14 resultados para Goddard Space Flight Center. Mission Operations and Data Systems Directorate.

em Consorci de Serveis Universitaris de Catalunya (CSUC), Spain


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The spectral efficiency achievable with joint processing of pilot and data symbol observations is compared with that achievable through the conventional (separate) approach of first estimating the channel on the basis of the pilot symbols alone, and subsequently detecting the datasymbols. Studied on the basis of a mutual information lower bound, joint processing is found to provide a non-negligible advantage relative to separate processing, particularly for fast fading. It is shown that, regardless of the fading rate, only a very small number of pilot symbols (at most one per transmit antenna and per channel coherence interval) shouldbe transmitted if joint processing is allowed.

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This article reviews the methodology of the studies on drug utilization with particular emphasis on primary care. Population based studies of drug inappropriateness can be done with microdata from Health Electronic Records and e-prescriptions. Multilevel models estimate the influence of factors affecting the appropriateness of drug prescription at different hierarchical levels: patient, doctor, health care organization and regulatory environment. Work by the GIUMAP suggest that patient characteristics are the most important factor in the appropriateness of prescriptions with significant effects at the general practicioner level.

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This article reviews the methodology of the studies on drug utilization with particular emphasis on primary care. Population based studies of drug inappropriateness can be done with microdata from Health Electronic Records and e-prescriptions. Multilevel models estimate the influence of factors affecting the appropriateness of drug prescription at different hierarchical levels: patient, doctor, health care organization and regulatory environment.Work by the GIUMAP suggest that patient characteristics are the most important factor in the appropriateness of prescriptions with significant effects at the general practicioner level.

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We study theoretical and empirical aspects of the mean exit time (MET) of financial time series. The theoretical modeling is done within the framework of continuous time random walk. We empirically verify that the mean exit time follows a quadratic scaling law and it has associated a prefactor which is specific to the analyzed stock. We perform a series of statistical tests to determine which kind of correlation are responsible for this specificity. The main contribution is associated with the autocorrelation property of stock returns. We introduce and solve analytically both two-state and three-state Markov chain models. The analytical results obtained with the two-state Markov chain model allows us to obtain a data collapse of the 20 measured MET profiles in a single master curve.

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In this correspondence, we propose applying the hiddenMarkov models (HMM) theory to the problem of blind channel estimationand data detection. The Baum–Welch (BW) algorithm, which is able toestimate all the parameters of the model, is enriched by introducingsome linear constraints emerging from a linear FIR hypothesis on thechannel. Additionally, a version of the algorithm that is suitable for timevaryingchannels is also presented. Performance is analyzed in a GSMenvironment using standard test channels and is found to be close to thatobtained with a nonblind receiver.

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We present a participant study that compares biological data exploration tasks using volume renderings of laser confocal microscopy data across three environments that vary in level of immersion: a desktop, fishtank, and cave system. For the tasks, data, and visualization approach used in our study, we found that subjects qualitatively preferred and quantitatively performed better in the cave compared with the fishtank and desktop. Subjects performed real-world biological data analysis tasks that emphasized understanding spatial relationships including characterizing the general features in a volume, identifying colocated features, and reporting geometric relationships such as whether clusters of cells were coplanar. After analyzing data in each environment, subjects were asked to choose which environment they wanted to analyze additional data sets in - subjects uniformly selected the cave environment.

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This work focuses on the prediction of the two main nitrogenous variables that describe the water quality at the effluent of a Wastewater Treatment Plant. We have developed two kind of Neural Networks architectures based on considering only one output or, in the other hand, the usual five effluent variables that define the water quality: suspended solids, biochemical organic matter, chemical organic matter, total nitrogen and total Kjedhal nitrogen. Two learning techniques based on a classical adaptative gradient and a Kalman filter have been implemented. In order to try to improve generalization and performance we have selected variables by means genetic algorithms and fuzzy systems. The training, testing and validation sets show that the final networks are able to learn enough well the simulated available data specially for the total nitrogen

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Prevention has been a main issue of recent policy orientations in health care. This renews the interest on how different organizational designs and the definition of payment schemes to providers may affect the incentives to provide preventive health care. We present, both the normative and the positive analyses of the change from independent providers to integrated services. We show the evaluation of that change to depend on the particular way payment to providers is done. We focus on the externality resulting from referral decisions from primary to acute care providers. This makes our analysis complementary to most works in the literature allowing to address in a more direct way the issue of preventive health care.

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"Vegeu el resum a l'inici del document del fitxer adjunt."

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Organizations often face the challenge of communicating their strategiesto local decision makers. The difficulty presents itself in finding away to measure performance wich meaningfully conveys how to implement theorganization's strategy at local levels. I show that organizations solvethis communication problem by combining performance measures in such away that performance gains come closest to mimicking value-added asdefined by the organization's strategy. I further show how organizationsrebalance performance measures in response to changes in their strategies.Applications to the design of performance metrics, gaming, and divisionalperformance evaluation are considered. The paper also suggests severalempirical ways to evaluate the practical importance of the communicationrole of measurement systems.

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This paper proposes a very fast method for blindly approximating a nonlinear mapping which transforms a sum of random variables. The estimation is surprisingly good even when the basic assumption is not satisfied.We use the method for providing a good initialization for inverting post-nonlinear mixtures and Wiener systems. Experiments show that the algorithm speed is strongly improved and the asymptotic performance is preserved with a very low extra computational cost.

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This paper proposes a very fast method for blindly initial- izing a nonlinear mapping which transforms a sum of random variables. The method provides a surprisingly good approximation even when the basic assumption is not fully satis¯ed. The method can been used success- fully for initializing nonlinearity in post-nonlinear mixtures or in Wiener system inversion, for improving algorithm speed and convergence.

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Rationale Methylone, a new drug of abuse sold as"bath salts' has similar effects to ecstasy or cocaine. Objective We have investigated changes in dopaminergic and serotoninergic markers, indicative of neuronal damage, induced by methylone in the frontal cortex, hippocampus and striatum of mice and according two different treatment schedules. Methods Methylone was given subcutaneously to male Swiss CD1 mice and at an ambient temperature of 26ºC. Treatment A: three doses of 25 mg/Kg at 3.5 h interval between doses for two consecutive days. Treatment B: four doses of 25 mg/Kg at 3 h interval in one day. Results Repeated methylone administration induced hyperthermia and a significant loss in body weight. Following treatment A, methylone induced transient dopaminergic (frontal cortex) and serotoninergic (hippocampus) impairment. Following treatment B, transient dopaminergic (frontal cortex) and serotonergic (frontal cortex and hippocampus) changes 7 days after treatment were found. We found evidence of astrogliosis in the CA1 and the dentate gyrus of the hippocampus following treatment B. The animals also showed an increase in immobility time in the forced swim test, pointing to a depressive-like behavior. In cultured cortical neurons, methylone (for 24 and 48 h) did not induce a remarkable cytotoxic effect. Conclusions The neural effects of methylone differ depending upon the treatment schedule. Neurochemical changes elicited by methylone are apparent when administered at an elevated ambient temperature, four times per day at 3 h intervals, which is in accordance with its short half-life.