979 resultados para exponential
Resumo:
Vertically pointing Doppler radar has been used to study the evolution of ice particles as they sediment through a cirrus cloud. The measured Doppler fall speeds, together with radar-derived estimates for the altitude of cloud top, are used to estimate a characteristic fall time tc for the `average' ice particle. The change in radar reflectivity Z is studied as a function of tc, and is found to increase exponentially with fall time. We use the idea of dynamically scaling particle size distributions to show that this behaviour implies exponential growth of the average particle size, and argue that this exponential growth is a signature of ice crystal aggregation.
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In this paper we investigate the use of the perfectly matched layer (PML) to truncate a time harmonic rough surface scattering problem in the direction away from the scatterer. We prove existence and uniqueness of the solution of the truncated problem as well as an error estimate depending on the thickness and composition of the layer. This global error estimate predicts a linear rate of convergence (under some conditions on the relative size of the real and imaginary parts of the PML function) rather than the usual exponential rate. We then consider scattering by a half-space and show that the solution of the PML truncated problem converges globally at most quadratically (up to logarithmic factors), providing support for our general theory. However we also prove exponential convergence on compact subsets. We continue by proposing an iterative correction method for the PML truncated problem and, using our estimate for the PML approximation, prove convergence of this method. Finally we provide some numerical results in 2D.(C) 2008 IMACS. Published by Elsevier B.V. All rights reserved.
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Soil contamination by arsenic (As) presents a hazard in many countries and there is a need for techniques to minimize As uptake by plants. A proposed in situ remediation method was tested by growing lettuce (Lactuca sativa L. cv. Kermit) in a greenhouse pot experiment on soil that contained 577 mg As kg(-1), taken from a former As smelter site. All combinations of iron (Fe) oxides, at concentrations of 0.00, 0.22, 0.54, and 1.09% (w/w), and lime, at concentrations of 0.00, 0.27, 0.68, and 1.36% (w/w), were tested in a factorial design. To create the treatments, field-moist soil, commercial-grade FeSO4, and ground agricultural lime were mixed and stored for one week, allowing Fe oxides to precipitate. Iron oxides gave highly significant (P < 0.001) reductions in lettuce As concentrations, down to 11% of the lettuce As concentration for untreated soil. For the Fe oxides and lime treatment combinations where soil pH was maintained nearly constant, the lettuce As concentration declined in an exponential relationship with increasing FeSO4 application rate and lettuce yield was almost unchanged. Iron oxides applied at a concentration of 1.09% did not give significantly lower lettuce As concentrations than the 0.54% treatment. Simultaneous addition of lime with FeSO4 was essential. Ferrous sulfate with insufficient lime lowered soil pH and caused mobilization of Al, Ba, Co, Cr, Cu, Fe, K, Mg, Mn, Na, Ni, Pb, Sr, and Zn. At the highest Fe oxide to lime ratios, Mn toxicity caused severe yield loss.
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There have been only a few studies of potassium (K) losses from grassland systems, and little is known about their dynamics, especially in relation to nitrogen (N) management. A study was performed during the autumn and winter of 1999 and 2000 to understand the effects of N and drainage on the dynamics of K leaching on a hillslope grassland soil in southwestern England. Two N application rates were studied (0 and 280 kg N ha(-1) yr(-1)), both with and without the drainage. Treatments receiving N also received farmyard manure (FM). Higher total K losses and K concentrations in the leachates were found in the N + FM treatments (150 and 185% higher than in 0 N treatments), which were related to K additions in the FM. Drainage reduced K losses by 35% because of an increase in dry matter production and a reduction in overland and preferential flow. The pattern of change in K concentration in the leachates was associated with preferential flow at the beginning of the drainage season and with matrix flow later in winter, and was best described by a double exponential curve. Rainfall intensity and the autumn application of FM were the main determinants of K losses by leaching. The study provided new insights into the relationships between soil hydrology, rainfall, and K leaching and its implications for grassland systems.
