975 resultados para Over adaptation
Resumo:
In monsoon regions, the seasonal migration of the intertropical convergence zone (ITCZ) is manifested as a seasonal reversal of winds. Most of the summer monsoon rainfall over India occurs owing to synoptic and large-scale convection associated with the continental ITCZ (Fig. 1). We have investigated the interaction between these large-scale convective systems and the ocean over which they are generated1â3, concentrating on the relationship between organized convection over the Indian Ocean and sea surface temperature (SST). We report here that on a monthly basis the degree of cloudiness correlates well with SST for the relatively colder oceans, but when SST is maintained above 28 °C it ceases to be an important factor in determining the variability of cloudiness. Over the major regions of convection east of 70°E, which are warm year after year, the observed cloudiness cannot be correlated with variations in SST.
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A variety of data structures such as inverted file, multi-lists, quad tree, k-d tree, range tree, polygon tree, quintary tree, multidimensional tries, segment tree, doubly chained tree, the grid file, d-fold tree. super B-tree, Multiple Attribute Tree (MAT), etc. have been studied for multidimensional searching and related problems. Physical data base organization, which is an important application of multidimensional searching, is traditionally and mostly handled by employing inverted file. This study proposes MAT data structure for bibliographic file systems, by illustrating the superiority of MAT data structure over inverted file. Both the methods are compared in terms of preprocessing, storage and query costs. Worst-case complexity analysis of both the methods, for a partial match query, is carried out in two cases: (a) when directory resides in main memory, (b) when directory resides in secondary memory. In both cases, MAT data structure is shown to be more efficient than the inverted file method. Arguments are given to illustrate the superiority of MAT data structure in an average case also. An efficient adaptation of MAT data structure, that exploits the special features of MAT structure and bibliographic files, is proposed for bibliographic file systems. In this adaptation, suitable techniques for fixing and ranking of the attributes for MAT data structure are proposed. Conclusions and proposals for future research are presented.
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An expression is derived for the probability that the determinant of an n x n matrix over a finite field vanishes; from this it is deduced that for a fixed field this probability tends to 1 as n tends to.
Time dependent rotational flow of a viscous fluid over an infinite porous disk with a magnetic field
Resumo:
Both the semi-similar and self-similar flows due to a viscous fluid rotating with time dependent angular velocity over a porous disk of large radius at rest with or without a magnetic field are investigated. For the self-similar case the resulting equations for the suction and no mass transfer cases are solved numerically by quasilinearization method whereas for the semi-similar case and injection in the self-similar case an implicit finite difference method with Newton's linearization is employed. For rapid deceleration of fluid and for moderate suction in the case of self-similar flow there exists a layer of fluid, close to the disk surface where the sense of rotation is opposite to that of the fluid rotating far away. The velocity profiles in the absence of magnetic field are found to be oscillatory except for suction. For the accelerating freestream, (semi-similar flow) the effect of time is to reduce the amplitude of the oscillations of the velocity components. On the other hand the effect of time for the oscillating case is just the opposite.
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Micropolar fluid flow over a semi-infinite flat plate has been described by using the parabolic co-ordinates and the method of series truncation in order to study the flow for low to large Reynolds numbers. These co-ordinates permit to study the flow regime at the leading edge. Numerical results have been presented for different Reynolds numbers. Results show a reduction in skin friction.
