980 resultados para Spatial Dependence


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In early generation variety trials, large numbers of new breeders' lines (varieties) may be compared, with each having little seed available. A so-called unreplicated trial has each new variety on just one plot at a site, but includes several replicated control varieties, making up around 10% and 20% of the trial. The aim of the trial is to choose some (usually around one third) good performing new varieties to go on for further testing, rather than precise estimation of their mean yields. Now that spatial analyses of data from field experiments are becoming more common, there is interest in an efficient layout of an experiment given a proposed spatial analysis and an efficiency criterion. Common optimal design criteria values depend on the usual C-matrix, which is very large, and hence it is time consuming to calculate its inverse. Since most varieties are unreplicated, the variety incidence matrix has a simple form, and some matrix manipulations can dramatically reduce the computation needed. However, there are many designs to compare, and numerical optimisation lacks insight into good design features. Some possible design criteria are discussed, and approximations to their values considered. These allow the features of efficient layouts under spatial dependence to be given and compared. (c) 2006 Elsevier Inc. All rights reserved.

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The article examines the extent to which foreign manufacturing firms in the UK promote productivity growth in the domestically owned manufacturing sector through their buying and supplying relationships. Evidence for intra- and inter-regional externalities from the presence of foreign manufacturing, and intraand inter-industry effects is brought to light. Externalities in the domestic sector are most noticeable where foreign manufacturing sells to domestic manufacturing. These externalities are, however, not wholly robust to different specifications of spatial dependence. The findings are positioned in a debate, which has tended to view backward (as opposed to forward) linkages from multinationals to domestically owned supply bases as a critical driver of indirect economic benefits. © RSAI 2004.

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The conventional, geometrically lumped description of the physical processes inside a high shear granulator is not reliable for process design and scale-up. In this study, a compartmental Population Balance Model (PBM) with spatial dependence is developed and validated in two lab-scale high shear granulation processes using a 1.9L MiPro granulator and 4L DIOSNA granulator. The compartmental structure is built using a heuristic approach based on computational fluid dynamics (CFD) analysis, which includes the overall flow pattern, velocity and solids concentration. The constant volume Monte Carlo approach is implemented to solve the multi-compartment population balance equations. Different spatial dependent mechanisms are included in the compartmental PBM to describe granule growth. It is concluded that for both cases (low and high liquid content), the adjustment of parameters (e.g. layering, coalescence and breakage rate) can provide a quantitative prediction of the granulation process.

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A multivariate statistical analysis was applied to a 10 year, multiparameter data set in an effort to describe the spatial dependence and inherent variation of water quality patterns in the mangrove estuaries of Ten Thousand Islands – Whitewater Bay area. Principal component analysis (PCA) of 16 water quality parameters collected monthly resulted in five groupings, which explained 72.5% of the variance of the original variables. The “Organic” component (PCI) was composed of alkaline phosphatase activity, total organic nitrogen, and total organic carbon; the “Dissolved Inorganic N” component (PCII) contained NO 3 − , NO 2 − , and NH 4 + ; the “Phytoplankton” component (PCIII) was made up of total phosphorus, chlorophyll a, and turbidity; dissolved oxygen and temperature were inversely related (PCIV); and salinity and soluble reactive phosphorus made up PCV. A cluster analysis of the mean and SD of PC scores resulted in the spatial aggregation of the 47 fixed stations into six classes having similar water quality, which we defined as: Mangrove Rivers, Whitewater Bay, Gulf Islands, Coot Bay, Blackwater River, and Inland Waterway. Marked differences in physical, chemical, and biological characteristics among classes were illustrated by this technique. Comparison of medians and variability of parameters among classes allowed large scale generalizations as to underlying differences in water quality in these regions. A strong south to north gradient in estuaries from high N - low P to low N - high P was ascribed to marked differences in landuse, freshwater input, geomorphology, and sedimentary geology along this tract. The ecological significance of this gradient discussed along with potential effects of future restoration plans.

