836 resultados para Data fusion applications


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It is common in econometric applications that several hypothesis tests arecarried out at the same time. The problem then becomes how to decide whichhypotheses to reject, accounting for the multitude of tests. In this paper,we suggest a stepwise multiple testing procedure which asymptoticallycontrols the familywise error rate at a desired level. Compared to relatedsingle-step methods, our procedure is more powerful in the sense that itoften will reject more false hypotheses. In addition, we advocate the useof studentization when it is feasible. Unlike some stepwise methods, ourmethod implicitly captures the joint dependence structure of the teststatistics, which results in increased ability to detect alternativehypotheses. We prove our method asymptotically controls the familywise errorrate under minimal assumptions. We present our methodology in the context ofcomparing several strategies to a common benchmark and deciding whichstrategies actually beat the benchmark. However, our ideas can easily beextended and/or modied to other contexts, such as making inference for theindividual regression coecients in a multiple regression framework. Somesimulation studies show the improvements of our methods over previous proposals. We also provide an application to a set of real data.

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Over the past decade, CMRA has emerged as a unique clinical imaging tool with applications in selected populations. Patients with suspected coronary artery anomalies and patients with Kawasaki disease and coronary aneurysms are among those for whom CMRA has demonstrated clinical usefulness. For assessment of patients with atherosclerotic CAD, CMRA is useful for detection of patency of bypass grafts. At centers with appropriate expertise and resources, CMRA also appears to be of value for exclusion of severe proximal multivessel CAD in selected patients. Data from multicenter trials will continue to define the clinical role of CMRA, particularly as it relates to assessment of CAD. Future developments and enhancements of CMRA promise better lumen and coronary artery wall imaging. This may become the new target in noninvasive evaluation of CAD.

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This paper presents and estimates a dynamic choice model in the attribute space considering rational consumers. In light of the evidence of several state-dependence patterns, the standard attribute-based model is extended by considering a general utility function where pure inertia and pure variety-seeking behaviors can be explained in the model as particular linear cases. The dynamics of the model are fully characterized by standard dynamic programming techniques. The model presents a stationary consumption pattern that can be inertial, where the consumer only buys one product, or a variety-seeking one, where the consumer shifts among varied products.We run some simulations to analyze the consumption paths out of the steady state. Underthe hybrid utility assumption, the consumer behaves inertially among the unfamiliar brandsfor several periods, eventually switching to a variety-seeking behavior when the stationary levels are approached. An empirical analysis is run using scanner databases for three different product categories: fabric softener, saltine cracker, and catsup. Non-linear specifications provide the best fit of the data, as hybrid functional forms are found in all the product categories for most attributes and segments. These results reveal the statistical superiority of the non-linear structure and confirm the gradual trend to seek variety as the level of familiarity with the purchased items increases.

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Correspondence analysis has found extensive use in ecology, archeology, linguisticsand the social sciences as a method for visualizing the patterns of association in a table offrequencies or nonnegative ratio-scale data. Inherent to the method is the expression of the datain each row or each column relative to their respective totals, and it is these sets of relativevalues (called profiles) that are visualized. This relativization of the data makes perfect sensewhen the margins of the table represent samples from sub-populations of inherently differentsizes. But in some ecological applications sampling is performed on equal areas or equalvolumes so that the absolute levels of the observed occurrences may be of relevance, in whichcase relativization may not be required. In this paper we define the correspondence analysis ofthe raw unrelativized data and discuss its properties, comparing this new method to regularcorrespondence analysis and to a related variant of non-symmetric correspondence analysis.

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Intracellular membrane fusion proceeds via distinct stages of membrane docking, hemifusion and fusion pore opening and depends on interacting families of Rab, SNARE and SM proteins. Trans-SNARE complexes dock the membranes in close apposition. Efficient fusion requires further SNARE-associated proteins. They might increase the number of trans-SNARE complexes or the fusogenic potential of a single SNARE complex. We investigated the contributions of the SM protein Vps33 to hemifusion and pore opening between yeast vacuoles. Mutations in Vps33 that weaken its interactions with the SNARE complex allowed normal trans-SNARE pairing and lipid mixing but retarded content mixing. Deleting the H(abc) domain of the vacuolar t-SNARE Vam3, which interacts with Vps33, had the same effect. This suggests that SM proteins promote fusion pore opening by enhancing the fusogenic activity of a SNARE complex. They should thus be considered integral parts of the fusion machinery.

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We continue the development of a method for the selection of a bandwidth or a number of design parameters in density estimation. We provideexplicit non-asymptotic density-free inequalities that relate the $L_1$ error of the selected estimate with that of the best possible estimate,and study in particular the connection between the richness of the classof density estimates and the performance bound. For example, our methodallows one to pick the bandwidth and kernel order in the kernel estimatesimultaneously and still assure that for {\it all densities}, the $L_1$error of the corresponding kernel estimate is not larger than aboutthree times the error of the estimate with the optimal smoothing factor and kernel plus a constant times $\sqrt{\log n/n}$, where $n$ is the sample size, and the constant only depends on the complexity of the family of kernels used in the estimate. Further applications include multivariate kernel estimates, transformed kernel estimates, and variablekernel estimates.