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In coastal waters and estuaries, seagrass meadows are often subject to light deprivation over short time scales (days to weeks) in response to increased turbidity from anthropogenic disturbances. Seagrasses may exhibit negative physiological responses to light deprivation and suffer stress, or tolerate such stresses through photo-adaptation of physiological processes allowing more efficient use of low light. Pulse Amplitude Modulated (PAM) fluorometery has been used to rapidly assess changes in photosynthetic responses along in situ gradients in light. In this study, however, light is experimentally manipulated in the field to examine the photosynthesis of Halophila ovalis and Zostera capricorni. We aimed to evaluate the tolerance of these seagrasses to short-term light reductions. The seagrasses were subject to four light treatments, 0, 5, 60, and 90% shading, for a period of 14 days. In both species, as shading increased the photosynthetic variables significantly (P < 0.05) decreased by up to 40% for maximum electron transport rates (ETRmax) and 70% for saturating irradiances (Ek). Photosynthetic efficiencies (a) and effective quantum yields (ΔF/Fm′ ) increased significantly (P < 0.05), in both species, for 90% shaded plants compared with 0% shaded plants. H. ovalis was more sensitive to 90% shading than Z. capricorni, showing greater reductions in ETR max, indicative of a reduced photosynthetic capacity. An increase in Ek, Fm′ and ΔF/Fm′ for H. ovalis and Z. capricorni under 90% shading suggested an increase in photochemical efficiency and a more efficient use of low-photon flux, consistent with photo-acclimation to shading. Similar responses were found along a depth gradient from 0 to10 m, where depth related changes in ETRmax and Ek in H. ovalis implied a strong difference of irradiance history between depths of 0 and 5-10 m. The results suggest that H. ovalis is more vulnerable to light deprivation than Z. capricorni and that H. ovalis, at depths of 5-10 m, would be more vulnerable to light deprivation than intertidal populations. Both species showed a strong degree of photo-adaptation to light manipulation that may enable them to tolerate and adapt to short-term reductions in light. These consistent responses to changes in light suggest that photosynthetic variables can be used to rapidly assess the status of seagrasses when subjected to sudden and prolonged periods of reduced light
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In this study, we examined the photosynthetic responses of five common seagrass species from a typical mixed meadow in Torres Strait at a depth of 5–7 m using pulse amplitude modulated (PAM) fluorometry. The photosynthetic response of each species was measured every 2 h throughout a single daily light cycle from dawn (6 am) to dusk (6 pm). PAM fluorometry was used to generate rapid light curves from which measures of electron transport rate (ETRmax), photosynthetic efficiency (α), saturating irradiance (Ek) and light-adapted quantum yield (ΔF/F′m) were derived for each species. The amount of light absorbed by leaves (absorption factor) was also determined for each species. Similar diurnal patterns were recorded among species with 3–4 fold increases in maximal electron rate from dawn to midday and a maintenance of ETRmax in the afternoon that would allow an optimal use of low light by all species. Differences in photosynthetic responses to changes in the daily light regime were also evident with Syringodium isoetifolium showing the highest photosynthetic rates and saturating irradiances suggesting a competitive advantage over other species under conditions of high light. In contrast Halophila ovalis, Halophila decipiens and Halophila spinulosa were characterised by comparatively low photosynthetic rates and minimum light requirements (i.e. low Ek) typical of shade adaptation. The structural makeup of each species may explain the observed differences with large, structurally complex species such as Syringodium isoetifolium and Cymodocea serrulata showing high photosynthetic effciciencies (α) and therefore high-light-adapted traits (e.g. high ETRmax and Ek) compared with the smaller Halophila species positioned lower in the canopy. For the smaller Halophila species these shade-adapted traits are features that optimise their survival during low-light conditions. Knowledge of these characteristics and responses improves our understanding of the underlying causes of changes in seagrass biomass, growth and survival that occur when modifications in light quantity and quality arise from anthropogenic and climatic disturbances that commonly occur in Torres Strait.
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Domain-invariant representations are key to addressing the domain shift problem where the training and test exam- ples follow different distributions. Existing techniques that have attempted to match the distributions of the source and target domains typically compare these distributions in the original feature space. This space, however, may not be di- rectly suitable for such a comparison, since some of the fea- tures may have been distorted by the domain shift, or may be domain specific. In this paper, we introduce a Domain Invariant Projection approach: An unsupervised domain adaptation method that overcomes this issue by extracting the information that is invariant across the source and tar- get domains. More specifically, we learn a projection of the data to a low-dimensional latent space where the distance between the empirical distributions of the source and target examples is minimized. We demonstrate the effectiveness of our approach on the task of visual object recognition and show that it outperforms state-of-the-art methods on a stan- dard domain adaptation benchmark dataset
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In this paper, we tackle the problem of unsupervised domain adaptation for classification. In the unsupervised scenario where no labeled samples from the target domain are provided, a popular approach consists in transforming the data such that the source and target distributions be- come similar. To compare the two distributions, existing approaches make use of the Maximum Mean Discrepancy (MMD). However, this does not exploit the fact that prob- ability distributions lie on a Riemannian manifold. Here, we propose to make better use of the structure of this man- ifold and rely on the distance on the manifold to compare the source and target distributions. In this framework, we introduce a sample selection method and a subspace-based method for unsupervised domain adaptation, and show that both these manifold-based techniques outperform the cor- responding approaches based on the MMD. Furthermore, we show that our subspace-based approach yields state-of- the-art results on a standard object recognition benchmark.