Resumo:
Soil contamination by arsenic (As) presents a hazard in many countries and there is a need for techniques to minimize As uptake by plants. A proposed in situ remediation method was tested by growing lettuce (Lactuca sativa L. cv. Kermit) in a greenhouse pot experiment on soil that contained 577 mg As kg(-1), taken from a former As smelter site. All combinations of iron (Fe) oxides, at concentrations of 0.00, 0.22, 0.54, and 1.09% (w/w), and lime, at concentrations of 0.00, 0.27, 0.68, and 1.36% (w/w), were tested in a factorial design. To create the treatments, field-moist soil, commercial-grade FeSO4, and ground agricultural lime were mixed and stored for one week, allowing Fe oxides to precipitate. Iron oxides gave highly significant (P < 0.001) reductions in lettuce As concentrations, down to 11% of the lettuce As concentration for untreated soil. For the Fe oxides and lime treatment combinations where soil pH was maintained nearly constant, the lettuce As concentration declined in an exponential relationship with increasing FeSO4 application rate and lettuce yield was almost unchanged. Iron oxides applied at a concentration of 1.09% did not give significantly lower lettuce As concentrations than the 0.54% treatment. Simultaneous addition of lime with FeSO4 was essential. Ferrous sulfate with insufficient lime lowered soil pH and caused mobilization of Al, Ba, Co, Cr, Cu, Fe, K, Mg, Mn, Na, Ni, Pb, Sr, and Zn. At the highest Fe oxide to lime ratios, Mn toxicity caused severe yield loss.
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This study uses a Granger causality time series modeling approach to quantitatively diagnose the feedback of daily sea surface temperatures (SSTs) on daily values of the North Atlantic Oscillation (NAO) as simulated by a realistic coupled general circulation model (GCM). Bivariate vector autoregressive time series models are carefully fitted to daily wintertime SST and NAO time series produced by a 50-yr simulation of the Third Hadley Centre Coupled Ocean-Atmosphere GCM (HadCM3). The approach demonstrates that there is a small yet statistically significant feedback of SSTs oil the NAO. The SST tripole index is found to provide additional predictive information for the NAO than that available by using only past values of NAO-the SST tripole is Granger causal for the NAO. Careful examination of local SSTs reveals that much of this effect is due to the effect of SSTs in the region of the Gulf Steam, especially south of Cape Hatteras. The effect of SSTs on NAO is responsible for the slower-than-exponential decay in lag-autocorrelations of NAO notable at lags longer than 10 days. The persistence induced in daily NAO by SSTs causes long-term means of NAO to have more variance than expected from averaging NAO noise if there is no feedback of the ocean on the atmosphere. There are greater long-term trends in NAO than can be expected from aggregating just short-term atmospheric noise, and NAO is potentially predictable provided that future SSTs are known. For example, there is about 10%-30% more variance in seasonal wintertime means of NAO and almost 70% more variance in annual means of NAO due to SST effects than one would expect if NAO were a purely atmospheric process.
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To test for magnetic flux buildup in the heliosphere from coronal mass ejections (CMEs), we simulate heliospheric flux as a constant background open flux with a time-varying interplanetary CME (ICME) contribution. As flux carried by ejecta can only contribute to the heliospheric flux budget while it remains closed, the ICME flux opening rate is an important factor. Two separate forms for the ICME flux opening rate are considered: (1) constant and (2) exponentially decaying with time. Coronagraph observations are used to determine the CME occurrence rates, while in situ observations are used to estimate the magnetic flux content of a typical ICME. Both static equilibrium and dynamic simulations, using the constant and exponential ICME flux opening models, require flux opening timescales of ∼50 days in order to match the observed doubling in the magnetic field intensity at 1 AU over the solar cycle. Such timescales are equivalent to a change in the ICME closed flux of only ∼7–12% between 1 and 5 AU, consistent with CSE signatures; no flux buildup results. The dynamic simulation yields a solar cycle flux variation with high variability that matches the overall variability of the observed magnetic field intensity remarkably well, including the double peak forming the Gnevyshev gap.
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A simple theoretical model for the intensification of tropical cyclones and polar lows is developed using a minimal set of physical assumptions. These disturbances are assumed to be balanced systems intensifying through the WISHE (Wind-Induced Surface Heat Exchange) intensification mechanism, driven by surface fluxes of heat and moisture into an atmosphere which is neutral to moist convection. The equation set is linearized about a resting basic state and solved as an initial-value problem. A system is predicted to intensify with an exponential perturbation growth rate scaled by the radial gradient of an efficiency parameter which crudely represents the effects of unsaturated processes. The form of this efficiency parameter is assumed to be defined by initial conditions, dependent on the nature of a pre-existing vortex required to precondition the atmosphere to a state in which the vortex can intensify. Evaluation of the simple model using a primitive-equation, nonlinear numerical model provides support for the prediction of exponential perturbation growth. Good agreement is found between the simple and numerical models for the sensitivities of the measured growth rate to various parameters, including surface roughness, the rate of transfer of heat and moisture from the ocean surface, and the scale for the growing vortex.