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This paper focuses on the switching behaviour of enrolees in the Swiss basic health insurance system. Even though the new Federal Law on Social Health Insurance (LAMal) was implemented in 1996 to promote competition among health insurers in basic insurance, there is limited evidence of premium convergence within cantons. This indicates that competition has not been effective so far, and reveals some inertia among consumers who seem reluctant to switch to less expensive funds. We investigate one possible barrier to switching behaviour, namely the influence of supplementary insurance. We use survey data on health plan choice (a sample of 1943 individuals whose switching behaviours were observed between 1997 and 2000) as well as administrative data relative to all insurance companies that operated in the 26 Swiss cantons between 1996 and 2005. The decision to switch and the decision to subscribe to a supplementary contract are jointly estimated.Our findings show that holding a supplementary insurance contract substantially decreases the propensity to switch. However, there is no negative impact of supplementary insurance on switching when the individual assesses his/her health as 'very good'. Our results give empirical support to one possible mechanism through which supplementary insurance might influence switching decisions: given that subscribing to basic and supplementary contracts with two different insurers may induce some administrative costs for the subscriber, holding supplementary insurance acts as a barrier to switch if customers who consider themselves 'bad risks' also believe that insurers reject applications for supplementary insurance on these grounds. In comparison with previous research, our main contribution is to offer a possible explanation for consumer inertia. Our analysis illustrates how consumer choice for one's basic health plan interacts with the decision to subscribe to supplementary insurance.

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Floods are the natural hazards that produce the highest number of casualties and material damage in the Western Mediterranean. An improvement in flood risk assessment and study of a possible increase in flooding occurrence are therefore needed. To carry out these tasks it is important to have at our disposal extensive knowledge on historical floods and to find an efficient way to manage this geographical data. In this paper we present a complete flood database spanning the 20th century for the whole of Catalonia (NE Spain), which includes documentary information (affected areas and damage) and instrumental information (meteorological and hydrological records). This geodatabase, named Inungama, has been implemented on a GIS (Geographical Information System) in order to display all the information within a given geographical scenario, as well as to carry out an analysis thereof using queries, overlays and calculus. Following a description of the type and amount of information stored in the database and the structure of the information system, the first applications of Inungama are presented. The geographical distribution of floods shows the localities which are more likely to be flooded, confirming that the most affected municipalities are the most densely populated ones in coastal areas. Regarding the existence of an increase in flooding occurrence, a temporal analysis has been carried out, showing a steady increase over the last 30 years.

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We have developed a processing methodology that allows crosshole ERT (electrical resistivity tomography) monitoring data to be used to derive temporal fluctuations of groundwater electrical resistivity and thereby characterize the dynamics of groundwater in a gravel aquifer as it is infiltrated by river water. Temporal variations of the raw ERT apparent-resistivity data were mainly sensitive to the resistivity (salinity), temperature and height of the groundwater, with the relative contributions of these effects depending on the time and the electrode configuration. To resolve the changes in groundwater resistivity, we first expressed fluctuations of temperature-detrended apparent-resistivity data as linear superpositions of (i) time series of riverwater-resistivity variations convolved with suitable filter functions and (ii) linear and quadratic representations of river-water-height variations multiplied by appropriate sensitivity factors; river-water height was determined to be a reliable proxy for groundwater height. Individual filter functions and sensitivity factors were obtained for each electrode configuration via deconvolution using a one month calibration period and then the predicted contributions related to changes in water height were removed prior to inversion of the temperature-detrended apparent-resistivity data. Applications of the filter functions and sensitivity factors accurately predicted the apparent-resistivity variations (the correlation coefficient was 0.98). Furthermore, the filtered ERT monitoring data and resultant time-lapse resistivity models correlated closely with independently measured groundwater electrical resistivity monitoring data and only weakly with the groundwater-height fluctuations. The inversion results based on the filtered ERT data also showed significantly less inversion artefacts than the raw data inversions. We observed resistivity increases of up to 10% and the arrival time peaks in the time-lapse resistivity models matched those in the groundwater resistivity monitoring data.

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Prediction of species' distributions is central to diverse applications in ecology, evolution and conservation science. There is increasing electronic access to vast sets of occurrence records in museums and herbaria, yet little effective guidance on how best to use this information in the context of numerous approaches for modelling distributions. To meet this need, we compared 16 modelling methods over 226 species from 6 regions of the world, creating the most comprehensive set of model comparisons to date. We used presence-only data to fit models, and independent presence-absence data to evaluate the predictions. Along with well-established modelling methods such as generalised additive models and GARP and BIOCLIM, we explored methods that either have been developed recently or have rarely been applied to modelling species' distributions. These include machine-learning methods and community models, both of which have features that may make them particularly well suited to noisy or sparse information, as is typical of species' occurrence data. Presence-only data were effective for modelling species' distributions for many species and regions. The novel methods consistently outperformed more established methods. The results of our analysis are promising for the use of data from museums and herbaria, especially as methods suited to the noise inherent in such data improve.