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Estimates of HIV prevalence are important for policy in order to establish the health status of a country's population and to evaluate the effectiveness of population-based interventions and campaigns. However, participation rates in testing for surveillance conducted as part of household surveys, on which many of these estimates are based, can be low. HIV positive individuals may be less likely to participate because they fear disclosure, in which case estimates obtained using conventional approaches to deal with missing data, such as imputation-based methods, will be biased. We develop a Heckman-type simultaneous equation approach which accounts for non-ignorable selection, but unlike previous implementations, allows for spatial dependence and does not impose a homogeneous selection process on all respondents. In addition, our framework addresses the issue of separation, where for instance some factors are severely unbalanced and highly predictive of the response, which would ordinarily prevent model convergence. Estimation is carried out within a penalized likelihood framework where smoothing is achieved using a parametrization of the smoothing criterion which makes estimation more stable and efficient. We provide the software for straightforward implementation of the proposed approach, and apply our methodology to estimating national and sub-national HIV prevalence in Swaziland, Zimbabwe and Zambia.

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In order to add value to soybens crops, and hence the marketing, medium and large producers have been using precision agriculture techniques (PA), as the Remote Sensing, Geographic Information Systems (GIS) and positioning satellite, to assist the management of crops. Thus, given the economic relevance of that culture to the southwest of Paraná State and Brazil, scientific studies to increase their productivity and profitability are of main importance. The objective of this study was to evaluate the correlation between the chemical soil properties and soybean yield for each estimated parameter of semivariogram (range, nugget and level effect), and the deployment of these correlations in direct and indirect effects, aiming to improve the mapping process of spatial variability of soil chemical properties for use in PA. The hypothesis is that not all attributes of soil used to estimate the semivariogram parameters has a direct effect on productivity, and that even in groups of plants within a larger area it is possible to estimate the parameters of the semivariograms. The experiment was conducted in a commercial area of 19.7 ha, located in the city of Pato Branco - PR, central geographic coordinates 26º 11 '35 "South, 52 43' 05" West longitude, and average altitude of 780 m. The area is planted with soybeans for over 30 years, currently being adopted to cultivate Brasmax Target RR - Don Mario 5.9i, with row spacing of 0.50 m and 13 plants m-1, totaling 260,000 plants ha-1. For georeferencing of the area of study and sampling points was used a couple of topographic ProMarkTM3 receptors, making a relative positioning to obtain the georeferenced coordinates. To collect data (chemical analyzes of soil and crop yield) were sampled 10 blocks in the experimental area, each with an area of 20 m2 (20 meters long x 1 meter wide) containing two spaced adjacent rows of 0.5 m. Each block was divided into 20 portions of 1 m2, and from each were collected four subsamples at a distance of 0.5 m in relation to the lines of blocks, making up a sample depth for 0-10 cm a sample to 10-20 cm for each plot, totaling 200 samples for each depth. The soybean crop was performed on the blocks depending on maturity, and in each block was considered a bundle at each meter. In the data analysis, it was performed a diagnosis of multicollinearity, and subsequently a path analysis of the main variables according to the explanatory variables (range of chemical attributes: pH, K, P, Ca, etc.). The results obtained by the path analysis of the parameters of the semivariogram of soil chemical properties, indicated that only the Fe, Mg, Mn, organic matter (OM), P and Saturation by bases (SB) exerted direct and indirect effects on soybean productivity, although they have not presented spatial variability, indicating that the distribution of blocks in the area was unable to identify the spatial dependence of these elements, making it impossible to draw up maps of the chemical attributes for use in PA.

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For derived flood frequency analysis based on hydrological modelling long continuous precipitation time series with high temporal resolution are needed. Often, the observation network with recording rainfall gauges is poor, especially regarding the limited length of the available rainfall time series. Stochastic precipitation synthesis is a good alternative either to extend or to regionalise rainfall series to provide adequate input for long-term rainfall-runoff modelling with subsequent estimation of design floods. Here, a new two step procedure for stochastic synthesis of continuous hourly space-time rainfall is proposed and tested for the extension of short observed precipitation time series. First, a single-site alternating renewal model is presented to simulate independent hourly precipitation time series for several locations. The alternating renewal model describes wet spell durations, dry spell durations and wet spell intensities using univariate frequency distributions separately for two seasons. The dependence between wet spell intensity and duration is accounted for by 2-copulas. For disaggregation of the wet spells into hourly intensities a predefined profile is used. In the second step a multi-site resampling procedure is applied on the synthetic point rainfall event series to reproduce the spatial dependence structure of rainfall. Resampling is carried out successively on all synthetic event series using simulated annealing with an objective function considering three bivariate spatial rainfall characteristics. In a case study synthetic precipitation is generated for some locations with short observation records in two mesoscale catchments of the Bode river basin located in northern Germany. The synthetic rainfall data are then applied for derived flood frequency analysis using the hydrological model HEC-HMS. The results show good performance in reproducing average and extreme rainfall characteristics as well as in reproducing observed flood frequencies. The presented model has the potential to be used for ungauged locations through regionalisation of the model parameters.