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Aims: To investigate the changes in the surface properties of Lactobacillus rhamnosus GG during growth, and relate them with the ability of the Lactobacillus cells to adhere to Caco-2 cells. Methods and Results: Lactobacillus rhamnosus GG was grown in complex medium, and cell samples taken at four time points and freeze dried. Untreated and trypsin treated freeze dried samples were analysed for their composition using SDS-PAGE analysis and Fourier transform infrared spectroscopy (FTIR), hydrophobicity and zeta potential, and for their ability to adhere to Caco-2 cells. The results suggested that in the case of early exponential phase samples (4 and 8 h), the net surface properties, i.e. hydrophobicity and charge, were determined to a large extent by anionic hydrophilic components, whereas in the case of stationary phase samples (13 and 26 h), hydrophobic proteins seemed to play the biggest role. Considerable differences were also observed between the ability of the different samples to adhere to Caco-2 cells; maximum adhesion was observed for the early stationary phase sample (13 h). The results suggested that the adhesion to Caco-2 cells was influenced by both proteins and non-proteinaceous compounds present on the surface of the Lactobacillus cells. Conclusion: The surface properties of Lact. rhamnosus GG changed during growth, which in return affected the ability of the Lactobacillus cells to adhere to Caco-2 cells. Significance and Impact of the Study: The levels of adhesion of Lactobacillus cells to Caco-2 cells were influenced by the growth time and reflected changes on the bacterial surface. This study provides critical information on the physicochemical factors that influence bacterial adhesion to intestinal cells.
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The invasion and infectivity of Meloidogyne javanica juveniles (J2) encumbered with spore of Pasteuria Penetrans were influenced by the temperature and the time J2 were in the soil before exposure to roots. The percentage of infected females decreased as the time juveniles spent in soil increased. When spore encumbered J2 were maintained at 30 degrees C the decrease in infection was greater than that at 18 degrees C. The thermal time requirements and the base temperature for P. penetrans development were estimated. The rate of development followed an exponential curve between 21 and 36 degrees C and the base temperature for development was estimated by extrapolation to be 18.5 degrees C. The effect of integrating a nematode resistant tomato cultivar with the biocontrol agent P. penetrans also was investigated. The ability of the biocontrol agent to reduce numbers of root-knot nematodes was dependent on the densities of the nematode and P. penetrans spores in the soil.
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Three goats provided with oesophageal and ruminal cannulae were used to determine variations in dry matter (DM) and neutral-detergent fibre (NDF) degradability of the forage consumed when grazing thorn scrubland in the semi-arid region of north Mexico, during two consecutive dry and wet periods. Ingesta samples were incubated intraruminally, the data were fitted to the exponential equation P = a + b (1-e(-ct)) and statistically analysed using a randomized-block design. Organic matter and crude protein (CP) contents were higher (P < 0.05) in the wet seasons. Values of NDF were similar in dry and wet season of both years whereas higher numerical values of acid-detergent fibre (ADF), lignin and cellulose were registered in the dry seasons. DM and NDF degradabilities after 24 and 48 h of ruminal incubation were higher (P < 0.05) in the wet seasons. Higher values (P < 0.05) in DM and NDF bag losses at zero time (A fraction) were registered in the two wet seasons. The insoluble but fermentable DM and NDF (B fractions) were higher (P < 0.05) in the 1999 wet season and variable in the rest of the studied period. Numerically higher values of DM and NDF c fraction were found in wet periods, whereas DM and NDF potential degradabilities were higher (P < 0.05) in the wet season in 1999 and similar across seasons in 2000. Lowest (P < 0.05) contents of CP in grazed forage, DM and NDF degradabilities after 48 h of ruminal incubation, and A, and B, and c fractions were observed in the dry seasons. Thus, these results may be related to both the lower feeding value of forage consumed by the animals and lower performance of livestock during this period. Then, the DM and NDF degradability after 48 h, together with the insoluble but fermentable matter and the c fraction permit the nutritive value of the forage consumed by grazing goats to be accurately described.