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Intensification of agricultural production without a sound management and regulations can lead to severe environmental problems, as in Western Santa Catarina State, Brazil, where intensive swine production has caused large accumulations of manure and consequently water pollution. Natural resource scientists are asked by decision-makers for advice on management and regulatory decisions. Distributed environmental models are useful tools, since they can be used to explore consequences of various management practices. However, in many areas of the world, quantitative data for model calibration and validation are lacking. The data-intensive distributed environmental model AgNPS was applied in a data-poor environment, the upper catchment (2,520 ha) of the Ariranhazinho River, near the city of Seara, in Santa Catarina State. Steps included data preparation, cell size selection, sensitivity analysis, model calibration and application to different management scenarios. The model was calibrated based on a best guess for model parameters and on a pragmatic sensitivity analysis. The parameters were adjusted to match model outputs (runoff volume, peak runoff rate and sediment concentration) closely with the sparse observed data. A modelling grid cell resolution of 150 m adduced appropriate and computer-fit results. The rainfall runoff response of the AgNPS model was calibrated using three separate rainfall ranges (< 25, 25-60, > 60 mm). Predicted sediment concentrations were consistently six to ten times higher than observed, probably due to sediment trapping along vegetated channel banks. Predicted N and P concentrations in stream water ranged from just below to well above regulatory norms. Expert knowledge of the area, in addition to experience reported in the literature, was able to compensate in part for limited calibration data. Several scenarios (actual, recommended and excessive manure applications, and point source pollution from swine operations) could be compared by the model, using a relative ranking rather than quantitative predictions.

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The current state of regional and urban science has been much discussed and a number of studies have speculated on possible future trends in the development of the discipline. However, there has been little empirical analysis of current publication patterns in regional and urban journals. This paper studies the kinds of topics, techniques and data used in articles published in nine top international journals during the 1990s with the aim of identifying current trends in this research field

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The current state of regional and urban science has been much discussed and a number of studies have speculated on possible future trends in the development of the discipline. However, there has been little empirical analysis of current publication patterns in regional and urban journals. This paper studies the kinds of topics, techniques and data used in articles published in nine top international journals during the 1990s with the aim of identifying current trends in this research field

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In many practical applications the state of field soils is monitored by recording the evolution of temperature and soil moisture at discrete depths. We theoretically investigate the systematic errors that arise when mass and energy balances are computed directly from these measurements. We show that, even with no measurement or model errors, large residuals might result when finite difference approximations are used to compute fluxes and storage term. To calculate the limits set by the use of spatially discrete measurements on the accuracy of balance closure, we derive an analytical solution to estimate the residual on the basis of the two key parameters: the penetration depth and the distance between the measurements. When the thickness of the control layer for which the balance is computed is comparable to the penetration depth of the forcing (which depends on the thermal diffusivity and on the forcing period) large residuals arise. The residual is also very sensitive to the distance between the measurements, which requires accurately controlling the position of the sensors in field experiments. We also demonstrate that, for the same experimental setup, mass residuals are sensitively larger than the energy residuals due to the nonlinearity of the moisture transport equation. Our analysis suggests that a careful assessment of the systematic mass error introduced by the use of spatially discrete data is required before using fluxes and residuals computed directly from field measurements.

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The biological properties of wild-type A75/17 and cell culture-adapted Onderstepoort canine distemper virus differ markedly. To learn more about the molecular basis for these differences, we have isolated and sequenced the protein-coding regions of the attachment and fusion proteins of wild-type canine distemper virus strain A75/17. In the attachment protein, a total of 57 amino acid differences were observed between the Onderstepoort strain and strain A75/17, and these were distributed evenly over the entire protein. Interestingly, the attachment protein of strain A75/17 contained an extension of three amino acids at the C terminus. Expression studies showed that the attachment protein of strain A75/17 had a higher apparent molecular mass than the attachment protein of the Onderstepoort strain, in both the presence and absence of tunicamycin. In the fusion protein, 60 amino acid differences were observed between the two strains, of which 44 were clustered in the much smaller F2 portion of the molecule. Significantly, the AUG that has been proposed as a translation initiation codon in the Onderstepoort strain is an AUA codon in strain A75/17. Detailed mutation analyses showed that both the first and second AUGs of strain A75/17 are the major translation initiation sites of the fusion protein. Similar analyses demonstrated that, also in the Onderstepoort strain, the first two AUGs are the translation initiation codons which contribute most to the generation of precursor molecules yielding the mature form of the fusion protein.