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The present study investigated whether memory for a room-sized spatial layout learned through auditory localization of sounds exhibits orientation dependence similar to that observed for spatial memory acquired from stationary viewing of the environment. Participants learned spatial layouts by viewing objects or localizing sounds and then performed judgments of relative direction among remembered locations. The results showed that direction judgments following auditory learning were performed most accurately at a particular orientation in the same way as were those following visual learning, indicating that auditorily encoded spatial memory is orientation dependent. In combination with previous findings that spatial memories derived from haptic and proprioceptive experiences are also orientation dependent, the present finding suggests that orientation dependence is a general functional property of human spatial memory independent of learning modality.

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The spatial coherence of a nanosecond pulsed germanium collisionally excited x-ray laser is measured experimentally for three target configurations. The diagnostic is based on Young's slit interference fringes with a dispersing element to resolve the 23.2- and 23.6-nm spectral lines. Target configurations include a double-slab target, known as the injector, and geometries in which the injector image is image relayed to seed either an additional single-slab target or a second double-slab target. A special feature of this study is the observation of the change in the apparent source size with angle of refraction across the diverging laser beam. Source sizes derived with a Gaussian source model decrease from 44 mu m for the injector target by a variable factor of as much as 2, according to target configuration, for beams leaving the additional amplifiers after strong refraction in the plasma. (C) 1998 Optical Society of America [S0740-3224(98)00810-8].

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The time dependence of the spatial coherence of the combined spectral lines at 23.2 and 23.6 nm from the Ge XXIII collisionally pumped soft-x-ray laser with a double-slab target is examined within a single nanosecond pulse by use of Young's interference fringes and a streak camera. High source intensity is linked with low spatial coherence and vice verse. Calculations of the source intensity, size, and position have also been made; these calculations refer to a single-slab source. Comparison between the observed and calculated intensities, and of the source sizes both calculated and derived from the Young's fringes by interpretation with a Gaussian model of source emission, show good agreement in general trends. (C) 1998 Optical Society of America [S0740-3224(98)01905-5].

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Spatial processes could play an important role in density-dependent population regulation because the disproportionate use of poor quality habitats as population size increases is widespread in animal populations-the so-called buffer effect. While the buffer effect patterns and their demographic consequences have been described in a number of wild populations, much less is known about how dispersal affects distribution patterns and ultimately density dependence. Here, we investigated the role of dispersal in spatial density dependence using an extraordinarily detailed dataset from a reintroduced Mauritius kestrel (Falco punctatus) population with a territorial (despotic) breeding system. We show that recruitment rates varied significantly between territories, and that territory occupancy was related to its recruitment rate, both of which are consistent with the buffer effect theory. However, we also show that restricted dispersal affects the patterns of territory occupancy with the territories close to release sites being occupied sooner and for longer as the population has grown than the territories further away. As a result of these dispersal patterns, the strength of spatial density dependence is significantly reduced. We conclude that restricted dispersal can modify spatial density dependence in the wild, which has implications for the way population dynamics are likely to be impacted by environmental change.

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The political economy literature on agriculture emphasizes influence over political outcomes via lobbying conduits in general, political action committee contributions in particular and the pervasive view that political preferences with respect to agricultural issues are inherently geographic. In this context, ‘interdependence’ in Congressional vote behaviour manifests itself in two dimensions. One dimension is the intensity by which neighboring vote propensities influence one another and the second is the geographic extent of voter influence. We estimate these facets of dependence using data on a Congressional vote on the 2001 Farm Bill using routine Markov chain Monte Carlo procedures and Bayesian model averaging, in particular. In so doing, we develop a novel procedure to examine both the reliability and the consequences of different model representations for measuring both the ‘scale’ and the ‘scope’ of spatial (geographic) co-relations in voting behaviour.

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Includes bibliography

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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)