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Pollination by bees and other animals increases the size, quality, or stability of harvests for 70% of leading global crops. Because native species pollinate many of these crops effectively, conserving habitats for wild pollinators within agricultural landscapes can help maintain pollination services. Using hierarchical Bayesian techniques, we synthesize the results of 23 studies - representing 16 crops on five continents - to estimate the general relationship between pollination services and distance from natural or semi-natural habitats. We find strong exponential declines in both pollinator richness and native visitation rate. Visitation rate declines more steeply, dropping to half of its maximum at 0.6 km from natural habitat, compared to 1.5 km for richness. Evidence of general decline in fruit and seed set - variables that directly affect yields - is less clear. Visitation rate drops more steeply in tropical compared with temperate regions, and slightly more steeply for social compared with solitary bees. Tropical crops pollinated primarily by social bees may therefore be most susceptible to pollination failure from habitat loss. Quantifying these general relationships can help predict consequences of land use change on pollinator communities and crop productivity, and can inform landscape conservation efforts that balance the needs of native species and people.
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Accurate knowledge of lactation curves has an important relevance to management and research of dairy production systems. A number of equations have been proposed to describe the lactation curve, the most widely applied being the gamma equation. The objective of this work was to compare and evaluate candidate functions for their predictive ability in describing lactation curves from central Mexican dairy cows reared under 2 contrasting management systems. Five equations were considered: Gaines ( exponential decay), Wood ( gamma equation), Rook ( Michaelis-Menten x exponential), and 2 more mechanistic ones (Dijkstra and Pollott). A database consisting of 701 and 1283 records of cows in small-scale and intensive systems, respectively, was used in the analysis. Before analysis, the database was divided into 6 groups representing first, second, and third and higher parity cows in both systems. In all cases except second and above parity cows in small-scale systems, all models improved on the Gaines equation. The Wood equation explained much of the variation, but its parameters do not have direct biological interpretation. Although the Rook equation fitted the data well, some of the parameter estimates were not significant. The Dijkstra equation consistently gave better predictions, and its parameters were usually statistically significant and lend themselves to physiological interpretation. As such, the differences between systems and parity could be explained due to variations in theoretical initial milk production at parturition, specific rates of secretory cell proliferation and death, and rate of decay, all of which are parameters in the model. The Pollott equation, although containing the most biology, was found to be over-parameterized and resulted in nonsignificant parameter estimates. For central Mexican dairy cows, the Dijkstra equation was the best option to use in describing the lactation curve.
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An appropriate model of recent human evolution is not only important to understand our own history, but it is necessary to disentangle the effects of demography and selection on genome diversity. Although most genetic data support the view that our species originated recently in Africa, it is still unclear if it completely replaced former members of the Homo genus, or if some interbreeding occurred during its range expansion. Several scenarios of modern human evolution have been proposed on the basis of molecular and paleontological data, but their likelihood has never been statistically assessed. Using DNA data from 50 nuclear loci sequenced in African, Asian and Native American samples, we show here by extensive simulations that a simple African replacement model with exponential growth has a higher probability (78%) as compared with alternative multiregional evolution or assimilation scenarios. A Bayesian analysis of the data under this best supported model points to an origin of our species approximate to 141 thousand years ago (Kya), an exit out-of-Africa approximate to 51 Kya, and a recent colonization of the Americas approximate to 10.5 Kya. We also find that the African replacement model explains not only the shallow ancestry of mtDNA or Y-chromosomes but also the occurrence of deep lineages at some autosomal loci, which has been formerly interpreted as a sign of interbreeding with Homo erectus.
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Long distance dispersal (LDD) plays an important role in many population processes like colonization, range expansion, and epidemics. LDD of small particles like fungal spores is often a result of turbulent wind dispersal and is best described by functions with power-law behavior in the tails ("fat tailed"). The influence of fat-tailed LDD on population genetic structure is reported in this article. In computer simulations, the population structure generated by power-law dispersal with exponents in the range of -2 to -1, in distinct contrast to that generated by exponential dispersal, has a fractal structure. As the power-law exponent becomes smaller, the distribution of individual genotypes becomes more self-similar at different scales. Common statistics like G(ST) are not well suited to summarizing differences between the population genetic structures. Instead, fractal and self-similarity statistics demonstrated differences in structure arising from fat-tailed and exponential dispersal. When dispersal is fat tailed, a log-log plot of the Simpson index against distance between subpopulations has an approximately constant gradient over a large range of spatial scales. The fractal dimension D-2 is linearly inversely related to the power-law exponent, with a slope of similar to -2. In a large simulation arena, fat-tailed LDD allows colonization of the entire space by all genotypes whereas exponentially bounded dispersal eventually confines all descendants of a single clonal lineage to a relatively small area.