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Synthetic backcrossed-derived bread wheats (SBWs) from CIMMYT were grown in the Northwest of Mexico at Centro de Investigaciones Agrícolas del Noroeste (CIANO) and sites across Australia during three seasons. During three consecutive years Australia received “shipments” of different SBWs from CIMMYT for evaluation. A different set of lines was evaluated each season, as new materials became available from the CIMMYT crop enhancement program. These consisted of approximately 100 advanced lines (F7) per year. SBWs had been top and backcrossed to CIMMYT cultivars in the first two shipments and to Australian wheat cultivars in the third one. At CIANO, the SBWs were trialled under receding soil moisture conditions. We evaluated both the performance of each line across all environments and the genotype-by-environment interaction using an analysis that fits a multiplicative mixed model, adjusted for spatial field trends. Data were organised in three groups of multienvironment trials (MET) containing germplasm from shipment 1 (METShip1), 2 (METShip2), and 3 (METShip3), respectively. Large components of variance for the genotype × environment interaction were found for each MET analysis, due to the diversity of environments included and the limited replication over years (only in METShip2, lines were tested over 2 years). The average percentage of genetic variance explained by the factor analytic models with two factors was 50.3% for METShip1, 46.7% for METShip2, and 48.7% for METShip3. Yield comparison focused only on lines that were present in all locations within a METShip, or “core” SBWs. A number of core SBWs, crossed to both Australian and CIMMYT backgrounds, outperformed the local benchmark checks at sites from the northern end of the Australian wheat belt, with reduced success at more southern locations. In general, lines that succeeded in the north were different from those in the south. The moderate positive genetic correlation between CIANO and locations in the northern wheat growing region likely reflects similarities in average temperature during flowering, high evaporative demand, and a short flowering interval. We are currently studying attributes of this germplasm that may contribute to adaptation, with the aim of improving the selection process in both Mexico and Australia.
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Based on the theory given by Saltzman and Ashe (1976), sensible heat fluxes are calculated for the active and break phases of the southwest monsoon over the Indian region. The conclusion drawn is that the sensible heat flux is generally larger during the break monsoon situation when compared with that for the active monsoon situation. The synoptic heat flux is negligible when compared with mean and diurnal heat fluxes over the Indian region even during the monsoon season.
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Laboratory-reared insects are widely known to have significantly reduced genetic diversity in comparison to wild populations; however, subtle behavioural changes between laboratory-adapted and wild or ‘wildish’ (i.e., within one or very few generations of field collected material) populations are less well understood. Quantifying alterations in behaviour, particularly sexual, in laboratory-adapted insects is important for mass-reared insects for use in pest management strategies, especially those that have a sterile insect technique component. We report subtle changes in sexual behaviour between ‘wildish’ Bactrocera dorsalis flies (F1 and F2) from central and southern Thailand and the same colonies 12 months later when at six generations from wild. Mating compatibility tests were undertaken under standardised semi-natural conditions, with number of homo/heterotypic couples and mating location in field cages analysed via compatibility indices. Central and southern populations of B. dorsalis displayed positive assortative mating in the 2010 trials but mated randomly in the 2011 trials. ‘Wildish’ southern Thailand males mated significantly earlier than central Thailand males in 2010; this difference was considerably reduced in 2011, yet homotypic couples from southern Thailand still formed significantly earlier than all other couple combinations. There was no significant difference in couple location in 2010; however, couple location significantly differed among pair types in 2011 with those involving southern Thailand females occurring significantly more often on the tree relative to those with central Thailand females. Relative participation also changed with time, with more southern Thailand females forming couples relative to central Thailand females in 2010; this difference was considerably decreased by 2011. These results reveal how subtle changes in sexual behaviour, as driven by laboratory rearing conditions, may significantly influence mating behaviour between laboratory-adapted and recently colonised tephritid fruit flies over a relatively short period of time.
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Gaussian processes (GPs) are promising Bayesian methods for classification and regression problems. Design of a GP classifier and making predictions using it is, however, computationally demanding, especially when the training set size is large. Sparse GP classifiers are known to overcome this limitation. In this letter, we propose and study a validation-based method for sparse GP classifier design. The proposed method uses a negative log predictive (NLP) loss measure, which is easy to compute for GP models. We use this measure for both basis vector selection and hyperparameter adaptation. The experimental results on several real-world benchmark data sets show better orcomparable generalization performance over existing methods.