of fly ash-soil mixes. Subsequently, in order to increase the CBR value, cement has been tried as an additive to fly ash-soil mixes. This paper reports the results.